SOLVED: Decision Analysis with Probability: On a sunny May morning, Marc Binton, CEO of Bay Area Automobile Gadgets (BAAG), enters the conference room on the 40th floor of the Gates building in San Francisco, where BAAG’s offices are located. The other ex (2024)

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SOLVED: Decision Analysis with Probability:On a sunny May morning, Marc Binton, CEO of Bay Area AutomobileGadgets (BAAG), enters the conference room on the 40th floor of theGates building in San Francisco, where BAAG’s offices are located.The other executive officers of the company have already gathered.The meeting has only one item on its agenda: planning a researchand development project to develop a new driver support system(DSS). Brian Huang, Manager of Research and Development, is walkingaround nervously. He has to inform the group about the R Dstrategy he has developed for the DSS. Marc has identified DSS asthe strategic new product for the company. Julie Aker,VicePresident of Marketing, will speak after Brian. She will givedetailed information about the target segment, expected sales, andmarketing costs associated with the introduction of the DSS.BAAG builds electronic nonaudio equipment for luxury cars. Foundedby a group of Stanford graduates, the company sold its firstproduct—a car routing system relying on a technology called globalpositioning satellites (GPS)—a few years ago. Such routing systemshelp drivers to find directions to their desired destinations usingsatellites to determine the exact position of the car. To keep upwith technology and to meet the wishes of their customers, thecompany has added a number of new features to its router during thelast few years. The DSS will be a completely new product,incorporating recent developments in GPS as well as voicerecognition and display technologies. Marc strongly supports thisproduct, as it will give BAAG a competitive advantage over itsAsian and European competitors.Driver support systems have been a field of intense research formore than a decade. These systems provide the driver with a widerange of information, such as directions, road conditions, trafficupdates, etc. The information exchange can take place verbally orvia projection of text onto the windscreen. Other features help thedriver avoid obstacles that have been identified by cars ahead onthe road (these cars transmit the information to the followingvehicles). Marc wants to incorporate all these features and othertechnologies into one support system that would then be sold toBAAG’s customers in the automobile industry.After all the attendees have taken their seats, Brian starts hispresentation: “Marc asked me to inform you about our efforts withthe driver support system, particularly the road scanning device.We have reached a stage where we basically have to make a go orno-go decision concerning the research for this device, which, asyou all know by now, is a key feature in the DSS. We have alreadyintegrated the other devices, such as the PGS-based positioning anddirection system. The question we have to deal with is whether tofund basic research into the road scanning device. If this researchwere successful, we then would have to decide if we want to developa product based on these results—or if we just want to sell thetechnology without developing a product. If we do decide to developthe product ourselves, there is a chance that the productdevelopment process might not be successful. In that case, we couldstill sell the technology. In the case of successful productdevelopment, we would have to decide whether to market the product.If we decide not to market the developed product, we could at leastsell the product concept that was the result of our successfulresearch and development efforts. Doing so would earn more thanjust selling the technology prematurely. If, on the other hand, wedecide to market the driver support system, then we are faced withthe uncertainty of how the product will be received by ourcustomers.”“You completely lost me.” snipes Marc.Max, Julie’s assistant, just shakes his head and murmurs, “thosetechno-nerds. ”Brian starts to explain: “Sorry for the confusion. Let’s just gothrough it again, step by step.” “Good idea—and perhaps makesmaller steps!” Julie obviously dislikes Brian’s style ofpresentation.“OK, the first decision we are facing is whether to invest inresearch for the road scanningdevice.”“How much would that cost us?” asks Marc.“Our estimated budget for this is 300,000. Once we invest thatmoney, the outcome of the research effort is somewhat uncertain.Our engineers assess the probability of successful research at 80percent.”“That’s a pretty optimistic success rate, don’t you think?” Julieremarks sarcastically. She still remembers the disaster withBrian’s last project, the fingerprint-based car security system.After spending half a million dollars, the development engineersconcluded that it would be impossible to produce the securitysystem at an attractive price.Brian senses Julie’s hostility and shoots back: “In engineering weare quite accustomed to these success rates— something we can’t sayabout marketing. ”“What would be the next step?” intervenes Marc.“Hm, sorry. If the research is not successful, then we can onlysell the DSS in its currentform.”“The profit estimate for that scenario is2 million,” Julie throwsin.“If, however, the research effort is successful, then we will haveto make another decision,namely, whether to go on to the development stage.”“If we wouldn’t want to develop a product at that point, would thatmean that we would have to sell the DSS as it is now?” asksMax.“Yes, Max. Except that additionally we would earn some 200,000from selling our research results to GM. Their research division isvery interested in our work and they have offered me that money forour findings.”“Ah, now that’s good news,” remarks Julie.Brian continues, “If, however, after successfully completing theresearch stage, we decide to develop a new product then we’ll haveto spend another800,000 for that task, at a chance of 35 percentof not being successful.”“So you are telling us we’ll have to spend 800,000 for a ticket ina lottery where we have a 35 percent chance of not winninganything?” asks Julie.“Julie, don’t focus on the losses, but on the potential gains! Thechance of winning in this lottery, as you call it, is 65 percent. Ibelieve that that’s much more than with a normal lottery ticket,”says Marc.“Thanks, Marc,” says Brian. “Once we invest that money indevelopment, we have two possible outcomes: either we will besuccessful in developing the road scanning device or we won’t. Ifwe fail, then once again we’ll sell the DSS in its current form andcash in the200,000 from GM for the research results. If thedevelopment process is successful, then we have to decide whetherto market the new product.”“Why wouldn’t we want to market it after successfully developingit?” asks Marc.“That’s a good question. Basically what I mean is that we coulddecide not to sell the product ourselves but instead give the rightto sell it to somebody else, to GM, for example. They would pay us1 million for it.”“I like those numbers!” remarks Julie.“Once we decide to build the product and market it, we will facethe market uncertainties and I’m sure that Julie has those numbersready for us. Thanks.”At this point, Brian sits down and Julie comes forward to give herpresentation. Immediately some colorful slides are projected on thewall behind her as Max operates the computer.“Thanks, Brian. Well, here’s the data we have been able to gatherfrom some marketing research. The acceptance of our new product inthe market can be high, medium, or low,” Julie is pointing to somefigures projected on the wall behind her. “Our estimates indicatethat high acceptance would result in profits of8.0 million, andthat medium acceptance would give us 4.0 million. In theunfortunate case of a poor reception by our customers, we stillexpect2.2 million in profit. I should mention that these profitsdo not include the additional costs of marketing or R Dexpenses.”“So, you are saying that in the worst case we’ll make barely moremoney than with the current product?” asks Brian.“Yes, that’s what I am saying.”Marc.“What budget would you need for the marketing of our DSS with theroad scanner?” asks“For that we would need an additional 200,000 on top of whathas already been included inthe profit estimates,” Julie replies.“What are the chances of ending up with a high, medium, or lowacceptance of the new DSS?” asks Brian.“We can see those numbers at the bottom of the slide,” says Julie,while she is turning toward the projection behind her. There is a30 percent chance of high market acceptance and a 20 percent chanceof low market acceptance.At this point, Marc moves in his seat and asks: “Given all thesenumbers and bits of information, what are you suggesting that wedo?”(a) Organize the available data on cost andprofit estimates in a table.(b) Formulate the problem in a decision tree.Clearly distinguish between decision and event nodes.(c) Calculate the expected payoffs for each nodein the decision tree.(d) What is BAAG’s optimal policy according toBayes’decision rule?(e) What would be the expected value of perfectinformation on the outcome of the research effort? (f ) What wouldbe the expected value of perfect information on the outcome of thedevelopment effort?(g) Marc is a risk-averse decision maker. In anumber of interviews, his utility function for money was assessedto beu(M) = 1 – e –M/12 , ——————– 1 – e –1/12where M is the company’s net profit in units of hundreds ofthousands of dollars (e.g., M = 8 would imply a net profit of800,000). Using Marc’s utility function, calculate the utility foreach terminal branch of the decision tree.(h) Determine the expected utilities for allnodes in the decision tree.(i) Based on Marc’s utility function, what isBAAG’s optimal policy?(j) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of theresearch effort?(k) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of thedevelopment effort? (1)

Question

Decision Analysis with Probability:On a sunny May morning, Marc Binton, CEO of Bay Area AutomobileGadgets (BAAG), enters the conference room on the 40th floor of theGates building in San Francisco, where BAAG’s offices are located.The other executive officers of the company have already gathered.The meeting has only one item on its agenda: planning a researchand development project to develop a new driver support system(DSS). Brian Huang, Manager of Research and Development, is walkingaround nervously. He has to inform the group about the R&Dstrategy he has developed for the DSS. Marc has identified DSS asthe strategic new product for the company. Julie Aker,VicePresident of Marketing, will speak after Brian. She will givedetailed information about the target segment, expected sales, andmarketing costs associated with the introduction of the DSS.BAAG builds electronic nonaudio equipment for luxury cars. Foundedby a group of Stanford graduates, the company sold its firstproduct—a car routing system relying on a technology called globalpositioning satellites (GPS)—a few years ago. Such routing systemshelp drivers to find directions to their desired destinations usingsatellites to determine the exact position of the car. To keep upwith technology and to meet the wishes of their customers, thecompany has added a number of new features to its router during thelast few years. The DSS will be a completely new product,incorporating recent developments in GPS as well as voicerecognition and display technologies. Marc strongly supports thisproduct, as it will give BAAG a competitive advantage over itsAsian and European competitors.Driver support systems have been a field of intense research formore than a decade. These systems provide the driver with a widerange of information, such as directions, road conditions, trafficupdates, etc. The information exchange can take place verbally orvia projection of text onto the windscreen. Other features help thedriver avoid obstacles that have been identified by cars ahead onthe road (these cars transmit the information to the followingvehicles). Marc wants to incorporate all these features and othertechnologies into one support system that would then be sold toBAAG’s customers in the automobile industry.After all the attendees have taken their seats, Brian starts hispresentation: “Marc asked me to inform you about our efforts withthe driver support system, particularly the road scanning device.We have reached a stage where we basically have to make a go orno-go decision concerning the research for this device, which, asyou all know by now, is a key feature in the DSS. We have alreadyintegrated the other devices, such as the PGS-based positioning anddirection system. The question we have to deal with is whether tofund basic research into the road scanning device. If this researchwere successful, we then would have to decide if we want to developa product based on these results—or if we just want to sell thetechnology without developing a product. If we do decide to developthe product ourselves, there is a chance that the productdevelopment process might not be successful. In that case, we couldstill sell the technology. In the case of successful productdevelopment, we would have to decide whether to market the product.If we decide not to market the developed product, we could at leastsell the product concept that was the result of our successfulresearch and development efforts. Doing so would earn more thanjust selling the technology prematurely. If, on the other hand, wedecide to market the driver support system, then we are faced withthe uncertainty of how the product will be received by ourcustomers.”“You completely lost me.” snipes Marc.Max, Julie’s assistant, just shakes his head and murmurs, “thosetechno-nerds. ”Brian starts to explain: “Sorry for the confusion. Let’s just gothrough it again, step by step.” “Good idea—and perhaps makesmaller steps!” Julie obviously dislikes Brian’s style ofpresentation.“OK, the first decision we are facing is whether to invest inresearch for the road scanningdevice.”“How much would that cost us?” asks Marc.“Our estimated budget for this is $300,000. Once we invest thatmoney, the outcome of the research effort is somewhat uncertain.Our engineers assess the probability of successful research at 80percent.”“That’s a pretty optimistic success rate, don’t you think?” Julieremarks sarcastically. She still remembers the disaster withBrian’s last project, the fingerprint-based car security system.After spending half a million dollars, the development engineersconcluded that it would be impossible to produce the securitysystem at an attractive price.Brian senses Julie’s hostility and shoots back: “In engineering weare quite accustomed to these success rates— something we can’t sayabout marketing. ”“What would be the next step?” intervenes Marc.“Hm, sorry. If the research is not successful, then we can onlysell the DSS in its currentform.”“The profit estimate for that scenario is $2 million,” Julie throwsin.“If, however, the research effort is successful, then we will haveto make another decision,namely, whether to go on to the development stage.”“If we wouldn’t want to develop a product at that point, would thatmean that we would have to sell the DSS as it is now?” asksMax.“Yes, Max. Except that additionally we would earn some $200,000from selling our research results to GM. Their research division isvery interested in our work and they have offered me that money forour findings.”“Ah, now that’s good news,” remarks Julie.Brian continues, “If, however, after successfully completing theresearch stage, we decide to develop a new product then we’ll haveto spend another $800,000 for that task, at a chance of 35 percentof not being successful.”“So you are telling us we’ll have to spend $800,000 for a ticket ina lottery where we have a 35 percent chance of not winninganything?” asks Julie.“Julie, don’t focus on the losses, but on the potential gains! Thechance of winning in this lottery, as you call it, is 65 percent. Ibelieve that that’s much more than with a normal lottery ticket,”says Marc.“Thanks, Marc,” says Brian. “Once we invest that money indevelopment, we have two possible outcomes: either we will besuccessful in developing the road scanning device or we won’t. Ifwe fail, then once again we’ll sell the DSS in its current form andcash in the $200,000 from GM for the research results. If thedevelopment process is successful, then we have to decide whetherto market the new product.”“Why wouldn’t we want to market it after successfully developingit?” asks Marc.“That’s a good question. Basically what I mean is that we coulddecide not to sell the product ourselves but instead give the rightto sell it to somebody else, to GM, for example. They would pay us$1 million for it.”“I like those numbers!” remarks Julie.“Once we decide to build the product and market it, we will facethe market uncertainties and I’m sure that Julie has those numbersready for us. Thanks.”At this point, Brian sits down and Julie comes forward to give herpresentation. Immediately some colorful slides are projected on thewall behind her as Max operates the computer.“Thanks, Brian. Well, here’s the data we have been able to gatherfrom some marketing research. The acceptance of our new product inthe market can be high, medium, or low,” Julie is pointing to somefigures projected on the wall behind her. “Our estimates indicatethat high acceptance would result in profits of $8.0 million, andthat medium acceptance would give us $4.0 million. In theunfortunate case of a poor reception by our customers, we stillexpect $2.2 million in profit. I should mention that these profitsdo not include the additional costs of marketing or R&Dexpenses.”“So, you are saying that in the worst case we’ll make barely moremoney than with the current product?” asks Brian.“Yes, that’s what I am saying.”Marc.“What budget would you need for the marketing of our DSS with theroad scanner?” asks“For that we would need an additional $200,000 on top of whathas already been included inthe profit estimates,” Julie replies.“What are the chances of ending up with a high, medium, or lowacceptance of the new DSS?” asks Brian.“We can see those numbers at the bottom of the slide,” says Julie,while she is turning toward the projection behind her. There is a30 percent chance of high market acceptance and a 20 percent chanceof low market acceptance.At this point, Marc moves in his seat and asks: “Given all thesenumbers and bits of information, what are you suggesting that wedo?”(a) Organize the available data on cost andprofit estimates in a table.(b) Formulate the problem in a decision tree.Clearly distinguish between decision and event nodes.(c) Calculate the expected payoffs for each nodein the decision tree.(d) What is BAAG’s optimal policy according toBayes’decision rule?(e) What would be the expected value of perfectinformation on the outcome of the research effort? (f ) What wouldbe the expected value of perfect information on the outcome of thedevelopment effort?(g) Marc is a risk-averse decision maker. In anumber of interviews, his utility function for money was assessedto beu(M) = 1 – e –M/12 , -------------------- 1 – e –1/12where M is the company’s net profit in units of hundreds ofthousands of dollars (e.g., M = 8 would imply a net profit of$800,000). Using Marc’s utility function, calculate the utility foreach terminal branch of the decision tree.(h) Determine the expected utilities for allnodes in the decision tree.(i) Based on Marc’s utility function, what isBAAG’s optimal policy?(j) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of theresearch effort?(k) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of thedevelopment effort?

