Interesting experiment in fuel economy, pitting a compact hybrid versus a midsize sedan. I don't know about the methodology, so I don't know if the results are scientific (ie, repeatable), but it does indicate that there are many solutions to the problems we face.
What are the costs of settling for what seems to be a good solution quickly, if that leads you to miss an even better solution later on? Modeling business decisions can lead managers to stop looking after they've found the "optimal" solution, too.
Saturday, March 29, 2008
Tuesday, March 25, 2008
New Class for Fall 2008 Semester
I will be teaching a new class, OPIM 4895 Spreadsheet Modeling for Business Decision Making.
The class will focus on the techniques that businesses use to obtain a competitive advantage through analytics. The course will be based in Excel, to learn how the techniques work, and students will be able to translate the skills from the class to special-purpose tools that companies often use for particular problems.
Problem settings will span all of the functional business areas: operations (my background), finance and marketing, and there will be case work involved in the class to look at how analytic modeling fits into the business situation that requires decisions to be made. The right decision is always a function of the business strategy, which is why different companies "solve" problems in different ways (consider that Delta, Southwest and Skybus can all fly you from Hartford, but in very different ways).
Part of the class will focus on "optimization." In these settings, we will try to represent complex decision settings where there are limits on what the decision maker can do. For example, suppose that as marketing manager, you have to allocate the money for a new product campaign across different channels (print, radio, television, web). What is the best use of the limited dollars? Or suppose you are trying to schedule people in a customer service center in such a way that their schedules are "attractive" and that customers get good service but also that the total cost is as low as possible.
We will also look at "decision analysis" where uncertainty about the world is only revealed after you must make your decision. Think about the poor person on Deal or No Deal, with everyone screaming different decisions. Is there a way to think about making "good" decisions? The answer is yes, by the way.
Part of the class will also be devoted to the increasing use of simulation in business. Older techniques use "scenarios" to evaluate a business decision in the face of different possible outcomes (interest rates rise by some amount, decrease by some amount, stay flat). Within a spreadsheet model, it is possible to create models that can sample thousands of possible scenarios and reveal the patterns of how the business works in those different scenarios. In much the same way that a pilot uses a simulator to practice landing in different weather situations, simulation can be used by businesses to "try out" different strategies against possible future scenarios to better understand how to proceed. Risk analysis is quite often done in this way for financial planning.
Please feel free to email me if you have other questions about the class.
The class will focus on the techniques that businesses use to obtain a competitive advantage through analytics. The course will be based in Excel, to learn how the techniques work, and students will be able to translate the skills from the class to special-purpose tools that companies often use for particular problems.
Problem settings will span all of the functional business areas: operations (my background), finance and marketing, and there will be case work involved in the class to look at how analytic modeling fits into the business situation that requires decisions to be made. The right decision is always a function of the business strategy, which is why different companies "solve" problems in different ways (consider that Delta, Southwest and Skybus can all fly you from Hartford, but in very different ways).
Part of the class will focus on "optimization." In these settings, we will try to represent complex decision settings where there are limits on what the decision maker can do. For example, suppose that as marketing manager, you have to allocate the money for a new product campaign across different channels (print, radio, television, web). What is the best use of the limited dollars? Or suppose you are trying to schedule people in a customer service center in such a way that their schedules are "attractive" and that customers get good service but also that the total cost is as low as possible.
We will also look at "decision analysis" where uncertainty about the world is only revealed after you must make your decision. Think about the poor person on Deal or No Deal, with everyone screaming different decisions. Is there a way to think about making "good" decisions? The answer is yes, by the way.
Part of the class will also be devoted to the increasing use of simulation in business. Older techniques use "scenarios" to evaluate a business decision in the face of different possible outcomes (interest rates rise by some amount, decrease by some amount, stay flat). Within a spreadsheet model, it is possible to create models that can sample thousands of possible scenarios and reveal the patterns of how the business works in those different scenarios. In much the same way that a pilot uses a simulator to practice landing in different weather situations, simulation can be used by businesses to "try out" different strategies against possible future scenarios to better understand how to proceed. Risk analysis is quite often done in this way for financial planning.
Please feel free to email me if you have other questions about the class.
Sunday, March 23, 2008
Supply and demand
Now, please understand that I am not a geologist and have no expertise about drilling for oil. But I do understand that when the price of something goes up, one of two amazing things happen (or a mixture of the two): demand goes down, or people find a way to supply more.
