I have a confession to make. An uneasy feeling rises up in me whenever I am in or near discussions to define measurements for use during the innovating process.
Measuring innovation after the fact (e.g., the classic X% of revenues or profit coming from products that the company was not making three years earlier, etc.) is certainly more reasonable than trying to measure innovating while you’re in the middle of it. Time-to-market, time-to-positive cash flow, or to time-to-break even, get close. But even these metrics are more hindsight than “now-sight.”
When you are in the midst of innovating—whether discovering a consumer pain, charting the topography surrounding a customer’s unmet need, inventing solutions, reducing a solution to practice, or iterating with inevitable adjustments—it is very difficult to find any objective metric that enables sponsors, managers or innovators themselves to avoid using their intuitive judgment.
It turns out, I am not alone in this uneasy feeling. One of my clients devoted considerable effort in developing just such a metric system for monitoring their in-process innovation portfolio. After several years, their enthusiasm for its usefulness has faded.
The need to monitor and measure is there for sure. But the ability to fill the need may be out of reach. Outputs can be measured. Inputs can certainly be measured as well. However, what may be impossible to measure is the “throughput” of content which is by definition “developing.” This content is forming and reforming into a prototypical instantiation, the ultimate value and success of which can only be determined when it enters the market. The more generative or creative the process, perhaps, the more difficult it is to measure and therefore manage—at least for those who ascribe to the management mantra of “you can only manage what you can measure.”
What happens in our desire to manage during the innovating process is that we measure what we can (the number of ideas, the nodes in our discovery networks, etc.). But just because something can be measured doesn’t mean that the resulting measure is important or useful. As Albert Einstein said, “Everything that can be counted does not necessarily count; and everything that counts cannot necessarily be counted.”
This difficulty reflects some misplaced expectations that we can actually manage innovation in a fashion similar to the way we manage operating or production systems—systems that have produced data and left tracks that can be measured. Innovation systems are different in that what they produce—innovations—have produced little if any data that can be tracked until they have entered the market. And there is much about innovating that happens before that entrance.
At a recent gathering of veteran innovators in Denver in October, one of the participants, Andrew Zander, a veteran director of engineering of many instrument innovation efforts, said something simple, but very profound. My paraphrase, with apologies to Andy if I got it wrong, is as follows:
“We shouldn’t confuse process with progress when it comes to innovating. We can’t measure process (in any meaningful way), which may not be that important to measure in the end anyway. What is important, however, is to make progress, which we will not be able to determine until, at various points in time, we stop and assess what we have learned, determine where we are, and clarify what our next steps should be. When we compare these points, then we can determine whether we are making progress or not. Only when we have determined whether progress is being made or not, are we really in any position to make decisions.”
Perhaps the key point for innovators, sponsors and innovation midwives is to let go of our quixotic quests for innovation metrics and get down to the business of making and assessing progress, not process. Then we will know better what decisions we need to make; and then, of course, we need to make them.
For measuring during the innovating process, perhaps Italian physicist Enrico Fermi said it best: “There are two possible outcomes: if the result confirms the hypothesis, then you’ve made a measurement. If the result is contrary to the hypothesis, then you’ve made a discovery.”
Measuring innovation after the fact (e.g., the classic X% of revenues or profit coming from products that the company was not making three years earlier, etc.) is certainly more reasonable than trying to measure innovating while you’re in the middle of it. Time-to-market, time-to-positive cash flow, or to time-to-break even, get close. But even these metrics are more hindsight than “now-sight.”
When you are in the midst of innovating—whether discovering a consumer pain, charting the topography surrounding a customer’s unmet need, inventing solutions, reducing a solution to practice, or iterating with inevitable adjustments—it is very difficult to find any objective metric that enables sponsors, managers or innovators themselves to avoid using their intuitive judgment.
It turns out, I am not alone in this uneasy feeling. One of my clients devoted considerable effort in developing just such a metric system for monitoring their in-process innovation portfolio. After several years, their enthusiasm for its usefulness has faded.
The need to monitor and measure is there for sure. But the ability to fill the need may be out of reach. Outputs can be measured. Inputs can certainly be measured as well. However, what may be impossible to measure is the “throughput” of content which is by definition “developing.” This content is forming and reforming into a prototypical instantiation, the ultimate value and success of which can only be determined when it enters the market. The more generative or creative the process, perhaps, the more difficult it is to measure and therefore manage—at least for those who ascribe to the management mantra of “you can only manage what you can measure.”
What happens in our desire to manage during the innovating process is that we measure what we can (the number of ideas, the nodes in our discovery networks, etc.). But just because something can be measured doesn’t mean that the resulting measure is important or useful. As Albert Einstein said, “Everything that can be counted does not necessarily count; and everything that counts cannot necessarily be counted.”
This difficulty reflects some misplaced expectations that we can actually manage innovation in a fashion similar to the way we manage operating or production systems—systems that have produced data and left tracks that can be measured. Innovation systems are different in that what they produce—innovations—have produced little if any data that can be tracked until they have entered the market. And there is much about innovating that happens before that entrance.
At a recent gathering of veteran innovators in Denver in October, one of the participants, Andrew Zander, a veteran director of engineering of many instrument innovation efforts, said something simple, but very profound. My paraphrase, with apologies to Andy if I got it wrong, is as follows:
“We shouldn’t confuse process with progress when it comes to innovating. We can’t measure process (in any meaningful way), which may not be that important to measure in the end anyway. What is important, however, is to make progress, which we will not be able to determine until, at various points in time, we stop and assess what we have learned, determine where we are, and clarify what our next steps should be. When we compare these points, then we can determine whether we are making progress or not. Only when we have determined whether progress is being made or not, are we really in any position to make decisions.”
Perhaps the key point for innovators, sponsors and innovation midwives is to let go of our quixotic quests for innovation metrics and get down to the business of making and assessing progress, not process. Then we will know better what decisions we need to make; and then, of course, we need to make them.
For measuring during the innovating process, perhaps Italian physicist Enrico Fermi said it best: “There are two possible outcomes: if the result confirms the hypothesis, then you’ve made a measurement. If the result is contrary to the hypothesis, then you’ve made a discovery.”
This article was originally published in Innovating Perspectives in November 2010. For this and other back issues of our newsletter, please visit our website at innovationsthatwork.com or call (415) 387-1270.
No comments:
Post a Comment