Submitted by Mariah C. SOLVED: Decision Analysis with Probability:On a sunny May morning, Marc Binton, CEO of Bay Area AutomobileGadgets (BAAG), enters the conference room on the 40th floor of theGates building in San Francisco, where BAAG’s offices are located.The other executive officers of the company have already gathered.The meeting has only one item on its agenda: planning a researchand development project to develop a new driver support system(DSS). Brian Huang, Manager of Research and Development, is walkingaround nervously. He has to inform the group about the R Dstrategy he has developed for the DSS. Marc has identified DSS asthe strategic new product for the company. Julie Aker,VicePresident of Marketing, will speak after Brian. She will givedetailed information about the target segment, expected sales, andmarketing costs associated with the introduction of the DSS.BAAG builds electronic nonaudio equipment for luxury cars. Foundedby a group of Stanford graduates, the company sold its firstproduct—a car routing system relying on a technology called globalpositioning satellites (GPS)—a few years ago. Such routing systemshelp drivers to find directions to their desired destinations usingsatellites to determine the exact position of the car. To keep upwith technology and to meet the wishes of their customers, thecompany has added a number of new features to its router during thelast few years. The DSS will be a completely new product,incorporating recent developments in GPS as well as voicerecognition and display technologies. Marc strongly supports thisproduct, as it will give BAAG a competitive advantage over itsAsian and European competitors.Driver support systems have been a field of intense research formore than a decade. These systems provide the driver with a widerange of information, such as directions, road conditions, trafficupdates, etc. The information exchange can take place verbally orvia projection of text onto the windscreen. Other features help thedriver avoid obstacles that have been identified by cars ahead onthe road (these cars transmit the information to the followingvehicles). Marc wants to incorporate all these features and othertechnologies into one support system that would then be sold toBAAG’s customers in the automobile industry.After all the attendees have taken their seats, Brian starts hispresentation: “Marc asked me to inform you about our efforts withthe driver support system, particularly the road scanning device.We have reached a stage where we basically have to make a go orno-go decision concerning the research for this device, which, asyou all know by now, is a key feature in the DSS. We have alreadyintegrated the other devices, such as the PGS-based positioning anddirection system. The question we have to deal with is whether tofund basic research into the road scanning device. If this researchwere successful, we then would have to decide if we want to developa product based on these results—or if we just want to sell thetechnology without developing a product. If we do decide to developthe product ourselves, there is a chance that the productdevelopment process might not be successful. In that case, we couldstill sell the technology. In the case of successful productdevelopment, we would have to decide whether to market the product.If we decide not to market the developed product, we could at leastsell the product concept that was the result of our successfulresearch and development efforts. Doing so would earn more thanjust selling the technology prematurely. If, on the other hand, wedecide to market the driver support system, then we are faced withthe uncertainty of how the product will be received by ourcustomers.”“You completely lost me.” snipes Marc.Max, Julie’s assistant, just shakes his head and murmurs, “thosetechno-nerds. ”Brian starts to explain: “Sorry for the confusion. Let’s just gothrough it again, step by step.” “Good idea—and perhaps makesmaller steps!” Julie obviously dislikes Brian’s style ofpresentation.“OK, the first decision we are facing is whether to invest inresearch for the road scanningdevice.”“How much would that cost us?” asks Marc.“Our estimated budget for this is 300,000. Once we invest thatmoney, the outcome of the research effort is somewhat uncertain.Our engineers assess the probability of successful research at 80percent.”“That’s a pretty optimistic success rate, don’t you think?” Julieremarks sarcastically. She still remembers the disaster withBrian’s last project, the fingerprint-based car security system.After spending half a million dollars, the development engineersconcluded that it would be impossible to produce the securitysystem at an attractive price.Brian senses Julie’s hostility and shoots back: “In engineering weare quite accustomed to these success rates— something we can’t sayabout marketing. ”“What would be the next step?” intervenes Marc.“Hm, sorry. If the research is not successful, then we can onlysell the DSS in its currentform.”“The profit estimate for that scenario is2 million,” Julie throwsin.“If, however, the research effort is successful, then we will haveto make another decision,namely, whether to go on to the development stage.”“If we wouldn’t want to develop a product at that point, would thatmean that we would have to sell the DSS as it is now?” asksMax.“Yes, Max. Except that additionally we would earn some 200,000from selling our research results to GM. Their research division isvery interested in our work and they have offered me that money forour findings.”“Ah, now that’s good news,” remarks Julie.Brian continues, “If, however, after successfully completing theresearch stage, we decide to develop a new product then we’ll haveto spend another800,000 for that task, at a chance of 35 percentof not being successful.”“So you are telling us we’ll have to spend 800,000 for a ticket ina lottery where we have a 35 percent chance of not winninganything?” asks Julie.“Julie, don’t focus on the losses, but on the potential gains! Thechance of winning in this lottery, as you call it, is 65 percent. Ibelieve that that’s much more than with a normal lottery ticket,”says Marc.“Thanks, Marc,” says Brian. “Once we invest that money indevelopment, we have two possible outcomes: either we will besuccessful in developing the road scanning device or we won’t. Ifwe fail, then once again we’ll sell the DSS in its current form andcash in the200,000 from GM for the research results. If thedevelopment process is successful, then we have to decide whetherto market the new product.”“Why wouldn’t we want to market it after successfully developingit?” asks Marc.“That’s a good question. Basically what I mean is that we coulddecide not to sell the product ourselves but instead give the rightto sell it to somebody else, to GM, for example. They would pay us1 million for it.”“I like those numbers!” remarks Julie.“Once we decide to build the product and market it, we will facethe market uncertainties and I’m sure that Julie has those numbersready for us. Thanks.”At this point, Brian sits down and Julie comes forward to give herpresentation. Immediately some colorful slides are projected on thewall behind her as Max operates the computer.“Thanks, Brian. Well, here’s the data we have been able to gatherfrom some marketing research. The acceptance of our new product inthe market can be high, medium, or low,” Julie is pointing to somefigures projected on the wall behind her. “Our estimates indicatethat high acceptance would result in profits of8.0 million, andthat medium acceptance would give us 4.0 million. In theunfortunate case of a poor reception by our customers, we stillexpect2.2 million in profit. I should mention that these profitsdo not include the additional costs of marketing or R Dexpenses.”“So, you are saying that in the worst case we’ll make barely moremoney than with the current product?” asks Brian.“Yes, that’s what I am saying.”Marc.“What budget would you need for the marketing of our DSS with theroad scanner?” asks“For that we would need an additional 200,000 on top of whathas already been included inthe profit estimates,” Julie replies.“What are the chances of ending up with a high, medium, or lowacceptance of the new DSS?” asks Brian.“We can see those numbers at the bottom of the slide,” says Julie,while she is turning toward the projection behind her. There is a30 percent chance of high market acceptance and a 20 percent chanceof low market acceptance.At this point, Marc moves in his seat and asks: “Given all thesenumbers and bits of information, what are you suggesting that wedo?”(a) Organize the available data on cost andprofit estimates in a table.(b) Formulate the problem in a decision tree.Clearly distinguish between decision and event nodes.(c) Calculate the expected payoffs for each nodein the decision tree.(d) What is BAAG’s optimal policy according toBayes’decision rule?(e) What would be the expected value of perfectinformation on the outcome of the research effort? (f ) What wouldbe the expected value of perfect information on the outcome of thedevelopment effort?(g) Marc is a risk-averse decision maker. In anumber of interviews, his utility function for money was assessedto beu(M) = 1 – e –M/12 , ——————– 1 – e –1/12where M is the company’s net profit in units of hundreds ofthousands of dollars (e.g., M = 8 would imply a net profit of800,000). Using Marc’s utility function, calculate the utility foreach terminal branch of the decision tree.(h) Determine the expected utilities for allnodes in the decision tree.(i) Based on Marc’s utility function, what isBAAG’s optimal policy?(j) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of theresearch effort?(k) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of thedevelopment effort? (2) Oct. 25, 2021 SOLVED: Decision Analysis with Probability:On a sunny May morning, Marc Binton, CEO of Bay Area AutomobileGadgets (BAAG), enters the conference room on the 40th floor of theGates building in San Francisco, where BAAG’s offices are located.The other executive officers of the company have already gathered.The meeting has only one item on its agenda: planning a researchand development project to develop a new driver support system(DSS). Brian Huang, Manager of Research and Development, is walkingaround nervously. He has to inform the group about the R Dstrategy he has developed for the DSS. Marc has identified DSS asthe strategic new product for the company. Julie Aker,VicePresident of Marketing, will speak after Brian. She will givedetailed information about the target segment, expected sales, andmarketing costs associated with the introduction of the DSS.BAAG builds electronic nonaudio equipment for luxury cars. Foundedby a group of Stanford graduates, the company sold its firstproduct—a car routing system relying on a technology called globalpositioning satellites (GPS)—a few years ago. Such routing systemshelp drivers to find directions to their desired destinations usingsatellites to determine the exact position of the car. To keep upwith technology and to meet the wishes of their customers, thecompany has added a number of new features to its router during thelast few years. The DSS will be a completely new product,incorporating recent developments in GPS as well as voicerecognition and display technologies. Marc strongly supports thisproduct, as it will give BAAG a competitive advantage over itsAsian and European competitors.Driver support systems have been a field of intense research formore than a decade. These systems provide the driver with a widerange of information, such as directions, road conditions, trafficupdates, etc. The information exchange can take place verbally orvia projection of text onto the windscreen. Other features help thedriver avoid obstacles that have been identified by cars ahead onthe road (these cars transmit the information to the followingvehicles). Marc wants to incorporate all these features and othertechnologies into one support system that would then be sold toBAAG’s customers in the automobile industry.After all the attendees have taken their seats, Brian starts hispresentation: “Marc asked me to inform you about our efforts withthe driver support system, particularly the road scanning device.We have reached a stage where we basically have to make a go orno-go decision concerning the research for this device, which, asyou all know by now, is a key feature in the DSS. We have alreadyintegrated the other devices, such as the PGS-based positioning anddirection system. The question we have to deal with is whether tofund basic research into the road scanning device. If this researchwere successful, we then would have to decide if we want to developa product based on these results—or if we just want to sell thetechnology without developing a product. If we do decide to developthe product ourselves, there is a chance that the productdevelopment process might not be successful. In that case, we couldstill sell the technology. In the case of successful productdevelopment, we would have to decide whether to market the product.If we decide not to market the developed product, we could at leastsell the product concept that was the result of our successfulresearch and development efforts. Doing so would earn more thanjust selling the technology prematurely. If, on the other hand, wedecide to market the driver support system, then we are faced withthe uncertainty of how the product will be received by ourcustomers.”“You completely lost me.” snipes Marc.Max, Julie’s assistant, just shakes his head and murmurs, “thosetechno-nerds. ”Brian starts to explain: “Sorry for the confusion. Let’s just gothrough it again, step by step.” “Good idea—and perhaps makesmaller steps!” Julie obviously dislikes Brian’s style ofpresentation.“OK, the first decision we are facing is whether to invest inresearch for the road scanningdevice.”“How much would that cost us?” asks Marc.“Our estimated budget for this is 300,000. Once we invest thatmoney, the outcome of the research effort is somewhat uncertain.Our engineers assess the probability of successful research at 80percent.”“That’s a pretty optimistic success rate, don’t you think?” Julieremarks sarcastically. She still remembers the disaster withBrian’s last project, the fingerprint-based car security system.After spending half a million dollars, the development engineersconcluded that it would be impossible to produce the securitysystem at an attractive price.Brian senses Julie’s hostility and shoots back: “In engineering weare quite accustomed to these success rates— something we can’t sayabout marketing. ”“What would be the next step?” intervenes Marc.“Hm, sorry. If the research is not successful, then we can onlysell the DSS in its currentform.”“The profit estimate for that scenario is2 million,” Julie throwsin.“If, however, the research effort is successful, then we will haveto make another decision,namely, whether to go on to the development stage.”“If we wouldn’t want to develop a product at that point, would thatmean that we would have to sell the DSS as it is now?” asksMax.“Yes, Max. Except that additionally we would earn some 200,000from selling our research results to GM. Their research division isvery interested in our work and they have offered me that money forour findings.”“Ah, now that’s good news,” remarks Julie.Brian continues, “If, however, after successfully completing theresearch stage, we decide to develop a new product then we’ll haveto spend another800,000 for that task, at a chance of 35 percentof not being successful.”“So you are telling us we’ll have to spend 800,000 for a ticket ina lottery where we have a 35 percent chance of not winninganything?” asks Julie.“Julie, don’t focus on the losses, but on the potential gains! Thechance of winning in this lottery, as you call it, is 65 percent. Ibelieve that that’s much more than with a normal lottery ticket,”says Marc.“Thanks, Marc,” says Brian. “Once we invest that money indevelopment, we have two possible outcomes: either we will besuccessful in developing the road scanning device or we won’t. Ifwe fail, then once again we’ll sell the DSS in its current form andcash in the200,000 from GM for the research results. If thedevelopment process is successful, then we have to decide whetherto market the new product.”“Why wouldn’t we want to market it after successfully developingit?” asks Marc.“That’s a good question. Basically what I mean is that we coulddecide not to sell the product ourselves but instead give the rightto sell it to somebody else, to GM, for example. They would pay us1 million for it.”“I like those numbers!” remarks Julie.“Once we decide to build the product and market it, we will facethe market uncertainties and I’m sure that Julie has those numbersready for us. Thanks.”At this point, Brian sits down and Julie comes forward to give herpresentation. Immediately some colorful slides are projected on thewall behind her as Max operates the computer.“Thanks, Brian. Well, here’s the data we have been able to gatherfrom some marketing research. The acceptance of our new product inthe market can be high, medium, or low,” Julie is pointing to somefigures projected on the wall behind her. “Our estimates indicatethat high acceptance would result in profits of8.0 million, andthat medium acceptance would give us 4.0 million. In theunfortunate case of a poor reception by our customers, we stillexpect2.2 million in profit. I should mention that these profitsdo not include the additional costs of marketing or R Dexpenses.”“So, you are saying that in the worst case we’ll make barely moremoney than with the current product?” asks Brian.“Yes, that’s what I am saying.”Marc.“What budget would you need for the marketing of our DSS with theroad scanner?” asks“For that we would need an additional 200,000 on top of whathas already been included inthe profit estimates,” Julie replies.“What are the chances of ending up with a high, medium, or lowacceptance of the new DSS?” asks Brian.“We can see those numbers at the bottom of the slide,” says Julie,while she is turning toward the projection behind her. There is a30 percent chance of high market acceptance and a 20 percent chanceof low market acceptance.At this point, Marc moves in his seat and asks: “Given all thesenumbers and bits of information, what are you suggesting that wedo?”(a) Organize the available data on cost andprofit estimates in a table.(b) Formulate the problem in a decision tree.Clearly distinguish between decision and event nodes.(c) Calculate the expected payoffs for each nodein the decision tree.(d) What is BAAG’s optimal policy according toBayes’decision rule?(e) What would be the expected value of perfectinformation on the outcome of the research effort? (f ) What wouldbe the expected value of perfect information on the outcome of thedevelopment effort?(g) Marc is a risk-averse decision maker. In anumber of interviews, his utility function for money was assessedto beu(M) = 1 – e –M/12 , ——————– 1 – e –1/12where M is the company’s net profit in units of hundreds ofthousands of dollars (e.g., M = 8 would imply a net profit of800,000). Using Marc’s utility function, calculate the utility foreach terminal branch of the decision tree.(h) Determine the expected utilities for allnodes in the decision tree.(i) Based on Marc’s utility function, what isBAAG’s optimal policy?(j) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of theresearch effort?(k) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of thedevelopment effort? (3) 05:48 p.m.