It hurts to fill up the car with gas these days, but here are two independent stories that are different from the usual gloom and doom we read everyday: oil field development in North Dakota and the Falkland Islands.
It hurts to fill up the car with gas these days, but here are two independent stories that are different from the usual gloom and doom we read everyday: oil field development in North Dakota and the Falkland Islands.
Saturday, March 22, 2008
Traveling Salesman Problem, part 2
Now for non-geeks, what does the cartoon in part one mean? When thinking about finding the optimal solution to a problem, one question is how "hard" is the problem. If there are only two solutions, then you could probably spend the time to evaluate both and pick the better one. Most problems have many solutions, and so any algorithm to find the best is going to have to evaluate some number of potential solutions in order to find the best.
This leads to the "order" notation, O(n). What this says is the problem is "order n" and that while we might not know the exact time to evaluate each possible solution, we know we are going to have to check about "n" of them.
Now the traveling salesman problem (TSP) is one where we have to visit some number of locations, one after the other. Suppose I sell golf balls and want to visit five different golf courses today. I start at my house, and I go to one of the golf courses. From there I can choose one of the remaining four. From there, I choose one of the three, and so on, until I return home at the end of the day. How many different ways are there to do this? Turns out that this is the number of permutations of the five (and if you count your home, actually six) locations, and the number of permutations is given by n! = n(n-1)(n-2)...(2)(1). One way to solve the problem is to check every solution, all n! of them.
Suppose there are 10 locations to visit, and that your laptop computer can figure out the length of a trip with a certain visiting sequence in one thousandth of a second. You can come back to your computer in about an hour for the solution. What happens if you add two locations to visit. The awful truth about factorials is they grow like crazy, and now your computer needs five days to find the solution. What to solve 15 locations? It will take your computer 40 years. Ouch.
So geeks try to find sneaky ways to evaluate all the "good" solutions, and implicitly check the others without doing any work. Dynamic programming is one of the sneaky methods for evaluating only some of the possible solutions, but still knowing that the best of the ones you find is better than all of the possible n! solutions. The algorithm in the cartoon is O(n^2 x 2^n). So for 10 locations, we can solve the problem in about one second (instead of an hour). Twelve locations takes four seconds, and 15 takes about a minute. Much better than 40 years!
So geeks win? Not so fast. Try thirty locations -- 12 days. Thirty-five locations? A year. Forty locations? 35 years. Don't even think about 100 locations...
What does O(1) mean? The third panel guy can sell to 100 golf courses by doing just one thing. Okay, you need to have a particularly warped sense of humor to find that funny. But such senses of humor do exist (me, unfortunately).
If you've read this far, thanks. But is this problem really important? Do salesmen really do this? Well think about oil delivery trucks or a beer distributor who restocks convenience stores. Lots of locations, lots of choices about who to visit today, and who to visit tomorrow, and the price of gas for your truck keeps going up.
Or think about making printed circuit boards. A robot arm (usually) picks the chips from a storage position (sometimes attached to a tape) and puts them on the board in a particular location. The optimal sequence (the shortest trip to visit the n chip sites on the board) may take a lot less time than a non-optimal one, increasing costs and reducing capacity. Could there be 100 chips on a board? Sure.
This leads to the "order" notation, O(n). What this says is the problem is "order n" and that while we might not know the exact time to evaluate each possible solution, we know we are going to have to check about "n" of them.
Now the traveling salesman problem (TSP) is one where we have to visit some number of locations, one after the other. Suppose I sell golf balls and want to visit five different golf courses today. I start at my house, and I go to one of the golf courses. From there I can choose one of the remaining four. From there, I choose one of the three, and so on, until I return home at the end of the day. How many different ways are there to do this? Turns out that this is the number of permutations of the five (and if you count your home, actually six) locations, and the number of permutations is given by n! = n(n-1)(n-2)...(2)(1). One way to solve the problem is to check every solution, all n! of them.
Suppose there are 10 locations to visit, and that your laptop computer can figure out the length of a trip with a certain visiting sequence in one thousandth of a second. You can come back to your computer in about an hour for the solution. What happens if you add two locations to visit. The awful truth about factorials is they grow like crazy, and now your computer needs five days to find the solution. What to solve 15 locations? It will take your computer 40 years. Ouch.
