My Business is Too Fast-Moving for Strategy
Of the many excuses I hear from executives for not ‘doing strategy,’ the most common goes something like this: “My business is too fast-moving for strategy. If I stop to do strategy, we will get left behind. Plus, there is so much uncertainty and change in our industry that it is impossible to analyze any data about it anyway, so even if I wanted to do strategy, I can’t. I just have to act.” This is particularly standard fare in technology industries. That is why I am dedicating my 16th Playing to Win/Practitioner Insights (PTW/PI) to My Business is Too Fast-Moving for Strategy. (Links for the rest of the PTW/PI series can be found here.)
Businesspeople say non-sensical things about strategy all the time, so this response doesn’t really surprise or bother me. But I find it grating the degree to which it said with the implication that the person is being tough-minded and practical in the face of an unrealistic and theoretical expectation for ‘a strategy.’ In my view, the response embodies two fundamental fallacies about strategy: a false distinction between strategy and acting; and a misconception of the structure and role of analysis in strategy.
“I just act” IS Your Strategy
As I have argued previously, strategy isn’t analysis, strategy isn’t plans, strategy is what you do! So, when you claim you ‘just do,’ you are, in fact, describing your strategy. You have a strategy and whether you acknowledge that or not is irrelevant. You have decided to do some things and not other things. You have decided where you will play and how you will compete. It might be a good set of choices or a bad set of choices or an indifferent set of choices. But it is your set of strategy choices.
It doesn’t matter in what kind of hurry you are or how unclear the future is. You have made choices and you have a strategy: and it is your strategy. There are no excuses as to whose it is. The only question is how robust the thinking behind your chosen actions is? And that leads into the second fallacy.
The Two Components of Analysis
The rationale I am given by the too-fast-moving-for-strategy folks is that they don’t have time for the data collection necessary for strategy and/or there isn’t actually data about their industry to crunch because it is so nascent/fast-changing. The implicit assumption is that without the crunching of data, you can’t do strategy.
This view unhelpfully conflates the two components of analysis. Analysis is the application of data to a logical structure to assess the degree to which the logical structure is confirmed or not. The first component is a logical structure (or hypothesis if you prefer) — for example, bigger plants can spread fixed costs across more units of production and therefore have a lower cost structure. The second component is data applied to the logical structure — for example, we gather cost data on 100 plants of varying sizes.
The resource-intensive component of analysis is data collection. It typically takes a great deal of elapsed time to collect data and the task is often quite expensive. Big corporations will tend to do lots of data collection — market research studies, competitor analyses, simulations, cost studies — in an attempt to achieve more rigorous support of the logical structure. As I have pointed out (repeatedly) before, there are limitations to data collection and application in any event. There isn’t actually data about the future in any situation — whether fast-moving or not — and the future can be different from the past limiting the value of any data from the past. In my experience, big corporations tend to spend more time and money than is optimal on collecting data to utilize in analyses.
Hence in a fast-moving/quickly changing context, there is plenty of excuse for not investing substantially in the data collection component of analysis. However, there is simply no excuse for not thinking through the strategy logic structure. It doesn’t take much time — especially elapsed time — to think through the strategy logic. It just takes hard thinking using a rigorous strategy framework — like Playing to Win (though it is by no means the only such framework). But because most conflate the two components of analysis, they toss out both of them together in a fast-moving context even if only one (data collection) is really a problem.
A Better Way
The better way, regardless of how fast-moving or sluggish your industry, is to invest hard thinking in developing your strategic logic structure. It needn’t take long. It just requires total concentration and the avoidance of distractions — like analyzing stuff. And it is important to write it down — even if you are too shy to share it with anybody else. The only way you can learn and get better is to prospectively write down your logic and then after you put it in action, you will be able to see how well your logic stood up. If you don’t write down your logic, mark my words, you will ex post rationalize that you had it totally right even when you most certainly did not, and you won’t have learned a thing.
Then, do only as much data collection against the logic as makes sense in your particular context. If it is fast-moving and emergent, then you might forego data collection entirely and just go with your logic. But prioritize. There may be particular areas in the logic that you could test and would find sufficiently valuable to spend the time and resources. View data collection as a variable that you adjust to the context.
In my experience, the investment pattern is the opposite regardless of the context. The strategic logic structure is given short shrift while useless bureaucratic data collection exercises like SWOT are pursued. And more time still is spent on fantasies like revenue budgeting. Millions of person-hours are spent every year on revenue budgets when the company has zero control over revenue. Customers control revenue while the company controls expenses. Yet companies budget for revenue as if it is in their control — a delusional and largely useless part of the overall strategic planning process for most companies.
All of this data collection takes away focus from the most important aspect of strategy — coming up with the strategic logic. There is no excuse for that.
And I put my money where my mouth is (as I always attempt to do) on this front. My only corporate equity investments are in early-stage private ventures. And on that front, I will only invest in start-ups that can lay out a compelling strategy logic for me. I don’t care about them showing a big total addressable market. I don’t even read the revenue forecasts because they are just made up. I care almost exclusively if they have a Where-to-Play/How-to-Win (WTP/HTW) combination that feels compelling to me.
I have made about twenty such investments, all of which could be accurately described as being in fast-moving technology businesses, ten of which are still active investments. I have, of course, made mistakes in which the data evolved inconsistently with the logic, meaning that the logic was fatally flawed. However, more than twice as many investments have achieved a payoff/valuation of greater than 2X (with some above 10X) than have produced either a payoff lower than 2X or a loss.
But I need to confess that before the above, I had to learn a very painful lesson. I began doing early-stage technology investing through an intermediary who convinced me he was a genius early-stage investor. I contributed an amount to his latest fund (of a size that was painful to lose), which made investments in eight companies. He celebrated me as one of his investors — the ‘strategy guru’ — and convinced me to give a talk on strategy at his first annual investor conference. After giving my talk, I listened to the founder/CEOs of the eight companies. I blanched as I listened. I went to the genius investor at the end of the night and asked him what he was thinking: they were all losers? Of course, he disagreed entirely. But, sadly, I turned out to be right. All were busts and the fund and my investment literally went to zero.
I learned an expensive lesson: focus on and audit the strategic logic yourself or don’t even think about investing.
There is no escape from making strategy choices, so don’t act as if you are not making them regardless of your context. The only question is how to make them best? If your context is fast-moving/quickly changing, focus hard on the strategy logic. Make sure you have a WTP/HTW theory and write it down. If you don’t have time and/or resources to collect data to test the theory, then just put your theory in practice.
Watch what happens and compare the outcomes to what your theory predicted. And then adjust. But again, think carefully about the new WTP/HTW, applying all the new data to which you have access thanks to the passage of time. Write down the new strategic logic. Put your updated theory into practice.
And watch again, and then adjust again, and then put it in practice again, and so on. That is how to do strategy in a fast-moving industry!