On Business Optimization

Is It Worth The Costs To Stop Global Warming?

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The debate over global warming is heating up again. A group of allegedly stolen e-mails is giving fuel to the fire to those who believe that global warming caused by human activities or Anthropogenic Global Warming (AGW) is a scientific fraud of massive proportions.

However, the question shouldn't be whether or not global warming is caused by AGW. It isn't a yes or no question.

The question should be: What is the percent probability that AGW will have catastrophic effects (between 0 and 100% probability)?

(Those of you who truly believe that the percent probability is 0% can stop reading now. And if you don't believe that any kind of global warming is occurring then you can also stop reading.)

After we have estimated the percent probability, we need to estimate what the economic costs will be if AGW causes a global catastrophe because we did nothing to stop it.

Let's assume the costs would represent millions or billions of dead human beings, beneficial ecosystems destroyed, and mass extinctions of animal and plant species. (I recognize that putting this in sterile economic terms will seem heartless to many, but we don't really have another good way to put a number on it.)

Once we have these two values, we can calculate the "expected value" of the cost of AGW. We'd take the cost of a global catastrophe and multiply it by the probability of it occurring:

Cost($) * Probability of occurrence(%) = expected value of the cost of AGW($)

Once we have that value, it would be prudent of us to figure out what the cost and risks of trying to stop or ameliorate the severity of AGW would be. If the cost to stop it is less than the expected value of the cost of a global catastrophe caused by AGW and the associated risks trying are acceptable, then we're fools as a species not to consider paying the costs of trying to stop it.

What do you think the expected value is?

Business At Microsecond Speeds – How Fast Can You Go?

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Quantitative financial analysts ("Quants") who design trading algorithms or optimize them to work just a few milliseconds or even microseconds faster are in high-demand these days. Successful trading algorithms often work by taking advantage of millisecond market inefficiencies that aren't widely recognized by other traders. This advantage is lost once other traders discover and begin to trade on the same inefficiencies.

Since the profitable lifespan of proprietary trading algorithms keeps getting shorter, optimizing an algorithm to execute faster is one way to extend its lifespan. So the competition for hiring really good quants that can discover, develop, and optimize new trading algorithms is fierce.

Your business probably doesn't require microsecond decision-making, but the speed and quality with which your business can execute is going continue to become increasingly important. World-wide competition is speeding up innovation, shortening product development times, and reducing product lifecycles.

While many companies are using IT to improve business processes, most of them are just scratching the surface when it comes to using meaningful business analytics to speed up those processes.

When everybody in an industry is using the same IT and business processes, nobody has an advantage. The advantage will come to those who can discover, develop, and optimize business processes beyond what everybody else is doing. That might mean just looking at the little things that everybody else overlooks (or doesn’t think is important) and speeding them up by a few days or even just a few hours. Just as saving a few microseconds is important to a quant, saving those few days or hours could mean the difference between leading in your business or just being one of the pack.

Look around. What's limiting the speed of your business?

Teaching and Learning Project Portfolio Management: What's Your Experience?

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I’ve also been toying for the last several years with the idea of developing a turn-key module for senior undergraduates or graduate business students in project portfolio management and/or decision analysis using Optsee®. It would be similar to an assignment I had at Wharton in an R&D Management class taught by Professor Earnest Gilmont, except that we didn't use any software or decision analysis tools. 

Each student would get a copy of Optsee® that is pre-loaded with an unoptimized portfolio of projects with pre-assigned attributes (such as rewards, costs, resources, risks, etc.) and sets of constraints created for a hypothetical company. The students would form teams, and each team would be assigned to take their set of projects and develop an optimized portfolio that was targeted for different strategic goals. For example:

• one team would develop a portfolio designed to make the company attractive for being acquired
• one team would develop a portfolio designed for implementing an outsourcing strategy
• one team would develop a portfolio to maximize short-term gain
• one team would develop a portfolio to maximize long-term sustainability

Each team would then put together a presentation and/or a paper presenting their portfolio and how they came to agree on it. This would require the team to agree on what attributes to use, the shapes of the attribute curves, the attribute weights, and what constraints they would need to apply.

I think that this could all be put into a nice educational package that would give students an excellent understanding of developing strategic project portfolios based on business goals through their own experiences and by seeing the different portfolios developed by their classmates. It would also give them a fundamental  understanding and appreciation of multi-criteria or multiattribute decision analysis, prioritization using Monte Carlo simulations, and optimization against multiple constraints. 

So I am curious. How did you learn about Project Portfolio Management? And if you're a professor, how do you teach it?

Chart Differences That Can Unconsciously Persuade Your Audience

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Researchers at the University of Münster in Germany have shown that people can be highly influenced in selecting financial assets simply by the way the risks are charted. Their study, published in the June 2009 issue of Decision Analysis, showed that people are significantly more likely to select data charted in one way versus the same data charted in a different way. They also showed that people who self-describe themselves as "risk averse" (as most people do) will prefer one type of data presentation over another type.

