system dynamics  
At Any Rate
by Bill Harris

Model 6, December 2003

You Need More Than Brilliant Ideas

A few months back, I had one of those fleeting thoughts: "What the world needs is a large, cheap disk drive with an Ethernet port for home and small office networks." A recent e-mail brought news of exactly such a product, along with a twinge of "Why didn't I do that? I could be rich and famous now." That's not the first time I've thought of a new product and done nothing, only to see it appear on the market some time later. Perhaps you've had similar experiences.

Of course, there's more to innovation than simply having a brilliant idea. It costs money to develop and launch a new product, and a company must have the resources to carry through. Moreover, a company must recoup its investment through profits from that product that allow it to grow the business and develop future generations of new products. In other words, innovation is both a business and a technical issue. And the situation is made more challenging by the long time delays between investing in a new product and seeing the returns on that investment-which can take months or even years. It's hard to gauge the effectiveness of actions when the results are so distant.

Systems dynamics is made for exactly these sorts of issues, in which there are long time delays between taking action and seeing the results of those actions and there are circular feedback loops, such as investment in new product development that drives future sales and profits, which in turn enable further new product development. How do companies manage this process successfully?

Al Bagley, retired group engineering manager of Hewlett-Packard's Electronic Instruments Group (now part of Agilent Technologies) and current member of the Board of Trustees for the SETI Institute, was known for, among other things, the Bagley Return Factor, a rule of thumb he used to decide whether a proposed new product should be developed. Although the rule carries his name, Bagley credits Bill Hewlett with instigating this measurement and decision approach. Let's let him tell the story:

In the early days of HP, Bill Hewlett thought it would be useful to have a way of quantitatively evaluating possible development projects. He came up with what he called "Return Factor," which was the expected operating profit over the lifetime of a product divided by its total development cost. This was often used to compare different potential product ideas with each other before proceeding to development.

After a while we became aware that 5 had been a fairly good HP return factor, and that particular number became kind of the first hurdle of acceptability for a project. We knew that both the numerator and denominator were pretty rough estimates, but the factor was still useful.

When I served as Group Engineering Manager for the HP Instrument Divisions . . . I thought it would be useful to see if the factor had an absolute value that would relate to a given financial business plan. . . . I guess I harassed the division engineering managers enough with the concept that some of them referred to it as the Bagley Factor. It was still nothing more than Bill's original factor.*


Calculating the Bagley Return Factor is quite simple, only requiring two figures: the projected operating profit (profit before taxes) over the life of the product and the total product development cost. The ratio of those two numbers is the Bagley Return Factor. At HP, if the Return Factor exceeded 5, the product was deemed viable. While this wasn't the only criterion used to make product development investment decisions, it conveniently aggregated the financial return aspect of that decision in a single, easy-to-understand number.

As Bagley noted, using this Return Factor can help with strategic product development decisions. Here's an example. Following Bagley's derivation, assume that product development projects spend money at a constant rate for A years, and that the product is then on the market for B years, selling a constant number of units (or, more specifically, bringing in a constant revenue) over that time.

If G is equal to one plus the company's growth rate (e.g., a 15% growth rate corresponds to G = 1.15), P is operating profit as a percent of revenue, and R is the percentage of revenue spent on product development, then equation 1 holds.
With this equation, we can now explore the relationship between profit, growth, new product development investment, and product and project lifetimes. For example, if a company invests 10% of its revenue into product development, if the typical product development project lasts 2 years, if products stay on the market an average of 5 years earning 25% profit before taxes, and if the company wants to grow at 15% per year, then the Bagley Return Factor must equal or exceed 4.01.

If the time to develop a product is about equal to its life, then this formula simplifies to equation 2.
The associated graph, courtesy of Bagley, shows a company's achievable growth rate as a function of the percentage invested in product development and the return factor threshold on new product investment decisions for a particular product development time, product life, and projected profit percentage. Thus, investing 8.5% of revenue in R&D and getting a Bagley Return Factor of 4.0 would lead to approximately an 11% growth rate; a return factor of 6.0 would lead to a 25% growth rate. If you're in the product development business, take a look at your company's figures and see where you fit.

George Richardson, professor of public administration, public policy, and information science in the Rockefeller College of Public Affairs and Policy at the University at Albany-State University of New York, provides another take on that decision process. Independently of Al's work, he wrote a paper giving a systemic, theoretical underpinning to making such product development investments. To find out how Bagley's and Richardson's work compares and to try your hand at managing a product development organization, download and explore the attached model.

*Correspondence between Al Bagley and Bill Harris, April 24, 2003.


Acknowledgements
Thanks to Al Bagley, Trustee of the SETI Institute; Karen Lewis, Agilent Technologies Archivist; and Dr. George Richardson, Professor of Public Administration, Public Policy, and Information Science, Rockefeller College of Public Affairs and Policy, University at Albany-State University of New York, for their insights.

Using the Model
To use the model, you'll need to download two files—the "current model" and the "isee Player" (the ithink® Runtime for the At Any Rate model series) that runs the model. Both are located in the "Get" section toward the top of the right-hand column. You'll then need to install the isee Player on your computer. (Once you have installed the isee Player on your computer, you no longer have to go through this process unless the reader is updated.)

1) Download the "Current Model"
• Click "Current Model."
• Choose "Save this file to a disk" and click "okay."
• In "Save As," save the ITR file to your desktop (or to a folder of your choosing).

2) Download and install the "isee Player"
• Follow the instructions on the isee Systems site.
After you install the isee Player, to run the model, you can go to your desktop and double-click on "model1.itr" or start the ithink® program and use the "file open" command to locate and open the model1.itr file.

You are ready to begin. Feel free to play with the model. We've put more content in it than we've described in this column. Try different things. If you've got an interesting idea, a question, or a comment, go to our Pegasus Forum. We'd enjoy hearing from you.
 

This learning lab was developed using the ithink® software, a computer simulation modeling package developed and distributed by isee Systems.

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At Any Rate 
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Related links

George Richardson, "Loop Polarity, Loop Dominance, and the Concept of Dominant Polarity" (paper presented at the System Dynamics Conference, Oslo, Norway, 1984), System Dynamics Review 11, no. 1 (Spring 1995)



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