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SOLVED: Decision Analysis with Probability:On a sunny May morning, Marc Binton, CEO of Bay Area AutomobileGadgets (BAAG), enters the conference room on the 40th floor of theGates building in San Francisco, where BAAG’s offices are located.The other executive officers of the company have already gathered.The meeting has only one item on its agenda: planning a researchand development project to develop a new driver support system(DSS). Brian Huang, Manager of Research and Development, is walkingaround nervously. He has to inform the group about the R Dstrategy he has developed for the DSS. Marc has identified DSS asthe strategic new product for the company. Julie Aker,VicePresident of Marketing, will speak after Brian. She will givedetailed information about the target segment, expected sales, andmarketing costs associated with the introduction of the DSS.BAAG builds electronic nonaudio equipment for luxury cars. Foundedby a group of Stanford graduates, the company sold its firstproduct—a car routing system relying on a technology called globalpositioning satellites (GPS)—a few years ago. Such routing systemshelp drivers to find directions to their desired destinations usingsatellites to determine the exact position of the car. To keep upwith technology and to meet the wishes of their customers, thecompany has added a number of new features to its router during thelast few years. The DSS will be a completely new product,incorporating recent developments in GPS as well as voicerecognition and display technologies. Marc strongly supports thisproduct, as it will give BAAG a competitive advantage over itsAsian and European competitors.Driver support systems have been a field of intense research formore than a decade. These systems provide the driver with a widerange of information, such as directions, road conditions, trafficupdates, etc. The information exchange can take place verbally orvia projection of text onto the windscreen. Other features help thedriver avoid obstacles that have been identified by cars ahead onthe road (these cars transmit the information to the followingvehicles). Marc wants to incorporate all these features and othertechnologies into one support system that would then be sold toBAAG’s customers in the automobile industry.After all the attendees have taken their seats, Brian starts hispresentation: “Marc asked me to inform you about our efforts withthe driver support system, particularly the road scanning device.We have reached a stage where we basically have to make a go orno-go decision concerning the research for this device, which, asyou all know by now, is a key feature in the DSS. We have alreadyintegrated the other devices, such as the PGS-based positioning anddirection system. The question we have to deal with is whether tofund basic research into the road scanning device. If this researchwere successful, we then would have to decide if we want to developa product based on these results—or if we just want to sell thetechnology without developing a product. If we do decide to developthe product ourselves, there is a chance that the productdevelopment process might not be successful. In that case, we couldstill sell the technology. In the case of successful productdevelopment, we would have to decide whether to market the product.If we decide not to market the developed product, we could at leastsell the product concept that was the result of our successfulresearch and development efforts. Doing so would earn more thanjust selling the technology prematurely. If, on the other hand, wedecide to market the driver support system, then we are faced withthe uncertainty of how the product will be received by ourcustomers.”“You completely lost me.” snipes Marc.Max, Julie’s assistant, just shakes his head and murmurs, “thosetechno-nerds. ”Brian starts to explain: “Sorry for the confusion. Let’s just gothrough it again, step by step.” “Good idea—and perhaps makesmaller steps!” Julie obviously dislikes Brian’s style ofpresentation.“OK, the first decision we are facing is whether to invest inresearch for the road scanningdevice.”“How much would that cost us?” asks Marc.“Our estimated budget for this is 300,000. Once we invest thatmoney, the outcome of the research effort is somewhat uncertain.Our engineers assess the probability of successful research at 80percent.”“That’s a pretty optimistic success rate, don’t you think?” Julieremarks sarcastically. She still remembers the disaster withBrian’s last project, the fingerprint-based car security system.After spending half a million dollars, the development engineersconcluded that it would be impossible to produce the securitysystem at an attractive price.Brian senses Julie’s hostility and shoots back: “In engineering weare quite accustomed to these success rates— something we can’t sayabout marketing. ”“What would be the next step?” intervenes Marc.“Hm, sorry. If the research is not successful, then we can onlysell the DSS in its currentform.”“The profit estimate for that scenario is2 million,” Julie throwsin.“If, however, the research effort is successful, then we will haveto make another decision,namely, whether to go on to the development stage.”“If we wouldn’t want to develop a product at that point, would thatmean that we would have to sell the DSS as it is now?” asksMax.“Yes, Max. Except that additionally we would earn some 200,000from selling our research results to GM. Their research division isvery interested in our work and they have offered me that money forour findings.”“Ah, now that’s good news,” remarks Julie.Brian continues, “If, however, after successfully completing theresearch stage, we decide to develop a new product then we’ll haveto spend another800,000 for that task, at a chance of 35 percentof not being successful.”“So you are telling us we’ll have to spend 800,000 for a ticket ina lottery where we have a 35 percent chance of not winninganything?” asks Julie.“Julie, don’t focus on the losses, but on the potential gains! Thechance of winning in this lottery, as you call it, is 65 percent. Ibelieve that that’s much more than with a normal lottery ticket,”says Marc.“Thanks, Marc,” says Brian. “Once we invest that money indevelopment, we have two possible outcomes: either we will besuccessful in developing the road scanning device or we won’t. Ifwe fail, then once again we’ll sell the DSS in its current form andcash in the200,000 from GM for the research results. If thedevelopment process is successful, then we have to decide whetherto market the new product.”“Why wouldn’t we want to market it after successfully developingit?” asks Marc.“That’s a good question. Basically what I mean is that we coulddecide not to sell the product ourselves but instead give the rightto sell it to somebody else, to GM, for example. They would pay us1 million for it.”“I like those numbers!” remarks Julie.“Once we decide to build the product and market it, we will facethe market uncertainties and I’m sure that Julie has those numbersready for us. Thanks.”At this point, Brian sits down and Julie comes forward to give herpresentation. Immediately some colorful slides are projected on thewall behind her as Max operates the computer.“Thanks, Brian. Well, here’s the data we have been able to gatherfrom some marketing research. The acceptance of our new product inthe market can be high, medium, or low,” Julie is pointing to somefigures projected on the wall behind her. “Our estimates indicatethat high acceptance would result in profits of8.0 million, andthat medium acceptance would give us 4.0 million. In theunfortunate case of a poor reception by our customers, we stillexpect2.2 million in profit. I should mention that these profitsdo not include the additional costs of marketing or R Dexpenses.”“So, you are saying that in the worst case we’ll make barely moremoney than with the current product?” asks Brian.“Yes, that’s what I am saying.”Marc.“What budget would you need for the marketing of our DSS with theroad scanner?” asks“For that we would need an additional 200,000 on top of whathas already been included inthe profit estimates,” Julie replies.“What are the chances of ending up with a high, medium, or lowacceptance of the new DSS?” asks Brian.“We can see those numbers at the bottom of the slide,” says Julie,while she is turning toward the projection behind her. There is a30 percent chance of high market acceptance and a 20 percent chanceof low market acceptance.At this point, Marc moves in his seat and asks: “Given all thesenumbers and bits of information, what are you suggesting that wedo?”(a) Organize the available data on cost andprofit estimates in a table.(b) Formulate the problem in a decision tree.Clearly distinguish between decision and event nodes.(c) Calculate the expected payoffs for each nodein the decision tree.(d) What is BAAG’s optimal policy according toBayes’decision rule?(e) What would be the expected value of perfectinformation on the outcome of the research effort? (f ) What wouldbe the expected value of perfect information on the outcome of thedevelopment effort?(g) Marc is a risk-averse decision maker. In anumber of interviews, his utility function for money was assessedto beu(M) = 1 – e –M/12 , ——————– 1 – e –1/12where M is the company’s net profit in units of hundreds ofthousands of dollars (e.g., M = 8 would imply a net profit of800,000). Using Marc’s utility function, calculate the utility foreach terminal branch of the decision tree.(h) Determine the expected utilities for allnodes in the decision tree.(i) Based on Marc’s utility function, what isBAAG’s optimal policy?(j) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of theresearch effort?(k) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of thedevelopment effort? (4) SOLVED: Decision Analysis with Probability:On a sunny May morning, Marc Binton, CEO of Bay Area AutomobileGadgets (BAAG), enters the conference room on the 40th floor of theGates building in San Francisco, where BAAG’s offices are located.The other executive officers of the company have already gathered.The meeting has only one item on its agenda: planning a researchand development project to develop a new driver support system(DSS). Brian Huang, Manager of Research and Development, is walkingaround nervously. He has to inform the group about the R Dstrategy he has developed for the DSS. Marc has identified DSS asthe strategic new product for the company. Julie Aker,VicePresident of Marketing, will speak after Brian. She will givedetailed information about the target segment, expected sales, andmarketing costs associated with the introduction of the DSS.BAAG builds electronic nonaudio equipment for luxury cars. Foundedby a group of Stanford graduates, the company sold its firstproduct—a car routing system relying on a technology called globalpositioning satellites (GPS)—a few years ago. Such routing systemshelp drivers to find directions to their desired destinations usingsatellites to determine the exact position of the car. To keep upwith technology and to meet the wishes of their customers, thecompany has added a number of new features to its router during thelast few years. The DSS will be a completely new product,incorporating recent developments in GPS as well as voicerecognition and display technologies. Marc strongly supports thisproduct, as it will give BAAG a competitive advantage over itsAsian and European competitors.Driver support systems have been a field of intense research formore than a decade. These systems provide the driver with a widerange of information, such as directions, road conditions, trafficupdates, etc. The information exchange can take place verbally orvia projection of text onto the windscreen. Other features help thedriver avoid obstacles that have been identified by cars ahead onthe road (these cars transmit the information to the followingvehicles). Marc wants to incorporate all these features and othertechnologies into one support system that would then be sold toBAAG’s customers in the automobile industry.After all the attendees have taken their seats, Brian starts hispresentation: “Marc asked me to inform you about our efforts withthe driver support system, particularly the road scanning device.We have reached a stage where we basically have to make a go orno-go decision concerning the research for this device, which, asyou all know by now, is a key feature in the DSS. We have alreadyintegrated the other devices, such as the PGS-based positioning anddirection system. The question we have to deal with is whether tofund basic research into the road scanning device. If this researchwere successful, we then would have to decide if we want to developa product based on these results—or if we just want to sell thetechnology without developing a product. If we do decide to developthe product ourselves, there is a chance that the productdevelopment process might not be successful. In that case, we couldstill sell the technology. In the case of successful productdevelopment, we would have to decide whether to market the product.If we decide not to market the developed product, we could at leastsell the product concept that was the result of our successfulresearch and development efforts. Doing so would earn more thanjust selling the technology prematurely. If, on the other hand, wedecide to market the driver support system, then we are faced withthe uncertainty of how the product will be received by ourcustomers.”“You completely lost me.” snipes Marc.Max, Julie’s assistant, just shakes his head and murmurs, “thosetechno-nerds. ”Brian starts to explain: “Sorry for the confusion. Let’s just gothrough it again, step by step.” “Good idea—and perhaps makesmaller steps!” Julie obviously dislikes Brian’s style ofpresentation.“OK, the first decision we are facing is whether to invest inresearch for the road scanningdevice.”“How much would that cost us?” asks Marc.“Our estimated budget for this is 300,000. Once we invest thatmoney, the outcome of the research effort is somewhat uncertain.Our engineers assess the probability of successful research at 80percent.”“That’s a pretty optimistic success rate, don’t you think?” Julieremarks sarcastically. She still remembers the disaster withBrian’s last project, the fingerprint-based car security system.After spending half a million dollars, the development engineersconcluded that it would be impossible to produce the securitysystem at an attractive price.Brian senses Julie’s hostility and shoots back: “In engineering weare quite accustomed to these success rates— something we can’t sayabout marketing. ”“What would be the next step?” intervenes Marc.“Hm, sorry. If the research is not successful, then we can onlysell the DSS in its currentform.”“The profit estimate for that scenario is2 million,” Julie throwsin.“If, however, the research effort is successful, then we will haveto make another decision,namely, whether to go on to the development stage.”“If we wouldn’t want to develop a product at that point, would thatmean that we would have to sell the DSS as it is now?” asksMax.“Yes, Max. Except that additionally we would earn some 200,000from selling our research results to GM. Their research division isvery interested in our work and they have offered me that money forour findings.”“Ah, now that’s good news,” remarks Julie.Brian continues, “If, however, after successfully completing theresearch stage, we decide to develop a new product then we’ll haveto spend another800,000 for that task, at a chance of 35 percentof not being successful.”“So you are telling us we’ll have to spend 800,000 for a ticket ina lottery where we have a 35 percent chance of not winninganything?” asks Julie.“Julie, don’t focus on the losses, but on the potential gains! Thechance of winning in this lottery, as you call it, is 65 percent. Ibelieve that that’s much more than with a normal lottery ticket,”says Marc.“Thanks, Marc,” says Brian. “Once we invest that money indevelopment, we have two possible outcomes: either we will besuccessful in developing the road scanning device or we won’t. Ifwe fail, then once again we’ll sell the DSS in its current form andcash in the200,000 from GM for the research results. If thedevelopment process is successful, then we have to decide whetherto market the new product.”“Why wouldn’t we want to market it after successfully developingit?” asks Marc.“That’s a good question. Basically what I mean is that we coulddecide not to sell the product ourselves but instead give the rightto sell it to somebody else, to GM, for example. They would pay us1 million for it.”“I like those numbers!” remarks Julie.“Once we decide to build the product and market it, we will facethe market uncertainties and I’m sure that Julie has those numbersready for us. Thanks.”At this point, Brian sits down and Julie comes forward to give herpresentation. Immediately some colorful slides are projected on thewall behind her as Max operates the computer.“Thanks, Brian. Well, here’s the data we have been able to gatherfrom some marketing research. The acceptance of our new product inthe market can be high, medium, or low,” Julie is pointing to somefigures projected on the wall behind her. “Our estimates indicatethat high acceptance would result in profits of8.0 million, andthat medium acceptance would give us 4.0 million. In theunfortunate case of a poor reception by our customers, we stillexpect2.2 million in profit. I should mention that these profitsdo not include the additional costs of marketing or R Dexpenses.”“So, you are saying that in the worst case we’ll make barely moremoney than with the current product?” asks Brian.“Yes, that’s what I am saying.”Marc.“What budget would you need for the marketing of our DSS with theroad scanner?” asks“For that we would need an additional 200,000 on top of whathas already been included inthe profit estimates,” Julie replies.“What are the chances of ending up with a high, medium, or lowacceptance of the new DSS?” asks Brian.“We can see those numbers at the bottom of the slide,” says Julie,while she is turning toward the projection behind her. There is a30 percent chance of high market acceptance and a 20 percent chanceof low market acceptance.At this point, Marc moves in his seat and asks: “Given all thesenumbers and bits of information, what are you suggesting that wedo?”(a) Organize the available data on cost andprofit estimates in a table.(b) Formulate the problem in a decision tree.Clearly distinguish between decision and event nodes.(c) Calculate the expected payoffs for each nodein the decision tree.(d) What is BAAG’s optimal policy according toBayes’decision rule?(e) What would be the expected value of perfectinformation on the outcome of the research effort? (f ) What wouldbe the expected value of perfect information on the outcome of thedevelopment effort?(g) Marc is a risk-averse decision maker. In anumber of interviews, his utility function for money was assessedto beu(M) = 1 – e –M/12 , ——————– 1 – e –1/12where M is the company’s net profit in units of hundreds ofthousands of dollars (e.g., M = 8 would imply a net profit of800,000). Using Marc’s utility function, calculate the utility foreach terminal branch of the decision tree.(h) Determine the expected utilities for allnodes in the decision tree.(i) Based on Marc’s utility function, what isBAAG’s optimal policy?(j) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of theresearch effort?(k) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of thedevelopment effort? (5) SOLVED: Decision Analysis with Probability:On a sunny May morning, Marc Binton, CEO of Bay Area AutomobileGadgets (BAAG), enters the conference room on the 40th floor of theGates building in San Francisco, where BAAG’s offices are located.The other executive officers of the company have already gathered.The meeting has only one item on its agenda: planning a researchand development project to develop a new driver support system(DSS). Brian Huang, Manager of Research and Development, is walkingaround nervously. He has to inform the group about the R Dstrategy he has developed for the DSS. Marc has identified DSS asthe strategic new product for the company. Julie Aker,VicePresident of Marketing, will speak after Brian. She will givedetailed information about the target segment, expected sales, andmarketing costs associated with the introduction of the DSS.BAAG builds electronic nonaudio equipment for luxury cars. Foundedby a group of Stanford graduates, the company sold its firstproduct—a car routing system relying on a technology called globalpositioning satellites (GPS)—a few years ago. Such routing systemshelp drivers to find directions to their desired destinations usingsatellites to determine the exact position of the car. To keep upwith technology and to meet the wishes of their customers, thecompany has added a number of new features to its router during thelast few years. The DSS will be a completely new product,incorporating recent developments in GPS as well as voicerecognition and display technologies. Marc strongly supports thisproduct, as it will give BAAG a competitive advantage over itsAsian and European competitors.Driver support systems have been a field of intense research formore than a decade. These systems provide the driver with a widerange of information, such as directions, road conditions, trafficupdates, etc. The information exchange can take place verbally orvia projection of text onto the windscreen. Other features help thedriver avoid obstacles that have been identified by cars ahead onthe road (these cars transmit the information to the followingvehicles). Marc wants to incorporate all these features and othertechnologies into one support system that would then be sold toBAAG’s customers in the automobile industry.After all the attendees have taken their seats, Brian starts hispresentation: “Marc asked me to inform you about our efforts withthe driver support system, particularly the road scanning device.We have reached a stage where we basically have to make a go orno-go decision concerning the research for this device, which, asyou all know by now, is a key feature in the DSS. We have alreadyintegrated the other devices, such as the PGS-based positioning anddirection system. The question we have to deal with is whether tofund basic research into the road scanning device. If this researchwere successful, we then would have to decide if we want to developa product based on these results—or if we just want to sell thetechnology without developing a product. If we do decide to developthe product ourselves, there is a chance that the productdevelopment process might not be successful. In that case, we couldstill sell the technology. In the case of successful productdevelopment, we would have to decide whether to market the product.If we decide not to market the developed product, we could at leastsell the product concept that was the result of our successfulresearch and development efforts. Doing so would earn more thanjust selling the technology prematurely. If, on the other hand, wedecide to market the driver support system, then we are faced withthe uncertainty of how the product will be received by ourcustomers.”“You completely lost me.” snipes Marc.Max, Julie’s assistant, just shakes his head and murmurs, “thosetechno-nerds. ”Brian starts to explain: “Sorry for the confusion. Let’s just gothrough it again, step by step.” “Good idea—and perhaps makesmaller steps!” Julie obviously dislikes Brian’s style ofpresentation.“OK, the first decision we are facing is whether to invest inresearch for the road scanningdevice.”“How much would that cost us?” asks Marc.“Our estimated budget for this is 300,000. Once we invest thatmoney, the outcome of the research effort is somewhat uncertain.Our engineers assess the probability of successful research at 80percent.”“That’s a pretty optimistic success rate, don’t you think?” Julieremarks sarcastically. She still remembers the disaster withBrian’s last project, the fingerprint-based car security system.After spending half a million dollars, the development engineersconcluded that it would be impossible to produce the securitysystem at an attractive price.Brian senses Julie’s hostility and shoots back: “In engineering weare quite accustomed to these success rates— something we can’t sayabout marketing. ”“What would be the next step?” intervenes Marc.“Hm, sorry. If the research is not successful, then we can onlysell the DSS in its currentform.”“The profit estimate for that scenario is2 million,” Julie throwsin.“If, however, the research effort is successful, then we will haveto make another decision,namely, whether to go on to the development stage.”“If we wouldn’t want to develop a product at that point, would thatmean that we would have to sell the DSS as it is now?” asksMax.“Yes, Max. Except that additionally we would earn some 200,000from selling our research results to GM. Their research division isvery interested in our work and they have offered me that money forour findings.”“Ah, now that’s good news,” remarks Julie.Brian continues, “If, however, after successfully completing theresearch stage, we decide to develop a new product then we’ll haveto spend another800,000 for that task, at a chance of 35 percentof not being successful.”“So you are telling us we’ll have to spend 800,000 for a ticket ina lottery where we have a 35 percent chance of not winninganything?” asks Julie.“Julie, don’t focus on the losses, but on the potential gains! Thechance of winning in this lottery, as you call it, is 65 percent. Ibelieve that that’s much more than with a normal lottery ticket,”says Marc.“Thanks, Marc,” says Brian. “Once we invest that money indevelopment, we have two possible outcomes: either we will besuccessful in developing the road scanning device or we won’t. Ifwe fail, then once again we’ll sell the DSS in its current form andcash in the200,000 from GM for the research results. If thedevelopment process is successful, then we have to decide whetherto market the new product.”“Why wouldn’t we want to market it after successfully developingit?” asks Marc.“That’s a good question. Basically what I mean is that we coulddecide not to sell the product ourselves but instead give the rightto sell it to somebody else, to GM, for example. They would pay us1 million for it.”“I like those numbers!” remarks Julie.“Once we decide to build the product and market it, we will facethe market uncertainties and I’m sure that Julie has those numbersready for us. Thanks.”At this point, Brian sits down and Julie comes forward to give herpresentation. Immediately some colorful slides are projected on thewall behind her as Max operates the computer.“Thanks, Brian. Well, here’s the data we have been able to gatherfrom some marketing research. The acceptance of our new product inthe market can be high, medium, or low,” Julie is pointing to somefigures projected on the wall behind her. “Our estimates indicatethat high acceptance would result in profits of8.0 million, andthat medium acceptance would give us 4.0 million. In theunfortunate case of a poor reception by our customers, we stillexpect2.2 million in profit. I should mention that these profitsdo not include the additional costs of marketing or R Dexpenses.”“So, you are saying that in the worst case we’ll make barely moremoney than with the current product?” asks Brian.“Yes, that’s what I am saying.”Marc.“What budget would you need for the marketing of our DSS with theroad scanner?” asks“For that we would need an additional 200,000 on top of whathas already been included inthe profit estimates,” Julie replies.“What are the chances of ending up with a high, medium, or lowacceptance of the new DSS?” asks Brian.“We can see those numbers at the bottom of the slide,” says Julie,while she is turning toward the projection behind her. There is a30 percent chance of high market acceptance and a 20 percent chanceof low market acceptance.At this point, Marc moves in his seat and asks: “Given all thesenumbers and bits of information, what are you suggesting that wedo?”(a) Organize the available data on cost andprofit estimates in a table.(b) Formulate the problem in a decision tree.Clearly distinguish between decision and event nodes.(c) Calculate the expected payoffs for each nodein the decision tree.(d) What is BAAG’s optimal policy according toBayes’decision rule?(e) What would be the expected value of perfectinformation on the outcome of the research effort? (f ) What wouldbe the expected value of perfect information on the outcome of thedevelopment effort?(g) Marc is a risk-averse decision maker. In anumber of interviews, his utility function for money was assessedto beu(M) = 1 – e –M/12 , ——————– 1 – e –1/12where M is the company’s net profit in units of hundreds ofthousands of dollars (e.g., M = 8 would imply a net profit of800,000). Using Marc’s utility function, calculate the utility foreach terminal branch of the decision tree.(h) Determine the expected utilities for allnodes in the decision tree.(i) Based on Marc’s utility function, what isBAAG’s optimal policy?(j) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of theresearch effort?(k) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of thedevelopment effort? (6)

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SOLVED: Decision Analysis with Probability:On a sunny May morning, Marc Binton, CEO of Bay Area AutomobileGadgets (BAAG), enters the conference room on the 40th floor of theGates building in San Francisco, where BAAG’s offices are located.The other executive officers of the company have already gathered.The meeting has only one item on its agenda: planning a researchand development project to develop a new driver support system(DSS). Brian Huang, Manager of Research and Development, is walkingaround nervously. He has to inform the group about the R Dstrategy he has developed for the DSS. Marc has identified DSS asthe strategic new product for the company. Julie Aker,VicePresident of Marketing, will speak after Brian. She will givedetailed information about the target segment, expected sales, andmarketing costs associated with the introduction of the DSS.BAAG builds electronic nonaudio equipment for luxury cars. Foundedby a group of Stanford graduates, the company sold its firstproduct—a car routing system relying on a technology called globalpositioning satellites (GPS)—a few years ago. Such routing systemshelp drivers to find directions to their desired destinations usingsatellites to determine the exact position of the car. To keep upwith technology and to meet the wishes of their customers, thecompany has added a number of new features to its router during thelast few years. The DSS will be a completely new product,incorporating recent developments in GPS as well as voicerecognition and display technologies. Marc strongly supports thisproduct, as it will give BAAG a competitive advantage over itsAsian and European competitors.Driver support systems have been a field of intense research formore than a decade. These systems provide the driver with a widerange of information, such as directions, road conditions, trafficupdates, etc. The information exchange can take place verbally orvia projection of text onto the windscreen. Other features help thedriver avoid obstacles that have been identified by cars ahead onthe road (these cars transmit the information to the followingvehicles). Marc wants to incorporate all these features and othertechnologies into one support system that would then be sold toBAAG’s customers in the automobile industry.After all the attendees have taken their seats, Brian starts hispresentation: “Marc asked me to inform you about our efforts withthe driver support system, particularly the road scanning device.We have reached a stage where we basically have to make a go orno-go decision concerning the research for this device, which, asyou all know by now, is a key feature in the DSS. We have alreadyintegrated the other devices, such as the PGS-based positioning anddirection system. The question we have to deal with is whether tofund basic research into the road scanning device. If this researchwere successful, we then would have to decide if we want to developa product based on these results—or if we just want to sell thetechnology without developing a product. If we do decide to developthe product ourselves, there is a chance that the productdevelopment process might not be successful. In that case, we couldstill sell the technology. In the case of successful productdevelopment, we would have to decide whether to market the product.If we decide not to market the developed product, we could at leastsell the product concept that was the result of our successfulresearch and development efforts. Doing so would earn more thanjust selling the technology prematurely. If, on the other hand, wedecide to market the driver support system, then we are faced withthe uncertainty of how the product will be received by ourcustomers.”“You completely lost me.” snipes Marc.Max, Julie’s assistant, just shakes his head and murmurs, “thosetechno-nerds. ”Brian starts to explain: “Sorry for the confusion. Let’s just gothrough it again, step by step.” “Good idea—and perhaps makesmaller steps!” Julie obviously dislikes Brian’s style ofpresentation.“OK, the first decision we are facing is whether to invest inresearch for the road scanningdevice.”“How much would that cost us?” asks Marc.“Our estimated budget for this is 300,000. Once we invest thatmoney, the outcome of the research effort is somewhat uncertain.Our engineers assess the probability of successful research at 80percent.”“That’s a pretty optimistic success rate, don’t you think?” Julieremarks sarcastically. She still remembers the disaster withBrian’s last project, the fingerprint-based car security system.After spending half a million dollars, the development engineersconcluded that it would be impossible to produce the securitysystem at an attractive price.Brian senses Julie’s hostility and shoots back: “In engineering weare quite accustomed to these success rates— something we can’t sayabout marketing. ”“What would be the next step?” intervenes Marc.“Hm, sorry. If the research is not successful, then we can onlysell the DSS in its currentform.”“The profit estimate for that scenario is2 million,” Julie throwsin.“If, however, the research effort is successful, then we will haveto make another decision,namely, whether to go on to the development stage.”“If we wouldn’t want to develop a product at that point, would thatmean that we would have to sell the DSS as it is now?” asksMax.“Yes, Max. Except that additionally we would earn some 200,000from selling our research results to GM. Their research division isvery interested in our work and they have offered me that money forour findings.”“Ah, now that’s good news,” remarks Julie.Brian continues, “If, however, after successfully completing theresearch stage, we decide to develop a new product then we’ll haveto spend another800,000 for that task, at a chance of 35 percentof not being successful.”“So you are telling us we’ll have to spend 800,000 for a ticket ina lottery where we have a 35 percent chance of not winninganything?” asks Julie.“Julie, don’t focus on the losses, but on the potential gains! Thechance of winning in this lottery, as you call it, is 65 percent. Ibelieve that that’s much more than with a normal lottery ticket,”says Marc.“Thanks, Marc,” says Brian. “Once we invest that money indevelopment, we have two possible outcomes: either we will besuccessful in developing the road scanning device or we won’t. Ifwe fail, then once again we’ll sell the DSS in its current form andcash in the200,000 from GM for the research results. If thedevelopment process is successful, then we have to decide whetherto market the new product.”“Why wouldn’t we want to market it after successfully developingit?” asks Marc.“That’s a good question. Basically what I mean is that we coulddecide not to sell the product ourselves but instead give the rightto sell it to somebody else, to GM, for example. They would pay us1 million for it.”“I like those numbers!” remarks Julie.“Once we decide to build the product and market it, we will facethe market uncertainties and I’m sure that Julie has those numbersready for us. Thanks.”At this point, Brian sits down and Julie comes forward to give herpresentation. Immediately some colorful slides are projected on thewall behind her as Max operates the computer.“Thanks, Brian. Well, here’s the data we have been able to gatherfrom some marketing research. The acceptance of our new product inthe market can be high, medium, or low,” Julie is pointing to somefigures projected on the wall behind her. “Our estimates indicatethat high acceptance would result in profits of8.0 million, andthat medium acceptance would give us 4.0 million. In theunfortunate case of a poor reception by our customers, we stillexpect2.2 million in profit. I should mention that these profitsdo not include the additional costs of marketing or R Dexpenses.”“So, you are saying that in the worst case we’ll make barely moremoney than with the current product?” asks Brian.“Yes, that’s what I am saying.”Marc.“What budget would you need for the marketing of our DSS with theroad scanner?” asks“For that we would need an additional 200,000 on top of whathas already been included inthe profit estimates,” Julie replies.“What are the chances of ending up with a high, medium, or lowacceptance of the new DSS?” asks Brian.“We can see those numbers at the bottom of the slide,” says Julie,while she is turning toward the projection behind her. There is a30 percent chance of high market acceptance and a 20 percent chanceof low market acceptance.At this point, Marc moves in his seat and asks: “Given all thesenumbers and bits of information, what are you suggesting that wedo?”(a) Organize the available data on cost andprofit estimates in a table.(b) Formulate the problem in a decision tree.Clearly distinguish between decision and event nodes.(c) Calculate the expected payoffs for each nodein the decision tree.(d) What is BAAG’s optimal policy according toBayes’decision rule?(e) What would be the expected value of perfectinformation on the outcome of the research effort? (f ) What wouldbe the expected value of perfect information on the outcome of thedevelopment effort?(g) Marc is a risk-averse decision maker. In anumber of interviews, his utility function for money was assessedto beu(M) = 1 – e –M/12 , ——————– 1 – e –1/12where M is the company’s net profit in units of hundreds ofthousands of dollars (e.g., M = 8 would imply a net profit of800,000). Using Marc’s utility function, calculate the utility foreach terminal branch of the decision tree.(h) Determine the expected utilities for allnodes in the decision tree.(i) Based on Marc’s utility function, what isBAAG’s optimal policy?(j) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of theresearch effort?(k) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of thedevelopment effort? (7)

