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Prime Future 44: How to Decide

I was recently making a big decision between two good options, which led me to Annie Duke’s book How to Decide. Duke is a professional poker player turned behavioral decision scientist. One of the most profound ideas from the book is that of evaluating the outcomes of a decision separately from the decision making. Duke points out that we tend evaluate the quality of a decision based on its outcome: good outcome = good decision, bad outcome = bad decision.

But that correlation does not always hold. Sometimes a well informed decision results in terrible outcomes. Sometimes a rash, impulsive decision results in fantastic outcomes. Duke’s thesis is that we can only improve our decision making process when we separate the decision from the outcome, ideally leading to more decisions with better outcomes.

In the first chapter of Netflix founder Reed Hasting’s book No Rules Rules, Reed tells about sitting across from the management of then $6B Blockbuster and proposing they acquire Netflix for $50M. Blockbuster passed.

It is tempting to hear that story and lol at Blockbuster for not making the acquisition. How could they not have seen that their industry was changing? How could they have been so shortsighted to think brick & mortar was the future? How could they have underestimated Reed & his team, or the future of streaming?

With the benefit of hindsight, we know of course that Blockbuster is no longer and Netflix is currently valued at $241B.

But, did Blockbuster make the wrong decision? Did Carmax make the wrong decision?

Here’s why this is all connected: in a tech obsessed world, particularly in winner-take-all markets (which are fewer than we think, but that’s for another time), the pressure is immense to not be Blockbuster, to not be left behind, to not be the one that didn’t embrace the future. Outsiders love to point out how agriculture is the “least digitized sector” and assume this is because farmers are slow to embrace tech products. Are farmers simply tech averse as outsiders assume….or are farmers making rational risk/benefit decisions that are appropriate for their business context?

Because the truth is, not all tech or innovation decisions lead to good outcomes. Not all innovation is the next big thing. Not every upstart is the next Netflix. Some of it is simply the Segway, cool tech that never finds its use case so it remains a niche product for tech nerds. Some of it is….dare I say….smoke and mirrors. On the super rare occasion, it even turns out to be outright fraud like Theranos (highly recommend the book Bad Blood).

For business leaders, the decision making process is the controllable, the improvable. In all things, including deciding what innovation or tech or tech companies to bet on (whatever the nature of the bet) or what industry trend to capitalize on.

Have you ever noticed that the decisions that led to really bad or really good outcomes are the ones that get all the attention? But, how many exceptionally wise decisions have been made to pass on a product/company that turned out to be the correct decision, that are never known outside of those sitting in the conference room?

Those stories don’t make it on the front page of the Wall Street Journal or into an HBR case study but I expect we could learn a lot if they did.

Here’s how I think hindsight leads us to assess the decisions to bet on a tech company or pass on it, based on the outcomes of how impactive the innovation turned out to be:

Here’s the thing – with the benefit of hindsight we can point to poignant examples of decision outcomes that fit into every category in the above matrix, except for examples of the Unsung Hero. Good defense never gets the same hype as good offense, even though you need both to win.

I could be convinced otherwise, but I think this framework holds true for more than just tech. I think it applies to any new industry trend and decisions made about how to leverage the trend, or not. And again, these decisions get evaluated from the outside based on outcomes.

But there are SO many factors that effect outcomes of early stage companies & early stage technology, from the tech itself, to product design, to go-to-market strategy, to funding sources, to the macro-environment, to industry specific tailwinds or headwinds, to the leadership team, to the pricing model, and on and on and on. Which means, there are SO many factors that affect the outcomes of decisions around early stage tech companies & products. So the decision making process is the controllable.

The relevant question for decision makers of any kind, is how do you make more Obvious Genius & Unsung Hero decisions? I would suggest the following:

  • Make more small bets.
  • Do your due diligence (seriously, reading the book Bad Blood will give you motivation for this).
  • Create a rigorous – and iterative – decision process that you refine as you learn each time. Document your thought process before the decision is made so you can evaluate it in hindsight – most of us are terrible at remembering what we knew or did not know at the time of a decision.
  • Reject all or nothing thinking. Find ways to experiment on a small scale before making go-big-or-go-home type decisions.

My bias is that much of the risk to early stage companies can be mitigated when founders engage early and often in customer discovery, but engaging in that process can also be a way for future customers/partners to de-risk. The challenge for founders is finding the right prospective customers/partners who are willing to engage in the messy, iterative process of innovation. Not everyone wants to see how that sausage gets made.

Right now there are a lot of innovations being thrown at the meat & poultry value chain. With the benefit of hindsight what will be said about bets on…cultured meat? Plant automation? Regenerative ag? Carbon markets? Traceability? eCommerce & brand building? Individual animal management? 3D bio-printing meat? CRISPR?

Time will tell.

How do you improve your decision making process?

On a side note, I usually find that even when I sit down to write for execs at big companies, there are corollary applications for founders of startups and for producers. And vice versa. I hope this was true in today’s content.

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