So geeks try to find sneaky ways to evaluate all the "good" solutions, and implicitly check the others without doing any work. Dynamic programming is one of the sneaky methods for evaluating only some of the possible solutions, but still knowing that the best of the ones you find is better than all of the possible n! solutions. The algorithm in the cartoon is O(n^2 x 2^n). So for 10 locations, we can solve the problem in about one second (instead of an hour). Twelve locations takes four seconds, and 15 takes about a minute. Much better than 40 years!
So geeks win? Not so fast. Try thirty locations -- 12 days. Thirty-five locations? A year. Forty locations? 35 years. Don't even think about 100 locations...
What does O(1) mean? The third panel guy can sell to 100 golf courses by doing just one thing. Okay, you need to have a particularly warped sense of humor to find that funny. But such senses of humor do exist (me, unfortunately).
If you've read this far, thanks. But is this problem really important? Do salesmen really do this? Well think about oil delivery trucks or a beer distributor who restocks convenience stores. Lots of locations, lots of choices about who to visit today, and who to visit tomorrow, and the price of gas for your truck keeps going up.
Or think about making printed circuit boards. A robot arm (usually) picks the chips from a storage position (sometimes attached to a tape) and puts them on the board in a particular location. The optimal sequence (the shortest trip to visit the n chip sites on the board) may take a lot less time than a non-optimal one, increasing costs and reducing capacity. Could there be 100 chips on a board? Sure.
Tracking inventory, among other things
We all see barcodes in action at most retail stores, and the increased accuracy that technology allows in collecting sales information opened up all kinds of analysis. A newer technology, radio frequency identification (RFID) takes this one step further by putting a chip on the merchandise that can talk to computers. IBM has a commercial where a truck is lost and it stops at an IBM help desk in the middle of the desert. The drivers ask how the help desk person knew they were lost. She says "the inventory told us." If the RFID tags know they are supposed to be heading east and they start going north, they could send out a "help us" message. Or a supermarket could tag everything, and when you go to the checkout, a computer could read all of the tags in your cart all at once. Cool, huh?
But one interesting part of technology is that the intended use and the actual uses often diverge. Here's a company with an interesting application of RFID. Watch where you walk.
But one interesting part of technology is that the intended use and the actual uses often diverge. Here's a company with an interesting application of RFID. Watch where you walk.
Friday, March 21, 2008
Traveling Salesman Problem
The traveling salesman problem is one of a class of "hard" problems, where even if you have insanely fast computers, the solution cannot be verified for thousands of years.
Of course, if you shift the problem setting slightly, the problem can become much easier.
note: this is a geek comic, and I will post what the notation means, and why it is funny (to a certain set of people) in a later post...
Of course, if you shift the problem setting slightly, the problem can become much easier.
note: this is a geek comic, and I will post what the notation means, and why it is funny (to a certain set of people) in a later post...
Tuesday, March 18, 2008
What do we know?
Science depends on statistics to allow us to "know" something. We experiment and show differences and try to show that those differences are not just random, but show some underlying effect.
Sometimes, even statistics are not enough, when enough people in a field are convinced of the current theories -- which are theories because they can never be "proved." An example is the struggle of two scientists who saw the data tell them that ulcers were not caused by what "everyone" knew they were caused by, but rather by a bacteria. Publishing their results was frustrated because the reviewers knew they must be wrong.
Lucky for us they persevered, and eventually on the Nobel Prize.
Sometimes, even statistics are not enough, when enough people in a field are convinced of the current theories -- which are theories because they can never be "proved." An example is the struggle of two scientists who saw the data tell them that ulcers were not caused by what "everyone" knew they were caused by, but rather by a bacteria. Publishing their results was frustrated because the reviewers knew they must be wrong.
Lucky for us they persevered, and eventually on the Nobel Prize.
Business School naming
Most business schools that are ranked among the best in the country have been named after a significant donor. Tuck, Sloan, Wharton, Stern, Fuqua, Simon (my alma mater) among others. Of course there are the exceptions who have enough money to not need someone's name -- Harvard and Stanford, for example. Then there are schools with no name that could find wonderful uses for such a gift. UConn, for example.
Wisconsin has found a way to have it both ways, when a group of alumni got together to give the school $85 million to not allow the name to be changed. So it will be the Wisconsin School of Business, at least for the next twenty years.
update: Why do people give in the first place?
Wisconsin has found a way to have it both ways, when a group of alumni got together to give the school $85 million to not allow the name to be changed. So it will be the Wisconsin School of Business, at least for the next twenty years.
update: Why do people give in the first place?