SOLVED: Decision Analysis with Probability:On a sunny May morning, Marc Binton, CEO of Bay Area AutomobileGadgets (BAAG), enters the conference room on the 40th floor of theGates building in San Francisco, where BAAG’s offices are located.The other executive officers of the company have already gathered.The meeting has only one item on its agenda: planning a researchand development project to develop a new driver support system(DSS). Brian Huang, Manager of Research and Development, is walkingaround nervously. He has to inform the group about the R Dstrategy he has developed for the DSS. Marc has identified DSS asthe strategic new product for the company. Julie Aker,VicePresident of Marketing, will speak after Brian. She will givedetailed information about the target segment, expected sales, andmarketing costs associated with the introduction of the DSS.BAAG builds electronic nonaudio equipment for luxury cars. Foundedby a group of Stanford graduates, the company sold its firstproduct—a car routing system relying on a technology called globalpositioning satellites (GPS)—a few years ago. Such routing systemshelp drivers to find directions to their desired destinations usingsatellites to determine the exact position of the car. To keep upwith technology and to meet the wishes of their customers, thecompany has added a number of new features to its router during thelast few years. The DSS will be a completely new product,incorporating recent developments in GPS as well as voicerecognition and display technologies. Marc strongly supports thisproduct, as it will give BAAG a competitive advantage over itsAsian and European competitors.Driver support systems have been a field of intense research formore than a decade. These systems provide the driver with a widerange of information, such as directions, road conditions, trafficupdates, etc. The information exchange can take place verbally orvia projection of text onto the windscreen. Other features help thedriver avoid obstacles that have been identified by cars ahead onthe road (these cars transmit the information to the followingvehicles). Marc wants to incorporate all these features and othertechnologies into one support system that would then be sold toBAAG’s customers in the automobile industry.After all the attendees have taken their seats, Brian starts hispresentation: “Marc asked me to inform you about our efforts withthe driver support system, particularly the road scanning device.We have reached a stage where we basically have to make a go orno-go decision concerning the research for this device, which, asyou all know by now, is a key feature in the DSS. We have alreadyintegrated the other devices, such as the PGS-based positioning anddirection system. The question we have to deal with is whether tofund basic research into the road scanning device. If this researchwere successful, we then would have to decide if we want to developa product based on these results—or if we just want to sell thetechnology without developing a product. If we do decide to developthe product ourselves, there is a chance that the productdevelopment process might not be successful. In that case, we couldstill sell the technology. In the case of successful productdevelopment, we would have to decide whether to market the product.If we decide not to market the developed product, we could at leastsell the product concept that was the result of our successfulresearch and development efforts. Doing so would earn more thanjust selling the technology prematurely. If, on the other hand, wedecide to market the driver support system, then we are faced withthe uncertainty of how the product will be received by ourcustomers.”“You completely lost me.” snipes Marc.Max, Julie’s assistant, just shakes his head and murmurs, “thosetechno-nerds. ”Brian starts to explain: “Sorry for the confusion. Let’s just gothrough it again, step by step.” “Good idea—and perhaps makesmaller steps!” Julie obviously dislikes Brian’s style ofpresentation.“OK, the first decision we are facing is whether to invest inresearch for the road scanningdevice.”“How much would that cost us?” asks Marc.“Our estimated budget for this is 300,000. Once we invest thatmoney, the outcome of the research effort is somewhat uncertain.Our engineers assess the probability of successful research at 80percent.”“That’s a pretty optimistic success rate, don’t you think?” Julieremarks sarcastically. She still remembers the disaster withBrian’s last project, the fingerprint-based car security system.After spending half a million dollars, the development engineersconcluded that it would be impossible to produce the securitysystem at an attractive price.Brian senses Julie’s hostility and shoots back: “In engineering weare quite accustomed to these success rates— something we can’t sayabout marketing. ”“What would be the next step?” intervenes Marc.“Hm, sorry. If the research is not successful, then we can onlysell the DSS in its currentform.”“The profit estimate for that scenario is2 million,” Julie throwsin.“If, however, the research effort is successful, then we will haveto make another decision,namely, whether to go on to the development stage.”“If we wouldn’t want to develop a product at that point, would thatmean that we would have to sell the DSS as it is now?” asksMax.“Yes, Max. Except that additionally we would earn some 200,000from selling our research results to GM. Their research division isvery interested in our work and they have offered me that money forour findings.”“Ah, now that’s good news,” remarks Julie.Brian continues, “If, however, after successfully completing theresearch stage, we decide to develop a new product then we’ll haveto spend another800,000 for that task, at a chance of 35 percentof not being successful.”“So you are telling us we’ll have to spend 800,000 for a ticket ina lottery where we have a 35 percent chance of not winninganything?” asks Julie.“Julie, don’t focus on the losses, but on the potential gains! Thechance of winning in this lottery, as you call it, is 65 percent. Ibelieve that that’s much more than with a normal lottery ticket,”says Marc.“Thanks, Marc,” says Brian. “Once we invest that money indevelopment, we have two possible outcomes: either we will besuccessful in developing the road scanning device or we won’t. Ifwe fail, then once again we’ll sell the DSS in its current form andcash in the200,000 from GM for the research results. If thedevelopment process is successful, then we have to decide whetherto market the new product.”“Why wouldn’t we want to market it after successfully developingit?” asks Marc.“That’s a good question. Basically what I mean is that we coulddecide not to sell the product ourselves but instead give the rightto sell it to somebody else, to GM, for example. They would pay us1 million for it.”“I like those numbers!” remarks Julie.“Once we decide to build the product and market it, we will facethe market uncertainties and I’m sure that Julie has those numbersready for us. Thanks.”At this point, Brian sits down and Julie comes forward to give herpresentation. Immediately some colorful slides are projected on thewall behind her as Max operates the computer.“Thanks, Brian. Well, here’s the data we have been able to gatherfrom some marketing research. The acceptance of our new product inthe market can be high, medium, or low,” Julie is pointing to somefigures projected on the wall behind her. “Our estimates indicatethat high acceptance would result in profits of8.0 million, andthat medium acceptance would give us 4.0 million. In theunfortunate case of a poor reception by our customers, we stillexpect2.2 million in profit. I should mention that these profitsdo not include the additional costs of marketing or R Dexpenses.”“So, you are saying that in the worst case we’ll make barely moremoney than with the current product?” asks Brian.“Yes, that’s what I am saying.”Marc.“What budget would you need for the marketing of our DSS with theroad scanner?” asks“For that we would need an additional 200,000 on top of whathas already been included inthe profit estimates,” Julie replies.“What are the chances of ending up with a high, medium, or lowacceptance of the new DSS?” asks Brian.“We can see those numbers at the bottom of the slide,” says Julie,while she is turning toward the projection behind her. There is a30 percent chance of high market acceptance and a 20 percent chanceof low market acceptance.At this point, Marc moves in his seat and asks: “Given all thesenumbers and bits of information, what are you suggesting that wedo?”(a) Organize the available data on cost andprofit estimates in a table.(b) Formulate the problem in a decision tree.Clearly distinguish between decision and event nodes.(c) Calculate the expected payoffs for each nodein the decision tree.(d) What is BAAG’s optimal policy according toBayes’decision rule?(e) What would be the expected value of perfectinformation on the outcome of the research effort? (f ) What wouldbe the expected value of perfect information on the outcome of thedevelopment effort?(g) Marc is a risk-averse decision maker. In anumber of interviews, his utility function for money was assessedto beu(M) = 1 – e –M/12 , ——————– 1 – e –1/12where M is the company’s net profit in units of hundreds ofthousands of dollars (e.g., M = 8 would imply a net profit of800,000). Using Marc’s utility function, calculate the utility foreach terminal branch of the decision tree.(h) Determine the expected utilities for allnodes in the decision tree.(i) Based on Marc’s utility function, what isBAAG’s optimal policy?(j) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of theresearch effort?(k) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of thedevelopment effort? (8)

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SOLVED: Decision Analysis with Probability:On a sunny May morning, Marc Binton, CEO of Bay Area AutomobileGadgets (BAAG), enters the conference room on the 40th floor of theGates building in San Francisco, where BAAG’s offices are located.The other executive officers of the company have already gathered.The meeting has only one item on its agenda: planning a researchand development project to develop a new driver support system(DSS). Brian Huang, Manager of Research and Development, is walkingaround nervously. He has to inform the group about the R Dstrategy he has developed for the DSS. Marc has identified DSS asthe strategic new product for the company. Julie Aker,VicePresident of Marketing, will speak after Brian. She will givedetailed information about the target segment, expected sales, andmarketing costs associated with the introduction of the DSS.BAAG builds electronic nonaudio equipment for luxury cars. Foundedby a group of Stanford graduates, the company sold its firstproduct—a car routing system relying on a technology called globalpositioning satellites (GPS)—a few years ago. Such routing systemshelp drivers to find directions to their desired destinations usingsatellites to determine the exact position of the car. To keep upwith technology and to meet the wishes of their customers, thecompany has added a number of new features to its router during thelast few years. The DSS will be a completely new product,incorporating recent developments in GPS as well as voicerecognition and display technologies. Marc strongly supports thisproduct, as it will give BAAG a competitive advantage over itsAsian and European competitors.Driver support systems have been a field of intense research formore than a decade. These systems provide the driver with a widerange of information, such as directions, road conditions, trafficupdates, etc. The information exchange can take place verbally orvia projection of text onto the windscreen. Other features help thedriver avoid obstacles that have been identified by cars ahead onthe road (these cars transmit the information to the followingvehicles). Marc wants to incorporate all these features and othertechnologies into one support system that would then be sold toBAAG’s customers in the automobile industry.After all the attendees have taken their seats, Brian starts hispresentation: “Marc asked me to inform you about our efforts withthe driver support system, particularly the road scanning device.We have reached a stage where we basically have to make a go orno-go decision concerning the research for this device, which, asyou all know by now, is a key feature in the DSS. We have alreadyintegrated the other devices, such as the PGS-based positioning anddirection system. The question we have to deal with is whether tofund basic research into the road scanning device. If this researchwere successful, we then would have to decide if we want to developa product based on these results—or if we just want to sell thetechnology without developing a product. If we do decide to developthe product ourselves, there is a chance that the productdevelopment process might not be successful. In that case, we couldstill sell the technology. In the case of successful productdevelopment, we would have to decide whether to market the product.If we decide not to market the developed product, we could at leastsell the product concept that was the result of our successfulresearch and development efforts. Doing so would earn more thanjust selling the technology prematurely. If, on the other hand, wedecide to market the driver support system, then we are faced withthe uncertainty of how the product will be received by ourcustomers.”“You completely lost me.” snipes Marc.Max, Julie’s assistant, just shakes his head and murmurs, “thosetechno-nerds. ”Brian starts to explain: “Sorry for the confusion. Let’s just gothrough it again, step by step.” “Good idea—and perhaps makesmaller steps!” Julie obviously dislikes Brian’s style ofpresentation.“OK, the first decision we are facing is whether to invest inresearch for the road scanningdevice.”“How much would that cost us?” asks Marc.“Our estimated budget for this is 300,000. Once we invest thatmoney, the outcome of the research effort is somewhat uncertain.Our engineers assess the probability of successful research at 80percent.”“That’s a pretty optimistic success rate, don’t you think?” Julieremarks sarcastically. She still remembers the disaster withBrian’s last project, the fingerprint-based car security system.After spending half a million dollars, the development engineersconcluded that it would be impossible to produce the securitysystem at an attractive price.Brian senses Julie’s hostility and shoots back: “In engineering weare quite accustomed to these success rates— something we can’t sayabout marketing. ”“What would be the next step?” intervenes Marc.“Hm, sorry. If the research is not successful, then we can onlysell the DSS in its currentform.”“The profit estimate for that scenario is2 million,” Julie throwsin.“If, however, the research effort is successful, then we will haveto make another decision,namely, whether to go on to the development stage.”“If we wouldn’t want to develop a product at that point, would thatmean that we would have to sell the DSS as it is now?” asksMax.“Yes, Max. Except that additionally we would earn some 200,000from selling our research results to GM. Their research division isvery interested in our work and they have offered me that money forour findings.”“Ah, now that’s good news,” remarks Julie.Brian continues, “If, however, after successfully completing theresearch stage, we decide to develop a new product then we’ll haveto spend another800,000 for that task, at a chance of 35 percentof not being successful.”“So you are telling us we’ll have to spend 800,000 for a ticket ina lottery where we have a 35 percent chance of not winninganything?” asks Julie.“Julie, don’t focus on the losses, but on the potential gains! Thechance of winning in this lottery, as you call it, is 65 percent. Ibelieve that that’s much more than with a normal lottery ticket,”says Marc.“Thanks, Marc,” says Brian. “Once we invest that money indevelopment, we have two possible outcomes: either we will besuccessful in developing the road scanning device or we won’t. Ifwe fail, then once again we’ll sell the DSS in its current form andcash in the200,000 from GM for the research results. If thedevelopment process is successful, then we have to decide whetherto market the new product.”“Why wouldn’t we want to market it after successfully developingit?” asks Marc.“That’s a good question. Basically what I mean is that we coulddecide not to sell the product ourselves but instead give the rightto sell it to somebody else, to GM, for example. They would pay us1 million for it.”“I like those numbers!” remarks Julie.“Once we decide to build the product and market it, we will facethe market uncertainties and I’m sure that Julie has those numbersready for us. Thanks.”At this point, Brian sits down and Julie comes forward to give herpresentation. Immediately some colorful slides are projected on thewall behind her as Max operates the computer.“Thanks, Brian. Well, here’s the data we have been able to gatherfrom some marketing research. The acceptance of our new product inthe market can be high, medium, or low,” Julie is pointing to somefigures projected on the wall behind her. “Our estimates indicatethat high acceptance would result in profits of8.0 million, andthat medium acceptance would give us 4.0 million. In theunfortunate case of a poor reception by our customers, we stillexpect2.2 million in profit. I should mention that these profitsdo not include the additional costs of marketing or R Dexpenses.”“So, you are saying that in the worst case we’ll make barely moremoney than with the current product?” asks Brian.“Yes, that’s what I am saying.”Marc.“What budget would you need for the marketing of our DSS with theroad scanner?” asks“For that we would need an additional 200,000 on top of whathas already been included inthe profit estimates,” Julie replies.“What are the chances of ending up with a high, medium, or lowacceptance of the new DSS?” asks Brian.“We can see those numbers at the bottom of the slide,” says Julie,while she is turning toward the projection behind her. There is a30 percent chance of high market acceptance and a 20 percent chanceof low market acceptance.At this point, Marc moves in his seat and asks: “Given all thesenumbers and bits of information, what are you suggesting that wedo?”(a) Organize the available data on cost andprofit estimates in a table.(b) Formulate the problem in a decision tree.Clearly distinguish between decision and event nodes.(c) Calculate the expected payoffs for each nodein the decision tree.(d) What is BAAG’s optimal policy according toBayes’decision rule?(e) What would be the expected value of perfectinformation on the outcome of the research effort? (f ) What wouldbe the expected value of perfect information on the outcome of thedevelopment effort?(g) Marc is a risk-averse decision maker. In anumber of interviews, his utility function for money was assessedto beu(M) = 1 – e –M/12 , ——————– 1 – e –1/12where M is the company’s net profit in units of hundreds ofthousands of dollars (e.g., M = 8 would imply a net profit of800,000). Using Marc’s utility function, calculate the utility foreach terminal branch of the decision tree.(h) Determine the expected utilities for allnodes in the decision tree.(i) Based on Marc’s utility function, what isBAAG’s optimal policy?(j) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of theresearch effort?(k) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of thedevelopment effort? (22)

