Management Information must have MEANING and inform ACTION.

(TL;DR at the end if you prefer and more on the application of this in What the #@$% is Going On?!)

Each piece of information is a tool, and like any tool, it’ll do the one specific job it’s designed to do.  The job is to inform a decision which, in time, will prove to be wise (more on decision-making here).  

It doesn’t matter what kind of decision it is, this applies to daily briefings coming to a CEO and quarterly Board papers destined for your non-execs.

The Meaning Of Meaning.

So much of the information I see is really just data which is easy to gather and concise to provide (i.e. it fits in a table or makes a good looking chart).  That isn’t meaningful.  

To be meaningful, information must be representative of something in the real world.  Just like models, all metrics are wrong but some are useful.   They’re simplifications for sure but, if they’re well chosen, they should reflect a real life occurrence that you need to understand to make a decision.

It must also be strategically aligned.  Start with your strategy, make the plan to get there (not necessarily starting from here!), then tell me what you need to know.  Never default to what’s easily measurable.  

“Identify a wish list of metrics with no regard for feasibility. Work backwards from there into what is possible.”   

Sahil Bloom

The Act Of Action.

Remember why we’re doing this (“to inform a decision which, in time, will prove to be wise”).  So start with a sense check and ask yourself “what do we do if this information changes?”.  If there’s no good answer to that, it’s not information, it’s data.

You can’t calibrate your action if you don’t know what what to expect.  “Numbers mean nothing without context. Is it big or small, rising or falling?” Pick a meaningful comparator to present alongside it.

You also need to know how noisy or uncertain you expect the information to be.  If a number goes up 5% is that:

• noisy (it moves about but that doesn’t really matter), 
• uncertain (we can’t measure it accurately so it may or may not have moved at all), or
• meaningful (we can draw a conclusion from it)?

And what if it goes up by 20%?

Watch What You’re Watching.

Don’t let your information replicate your biases, use a proper decision architecture to manage them out; ask around the team and include the contrarians. 

Don’t neglect what you don’t measure:

• Some things just aren’t easily, or at least not obviously, measurable but it doesn’t mean they’re not important.  McNamarra was (very) wrong.
• Think through the unintended consequences and consider a ‘counter-metric’.  This is all the more important if your information point becomes a target (I do not love targets).  You can avoid creating perverse incentives by paying attention to the measures which would alert you to an unintended consequence.
• Don’t assume you’ve got it right first time, keep an eye out for information which could be informative.  Revisit your assumptions.  Use your feedback.

A lot of this is easier with a little distance and it requires the right data and a good decision architecture but it’s all super-doable and it’ll pay dividends… hopefully, literally!

Let’s talk about where we start.