Thursday, March 13, 2008
Some Study Abroad Pictures
Here is a small album that I've used for the study abroad fair. Most of the pictures are Italy, but there are a few from Ireland, the Netherlands, Switzerland, Barcelona, Denmark and Guatemala. I will put up a more complete set of pictures from the 2007 Florence business program a little later.
Wednesday, March 12, 2008
Subprime mortgage mess
Ok, you have to be warned that there's a bit of less-than-polite language, but this is an interesting explanation of the subprime mortgage mess. I'm sure there was also some sophisticated modeling involved that, unfortunately, depended on an assumption that gets mentioned in the link. That assumption is not holding, and so the modeling has not played out as expected.
Traffic jams
The same queueing effects we see in operations happens on the road every day -- you can come across a lengthy backup on the Merritt Parkway and find that there was no accident or other "cause" for the delay. This article links to some work in this area. Small amounts of variability have more power to affect things than people realize.
Thursday, February 28, 2008
Hal Varian
Hal Varian is a very smart guy who was at UC Berkely and is now at Google. Here's an interview in the NY Times, and an earlier one in the Wall Street Journal. Good reading and some good advice.
Tuesday, February 26, 2008
Pie Charts
Most pie charts are not very efficient at showing relationships (often you can just write the numbers instead). I finally found a pie chart that does more.
How things are made
Stanford has a wonderful site that has some videos about how different kinds of products are made.
Small Italian firms go global
Story about a small (50 employees) Italian company that makes dresses, but sells them around the world. Going global was the only way for the company to stay in business, because the number of local customers willing to pay for the quality and detail work of their dresses would not have been large enough for the company to stay in business.
Next time you see a website for a company (especially one that does very specialized products), think about how many employees there might be at that "global" company.
Next time you see a website for a company (especially one that does very specialized products), think about how many employees there might be at that "global" company.
Monday, February 25, 2008
Microsoft and Yahoo
Interesting article in the NYTimes about Microsoft's offer for Yahoo. Seems to me that Microsoft is trying to sort out what business it is in in the long run, especially with the advent of open source software and on-line tools (Google docs anyone?). The Yahoo strategy seems to indicate that Microsoft is betting that computing is becoming Web 2.0 enabled (rather than driven by software loaded onto your computer). As a thought exercise, consider the minimum amount of software you would need on your computer to do most (all?) of your work. BTW, is this the market that the Apple Air is targeting? If you have everything on the web, a DVD drive and lots of USB ports aren't as important, eh?
I had not thought about the SAP strategy before reading the article, but that provides a completely different strategy, where in fact Microsoft products (Office, Outlook, etc) continue to be purchased because of their integration with the software that drives enterprises. Individuals use Office-like tools and web based email, but Microsoft stops thinking of them as their customers.
What are the margins in these two businesses? This strikes me as a very interesting case study: the company knows the current business model is not sustainable and has two very viable ways to reinvent itself. Which does it choose and how does it decide?
I had not thought about the SAP strategy before reading the article, but that provides a completely different strategy, where in fact Microsoft products (Office, Outlook, etc) continue to be purchased because of their integration with the software that drives enterprises. Individuals use Office-like tools and web based email, but Microsoft stops thinking of them as their customers.
What are the margins in these two businesses? This strikes me as a very interesting case study: the company knows the current business model is not sustainable and has two very viable ways to reinvent itself. Which does it choose and how does it decide?
Saturday, February 23, 2008
Wikipedia
How many people actually contribute to wikipedia? Do they contribute a little or a lot? Here is an article about some research into how democratic collaborative sites like wikipedia and digg are.
Wednesday, February 13, 2008
Housing prices
Here's an interesting set of graphs of the movement of housing prices over the years. Think about what the graphs "say" and the implications of the way they are constructed. What changes could you make to tell a the kind of story that the text argues for?
Tuesday, February 12, 2008
Economies of scale in marriage
In operations management, we are careful to look at how economies of scale allow for new products and decreasing costs for existing products -- think about how much computing power you can carry around with you that used to take up an entire room (and special air conditioning and a staff of operators). Here's an interesting article that applies the notion of economies of scale to marriage and divorce.
Modeling the effects of global warming
In article in the NY Times, there is some analysis between two alternatives: trying to stop global warming and preserve the current climate versus assuming the worst case for climate change (much warmer earth) and then trying to adapt to that climate.
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