More Than Just

SOLVED: Decision Analysis with Probability:On a sunny May morning, Marc Binton, CEO of Bay Area AutomobileGadgets (BAAG), enters the conference room on the 40th floor of theGates building in San Francisco, where BAAG’s offices are located.The other executive officers of the company have already gathered.The meeting has only one item on its agenda: planning a researchand development project to develop a new driver support system(DSS). Brian Huang, Manager of Research and Development, is walkingaround nervously. He has to inform the group about the R Dstrategy he has developed for the DSS. Marc has identified DSS asthe strategic new product for the company. Julie Aker,VicePresident of Marketing, will speak after Brian. She will givedetailed information about the target segment, expected sales, andmarketing costs associated with the introduction of the DSS.BAAG builds electronic nonaudio equipment for luxury cars. Foundedby a group of Stanford graduates, the company sold its firstproduct—a car routing system relying on a technology called globalpositioning satellites (GPS)—a few years ago. Such routing systemshelp drivers to find directions to their desired destinations usingsatellites to determine the exact position of the car. To keep upwith technology and to meet the wishes of their customers, thecompany has added a number of new features to its router during thelast few years. The DSS will be a completely new product,incorporating recent developments in GPS as well as voicerecognition and display technologies. Marc strongly supports thisproduct, as it will give BAAG a competitive advantage over itsAsian and European competitors.Driver support systems have been a field of intense research formore than a decade. These systems provide the driver with a widerange of information, such as directions, road conditions, trafficupdates, etc. The information exchange can take place verbally orvia projection of text onto the windscreen. Other features help thedriver avoid obstacles that have been identified by cars ahead onthe road (these cars transmit the information to the followingvehicles). Marc wants to incorporate all these features and othertechnologies into one support system that would then be sold toBAAG’s customers in the automobile industry.After all the attendees have taken their seats, Brian starts hispresentation: “Marc asked me to inform you about our efforts withthe driver support system, particularly the road scanning device.We have reached a stage where we basically have to make a go orno-go decision concerning the research for this device, which, asyou all know by now, is a key feature in the DSS. We have alreadyintegrated the other devices, such as the PGS-based positioning anddirection system. The question we have to deal with is whether tofund basic research into the road scanning device. If this researchwere successful, we then would have to decide if we want to developa product based on these results—or if we just want to sell thetechnology without developing a product. If we do decide to developthe product ourselves, there is a chance that the productdevelopment process might not be successful. In that case, we couldstill sell the technology. In the case of successful productdevelopment, we would have to decide whether to market the product.If we decide not to market the developed product, we could at leastsell the product concept that was the result of our successfulresearch and development efforts. Doing so would earn more thanjust selling the technology prematurely. If, on the other hand, wedecide to market the driver support system, then we are faced withthe uncertainty of how the product will be received by ourcustomers.”“You completely lost me.” snipes Marc.Max, Julie’s assistant, just shakes his head and murmurs, “thosetechno-nerds. ”Brian starts to explain: “Sorry for the confusion. Let’s just gothrough it again, step by step.” “Good idea—and perhaps makesmaller steps!” Julie obviously dislikes Brian’s style ofpresentation.“OK, the first decision we are facing is whether to invest inresearch for the road scanningdevice.”“How much would that cost us?” asks Marc.“Our estimated budget for this is 300,000. Once we invest thatmoney, the outcome of the research effort is somewhat uncertain.Our engineers assess the probability of successful research at 80percent.”“That’s a pretty optimistic success rate, don’t you think?” Julieremarks sarcastically. She still remembers the disaster withBrian’s last project, the fingerprint-based car security system.After spending half a million dollars, the development engineersconcluded that it would be impossible to produce the securitysystem at an attractive price.Brian senses Julie’s hostility and shoots back: “In engineering weare quite accustomed to these success rates— something we can’t sayabout marketing. ”“What would be the next step?” intervenes Marc.“Hm, sorry. If the research is not successful, then we can onlysell the DSS in its currentform.”“The profit estimate for that scenario is2 million,” Julie throwsin.“If, however, the research effort is successful, then we will haveto make another decision,namely, whether to go on to the development stage.”“If we wouldn’t want to develop a product at that point, would thatmean that we would have to sell the DSS as it is now?” asksMax.“Yes, Max. Except that additionally we would earn some 200,000from selling our research results to GM. Their research division isvery interested in our work and they have offered me that money forour findings.”“Ah, now that’s good news,” remarks Julie.Brian continues, “If, however, after successfully completing theresearch stage, we decide to develop a new product then we’ll haveto spend another800,000 for that task, at a chance of 35 percentof not being successful.”“So you are telling us we’ll have to spend 800,000 for a ticket ina lottery where we have a 35 percent chance of not winninganything?” asks Julie.“Julie, don’t focus on the losses, but on the potential gains! Thechance of winning in this lottery, as you call it, is 65 percent. Ibelieve that that’s much more than with a normal lottery ticket,”says Marc.“Thanks, Marc,” says Brian. “Once we invest that money indevelopment, we have two possible outcomes: either we will besuccessful in developing the road scanning device or we won’t. Ifwe fail, then once again we’ll sell the DSS in its current form andcash in the200,000 from GM for the research results. If thedevelopment process is successful, then we have to decide whetherto market the new product.”“Why wouldn’t we want to market it after successfully developingit?” asks Marc.“That’s a good question. Basically what I mean is that we coulddecide not to sell the product ourselves but instead give the rightto sell it to somebody else, to GM, for example. They would pay us1 million for it.”“I like those numbers!” remarks Julie.“Once we decide to build the product and market it, we will facethe market uncertainties and I’m sure that Julie has those numbersready for us. Thanks.”At this point, Brian sits down and Julie comes forward to give herpresentation. Immediately some colorful slides are projected on thewall behind her as Max operates the computer.“Thanks, Brian. Well, here’s the data we have been able to gatherfrom some marketing research. The acceptance of our new product inthe market can be high, medium, or low,” Julie is pointing to somefigures projected on the wall behind her. “Our estimates indicatethat high acceptance would result in profits of8.0 million, andthat medium acceptance would give us 4.0 million. In theunfortunate case of a poor reception by our customers, we stillexpect2.2 million in profit. I should mention that these profitsdo not include the additional costs of marketing or R Dexpenses.”“So, you are saying that in the worst case we’ll make barely moremoney than with the current product?” asks Brian.“Yes, that’s what I am saying.”Marc.“What budget would you need for the marketing of our DSS with theroad scanner?” asks“For that we would need an additional 200,000 on top of whathas already been included inthe profit estimates,” Julie replies.“What are the chances of ending up with a high, medium, or lowacceptance of the new DSS?” asks Brian.“We can see those numbers at the bottom of the slide,” says Julie,while she is turning toward the projection behind her. There is a30 percent chance of high market acceptance and a 20 percent chanceof low market acceptance.At this point, Marc moves in his seat and asks: “Given all thesenumbers and bits of information, what are you suggesting that wedo?”(a) Organize the available data on cost andprofit estimates in a table.(b) Formulate the problem in a decision tree.Clearly distinguish between decision and event nodes.(c) Calculate the expected payoffs for each nodein the decision tree.(d) What is BAAG’s optimal policy according toBayes’decision rule?(e) What would be the expected value of perfectinformation on the outcome of the research effort? (f ) What wouldbe the expected value of perfect information on the outcome of thedevelopment effort?(g) Marc is a risk-averse decision maker. In anumber of interviews, his utility function for money was assessedto beu(M) = 1 – e –M/12 , ——————– 1 – e –1/12where M is the company’s net profit in units of hundreds ofthousands of dollars (e.g., M = 8 would imply a net profit of800,000). Using Marc’s utility function, calculate the utility foreach terminal branch of the decision tree.(h) Determine the expected utilities for allnodes in the decision tree.(i) Based on Marc’s utility function, what isBAAG’s optimal policy?(j) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of theresearch effort?(k) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of thedevelopment effort? (23)

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SOLVED: Decision Analysis with Probability:On a sunny May morning, Marc Binton, CEO of Bay Area AutomobileGadgets (BAAG), enters the conference room on the 40th floor of theGates building in San Francisco, where BAAG’s offices are located.The other executive officers of the company have already gathered.The meeting has only one item on its agenda: planning a researchand development project to develop a new driver support system(DSS). Brian Huang, Manager of Research and Development, is walkingaround nervously. He has to inform the group about the R Dstrategy he has developed for the DSS. Marc has identified DSS asthe strategic new product for the company. Julie Aker,VicePresident of Marketing, will speak after Brian. She will givedetailed information about the target segment, expected sales, andmarketing costs associated with the introduction of the DSS.BAAG builds electronic nonaudio equipment for luxury cars. Foundedby a group of Stanford graduates, the company sold its firstproduct—a car routing system relying on a technology called globalpositioning satellites (GPS)—a few years ago. Such routing systemshelp drivers to find directions to their desired destinations usingsatellites to determine the exact position of the car. To keep upwith technology and to meet the wishes of their customers, thecompany has added a number of new features to its router during thelast few years. The DSS will be a completely new product,incorporating recent developments in GPS as well as voicerecognition and display technologies. Marc strongly supports thisproduct, as it will give BAAG a competitive advantage over itsAsian and European competitors.Driver support systems have been a field of intense research formore than a decade. These systems provide the driver with a widerange of information, such as directions, road conditions, trafficupdates, etc. The information exchange can take place verbally orvia projection of text onto the windscreen. Other features help thedriver avoid obstacles that have been identified by cars ahead onthe road (these cars transmit the information to the followingvehicles). Marc wants to incorporate all these features and othertechnologies into one support system that would then be sold toBAAG’s customers in the automobile industry.After all the attendees have taken their seats, Brian starts hispresentation: “Marc asked me to inform you about our efforts withthe driver support system, particularly the road scanning device.We have reached a stage where we basically have to make a go orno-go decision concerning the research for this device, which, asyou all know by now, is a key feature in the DSS. We have alreadyintegrated the other devices, such as the PGS-based positioning anddirection system. The question we have to deal with is whether tofund basic research into the road scanning device. If this researchwere successful, we then would have to decide if we want to developa product based on these results—or if we just want to sell thetechnology without developing a product. If we do decide to developthe product ourselves, there is a chance that the productdevelopment process might not be successful. In that case, we couldstill sell the technology. In the case of successful productdevelopment, we would have to decide whether to market the product.If we decide not to market the developed product, we could at leastsell the product concept that was the result of our successfulresearch and development efforts. Doing so would earn more thanjust selling the technology prematurely. If, on the other hand, wedecide to market the driver support system, then we are faced withthe uncertainty of how the product will be received by ourcustomers.”“You completely lost me.” snipes Marc.Max, Julie’s assistant, just shakes his head and murmurs, “thosetechno-nerds. ”Brian starts to explain: “Sorry for the confusion. Let’s just gothrough it again, step by step.” “Good idea—and perhaps makesmaller steps!” Julie obviously dislikes Brian’s style ofpresentation.“OK, the first decision we are facing is whether to invest inresearch for the road scanningdevice.”“How much would that cost us?” asks Marc.“Our estimated budget for this is 300,000. Once we invest thatmoney, the outcome of the research effort is somewhat uncertain.Our engineers assess the probability of successful research at 80percent.”“That’s a pretty optimistic success rate, don’t you think?” Julieremarks sarcastically. She still remembers the disaster withBrian’s last project, the fingerprint-based car security system.After spending half a million dollars, the development engineersconcluded that it would be impossible to produce the securitysystem at an attractive price.Brian senses Julie’s hostility and shoots back: “In engineering weare quite accustomed to these success rates— something we can’t sayabout marketing. ”“What would be the next step?” intervenes Marc.“Hm, sorry. If the research is not successful, then we can onlysell the DSS in its currentform.”“The profit estimate for that scenario is2 million,” Julie throwsin.“If, however, the research effort is successful, then we will haveto make another decision,namely, whether to go on to the development stage.”“If we wouldn’t want to develop a product at that point, would thatmean that we would have to sell the DSS as it is now?” asksMax.“Yes, Max. Except that additionally we would earn some 200,000from selling our research results to GM. Their research division isvery interested in our work and they have offered me that money forour findings.”“Ah, now that’s good news,” remarks Julie.Brian continues, “If, however, after successfully completing theresearch stage, we decide to develop a new product then we’ll haveto spend another800,000 for that task, at a chance of 35 percentof not being successful.”“So you are telling us we’ll have to spend 800,000 for a ticket ina lottery where we have a 35 percent chance of not winninganything?” asks Julie.“Julie, don’t focus on the losses, but on the potential gains! Thechance of winning in this lottery, as you call it, is 65 percent. Ibelieve that that’s much more than with a normal lottery ticket,”says Marc.“Thanks, Marc,” says Brian. “Once we invest that money indevelopment, we have two possible outcomes: either we will besuccessful in developing the road scanning device or we won’t. Ifwe fail, then once again we’ll sell the DSS in its current form andcash in the200,000 from GM for the research results. If thedevelopment process is successful, then we have to decide whetherto market the new product.”“Why wouldn’t we want to market it after successfully developingit?” asks Marc.“That’s a good question. Basically what I mean is that we coulddecide not to sell the product ourselves but instead give the rightto sell it to somebody else, to GM, for example. They would pay us1 million for it.”“I like those numbers!” remarks Julie.“Once we decide to build the product and market it, we will facethe market uncertainties and I’m sure that Julie has those numbersready for us. Thanks.”At this point, Brian sits down and Julie comes forward to give herpresentation. Immediately some colorful slides are projected on thewall behind her as Max operates the computer.“Thanks, Brian. Well, here’s the data we have been able to gatherfrom some marketing research. The acceptance of our new product inthe market can be high, medium, or low,” Julie is pointing to somefigures projected on the wall behind her. “Our estimates indicatethat high acceptance would result in profits of8.0 million, andthat medium acceptance would give us 4.0 million. In theunfortunate case of a poor reception by our customers, we stillexpect2.2 million in profit. I should mention that these profitsdo not include the additional costs of marketing or R Dexpenses.”“So, you are saying that in the worst case we’ll make barely moremoney than with the current product?” asks Brian.“Yes, that’s what I am saying.”Marc.“What budget would you need for the marketing of our DSS with theroad scanner?” asks“For that we would need an additional 200,000 on top of whathas already been included inthe profit estimates,” Julie replies.“What are the chances of ending up with a high, medium, or lowacceptance of the new DSS?” asks Brian.“We can see those numbers at the bottom of the slide,” says Julie,while she is turning toward the projection behind her. There is a30 percent chance of high market acceptance and a 20 percent chanceof low market acceptance.At this point, Marc moves in his seat and asks: “Given all thesenumbers and bits of information, what are you suggesting that wedo?”(a) Organize the available data on cost andprofit estimates in a table.(b) Formulate the problem in a decision tree.Clearly distinguish between decision and event nodes.(c) Calculate the expected payoffs for each nodein the decision tree.(d) What is BAAG’s optimal policy according toBayes’decision rule?(e) What would be the expected value of perfectinformation on the outcome of the research effort? (f ) What wouldbe the expected value of perfect information on the outcome of thedevelopment effort?(g) Marc is a risk-averse decision maker. In anumber of interviews, his utility function for money was assessedto beu(M) = 1 – e –M/12 , ——————– 1 – e –1/12where M is the company’s net profit in units of hundreds ofthousands of dollars (e.g., M = 8 would imply a net profit of800,000). Using Marc’s utility function, calculate the utility foreach terminal branch of the decision tree.(h) Determine the expected utilities for allnodes in the decision tree.(i) Based on Marc’s utility function, what isBAAG’s optimal policy?(j) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of theresearch effort?(k) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of thedevelopment effort? (24)Ace Chat

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SOLVED: Decision Analysis with Probability:On a sunny May morning, Marc Binton, CEO of Bay Area AutomobileGadgets (BAAG), enters the conference room on the 40th floor of theGates building in San Francisco, where BAAG’s offices are located.The other executive officers of the company have already gathered.The meeting has only one item on its agenda: planning a researchand development project to develop a new driver support system(DSS). Brian Huang, Manager of Research and Development, is walkingaround nervously. He has to inform the group about the R Dstrategy he has developed for the DSS. Marc has identified DSS asthe strategic new product for the company. Julie Aker,VicePresident of Marketing, will speak after Brian. She will givedetailed information about the target segment, expected sales, andmarketing costs associated with the introduction of the DSS.BAAG builds electronic nonaudio equipment for luxury cars. Foundedby a group of Stanford graduates, the company sold its firstproduct—a car routing system relying on a technology called globalpositioning satellites (GPS)—a few years ago. Such routing systemshelp drivers to find directions to their desired destinations usingsatellites to determine the exact position of the car. To keep upwith technology and to meet the wishes of their customers, thecompany has added a number of new features to its router during thelast few years. The DSS will be a completely new product,incorporating recent developments in GPS as well as voicerecognition and display technologies. Marc strongly supports thisproduct, as it will give BAAG a competitive advantage over itsAsian and European competitors.Driver support systems have been a field of intense research formore than a decade. These systems provide the driver with a widerange of information, such as directions, road conditions, trafficupdates, etc. The information exchange can take place verbally orvia projection of text onto the windscreen. Other features help thedriver avoid obstacles that have been identified by cars ahead onthe road (these cars transmit the information to the followingvehicles). Marc wants to incorporate all these features and othertechnologies into one support system that would then be sold toBAAG’s customers in the automobile industry.After all the attendees have taken their seats, Brian starts hispresentation: “Marc asked me to inform you about our efforts withthe driver support system, particularly the road scanning device.We have reached a stage where we basically have to make a go orno-go decision concerning the research for this device, which, asyou all know by now, is a key feature in the DSS. We have alreadyintegrated the other devices, such as the PGS-based positioning anddirection system. The question we have to deal with is whether tofund basic research into the road scanning device. If this researchwere successful, we then would have to decide if we want to developa product based on these results—or if we just want to sell thetechnology without developing a product. If we do decide to developthe product ourselves, there is a chance that the productdevelopment process might not be successful. In that case, we couldstill sell the technology. In the case of successful productdevelopment, we would have to decide whether to market the product.If we decide not to market the developed product, we could at leastsell the product concept that was the result of our successfulresearch and development efforts. Doing so would earn more thanjust selling the technology prematurely. If, on the other hand, wedecide to market the driver support system, then we are faced withthe uncertainty of how the product will be received by ourcustomers.”“You completely lost me.” snipes Marc.Max, Julie’s assistant, just shakes his head and murmurs, “thosetechno-nerds. ”Brian starts to explain: “Sorry for the confusion. Let’s just gothrough it again, step by step.” “Good idea—and perhaps makesmaller steps!” Julie obviously dislikes Brian’s style ofpresentation.“OK, the first decision we are facing is whether to invest inresearch for the road scanningdevice.”“How much would that cost us?” asks Marc.“Our estimated budget for this is 300,000. Once we invest thatmoney, the outcome of the research effort is somewhat uncertain.Our engineers assess the probability of successful research at 80percent.”“That’s a pretty optimistic success rate, don’t you think?” Julieremarks sarcastically. She still remembers the disaster withBrian’s last project, the fingerprint-based car security system.After spending half a million dollars, the development engineersconcluded that it would be impossible to produce the securitysystem at an attractive price.Brian senses Julie’s hostility and shoots back: “In engineering weare quite accustomed to these success rates— something we can’t sayabout marketing. ”“What would be the next step?” intervenes Marc.“Hm, sorry. If the research is not successful, then we can onlysell the DSS in its currentform.”“The profit estimate for that scenario is2 million,” Julie throwsin.“If, however, the research effort is successful, then we will haveto make another decision,namely, whether to go on to the development stage.”“If we wouldn’t want to develop a product at that point, would thatmean that we would have to sell the DSS as it is now?” asksMax.“Yes, Max. Except that additionally we would earn some 200,000from selling our research results to GM. Their research division isvery interested in our work and they have offered me that money forour findings.”“Ah, now that’s good news,” remarks Julie.Brian continues, “If, however, after successfully completing theresearch stage, we decide to develop a new product then we’ll haveto spend another800,000 for that task, at a chance of 35 percentof not being successful.”“So you are telling us we’ll have to spend 800,000 for a ticket ina lottery where we have a 35 percent chance of not winninganything?” asks Julie.“Julie, don’t focus on the losses, but on the potential gains! Thechance of winning in this lottery, as you call it, is 65 percent. Ibelieve that that’s much more than with a normal lottery ticket,”says Marc.“Thanks, Marc,” says Brian. “Once we invest that money indevelopment, we have two possible outcomes: either we will besuccessful in developing the road scanning device or we won’t. Ifwe fail, then once again we’ll sell the DSS in its current form andcash in the200,000 from GM for the research results. If thedevelopment process is successful, then we have to decide whetherto market the new product.”“Why wouldn’t we want to market it after successfully developingit?” asks Marc.“That’s a good question. Basically what I mean is that we coulddecide not to sell the product ourselves but instead give the rightto sell it to somebody else, to GM, for example. They would pay us1 million for it.”“I like those numbers!” remarks Julie.“Once we decide to build the product and market it, we will facethe market uncertainties and I’m sure that Julie has those numbersready for us. Thanks.”At this point, Brian sits down and Julie comes forward to give herpresentation. Immediately some colorful slides are projected on thewall behind her as Max operates the computer.“Thanks, Brian. Well, here’s the data we have been able to gatherfrom some marketing research. The acceptance of our new product inthe market can be high, medium, or low,” Julie is pointing to somefigures projected on the wall behind her. “Our estimates indicatethat high acceptance would result in profits of8.0 million, andthat medium acceptance would give us 4.0 million. In theunfortunate case of a poor reception by our customers, we stillexpect2.2 million in profit. I should mention that these profitsdo not include the additional costs of marketing or R Dexpenses.”“So, you are saying that in the worst case we’ll make barely moremoney than with the current product?” asks Brian.“Yes, that’s what I am saying.”Marc.“What budget would you need for the marketing of our DSS with theroad scanner?” asks“For that we would need an additional 200,000 on top of whathas already been included inthe profit estimates,” Julie replies.“What are the chances of ending up with a high, medium, or lowacceptance of the new DSS?” asks Brian.“We can see those numbers at the bottom of the slide,” says Julie,while she is turning toward the projection behind her. There is a30 percent chance of high market acceptance and a 20 percent chanceof low market acceptance.At this point, Marc moves in his seat and asks: “Given all thesenumbers and bits of information, what are you suggesting that wedo?”(a) Organize the available data on cost andprofit estimates in a table.(b) Formulate the problem in a decision tree.Clearly distinguish between decision and event nodes.(c) Calculate the expected payoffs for each nodein the decision tree.(d) What is BAAG’s optimal policy according toBayes’decision rule?(e) What would be the expected value of perfectinformation on the outcome of the research effort? (f ) What wouldbe the expected value of perfect information on the outcome of thedevelopment effort?(g) Marc is a risk-averse decision maker. In anumber of interviews, his utility function for money was assessedto beu(M) = 1 – e –M/12 , ——————– 1 – e –1/12where M is the company’s net profit in units of hundreds ofthousands of dollars (e.g., M = 8 would imply a net profit of800,000). Using Marc’s utility function, calculate the utility foreach terminal branch of the decision tree.(h) Determine the expected utilities for allnodes in the decision tree.(i) Based on Marc’s utility function, what isBAAG’s optimal policy?(j) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of theresearch effort?(k) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of thedevelopment effort? (25)Ask Our Educators

