Preston Smith's Corner

The Risk in Time to Market

2002 Product Development Management Columns

Over the past decade, many companies have worked to improve their time-to-market and most have made great strides in cutting their cycle time. More recently, some of these firms have shifted their attention to managing the risks in their development projects. Is there a connection between these seemingly quite different approaches to excellence – one apparently energetic and optimistic and the other evidently more methodical and even pessimistic? I believe there is, and that this connection reveals a great deal about how product development can be improved.

Product development cycle times vary greatly by industry, company and product. For purposes of discussion, let’s say that your cycle time was 24 months a decade ago, and you have reduced it to half this amount – 12 months – today, as shown in the illustration. You base these numbers on solid measurements from many projects for which you have carefully defined the beginning and end dates.

However, in reality, if you have measured your cycle time carefully, you will notice that it varies greatly, even for similar projects. That is, cycle time is actually a random variable. Mathematicians have ways of characterizing random variables. The first thing they measure is its average, also called its mean or expectation. When I said that your cycle time had decreased from 24 to 12 months, I was implying that these were average values over many projects.

The second statistic of a random variable is its variance, measured by its standard variation. To continue with the example, let’s say that the standard deviation in your cycle time is three months. This means that about 95 percent of your projects complete within two standard deviations (six months) of the mean. This is shown in the second illustration.

illustration product development cycle time

I have applied the same three-month standard deviation to both your decade-old results and your current results. This is the key point I wish to make. Even though you have cut your mean cycle time in half, your variation has remained the same. Why? Because the methods of reducing the mean are completely different from the ones affecting the variation. The techniques we have been emphasizing over the past decade have been aimed at the averages: cross-functional teams, voice of the customer, product platforms and module reuse, and early supplier involvement, for instance.

In contrast, you reduce the variance by means aimed at it, principally by identifying and proactively managing the risks in a project. This is why some companies are now concentrating on project risk management. They recognize that although they can bring products to market relatively quickly now, the uncertainty (or “surprises”) in their cycle times are their current challenge. For some products, such as consumer products aimed at certain holidays or seasons, or industrial products dependent on annual trade shows for the majority of their sales, cycle-time uncertainty is more damaging than its average value.

Another advantage to managing risks is that this technique can be applied just as effectively to reducing uncertainty in other measures, such as product cost or performance or project expense.

(c) Copyright 2013 Preston G. Smith. All Rights Reserved.

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