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have happened. So there are a lot of links in the chain. The R&D link has to be strong enough to hold up its piece of that total value chain.
Second, there are commercial products available that will lead you through the process needed to obtain a reasonable estimate of how likely a project is to be successful or not, both commercially and technically. If you have such a tool, it would certainly help in project selection. A project should either have a big bang or be real cheap. That then leads you back into portfolio management and all of the various dimensions of portfolio management.
If you can do all of this, you can start using the metrics that help improve and estimate R&D productivity. Productivity, by most people's definition, is what you get out for what you put in. It is pretty easy to tell what you put in (just ask your accountant), and some of these metrics help you know what you are getting out. The metrics of effectiveness deal with issues such as stage-gate usage and so forth.
One of our earliest speakers spoke of this whole effort as potentially dangerous, and I share that view. Indeed, quality management, if it tells us nothing else, tells us that you tend to get what you measure. I would argue, then, that you had better be careful in selecting the metrics you use. In fact, that was one of the reasons that, when we built this program, we could not eliminate too many metrics, because we wanted corporations to be able to pick metrics that met their strategic needs. So, pick your metrics with great care, because if you use them, you will drive behaviors that get you what you are measuring. Nevertheless, I think that on balance, metrics are a benefit in terms of helping us all do our job more effectively, and so, the reward is worth the risk.