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SOLVED: Decision Analysis with Probability:On a sunny May morning, Marc Binton, CEO of Bay Area AutomobileGadgets (BAAG), enters the conference room on the 40th floor of theGates building in San Francisco, where BAAG’s offices are located.The other executive officers of the company have already gathered.The meeting has only one item on its agenda: planning a researchand development project to develop a new driver support system(DSS). Brian Huang, Manager of Research and Development, is walkingaround nervously. He has to inform the group about the R Dstrategy he has developed for the DSS. Marc has identified DSS asthe strategic new product for the company. Julie Aker,VicePresident of Marketing, will speak after Brian. She will givedetailed information about the target segment, expected sales, andmarketing costs associated with the introduction of the DSS.BAAG builds electronic nonaudio equipment for luxury cars. Foundedby a group of Stanford graduates, the company sold its firstproduct—a car routing system relying on a technology called globalpositioning satellites (GPS)—a few years ago. Such routing systemshelp drivers to find directions to their desired destinations usingsatellites to determine the exact position of the car. To keep upwith technology and to meet the wishes of their customers, thecompany has added a number of new features to its router during thelast few years. The DSS will be a completely new product,incorporating recent developments in GPS as well as voicerecognition and display technologies. Marc strongly supports thisproduct, as it will give BAAG a competitive advantage over itsAsian and European competitors.Driver support systems have been a field of intense research formore than a decade. These systems provide the driver with a widerange of information, such as directions, road conditions, trafficupdates, etc. The information exchange can take place verbally orvia projection of text onto the windscreen. Other features help thedriver avoid obstacles that have been identified by cars ahead onthe road (these cars transmit the information to the followingvehicles). Marc wants to incorporate all these features and othertechnologies into one support system that would then be sold toBAAG’s customers in the automobile industry.After all the attendees have taken their seats, Brian starts hispresentation: “Marc asked me to inform you about our efforts withthe driver support system, particularly the road scanning device.We have reached a stage where we basically have to make a go orno-go decision concerning the research for this device, which, asyou all know by now, is a key feature in the DSS. We have alreadyintegrated the other devices, such as the PGS-based positioning anddirection system. The question we have to deal with is whether tofund basic research into the road scanning device. If this researchwere successful, we then would have to decide if we want to developa product based on these results—or if we just want to sell thetechnology without developing a product. If we do decide to developthe product ourselves, there is a chance that the productdevelopment process might not be successful. In that case, we couldstill sell the technology. In the case of successful productdevelopment, we would have to decide whether to market the product.If we decide not to market the developed product, we could at leastsell the product concept that was the result of our successfulresearch and development efforts. Doing so would earn more thanjust selling the technology prematurely. If, on the other hand, wedecide to market the driver support system, then we are faced withthe uncertainty of how the product will be received by ourcustomers.”“You completely lost me.” snipes Marc.Max, Julie’s assistant, just shakes his head and murmurs, “thosetechno-nerds. ”Brian starts to explain: “Sorry for the confusion. Let’s just gothrough it again, step by step.” “Good idea—and perhaps makesmaller steps!” Julie obviously dislikes Brian’s style ofpresentation.“OK, the first decision we are facing is whether to invest inresearch for the road scanningdevice.”“How much would that cost us?” asks Marc.“Our estimated budget for this is 300,000. Once we invest thatmoney, the outcome of the research effort is somewhat uncertain.Our engineers assess the probability of successful research at 80percent.”“That’s a pretty optimistic success rate, don’t you think?” Julieremarks sarcastically. She still remembers the disaster withBrian’s last project, the fingerprint-based car security system.After spending half a million dollars, the development engineersconcluded that it would be impossible to produce the securitysystem at an attractive price.Brian senses Julie’s hostility and shoots back: “In engineering weare quite accustomed to these success rates— something we can’t sayabout marketing. ”“What would be the next step?” intervenes Marc.“Hm, sorry. If the research is not successful, then we can onlysell the DSS in its currentform.”“The profit estimate for that scenario is2 million,” Julie throwsin.“If, however, the research effort is successful, then we will haveto make another decision,namely, whether to go on to the development stage.”“If we wouldn’t want to develop a product at that point, would thatmean that we would have to sell the DSS as it is now?” asksMax.“Yes, Max. Except that additionally we would earn some 200,000from selling our research results to GM. Their research division isvery interested in our work and they have offered me that money forour findings.”“Ah, now that’s good news,” remarks Julie.Brian continues, “If, however, after successfully completing theresearch stage, we decide to develop a new product then we’ll haveto spend another800,000 for that task, at a chance of 35 percentof not being successful.”“So you are telling us we’ll have to spend 800,000 for a ticket ina lottery where we have a 35 percent chance of not winninganything?” asks Julie.“Julie, don’t focus on the losses, but on the potential gains! Thechance of winning in this lottery, as you call it, is 65 percent. Ibelieve that that’s much more than with a normal lottery ticket,”says Marc.“Thanks, Marc,” says Brian. “Once we invest that money indevelopment, we have two possible outcomes: either we will besuccessful in developing the road scanning device or we won’t. Ifwe fail, then once again we’ll sell the DSS in its current form andcash in the200,000 from GM for the research results. If thedevelopment process is successful, then we have to decide whetherto market the new product.”“Why wouldn’t we want to market it after successfully developingit?” asks Marc.“That’s a good question. Basically what I mean is that we coulddecide not to sell the product ourselves but instead give the rightto sell it to somebody else, to GM, for example. They would pay us1 million for it.”“I like those numbers!” remarks Julie.“Once we decide to build the product and market it, we will facethe market uncertainties and I’m sure that Julie has those numbersready for us. Thanks.”At this point, Brian sits down and Julie comes forward to give herpresentation. Immediately some colorful slides are projected on thewall behind her as Max operates the computer.“Thanks, Brian. Well, here’s the data we have been able to gatherfrom some marketing research. The acceptance of our new product inthe market can be high, medium, or low,” Julie is pointing to somefigures projected on the wall behind her. “Our estimates indicatethat high acceptance would result in profits of8.0 million, andthat medium acceptance would give us 4.0 million. In theunfortunate case of a poor reception by our customers, we stillexpect2.2 million in profit. I should mention that these profitsdo not include the additional costs of marketing or R Dexpenses.”“So, you are saying that in the worst case we’ll make barely moremoney than with the current product?” asks Brian.“Yes, that’s what I am saying.”Marc.“What budget would you need for the marketing of our DSS with theroad scanner?” asks“For that we would need an additional 200,000 on top of whathas already been included inthe profit estimates,” Julie replies.“What are the chances of ending up with a high, medium, or lowacceptance of the new DSS?” asks Brian.“We can see those numbers at the bottom of the slide,” says Julie,while she is turning toward the projection behind her. There is a30 percent chance of high market acceptance and a 20 percent chanceof low market acceptance.At this point, Marc moves in his seat and asks: “Given all thesenumbers and bits of information, what are you suggesting that wedo?”(a) Organize the available data on cost andprofit estimates in a table.(b) Formulate the problem in a decision tree.Clearly distinguish between decision and event nodes.(c) Calculate the expected payoffs for each nodein the decision tree.(d) What is BAAG’s optimal policy according toBayes’decision rule?(e) What would be the expected value of perfectinformation on the outcome of the research effort? (f ) What wouldbe the expected value of perfect information on the outcome of thedevelopment effort?(g) Marc is a risk-averse decision maker. In anumber of interviews, his utility function for money was assessedto beu(M) = 1 – e –M/12 , ——————– 1 – e –1/12where M is the company’s net profit in units of hundreds ofthousands of dollars (e.g., M = 8 would imply a net profit of800,000). Using Marc’s utility function, calculate the utility foreach terminal branch of the decision tree.(h) Determine the expected utilities for allnodes in the decision tree.(i) Based on Marc’s utility function, what isBAAG’s optimal policy?(j) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of theresearch effort?(k) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of thedevelopment effort? (26)Notes & Exams

