Mercury's Blog

Companies that are looking to use prediction markets in their business need to build a business case for doing so.  In order to build that case, they need to determine what information can a market efficiently provide, and how can that improve their strategy and day-to-day operations?  I’d like to address three main question areas that prediction markets can solve, and how you can start developing a business case based on the results of the improved forecasting.

The first, and perhaps most powerful, is project management.

Every project has various key milestones, and those on the critical path are even more visible to and closely watched by managers and executives.  Most forecasting to date is largely self-reported by team leaders.  They are largely meant to be as honest as possible in reporting project status.  In reality, this is highly dependent on the company’s culture, and in far too many businesses, project status is a commonly-known lie.  (Unfortunately, this also means that it can be a politically dangerous kind of market to implement, since the project managers that tell these lies usually don’t want to be exposed!)

The business case for a prediction market in project management should be calculated based on the effects of slips in a project’s schedule.  For projects or products where sales are front-loaded (such as films, major software releases, ground-breaking new drugs, and the like) a project’s slip into the next fiscal quarter or next fiscal year could cause a serious impact in potential earnings.  If that information was available weeks or months earlier, how would that affect sales, reputation in the marketplace, and other factors important in your industry?  How much does it cost to plan for a major product roll-out in January, only to have to cancel it all and do it all over again in April?  These are the questions that can build a business case for a project management prediction market.

The second type of market quantifies your industry.

In many industries, this means defining the cost of goods needing to be purchased, the quantity of goods or services to be sold, or the price potential of the goods or services to be sold.  In some industries, this could mean quantifying the user growth of a given product.  (Such as Google’s prediction markets, “How many users of [Google product] will we have at the end of Q3?”)  This is the classic case written about by HP’s research center, when they asked their traders to predict sales figures for various products for the next quarter.  It turned out they were measurably better than the forecasting system they had been using.

Quantifying a business case here is generally more computational, and therefore more straightforward.  What are your costs associated with inventory of products that you can’t sell because you thought there was more demand?  How much less revenue do you earn because you have to discount products to move them out the door?  Alternately, what are your costs associated with paying extra to ramp up capacity because you didn’t realise the demand was as big as it was?  How many lost sales did you experience because of empty shelves?  These numbers are concrete and can hit your company’s bottom line.  They can sometimes be the easiest way to prove your business case.

The third type of prediction market I want to discuss quantifies risk.

Each industry and company has its own measures of risk.  Perhaps it is a measure of exposure to outside influences, such as bad weather for golf courses.  It might even be a measure of product quality, where it is a significant risk to reputation.  (An example could be a market for quantity of high-risk bugs found in the first month of Microsoft Vista deployment.)  Your company likely has key metrics that don’t directly relate to sales, costs, or projects schedules, even though they are key data points for your business.  The results of some of these markets could also be valuable inputs for sales forecasts, and for more advanced companies there is the option of operating combinatorial markets.  (I will be posting more on this later.)

It can be challenging to build a business case for these types of prediction markets, but is certainly still possible.  One method is to take a good-weather/bad-weather approach.  Most businesses plan for good weather, and have contingencies for bad weather.  What if disaster struck, and the actual outcome was worse than even your bad weather scenario?  What would be the financial impact for your company?  Again, how much is that information worth weeks or months in advance?  Those are the calculations that can prove the need for a proper prediction market for these metrics.

In summary, these are three main ways that prediction markets can be implemented in your company.  More importantly, each shows the basics of how to calculate a business case to prove their worth.  Please feel free to leave comments below, or contact me directly with any questions.

This entry was posted on Tuesday, February 6th, 2007 at 11:12 pm and is filed under General.