In particular, two types of commonly used data distribution curves were discussed: probability density functions (skewed bell curves) and cumulative distribution functions (S-type or logistic curves):

In multiple experiments involving subjects selecting financial asset models using data with "right skewness" in probability density plots, people were significantly more likely to select the model if it was instead displayed as a cumulative distribution function (S-type curve). For financial asset models data with "left skewness," the opposite was true; people were more likely to select it if the model was presented as a probability density plot (left-skewed bell curve). Furthermore, the researchers found that "Individuals that judge themselves as more risk averse show a stronger preference for right skewness."

The authors note that:

"The findings of this paper have several practical implications. First, in advertising their products a financial services firm may choose the presentation format that is most likely to induce specific preferences for the considered financial product. For example, the sales brochure of a mutual fund investing exclusively in growth firms may use a presentation format that induces a preference for right skewness. Similarly, a firm advertising a discount certificate, a financial instrument that implements a covered call strategy and thereby generates a left-skewed distribution, may use a density function to communicate the asset’s risk."

What are the implications of this if you're not an advertiser trying to pitch financial services to potential customers?

Well, if you do any kind of business analysis presentations, like project portfolio management analyses, you'll want to remember that the chart types that you select for your data can strongly influence your audience based on their unconscious preferences. 

And if you're looking at charts in order to make a decision based on the data, be sure that you look at the data in different chart types so you don't make your selection based on your own unconscious preferences.

Where's Your "Solve My Problem" Button?

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We all want one of these buttons, right? Wouldn't it be nice to pry the "Help" button off your keyboard and put one of these in its place? When I want a problem solved, I don't want to look through dozens of menu items and forms, navigate through features I'll never use, and search through websites and PDF files. 

I just want my problem solved. And so do your customers.

Two years ago, while everybody else was developing more and more feature-rich (and complicated) video cameras, a company called PureDigital released the point-and-shoot equivalent of a video camera called the Flip Ultra. It was small, inexpensive, simple to operate, and had only essential functionality. And it sold like crazy.

The problem it solved? How to get videos on the web easily and quickly without having to read a novel-sized instruction manual. Today, the Flip Ultra products are the best selling video cameras in the U.S.

Feature-creep and the resultant complexity are big challenges to many technology products. So instead of trying to improve your company's products and services by adding new features, what if you optimized them by removing some features and combining others? 

What if your products and services could have only one button: the "Solve My Problem" button? What would it do? And since one button usually isn't realistic, what are the minimum numbers of "Solve My Problem" buttons that you need to solve your customers' problems in a delightful and surprisingly simple way? What if you prioritized your most important and fundamental customer benefits and then offered a product that delivered only those features and nothing else?

In designing our project portfolio management tools, we try to answer those questions every day. For example, we've reduced the effort of prioritizing your portfolio using Monte Carlo simulations to a couple of mouse clicks. If you can answer those questions while nobody else in your industry is even asking them, you may discover a whole new market out there waiting for you.

The Future of Business Optimization: A Person, A Dog, and A Computer

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Brendan Coveney, President of 4D Inc., once remarked that the business of the future will consist of a person, a dog, and a computer. The purpose of the computer will be to run the business and the purpose of the dog will be to keep the person away from the computer.

Fortunately, we’re not there – yet. But we are at a point where we could be using our computers to optimize our businesses much more effectively. Many businesses are still in the "steam shovel" era of business optimization, using only spreadsheets to track and improve business performance. Certainly, this is far better than doing it by hand but not nearly as powerful as the modern tools that they could be using.

“But what's wrong with spreadsheets?” you might ask. Nothing. Spreadsheets are great but they still require a tremendous amount of manual labor to prepare, maintain, and audit. Fall down in any one of those tasks and the value of the spreadsheet and the data quickly deteriorates. And so do the business functions depending on it.

Instead of spreadsheets, what if you were using applications that were already set up to prepare, maintain, and audit your data as well as perform complex analyses of your data in just a few mouse clicks?

So now you can move beyond spreadsheets into applications that do much of the left brain quantitative drudge work for us so we can direct our thinking to creatively extracting more valuable concepts, ideas, and wisdom from our numbers and data. And we can do that by using algorithms.

But before you say, “I don’t want to have to learn algorithms to do my business analyses,” let me assure you that you won’t have to. The idea is to have applications designed and built for you that let you focus on running your business, not on building applications or customizing spreadsheets.

For example, there’s a clever little “artificial intelligence” algorithm for finding the shortest distance between multiple points called “the ant algorithm.” The ant algorithm is based on the way an ant colony learns the shortest distance from the anthill to a food source. Now you don’t even need to know the name of this algorithm or where it originated; all you need to know is that it can help you find an optimum solution when applied to a particular business problem. An elegant and well-designed application will do this type of work for you without you needing to learn how to program or write spreadsheet macros.

In this blog, I’ll be writing about the intersection of business, science, design, and technology as a place where we can use well-designed technology to do far more than just crunch numbers and make pretty graphics. We'll explore other best practices and innovations that business are using to optimize their processes, products, and markets like we do with our own project portfolio management tool, Optsee^®.