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Best Matched Videos Solved By Our Expert Educators SOLVED: Decision Analysis with Probability:On a sunny May morning, Marc Binton, CEO of Bay Area AutomobileGadgets (BAAG), enters the conference room on the 40th floor of theGates building in San Francisco, where BAAG’s offices are located.The other executive officers of the company have already gathered.The meeting has only one item on its agenda: planning a researchand development project to develop a new driver support system(DSS). Brian Huang, Manager of Research and Development, is walkingaround nervously. He has to inform the group about the R Dstrategy he has developed for the DSS. Marc has identified DSS asthe strategic new product for the company. Julie Aker,VicePresident of Marketing, will speak after Brian. She will givedetailed information about the target segment, expected sales, andmarketing costs associated with the introduction of the DSS.BAAG builds electronic nonaudio equipment for luxury cars. Foundedby a group of Stanford graduates, the company sold its firstproduct—a car routing system relying on a technology called globalpositioning satellites (GPS)—a few years ago. Such routing systemshelp drivers to find directions to their desired destinations usingsatellites to determine the exact position of the car. To keep upwith technology and to meet the wishes of their customers, thecompany has added a number of new features to its router during thelast few years. The DSS will be a completely new product,incorporating recent developments in GPS as well as voicerecognition and display technologies. Marc strongly supports thisproduct, as it will give BAAG a competitive advantage over itsAsian and European competitors.Driver support systems have been a field of intense research formore than a decade. These systems provide the driver with a widerange of information, such as directions, road conditions, trafficupdates, etc. The information exchange can take place verbally orvia projection of text onto the windscreen. Other features help thedriver avoid obstacles that have been identified by cars ahead onthe road (these cars transmit the information to the followingvehicles). Marc wants to incorporate all these features and othertechnologies into one support system that would then be sold toBAAG’s customers in the automobile industry.After all the attendees have taken their seats, Brian starts hispresentation: “Marc asked me to inform you about our efforts withthe driver support system, particularly the road scanning device.We have reached a stage where we basically have to make a go orno-go decision concerning the research for this device, which, asyou all know by now, is a key feature in the DSS. We have alreadyintegrated the other devices, such as the PGS-based positioning anddirection system. The question we have to deal with is whether tofund basic research into the road scanning device. If this researchwere successful, we then would have to decide if we want to developa product based on these results—or if we just want to sell thetechnology without developing a product. If we do decide to developthe product ourselves, there is a chance that the productdevelopment process might not be successful. In that case, we couldstill sell the technology. In the case of successful productdevelopment, we would have to decide whether to market the product.If we decide not to market the developed product, we could at leastsell the product concept that was the result of our successfulresearch and development efforts. Doing so would earn more thanjust selling the technology prematurely. If, on the other hand, wedecide to market the driver support system, then we are faced withthe uncertainty of how the product will be received by ourcustomers.”“You completely lost me.” snipes Marc.Max, Julie’s assistant, just shakes his head and murmurs, “thosetechno-nerds. ”Brian starts to explain: “Sorry for the confusion. Let’s just gothrough it again, step by step.” “Good idea—and perhaps makesmaller steps!” Julie obviously dislikes Brian’s style ofpresentation.“OK, the first decision we are facing is whether to invest inresearch for the road scanningdevice.”“How much would that cost us?” asks Marc.“Our estimated budget for this is 300,000. Once we invest thatmoney, the outcome of the research effort is somewhat uncertain.Our engineers assess the probability of successful research at 80percent.”“That’s a pretty optimistic success rate, don’t you think?” Julieremarks sarcastically. She still remembers the disaster withBrian’s last project, the fingerprint-based car security system.After spending half a million dollars, the development engineersconcluded that it would be impossible to produce the securitysystem at an attractive price.Brian senses Julie’s hostility and shoots back: “In engineering weare quite accustomed to these success rates— something we can’t sayabout marketing. ”“What would be the next step?” intervenes Marc.“Hm, sorry. If the research is not successful, then we can onlysell the DSS in its currentform.”“The profit estimate for that scenario is2 million,” Julie throwsin.“If, however, the research effort is successful, then we will haveto make another decision,namely, whether to go on to the development stage.”“If we wouldn’t want to develop a product at that point, would thatmean that we would have to sell the DSS as it is now?” asksMax.“Yes, Max. Except that additionally we would earn some 200,000from selling our research results to GM. Their research division isvery interested in our work and they have offered me that money forour findings.”“Ah, now that’s good news,” remarks Julie.Brian continues, “If, however, after successfully completing theresearch stage, we decide to develop a new product then we’ll haveto spend another800,000 for that task, at a chance of 35 percentof not being successful.”“So you are telling us we’ll have to spend 800,000 for a ticket ina lottery where we have a 35 percent chance of not winninganything?” asks Julie.“Julie, don’t focus on the losses, but on the potential gains! Thechance of winning in this lottery, as you call it, is 65 percent. Ibelieve that that’s much more than with a normal lottery ticket,”says Marc.“Thanks, Marc,” says Brian. “Once we invest that money indevelopment, we have two possible outcomes: either we will besuccessful in developing the road scanning device or we won’t. Ifwe fail, then once again we’ll sell the DSS in its current form andcash in the200,000 from GM for the research results. If thedevelopment process is successful, then we have to decide whetherto market the new product.”“Why wouldn’t we want to market it after successfully developingit?” asks Marc.“That’s a good question. Basically what I mean is that we coulddecide not to sell the product ourselves but instead give the rightto sell it to somebody else, to GM, for example. They would pay us1 million for it.”“I like those numbers!” remarks Julie.“Once we decide to build the product and market it, we will facethe market uncertainties and I’m sure that Julie has those numbersready for us. Thanks.”At this point, Brian sits down and Julie comes forward to give herpresentation. Immediately some colorful slides are projected on thewall behind her as Max operates the computer.“Thanks, Brian. Well, here’s the data we have been able to gatherfrom some marketing research. The acceptance of our new product inthe market can be high, medium, or low,” Julie is pointing to somefigures projected on the wall behind her. “Our estimates indicatethat high acceptance would result in profits of8.0 million, andthat medium acceptance would give us 4.0 million. In theunfortunate case of a poor reception by our customers, we stillexpect2.2 million in profit. I should mention that these profitsdo not include the additional costs of marketing or R Dexpenses.”“So, you are saying that in the worst case we’ll make barely moremoney than with the current product?” asks Brian.“Yes, that’s what I am saying.”Marc.“What budget would you need for the marketing of our DSS with theroad scanner?” asks“For that we would need an additional 200,000 on top of whathas already been included inthe profit estimates,” Julie replies.“What are the chances of ending up with a high, medium, or lowacceptance of the new DSS?” asks Brian.“We can see those numbers at the bottom of the slide,” says Julie,while she is turning toward the projection behind her. There is a30 percent chance of high market acceptance and a 20 percent chanceof low market acceptance.At this point, Marc moves in his seat and asks: “Given all thesenumbers and bits of information, what are you suggesting that wedo?”(a) Organize the available data on cost andprofit estimates in a table.(b) Formulate the problem in a decision tree.Clearly distinguish between decision and event nodes.(c) Calculate the expected payoffs for each nodein the decision tree.(d) What is BAAG’s optimal policy according toBayes’decision rule?(e) What would be the expected value of perfectinformation on the outcome of the research effort? (f ) What wouldbe the expected value of perfect information on the outcome of thedevelopment effort?(g) Marc is a risk-averse decision maker. In anumber of interviews, his utility function for money was assessedto beu(M) = 1 – e –M/12 , ——————– 1 – e –1/12where M is the company’s net profit in units of hundreds ofthousands of dollars (e.g., M = 8 would imply a net profit of800,000). Using Marc’s utility function, calculate the utility foreach terminal branch of the decision tree.(h) Determine the expected utilities for allnodes in the decision tree.(i) Based on Marc’s utility function, what isBAAG’s optimal policy?(j) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of theresearch effort?(k) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of thedevelopment effort? (27) SOLVED: Decision Analysis with Probability:On a sunny May morning, Marc Binton, CEO of Bay Area AutomobileGadgets (BAAG), enters the conference room on the 40th floor of theGates building in San Francisco, where BAAG’s offices are located.The other executive officers of the company have already gathered.The meeting has only one item on its agenda: planning a researchand development project to develop a new driver support system(DSS). Brian Huang, Manager of Research and Development, is walkingaround nervously. He has to inform the group about the R Dstrategy he has developed for the DSS. Marc has identified DSS asthe strategic new product for the company. Julie Aker,VicePresident of Marketing, will speak after Brian. She will givedetailed information about the target segment, expected sales, andmarketing costs associated with the introduction of the DSS.BAAG builds electronic nonaudio equipment for luxury cars. Foundedby a group of Stanford graduates, the company sold its firstproduct—a car routing system relying on a technology called globalpositioning satellites (GPS)—a few years ago. Such routing systemshelp drivers to find directions to their desired destinations usingsatellites to determine the exact position of the car. To keep upwith technology and to meet the wishes of their customers, thecompany has added a number of new features to its router during thelast few years. The DSS will be a completely new product,incorporating recent developments in GPS as well as voicerecognition and display technologies. Marc strongly supports thisproduct, as it will give BAAG a competitive advantage over itsAsian and European competitors.Driver support systems have been a field of intense research formore than a decade. These systems provide the driver with a widerange of information, such as directions, road conditions, trafficupdates, etc. The information exchange can take place verbally orvia projection of text onto the windscreen. Other features help thedriver avoid obstacles that have been identified by cars ahead onthe road (these cars transmit the information to the followingvehicles). Marc wants to incorporate all these features and othertechnologies into one support system that would then be sold toBAAG’s customers in the automobile industry.After all the attendees have taken their seats, Brian starts hispresentation: “Marc asked me to inform you about our efforts withthe driver support system, particularly the road scanning device.We have reached a stage where we basically have to make a go orno-go decision concerning the research for this device, which, asyou all know by now, is a key feature in the DSS. We have alreadyintegrated the other devices, such as the PGS-based positioning anddirection system. The question we have to deal with is whether tofund basic research into the road scanning device. If this researchwere successful, we then would have to decide if we want to developa product based on these results—or if we just want to sell thetechnology without developing a product. If we do decide to developthe product ourselves, there is a chance that the productdevelopment process might not be successful. In that case, we couldstill sell the technology. In the case of successful productdevelopment, we would have to decide whether to market the product.If we decide not to market the developed product, we could at leastsell the product concept that was the result of our successfulresearch and development efforts. Doing so would earn more thanjust selling the technology prematurely. If, on the other hand, wedecide to market the driver support system, then we are faced withthe uncertainty of how the product will be received by ourcustomers.”“You completely lost me.” snipes Marc.Max, Julie’s assistant, just shakes his head and murmurs, “thosetechno-nerds. ”Brian starts to explain: “Sorry for the confusion. Let’s just gothrough it again, step by step.” “Good idea—and perhaps makesmaller steps!” Julie obviously dislikes Brian’s style ofpresentation.“OK, the first decision we are facing is whether to invest inresearch for the road scanningdevice.”“How much would that cost us?” asks Marc.“Our estimated budget for this is 300,000. Once we invest thatmoney, the outcome of the research effort is somewhat uncertain.Our engineers assess the probability of successful research at 80percent.”“That’s a pretty optimistic success rate, don’t you think?” Julieremarks sarcastically. She still remembers the disaster withBrian’s last project, the fingerprint-based car security system.After spending half a million dollars, the development engineersconcluded that it would be impossible to produce the securitysystem at an attractive price.Brian senses Julie’s hostility and shoots back: “In engineering weare quite accustomed to these success rates— something we can’t sayabout marketing. ”“What would be the next step?” intervenes Marc.“Hm, sorry. If the research is not successful, then we can onlysell the DSS in its currentform.”“The profit estimate for that scenario is2 million,” Julie throwsin.“If, however, the research effort is successful, then we will haveto make another decision,namely, whether to go on to the development stage.”“If we wouldn’t want to develop a product at that point, would thatmean that we would have to sell the DSS as it is now?” asksMax.“Yes, Max. Except that additionally we would earn some 200,000from selling our research results to GM. Their research division isvery interested in our work and they have offered me that money forour findings.”“Ah, now that’s good news,” remarks Julie.Brian continues, “If, however, after successfully completing theresearch stage, we decide to develop a new product then we’ll haveto spend another800,000 for that task, at a chance of 35 percentof not being successful.”“So you are telling us we’ll have to spend 800,000 for a ticket ina lottery where we have a 35 percent chance of not winninganything?” asks Julie.“Julie, don’t focus on the losses, but on the potential gains! Thechance of winning in this lottery, as you call it, is 65 percent. Ibelieve that that’s much more than with a normal lottery ticket,”says Marc.“Thanks, Marc,” says Brian. “Once we invest that money indevelopment, we have two possible outcomes: either we will besuccessful in developing the road scanning device or we won’t. Ifwe fail, then once again we’ll sell the DSS in its current form andcash in the200,000 from GM for the research results. If thedevelopment process is successful, then we have to decide whetherto market the new product.”“Why wouldn’t we want to market it after successfully developingit?” asks Marc.“That’s a good question. Basically what I mean is that we coulddecide not to sell the product ourselves but instead give the rightto sell it to somebody else, to GM, for example. They would pay us1 million for it.”“I like those numbers!” remarks Julie.“Once we decide to build the product and market it, we will facethe market uncertainties and I’m sure that Julie has those numbersready for us. Thanks.”At this point, Brian sits down and Julie comes forward to give herpresentation. Immediately some colorful slides are projected on thewall behind her as Max operates the computer.“Thanks, Brian. Well, here’s the data we have been able to gatherfrom some marketing research. The acceptance of our new product inthe market can be high, medium, or low,” Julie is pointing to somefigures projected on the wall behind her. “Our estimates indicatethat high acceptance would result in profits of8.0 million, andthat medium acceptance would give us 4.0 million. In theunfortunate case of a poor reception by our customers, we stillexpect2.2 million in profit. I should mention that these profitsdo not include the additional costs of marketing or R Dexpenses.”“So, you are saying that in the worst case we’ll make barely moremoney than with the current product?” asks Brian.“Yes, that’s what I am saying.”Marc.“What budget would you need for the marketing of our DSS with theroad scanner?” asks“For that we would need an additional 200,000 on top of whathas already been included inthe profit estimates,” Julie replies.“What are the chances of ending up with a high, medium, or lowacceptance of the new DSS?” asks Brian.“We can see those numbers at the bottom of the slide,” says Julie,while she is turning toward the projection behind her. There is a30 percent chance of high market acceptance and a 20 percent chanceof low market acceptance.At this point, Marc moves in his seat and asks: “Given all thesenumbers and bits of information, what are you suggesting that wedo?”(a) Organize the available data on cost andprofit estimates in a table.(b) Formulate the problem in a decision tree.Clearly distinguish between decision and event nodes.(c) Calculate the expected payoffs for each nodein the decision tree.(d) What is BAAG’s optimal policy according toBayes’decision rule?(e) What would be the expected value of perfectinformation on the outcome of the research effort? (f ) What wouldbe the expected value of perfect information on the outcome of thedevelopment effort?(g) Marc is a risk-averse decision maker. In anumber of interviews, his utility function for money was assessedto beu(M) = 1 – e –M/12 , ——————– 1 – e –1/12where M is the company’s net profit in units of hundreds ofthousands of dollars (e.g., M = 8 would imply a net profit of800,000). Using Marc’s utility function, calculate the utility foreach terminal branch of the decision tree.(h) Determine the expected utilities for allnodes in the decision tree.(i) Based on Marc’s utility function, what isBAAG’s optimal policy?(j) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of theresearch effort?(k) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of thedevelopment effort? (28) SOLVED: Decision Analysis with Probability:On a sunny May morning, Marc Binton, CEO of Bay Area AutomobileGadgets (BAAG), enters the conference room on the 40th floor of theGates building in San Francisco, where BAAG’s offices are located.The other executive officers of the company have already gathered.The meeting has only one item on its agenda: planning a researchand development project to develop a new driver support system(DSS). Brian Huang, Manager of Research and Development, is walkingaround nervously. He has to inform the group about the R Dstrategy he has developed for the DSS. Marc has identified DSS asthe strategic new product for the company. Julie Aker,VicePresident of Marketing, will speak after Brian. She will givedetailed information about the target segment, expected sales, andmarketing costs associated with the introduction of the DSS.BAAG builds electronic nonaudio equipment for luxury cars. Foundedby a group of Stanford graduates, the company sold its firstproduct—a car routing system relying on a technology called globalpositioning satellites (GPS)—a few years ago. Such routing systemshelp drivers to find directions to their desired destinations usingsatellites to determine the exact position of the car. To keep upwith technology and to meet the wishes of their customers, thecompany has added a number of new features to its router during thelast few years. The DSS will be a completely new product,incorporating recent developments in GPS as well as voicerecognition and display technologies. Marc strongly supports thisproduct, as it will give BAAG a competitive advantage over itsAsian and European competitors.Driver support systems have been a field of intense research formore than a decade. These systems provide the driver with a widerange of information, such as directions, road conditions, trafficupdates, etc. The information exchange can take place verbally orvia projection of text onto the windscreen. Other features help thedriver avoid obstacles that have been identified by cars ahead onthe road (these cars transmit the information to the followingvehicles). Marc wants to incorporate all these features and othertechnologies into one support system that would then be sold toBAAG’s customers in the automobile industry.After all the attendees have taken their seats, Brian starts hispresentation: “Marc asked me to inform you about our efforts withthe driver support system, particularly the road scanning device.We have reached a stage where we basically have to make a go orno-go decision concerning the research for this device, which, asyou all know by now, is a key feature in the DSS. We have alreadyintegrated the other devices, such as the PGS-based positioning anddirection system. The question we have to deal with is whether tofund basic research into the road scanning device. If this researchwere successful, we then would have to decide if we want to developa product based on these results—or if we just want to sell thetechnology without developing a product. If we do decide to developthe product ourselves, there is a chance that the productdevelopment process might not be successful. In that case, we couldstill sell the technology. In the case of successful productdevelopment, we would have to decide whether to market the product.If we decide not to market the developed product, we could at leastsell the product concept that was the result of our successfulresearch and development efforts. Doing so would earn more thanjust selling the technology prematurely. If, on the other hand, wedecide to market the driver support system, then we are faced withthe uncertainty of how the product will be received by ourcustomers.”“You completely lost me.” snipes Marc.Max, Julie’s assistant, just shakes his head and murmurs, “thosetechno-nerds. ”Brian starts to explain: “Sorry for the confusion. Let’s just gothrough it again, step by step.” “Good idea—and perhaps makesmaller steps!” Julie obviously dislikes Brian’s style ofpresentation.“OK, the first decision we are facing is whether to invest inresearch for the road scanningdevice.”“How much would that cost us?” asks Marc.“Our estimated budget for this is 300,000. Once we invest thatmoney, the outcome of the research effort is somewhat uncertain.Our engineers assess the probability of successful research at 80percent.”“That’s a pretty optimistic success rate, don’t you think?” Julieremarks sarcastically. She still remembers the disaster withBrian’s last project, the fingerprint-based car security system.After spending half a million dollars, the development engineersconcluded that it would be impossible to produce the securitysystem at an attractive price.Brian senses Julie’s hostility and shoots back: “In engineering weare quite accustomed to these success rates— something we can’t sayabout marketing. ”“What would be the next step?” intervenes Marc.“Hm, sorry. If the research is not successful, then we can onlysell the DSS in its currentform.”“The profit estimate for that scenario is2 million,” Julie throwsin.“If, however, the research effort is successful, then we will haveto make another decision,namely, whether to go on to the development stage.”“If we wouldn’t want to develop a product at that point, would thatmean that we would have to sell the DSS as it is now?” asksMax.“Yes, Max. Except that additionally we would earn some 200,000from selling our research results to GM. Their research division isvery interested in our work and they have offered me that money forour findings.”“Ah, now that’s good news,” remarks Julie.Brian continues, “If, however, after successfully completing theresearch stage, we decide to develop a new product then we’ll haveto spend another800,000 for that task, at a chance of 35 percentof not being successful.”“So you are telling us we’ll have to spend 800,000 for a ticket ina lottery where we have a 35 percent chance of not winninganything?” asks Julie.“Julie, don’t focus on the losses, but on the potential gains! Thechance of winning in this lottery, as you call it, is 65 percent. Ibelieve that that’s much more than with a normal lottery ticket,”says Marc.“Thanks, Marc,” says Brian. “Once we invest that money indevelopment, we have two possible outcomes: either we will besuccessful in developing the road scanning device or we won’t. Ifwe fail, then once again we’ll sell the DSS in its current form andcash in the200,000 from GM for the research results. If thedevelopment process is successful, then we have to decide whetherto market the new product.”“Why wouldn’t we want to market it after successfully developingit?” asks Marc.“That’s a good question. Basically what I mean is that we coulddecide not to sell the product ourselves but instead give the rightto sell it to somebody else, to GM, for example. They would pay us1 million for it.”“I like those numbers!” remarks Julie.“Once we decide to build the product and market it, we will facethe market uncertainties and I’m sure that Julie has those numbersready for us. Thanks.”At this point, Brian sits down and Julie comes forward to give herpresentation. Immediately some colorful slides are projected on thewall behind her as Max operates the computer.“Thanks, Brian. Well, here’s the data we have been able to gatherfrom some marketing research. The acceptance of our new product inthe market can be high, medium, or low,” Julie is pointing to somefigures projected on the wall behind her. “Our estimates indicatethat high acceptance would result in profits of8.0 million, andthat medium acceptance would give us 4.0 million. In theunfortunate case of a poor reception by our customers, we stillexpect2.2 million in profit. I should mention that these profitsdo not include the additional costs of marketing or R Dexpenses.”“So, you are saying that in the worst case we’ll make barely moremoney than with the current product?” asks Brian.“Yes, that’s what I am saying.”Marc.“What budget would you need for the marketing of our DSS with theroad scanner?” asks“For that we would need an additional 200,000 on top of whathas already been included inthe profit estimates,” Julie replies.“What are the chances of ending up with a high, medium, or lowacceptance of the new DSS?” asks Brian.“We can see those numbers at the bottom of the slide,” says Julie,while she is turning toward the projection behind her. There is a30 percent chance of high market acceptance and a 20 percent chanceof low market acceptance.At this point, Marc moves in his seat and asks: “Given all thesenumbers and bits of information, what are you suggesting that wedo?”(a) Organize the available data on cost andprofit estimates in a table.(b) Formulate the problem in a decision tree.Clearly distinguish between decision and event nodes.(c) Calculate the expected payoffs for each nodein the decision tree.(d) What is BAAG’s optimal policy according toBayes’decision rule?(e) What would be the expected value of perfectinformation on the outcome of the research effort? (f ) What wouldbe the expected value of perfect information on the outcome of thedevelopment effort?(g) Marc is a risk-averse decision maker. In anumber of interviews, his utility function for money was assessedto beu(M) = 1 – e –M/12 , ——————– 1 – e –1/12where M is the company’s net profit in units of hundreds ofthousands of dollars (e.g., M = 8 would imply a net profit of800,000). Using Marc’s utility function, calculate the utility foreach terminal branch of the decision tree.(h) Determine the expected utilities for allnodes in the decision tree.(i) Based on Marc’s utility function, what isBAAG’s optimal policy?(j) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of theresearch effort?(k) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of thedevelopment effort? (29) SOLVED: Decision Analysis with Probability:On a sunny May morning, Marc Binton, CEO of Bay Area AutomobileGadgets (BAAG), enters the conference room on the 40th floor of theGates building in San Francisco, where BAAG’s offices are located.The other executive officers of the company have already gathered.The meeting has only one item on its agenda: planning a researchand development project to develop a new driver support system(DSS). Brian Huang, Manager of Research and Development, is walkingaround nervously. He has to inform the group about the R Dstrategy he has developed for the DSS. Marc has identified DSS asthe strategic new product for the company. Julie Aker,VicePresident of Marketing, will speak after Brian. She will givedetailed information about the target segment, expected sales, andmarketing costs associated with the introduction of the DSS.BAAG builds electronic nonaudio equipment for luxury cars. Foundedby a group of Stanford graduates, the company sold its firstproduct—a car routing system relying on a technology called globalpositioning satellites (GPS)—a few years ago. Such routing systemshelp drivers to find directions to their desired destinations usingsatellites to determine the exact position of the car. To keep upwith technology and to meet the wishes of their customers, thecompany has added a number of new features to its router during thelast few years. The DSS will be a completely new product,incorporating recent developments in GPS as well as voicerecognition and display technologies. Marc strongly supports thisproduct, as it will give BAAG a competitive advantage over itsAsian and European competitors.Driver support systems have been a field of intense research formore than a decade. These systems provide the driver with a widerange of information, such as directions, road conditions, trafficupdates, etc. The information exchange can take place verbally orvia projection of text onto the windscreen. Other features help thedriver avoid obstacles that have been identified by cars ahead onthe road (these cars transmit the information to the followingvehicles). Marc wants to incorporate all these features and othertechnologies into one support system that would then be sold toBAAG’s customers in the automobile industry.After all the attendees have taken their seats, Brian starts hispresentation: “Marc asked me to inform you about our efforts withthe driver support system, particularly the road scanning device.We have reached a stage where we basically have to make a go orno-go decision concerning the research for this device, which, asyou all know by now, is a key feature in the DSS. We have alreadyintegrated the other devices, such as the PGS-based positioning anddirection system. The question we have to deal with is whether tofund basic research into the road scanning device. If this researchwere successful, we then would have to decide if we want to developa product based on these results—or if we just want to sell thetechnology without developing a product. If we do decide to developthe product ourselves, there is a chance that the productdevelopment process might not be successful. In that case, we couldstill sell the technology. In the case of successful productdevelopment, we would have to decide whether to market the product.If we decide not to market the developed product, we could at leastsell the product concept that was the result of our successfulresearch and development efforts. Doing so would earn more thanjust selling the technology prematurely. If, on the other hand, wedecide to market the driver support system, then we are faced withthe uncertainty of how the product will be received by ourcustomers.”“You completely lost me.” snipes Marc.Max, Julie’s assistant, just shakes his head and murmurs, “thosetechno-nerds. ”Brian starts to explain: “Sorry for the confusion. Let’s just gothrough it again, step by step.” “Good idea—and perhaps makesmaller steps!” Julie obviously dislikes Brian’s style ofpresentation.“OK, the first decision we are facing is whether to invest inresearch for the road scanningdevice.”“How much would that cost us?” asks Marc.“Our estimated budget for this is 300,000. Once we invest thatmoney, the outcome of the research effort is somewhat uncertain.Our engineers assess the probability of successful research at 80percent.”“That’s a pretty optimistic success rate, don’t you think?” Julieremarks sarcastically. She still remembers the disaster withBrian’s last project, the fingerprint-based car security system.After spending half a million dollars, the development engineersconcluded that it would be impossible to produce the securitysystem at an attractive price.Brian senses Julie’s hostility and shoots back: “In engineering weare quite accustomed to these success rates— something we can’t sayabout marketing. ”“What would be the next step?” intervenes Marc.“Hm, sorry. If the research is not successful, then we can onlysell the DSS in its currentform.”“The profit estimate for that scenario is2 million,” Julie throwsin.“If, however, the research effort is successful, then we will haveto make another decision,namely, whether to go on to the development stage.”“If we wouldn’t want to develop a product at that point, would thatmean that we would have to sell the DSS as it is now?” asksMax.“Yes, Max. Except that additionally we would earn some 200,000from selling our research results to GM. Their research division isvery interested in our work and they have offered me that money forour findings.”“Ah, now that’s good news,” remarks Julie.Brian continues, “If, however, after successfully completing theresearch stage, we decide to develop a new product then we’ll haveto spend another800,000 for that task, at a chance of 35 percentof not being successful.”“So you are telling us we’ll have to spend 800,000 for a ticket ina lottery where we have a 35 percent chance of not winninganything?” asks Julie.“Julie, don’t focus on the losses, but on the potential gains! Thechance of winning in this lottery, as you call it, is 65 percent. Ibelieve that that’s much more than with a normal lottery ticket,”says Marc.“Thanks, Marc,” says Brian. “Once we invest that money indevelopment, we have two possible outcomes: either we will besuccessful in developing the road scanning device or we won’t. Ifwe fail, then once again we’ll sell the DSS in its current form andcash in the200,000 from GM for the research results. If thedevelopment process is successful, then we have to decide whetherto market the new product.”“Why wouldn’t we want to market it after successfully developingit?” asks Marc.“That’s a good question. Basically what I mean is that we coulddecide not to sell the product ourselves but instead give the rightto sell it to somebody else, to GM, for example. They would pay us1 million for it.”“I like those numbers!” remarks Julie.“Once we decide to build the product and market it, we will facethe market uncertainties and I’m sure that Julie has those numbersready for us. Thanks.”At this point, Brian sits down and Julie comes forward to give herpresentation. Immediately some colorful slides are projected on thewall behind her as Max operates the computer.“Thanks, Brian. Well, here’s the data we have been able to gatherfrom some marketing research. The acceptance of our new product inthe market can be high, medium, or low,” Julie is pointing to somefigures projected on the wall behind her. “Our estimates indicatethat high acceptance would result in profits of8.0 million, andthat medium acceptance would give us 4.0 million. In theunfortunate case of a poor reception by our customers, we stillexpect2.2 million in profit. I should mention that these profitsdo not include the additional costs of marketing or R Dexpenses.”“So, you are saying that in the worst case we’ll make barely moremoney than with the current product?” asks Brian.“Yes, that’s what I am saying.”Marc.“What budget would you need for the marketing of our DSS with theroad scanner?” asks“For that we would need an additional 200,000 on top of whathas already been included inthe profit estimates,” Julie replies.“What are the chances of ending up with a high, medium, or lowacceptance of the new DSS?” asks Brian.“We can see those numbers at the bottom of the slide,” says Julie,while she is turning toward the projection behind her. There is a30 percent chance of high market acceptance and a 20 percent chanceof low market acceptance.At this point, Marc moves in his seat and asks: “Given all thesenumbers and bits of information, what are you suggesting that wedo?”(a) Organize the available data on cost andprofit estimates in a table.(b) Formulate the problem in a decision tree.Clearly distinguish between decision and event nodes.(c) Calculate the expected payoffs for each nodein the decision tree.(d) What is BAAG’s optimal policy according toBayes’decision rule?(e) What would be the expected value of perfectinformation on the outcome of the research effort? (f ) What wouldbe the expected value of perfect information on the outcome of thedevelopment effort?(g) Marc is a risk-averse decision maker. In anumber of interviews, his utility function for money was assessedto beu(M) = 1 – e –M/12 , ——————– 1 – e –1/12where M is the company’s net profit in units of hundreds ofthousands of dollars (e.g., M = 8 would imply a net profit of800,000). Using Marc’s utility function, calculate the utility foreach terminal branch of the decision tree.(h) Determine the expected utilities for allnodes in the decision tree.(i) Based on Marc’s utility function, what isBAAG’s optimal policy?(j) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of theresearch effort?(k) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of thedevelopment effort? (30) SOLVED: Decision Analysis with Probability:On a sunny May morning, Marc Binton, CEO of Bay Area AutomobileGadgets (BAAG), enters the conference room on the 40th floor of theGates building in San Francisco, where BAAG’s offices are located.The other executive officers of the company have already gathered.The meeting has only one item on its agenda: planning a researchand development project to develop a new driver support system(DSS). Brian Huang, Manager of Research and Development, is walkingaround nervously. He has to inform the group about the R Dstrategy he has developed for the DSS. Marc has identified DSS asthe strategic new product for the company. Julie Aker,VicePresident of Marketing, will speak after Brian. She will givedetailed information about the target segment, expected sales, andmarketing costs associated with the introduction of the DSS.BAAG builds electronic nonaudio equipment for luxury cars. Foundedby a group of Stanford graduates, the company sold its firstproduct—a car routing system relying on a technology called globalpositioning satellites (GPS)—a few years ago. Such routing systemshelp drivers to find directions to their desired destinations usingsatellites to determine the exact position of the car. To keep upwith technology and to meet the wishes of their customers, thecompany has added a number of new features to its router during thelast few years. The DSS will be a completely new product,incorporating recent developments in GPS as well as voicerecognition and display technologies. Marc strongly supports thisproduct, as it will give BAAG a competitive advantage over itsAsian and European competitors.Driver support systems have been a field of intense research formore than a decade. These systems provide the driver with a widerange of information, such as directions, road conditions, trafficupdates, etc. The information exchange can take place verbally orvia projection of text onto the windscreen. Other features help thedriver avoid obstacles that have been identified by cars ahead onthe road (these cars transmit the information to the followingvehicles). Marc wants to incorporate all these features and othertechnologies into one support system that would then be sold toBAAG’s customers in the automobile industry.After all the attendees have taken their seats, Brian starts hispresentation: “Marc asked me to inform you about our efforts withthe driver support system, particularly the road scanning device.We have reached a stage where we basically have to make a go orno-go decision concerning the research for this device, which, asyou all know by now, is a key feature in the DSS. We have alreadyintegrated the other devices, such as the PGS-based positioning anddirection system. The question we have to deal with is whether tofund basic research into the road scanning device. If this researchwere successful, we then would have to decide if we want to developa product based on these results—or if we just want to sell thetechnology without developing a product. If we do decide to developthe product ourselves, there is a chance that the productdevelopment process might not be successful. In that case, we couldstill sell the technology. In the case of successful productdevelopment, we would have to decide whether to market the product.If we decide not to market the developed product, we could at leastsell the product concept that was the result of our successfulresearch and development efforts. Doing so would earn more thanjust selling the technology prematurely. If, on the other hand, wedecide to market the driver support system, then we are faced withthe uncertainty of how the product will be received by ourcustomers.”“You completely lost me.” snipes Marc.Max, Julie’s assistant, just shakes his head and murmurs, “thosetechno-nerds. ”Brian starts to explain: “Sorry for the confusion. Let’s just gothrough it again, step by step.” “Good idea—and perhaps makesmaller steps!” Julie obviously dislikes Brian’s style ofpresentation.“OK, the first decision we are facing is whether to invest inresearch for the road scanningdevice.”“How much would that cost us?” asks Marc.“Our estimated budget for this is 300,000. Once we invest thatmoney, the outcome of the research effort is somewhat uncertain.Our engineers assess the probability of successful research at 80percent.”“That’s a pretty optimistic success rate, don’t you think?” Julieremarks sarcastically. She still remembers the disaster withBrian’s last project, the fingerprint-based car security system.After spending half a million dollars, the development engineersconcluded that it would be impossible to produce the securitysystem at an attractive price.Brian senses Julie’s hostility and shoots back: “In engineering weare quite accustomed to these success rates— something we can’t sayabout marketing. ”“What would be the next step?” intervenes Marc.“Hm, sorry. If the research is not successful, then we can onlysell the DSS in its currentform.”“The profit estimate for that scenario is2 million,” Julie throwsin.“If, however, the research effort is successful, then we will haveto make another decision,namely, whether to go on to the development stage.”“If we wouldn’t want to develop a product at that point, would thatmean that we would have to sell the DSS as it is now?” asksMax.“Yes, Max. Except that additionally we would earn some 200,000from selling our research results to GM. Their research division isvery interested in our work and they have offered me that money forour findings.”“Ah, now that’s good news,” remarks Julie.Brian continues, “If, however, after successfully completing theresearch stage, we decide to develop a new product then we’ll haveto spend another800,000 for that task, at a chance of 35 percentof not being successful.”“So you are telling us we’ll have to spend 800,000 for a ticket ina lottery where we have a 35 percent chance of not winninganything?” asks Julie.“Julie, don’t focus on the losses, but on the potential gains! Thechance of winning in this lottery, as you call it, is 65 percent. Ibelieve that that’s much more than with a normal lottery ticket,”says Marc.“Thanks, Marc,” says Brian. “Once we invest that money indevelopment, we have two possible outcomes: either we will besuccessful in developing the road scanning device or we won’t. Ifwe fail, then once again we’ll sell the DSS in its current form andcash in the200,000 from GM for the research results. If thedevelopment process is successful, then we have to decide whetherto market the new product.”“Why wouldn’t we want to market it after successfully developingit?” asks Marc.“That’s a good question. Basically what I mean is that we coulddecide not to sell the product ourselves but instead give the rightto sell it to somebody else, to GM, for example. They would pay us1 million for it.”“I like those numbers!” remarks Julie.“Once we decide to build the product and market it, we will facethe market uncertainties and I’m sure that Julie has those numbersready for us. Thanks.”At this point, Brian sits down and Julie comes forward to give herpresentation. Immediately some colorful slides are projected on thewall behind her as Max operates the computer.“Thanks, Brian. Well, here’s the data we have been able to gatherfrom some marketing research. The acceptance of our new product inthe market can be high, medium, or low,” Julie is pointing to somefigures projected on the wall behind her. “Our estimates indicatethat high acceptance would result in profits of8.0 million, andthat medium acceptance would give us 4.0 million. In theunfortunate case of a poor reception by our customers, we stillexpect2.2 million in profit. I should mention that these profitsdo not include the additional costs of marketing or R Dexpenses.”“So, you are saying that in the worst case we’ll make barely moremoney than with the current product?” asks Brian.“Yes, that’s what I am saying.”Marc.“What budget would you need for the marketing of our DSS with theroad scanner?” asks“For that we would need an additional 200,000 on top of whathas already been included inthe profit estimates,” Julie replies.“What are the chances of ending up with a high, medium, or lowacceptance of the new DSS?” asks Brian.“We can see those numbers at the bottom of the slide,” says Julie,while she is turning toward the projection behind her. There is a30 percent chance of high market acceptance and a 20 percent chanceof low market acceptance.At this point, Marc moves in his seat and asks: “Given all thesenumbers and bits of information, what are you suggesting that wedo?”(a) Organize the available data on cost andprofit estimates in a table.(b) Formulate the problem in a decision tree.Clearly distinguish between decision and event nodes.(c) Calculate the expected payoffs for each nodein the decision tree.(d) What is BAAG’s optimal policy according toBayes’decision rule?(e) What would be the expected value of perfectinformation on the outcome of the research effort? (f ) What wouldbe the expected value of perfect information on the outcome of thedevelopment effort?(g) Marc is a risk-averse decision maker. In anumber of interviews, his utility function for money was assessedto beu(M) = 1 – e –M/12 , ——————– 1 – e –1/12where M is the company’s net profit in units of hundreds ofthousands of dollars (e.g., M = 8 would imply a net profit of800,000). Using Marc’s utility function, calculate the utility foreach terminal branch of the decision tree.(h) Determine the expected utilities for allnodes in the decision tree.(i) Based on Marc’s utility function, what isBAAG’s optimal policy?(j) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of theresearch effort?(k) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of thedevelopment effort? (31)

