Decisions are inherently windows of opportunity. Now. Decisions may actually feel like less of an opportunity to many people because the tricky part is windows of opportunity demand an emphasis on time, therefore, having the right information, being able to assess that information in a timely fashion, and knowing what to do with that assessment (make a decision), becomes really important. Yeah. Opportunity comes with some strings attached.
So, let’s get to that information thing because in today’s business world that is most likely ‘data.’
Data is most typically contextual to a certain situation. Don’t believe me? Change the context of the data you trust the most to make a decision and I would bet it changes the probabilities of conclusions. I suggest everyone do this just for chuckles mostly because it reminds everyone that knowledge (input) never stops and knowledge, in and of itself, changes environment which changes data which changes, well, decisions.
All of which leads me to my uncomfortable relationship with measurement, or, my personal Achilles heel.
Sure.
- Set meaningful objectives and metrics
- Create plans that deliver goals
- Show impact
But my discomfort resides in if everything is contextual, what value does measurement have? Yeah, yeah, yeah. I get the “how do you know what works?” and “how do you know what to do next?” and I (flippantly) think “why do I care?”
I find the majority of people who seek “what worked” tend to like management by metrics. They tend to chase measured goals and seek to replicate them. They think if they remove a part with a bad metric that the whole will improve. I may have said this the best when I was writing about emergent strategies in agile strategic perspective with vision:
The past rarely teaches us how to manage the future <let alone predict it>. Strategists, and business, needs to resist the temptation to focus on indicators telling us how we have done. Wherever possible, identify operating metrics that are effective leading indicators of the kind of performance you are seeking to achieve. And focus on operating metrics that are specific to the desired position in the future even if these operating metrics are marginal to your current business performance.
Here’s the next thought that will make businesses sweat: forget about performance snapshots that focus on your performance at any specific point in time. Strategies of trajectory focus on acceleration – they’re about performance over time. Is your performance stable, increasing linearly or accelerating? If it’s not accelerating in an exponential world, something is wrong. So, strategies of trajectory are relentlessly focused on patterns of movement over time. What exists in the present is important, but only to the extent that it provides resources to support you to be agile enough to get you where you want to go by enabling small moves, smartly made, to get big things in motion.
All that said, data, if you squint enough, offers you a variety of lessons on how to work with it. There is always a gap between the way you think something works and how it actually functions. Data will tell you the difference IF you pay attention to what it tells you. The gap becomes clearer when you actually embed yourself within the structure of the data, the patterns, and only then. You actually have to tinker with data to sensemake before you can choicemake which may seem counterintuitive to those who see data as ‘truth to be used to make A choice.’
“The strategy for the discoverers and entrepreneurs is to rely less on top-down plannings … focus on maximum tinkering and recognizing opportunities when they present themselves.”
Nassim Taleb, Black Swan
I am not a data guy but I am certainly a data decipherer. I am not sure you need to immerse yourself in the micro data (all the time), but I do believe you have to at least understand the underlying tables (data gathered) if only because this is the path to effective tinkering. We talk about trial & error and experimentation in business all the time – but rarely with data. But if you want someone to become data literate, I would argue don’t send them to some data school, but rather embed them in tinkering with data (and, yes, this will demand some education). Tinkering, in and of itself, is the enemy of accepting superficial dashboards. If I tinker and get three different dashboards instead of creating confusion, it should create curiosity. And curiosity is the most effective companion to data.
Now.
Before anyone panics that I am suggesting everyone become a data scientist, I am not. The reality is all this tinkering and observing I am talking about can happen with a fairly finite amount of data. Just as Brooks pointed out in The Mythical Man Month that “a certain small set of documents embodies and expresses much of the managerial work” this is also true of data. Not all data is created equal in a number of ways, but in decision making there will always be a set of data which serves as the basic ‘surveillance and warning mechanism.’ Effective decision making is actually a tinkering task using accumulated information and observing. I am not sure any business school will teach that but maybe they should.