Sharing Too Much Data With Everybody Doesn't Help Anybody
Don't overload your team with information that can't help them. Here's a four-step guide to who-gets-what.
BY HOWARD
TULLMAN, GENERAL MANAGING PARTNER, G2T3V AND CHICAGO HIGH TECH
INVESTORS@TULLMAN
I'm afraid that the
latest vogue in information sharing-- radical transparency, where everyone allegedly
knows everything about what's going on in your business-- is one of those
virtuous endeavors that starts out with the best of intentions and fairly
quickly ends up in tears and a swamp of confusion. It's just the latest
instance of the ancient caution-- "be careful what you wish for" --
but it's also something that every business, especially new ones, needs to
address before things get completely out of hand, with the inmates demanding to
run the entire asylum. Watching Netflix and a host of other companies try to
drag back the drawbridge, rewrite their corporate philosophies, and explain
why not everybody in the company any longer needs to get a
"say" in everything is a case in point. Asking your
engineers about art direction is like inviting a turkey to Thanksgiving dinner.
But the issue is much broader than simply one of conflicting
politics, busybodies, and concerns about transphobia and cancel culture. To do
their own jobs well, there's no question that your team needs the proper
desire, direction, and data. This is a critical component of both innovation
and iteration, which are the keys to progress. But sharing critical and
sensitive information isn't an invitation to a free-for-all. People butting in
and adding their two cents to the way that everyone else is doing their jobs is
a formula for failure and chaos. The fact that
they're just trying to help might be an explanation, but it's no excuse. The
key is to give your people the resources they need and the tools to track how
they're doing and then to get out of their way as long as they stay in their
own lanes. If they don't, your job -- among a million others -- is to run
interference and back off the butt-in-skis.
To help your folks do their jobs and do their best, there's
nothing more essential than timely and relevant metrics. As
management guru Peter Drucker said many years ago, you can't manage what you
can't measure and that's still largely true. Even more to the point, it's clear
that what gets measured is what gets done and, in true learning organizations,
what gets measured and modified appropriately gets better over time. Constant
iteration and successive approximation mean you're always improving.
But, as with everything else in life, too much of a good thing
can simply be too much for an organization to ingest and digest effectively.
Bean counting, in and of itself, is never good for business. If you can't
swiftly and successfully integrate the data you're assembling, it's just
make-work. And frankly, even in today's hyper-technical world, there are plenty
of important but intangible concerns and considerations that you still can't
simply measure.
Unfortunately, when there's constant pressure for results and
"accountability," there's often a tendency to invent and massage the
facts and figures so that the numbers add up. In far too many businesses, a
slavish allegiance to budgets and projections and a fetish with false precision and made-up metrics can
lead to disaster. When the measurement and the process itself become the goal,
you can easily lose sight of the real objectives. If you insist on overdoing
it, the very act of measurement will alter whatever it is that you're trying to
measure and, most often, not in a good way.
Examples of this kind of make-believe management reporting
abound in marketing. While direct mail marketing is completely quantifiable,
it's clear that the impact and results of most brand marketing is, at best, a
touchy-feely guess. In areas like these the best plan isn't even precision guesswork;
it's fencing in the parameters within reason-- taking your best shot at a realistic estimate and moving
on. After the fact, when you have some actual numbers and results,
you can fine tune your approach and strategy.
Ultimately, the real job is pretty simple. You need to decide
who really needs to get what kind of information to do their best work and then
make sure they get what they need. Spoiler alert: practically no one in the
entire company needs to know what everyone else earns. Compensation issues,
competitive comparisons, and constant complaints are the personnel problems
that have sunk more startups than just about any other matter. Whatever the
alleged benefit might be of widely sharing sensitive and highly personal
material like pay or performance rankings, I assure you that the pain is never
worth the hoped-for gain.
So, how do you determine who really needs to know what? Four
simple questions.
1) Is the requested information available and readily
accessible?
As noted above, for example, impact and effectiveness data for
brand marketing is easy to come by, but it's mostly the product of wishful
thinking. Call it "anecdata," an intoxicating cocktail of facts and
factoids. While it may make people feel better, the data adds little to their
future performance or results. Understand, too, that the right data may inform
ongoing decision-making, but it's not going to ultimately make the correct
choices for your people. The final call and the responsibility are theirs;
using the data as a crutch for their decisions is like the drunk using a
lamppost for support rather than illumination.
2) Do they need the specific requested information to better do
their jobs?
Even if it's good information, you still need to know the
difference between nice (or interesting) to have and need to have. Everyone
likes to keep score. Showrunners constantly complain that the streaming
services don't tell them how their shows are performing until the decision to
renew comes up. But telling them after production is complete about some random
and relative numbers has nothing to do with the progress, quality or success of
the next show they're working on. It's more likely to create anxiety and anger
rather than any changed or improved behavior.
3) Can and will the team members use it effectively if it's
provided in a timely fashion?
Here again, the writers and teams that assemble 8-to -12 shows
for Netflix or Hulu typically deliver the finished series before even the first
episode or three-pack airs. So, telling them how specific episodes performed
may make them feel better or worse, but it's not information they can use to
revise their completed work. Makers in Hollywood are still treated mainly like
mushrooms and management sees no reason to think about changing the rules.
4) Can the data be assembled and provided at a reasonable cost?
Good, clean data isn't cheap. It's essential to determine
whether the likely benefits will outweigh the costs before you start down the
path because--much like rabbits --both the demand and the dimensions of the
undertaking will multiply over a relatively short timeframe since the desire
for more and better guidance is perpetually progressive and relatively insatiable.
Nielsen used to track home TV viewership
and even as the only game in town its reports were accepted by the industry,
reasonably priced, and fairly valued for the actual quality of the guidance they
provided. But then the world changed in two critical ways: (1) a scrappy
new competitor, Comscore entered the market with more
advanced and precise measurement technology across multiple media delivery
platforms; and (2) the media marketplace fragmented and exploded with
viewership in and out of home on cable, digital, desktop, and mobile
delivery systems.
Today, there are twice as many smart phones in the average
American home as TV sets and each one constantly consumes media. Both the
challenges of capturing accurate usage and viewership data across an
ever-expanding spectrum and the users' costs of acquiring such data continue to
grow exponentially.
Every use case in every industry is going to have different data
needs that will also change regularly, but never diminish. No one is likely to
get the parameters exactly right and make the best choices on a consistent
basis, but the critical conversations and the time-sensitive decisions are
unavoidable and imminent.
All we know for absolutely certain is that data is the oil of
the digital age and that the volume of the data being created and aggregated
will grow exponentially forever. Every organization will need to develop
strategies and firm but flexible guidelines for its information policies.
It's important to have data, but it's infinitely more important
to know how to employ and interpret it. Having more data is not the same as
having better information, even if your people want it all.