01:31 BEST MATCH The Mexton Machines Company was founded in the 1950s on an old RAF airfield in the East Midlands of England. Originally, the company produced a range of small machines and tools for industry, but it expanded rapidly during the 60s and early 70s and acquired interests in industrial paint manufacture, prefabricated garages, and building materials. New production units were opened in Leicestershire, Yorkshire, and Bristol, and the Head Office was moved to Loughborough. However, the company fared badly during the recession of the early 1980s. The paint manufacturing side of the business was scaled down, and prefabricated garage production ceased. In 1996, a new management team took over, and it was decided that the company should diversify into the consumer goods market. A range of products was developed for the DIY enthusiast, including an electric drill and a car engine tuner. These are sold through the major DIY chains and hardware stores. To date, the products have been fairly success…
04:10 CASEJim Wells, vice-president for manufacturing of the Northern Airplane Company, is exasperated. His walk through the company’s most important plant this morning has left him in a foul mood. However, he now can vent his temper at Jerry Carstairs, the plant’s production manager, who has just been summoned to Jim’s office.“Jerry, I just got back from walking through the plant, and I am very upset.”“What is the problem, Jim?”“Well, you know how much I have been emphasizing the need to cut down on our in-process inventory.”“Yes, we’ve been working hard on that,” responds Jerry.“Well, not hard enough!” Jim raises his voice even higher. “Do you know what I found by the presses?”“No.”“Five metal sheets still waiting to be formed into wing sections. And then, right next door at the inspection station, 13 wing sections! The inspector was inspecting one of them, but the other 12 were just sitting there. You know we have a couple hundred tho…
03:38 This is a Case The Applegold company Applegold is a major cider producer withsales representing about 30% the UK cider market. The company,which is located in the West Midlands of England, sells its productin bottles and cans, and on draught in clubs and public houses. Inthe financial year 2001/2 the company achieved excellent results.The value of sales increased by 28% to $60 million and pre-taxprofits of $6 million represented and increase of 55% on theprevious year. Much of the company's success was based on sales ofdraught cider. The number of outlets selling the product hadincreased substantially over recent years and the upward trend insales had been accelerating. The growth in draught cider sales had,however, created some problems for the company's managers. Inparticular, there was concern that in August, when sales reached aseasonal peak, there might not be enough kegs available to meetdemand. Kegs are 11-gallon, stainless steel containers in whichdraught cider…
00:33 NIEDERHOFF SCM 265 WHITMAN SCHOOL OF MANAGEMENT SYRACUSE UNIVERSITYStrategy Essay"THE GOAL" by E.M. GoldrattWhat is The Goal? The book claims to be many things. It claims to be about science and education, about progress, about global principles of manufacturing, and some of you might say that it is about a love story (for those of you that think so, please let me know your names so I can preassign your course grades). For me, the book is:(a) a fascinating description of an operations process (for those of you without an operations background, an excellent opportunity to get an introduction to manufacturing environments),(b) an excellent example of how supply chain management should be viewed: as a business function which can be understood with the use of a business language and not with the use of obscure technical terminology, and(c) a powerful demonstration that the important, and in most cases only, prerequisite for becoming an operations manager is common sense and inte…
00:33 What Do We Not Want Algorithms to Dofor Us?Transparency is the great virtue of our digital age, and thealgorithm is often heralded as its handmaiden. Thanks toincreasingly sophisticated algorithms, we can discern patterns andpredict outcomes in everything from financial markets to Netflixpreferences. Algorithms can write reports and nonfictionnews stories; compose music, and offermedical diagnoses. Elegant in their simplicity, they bringinto the open things that have long been hidden. They doextraordinary things.What they can’t yet do is set limits on their own power; thatremains a task for people. And it’s one we are largely failing toperform. A recent story in the Wall StreetJournal about Castlight Health triggeredconcern when it was revealed that employers were using the serviceto mine employee health data in order to predict how many of theirworkers might develop specific health conditions, includingpregnancy.Castlight and other third-party data mining companies…

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SOLVED: Decision Analysis with Probability:On a sunny May morning, Marc Binton, CEO of Bay Area AutomobileGadgets (BAAG), enters the conference room on the 40th floor of theGates building in San Francisco, where BAAG’s offices are located.The other executive officers of the company have already gathered.The meeting has only one item on its agenda: planning a researchand development project to develop a new driver support system(DSS). Brian Huang, Manager of Research and Development, is walkingaround nervously. He has to inform the group about the R Dstrategy he has developed for the DSS. Marc has identified DSS asthe strategic new product for the company. Julie Aker,VicePresident of Marketing, will speak after Brian. She will givedetailed information about the target segment, expected sales, andmarketing costs associated with the introduction of the DSS.BAAG builds electronic nonaudio equipment for luxury cars. Foundedby a group of Stanford graduates, the company sold its firstproduct—a car routing system relying on a technology called globalpositioning satellites (GPS)—a few years ago. Such routing systemshelp drivers to find directions to their desired destinations usingsatellites to determine the exact position of the car. To keep upwith technology and to meet the wishes of their customers, thecompany has added a number of new features to its router during thelast few years. The DSS will be a completely new product,incorporating recent developments in GPS as well as voicerecognition and display technologies. Marc strongly supports thisproduct, as it will give BAAG a competitive advantage over itsAsian and European competitors.Driver support systems have been a field of intense research formore than a decade. These systems provide the driver with a widerange of information, such as directions, road conditions, trafficupdates, etc. The information exchange can take place verbally orvia projection of text onto the windscreen. Other features help thedriver avoid obstacles that have been identified by cars ahead onthe road (these cars transmit the information to the followingvehicles). Marc wants to incorporate all these features and othertechnologies into one support system that would then be sold toBAAG’s customers in the automobile industry.After all the attendees have taken their seats, Brian starts hispresentation: “Marc asked me to inform you about our efforts withthe driver support system, particularly the road scanning device.We have reached a stage where we basically have to make a go orno-go decision concerning the research for this device, which, asyou all know by now, is a key feature in the DSS. We have alreadyintegrated the other devices, such as the PGS-based positioning anddirection system. The question we have to deal with is whether tofund basic research into the road scanning device. If this researchwere successful, we then would have to decide if we want to developa product based on these results—or if we just want to sell thetechnology without developing a product. If we do decide to developthe product ourselves, there is a chance that the productdevelopment process might not be successful. In that case, we couldstill sell the technology. In the case of successful productdevelopment, we would have to decide whether to market the product.If we decide not to market the developed product, we could at leastsell the product concept that was the result of our successfulresearch and development efforts. Doing so would earn more thanjust selling the technology prematurely. If, on the other hand, wedecide to market the driver support system, then we are faced withthe uncertainty of how the product will be received by ourcustomers.”“You completely lost me.” snipes Marc.Max, Julie’s assistant, just shakes his head and murmurs, “thosetechno-nerds. ”Brian starts to explain: “Sorry for the confusion. Let’s just gothrough it again, step by step.” “Good idea—and perhaps makesmaller steps!” Julie obviously dislikes Brian’s style ofpresentation.“OK, the first decision we are facing is whether to invest inresearch for the road scanningdevice.”“How much would that cost us?” asks Marc.“Our estimated budget for this is 300,000. Once we invest thatmoney, the outcome of the research effort is somewhat uncertain.Our engineers assess the probability of successful research at 80percent.”“That’s a pretty optimistic success rate, don’t you think?” Julieremarks sarcastically. She still remembers the disaster withBrian’s last project, the fingerprint-based car security system.After spending half a million dollars, the development engineersconcluded that it would be impossible to produce the securitysystem at an attractive price.Brian senses Julie’s hostility and shoots back: “In engineering weare quite accustomed to these success rates— something we can’t sayabout marketing. ”“What would be the next step?” intervenes Marc.“Hm, sorry. If the research is not successful, then we can onlysell the DSS in its currentform.”“The profit estimate for that scenario is2 million,” Julie throwsin.“If, however, the research effort is successful, then we will haveto make another decision,namely, whether to go on to the development stage.”“If we wouldn’t want to develop a product at that point, would thatmean that we would have to sell the DSS as it is now?” asksMax.“Yes, Max. Except that additionally we would earn some 200,000from selling our research results to GM. Their research division isvery interested in our work and they have offered me that money forour findings.”“Ah, now that’s good news,” remarks Julie.Brian continues, “If, however, after successfully completing theresearch stage, we decide to develop a new product then we’ll haveto spend another800,000 for that task, at a chance of 35 percentof not being successful.”“So you are telling us we’ll have to spend 800,000 for a ticket ina lottery where we have a 35 percent chance of not winninganything?” asks Julie.“Julie, don’t focus on the losses, but on the potential gains! Thechance of winning in this lottery, as you call it, is 65 percent. Ibelieve that that’s much more than with a normal lottery ticket,”says Marc.“Thanks, Marc,” says Brian. “Once we invest that money indevelopment, we have two possible outcomes: either we will besuccessful in developing the road scanning device or we won’t. Ifwe fail, then once again we’ll sell the DSS in its current form andcash in the200,000 from GM for the research results. If thedevelopment process is successful, then we have to decide whetherto market the new product.”“Why wouldn’t we want to market it after successfully developingit?” asks Marc.“That’s a good question. Basically what I mean is that we coulddecide not to sell the product ourselves but instead give the rightto sell it to somebody else, to GM, for example. They would pay us1 million for it.”“I like those numbers!” remarks Julie.“Once we decide to build the product and market it, we will facethe market uncertainties and I’m sure that Julie has those numbersready for us. Thanks.”At this point, Brian sits down and Julie comes forward to give herpresentation. Immediately some colorful slides are projected on thewall behind her as Max operates the computer.“Thanks, Brian. Well, here’s the data we have been able to gatherfrom some marketing research. The acceptance of our new product inthe market can be high, medium, or low,” Julie is pointing to somefigures projected on the wall behind her. “Our estimates indicatethat high acceptance would result in profits of8.0 million, andthat medium acceptance would give us 4.0 million. In theunfortunate case of a poor reception by our customers, we stillexpect2.2 million in profit. I should mention that these profitsdo not include the additional costs of marketing or R Dexpenses.”“So, you are saying that in the worst case we’ll make barely moremoney than with the current product?” asks Brian.“Yes, that’s what I am saying.”Marc.“What budget would you need for the marketing of our DSS with theroad scanner?” asks“For that we would need an additional 200,000 on top of whathas already been included inthe profit estimates,” Julie replies.“What are the chances of ending up with a high, medium, or lowacceptance of the new DSS?” asks Brian.“We can see those numbers at the bottom of the slide,” says Julie,while she is turning toward the projection behind her. There is a30 percent chance of high market acceptance and a 20 percent chanceof low market acceptance.At this point, Marc moves in his seat and asks: “Given all thesenumbers and bits of information, what are you suggesting that wedo?”(a) Organize the available data on cost andprofit estimates in a table.(b) Formulate the problem in a decision tree.Clearly distinguish between decision and event nodes.(c) Calculate the expected payoffs for each nodein the decision tree.(d) What is BAAG’s optimal policy according toBayes’decision rule?(e) What would be the expected value of perfectinformation on the outcome of the research effort? (f ) What wouldbe the expected value of perfect information on the outcome of thedevelopment effort?(g) Marc is a risk-averse decision maker. In anumber of interviews, his utility function for money was assessedto beu(M) = 1 – e –M/12 , ——————– 1 – e –1/12where M is the company’s net profit in units of hundreds ofthousands of dollars (e.g., M = 8 would imply a net profit of800,000). Using Marc’s utility function, calculate the utility foreach terminal branch of the decision tree.(h) Determine the expected utilities for allnodes in the decision tree.(i) Based on Marc’s utility function, what isBAAG’s optimal policy?(j) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of theresearch effort?(k) Based on Marc’s utility function, what wouldbe the expected value of perfect information on the outcome of thedevelopment effort? (43)

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SOLVED: Decision Analysis with Probability: On a sunny May morning, Marc Binton, CEO of Bay Area Automobile Gadgets (BAAG), enters the conference room on the 40th floor of the Gates building in San Francisco, where BAAG’s offices are located. The other ex (2024)
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