Information overload as the price of strategy dogmatism
Wow, that's a mouthful. And it seems like a stretch. Why should dogmatism about your current business or public policy strategy have anything to do with the amount of data floating around your organization?
While a more critical attitude toward strategy can't make data go away, it can have a huge impact on how we filter it. But I realize even that's controversial because you might think open-mindedness about whether your strategy's right might leave you even less sure about which data matter -- and especially which performance data.
While that's a natural belief, I now think it's mistaken. In fact, this is the subject on which the research for my book "Relevance: Hitting Your Goals by Knowing What Matters" (Wiley 2008) most changed my mind. Here's why.
Dogmatism about strategy means you think it's right. Managers who think their strategy is right focus on the quality of execution. So they measure factors affecting that quality and don't spend much time testing their strategic assumptions. And it turns out there's no end to the factors that affect the quality of execution.
But if you're willing to test those strategic assumptions, they will provide a sharp set of priorities regarding what to measure. You'll track the factors you assume are most likely to drive a wedge between your goal and actual results. In other words, you'll track indicators that test your least certain high-impact assumptions.
The good news is that you only need a few mistaken assumptions to explain most of the performance surprises that organizations generate. And you'll be able to tell (if your strategy is clear enough) whether you're missing an assumption that's critical for explaining all of a performance surprise.
The upshot is that your assumptions provide the best available guide as to which few vital performance factors, indicators, or metrics you really need to watch. And this is the case even if you can't be sure whether you're missing an important assumption. If you are, the results will force you to look for new ones -- and what higher use could performance data have than that?
So the moral of the story is that managers who are open-minded about testing their assumptions get a payoff few appreciate. They know where to focus.
Wow, that's a mouthful. And it seems like a stretch. Why should dogmatism about your current business or public policy strategy have anything to do with the amount of data floating around your organization?
While a more critical attitude toward strategy can't make data go away, it can have a huge impact on how we filter it. But I realize even that's controversial because you might think open-mindedness about whether your strategy's right might leave you even less sure about which data matter -- and especially which performance data.
While that's a natural belief, I now think it's mistaken. In fact, this is the subject on which the research for my book "Relevance: Hitting Your Goals by Knowing What Matters" (Wiley 2008) most changed my mind. Here's why.
Dogmatism about strategy means you think it's right. Managers who think their strategy is right focus on the quality of execution. So they measure factors affecting that quality and don't spend much time testing their strategic assumptions. And it turns out there's no end to the factors that affect the quality of execution.
But if you're willing to test those strategic assumptions, they will provide a sharp set of priorities regarding what to measure. You'll track the factors you assume are most likely to drive a wedge between your goal and actual results. In other words, you'll track indicators that test your least certain high-impact assumptions.
The good news is that you only need a few mistaken assumptions to explain most of the performance surprises that organizations generate. And you'll be able to tell (if your strategy is clear enough) whether you're missing an assumption that's critical for explaining all of a performance surprise.
The upshot is that your assumptions provide the best available guide as to which few vital performance factors, indicators, or metrics you really need to watch. And this is the case even if you can't be sure whether you're missing an important assumption. If you are, the results will force you to look for new ones -- and what higher use could performance data have than that?
So the moral of the story is that managers who are open-minded about testing their assumptions get a payoff few appreciate. They know where to focus.
Labels: information overload, question strategic assumptions, relevant metrics, strategy dogmatism, testable strategy
posted by DA at 7:11 AM
0 Comments:
Post a Comment
<< Home