Sharing Too Much Data With Everyone Doesn’t Help Anyone

I’m afraid the latest trend in information sharing–radical transparency, where everyone allegedly knows everything about what’s going on in your business–is one of those cool efforts that’s best done. Begins with intentions and ends fairly quickly with a swamp of tears and confusion. It’s the latest example 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 it gets completely out of hand. Entire asylum with demands to run prisoners. Watching Netflix and many other companies try to pull back the drawbridge, rewrite their corporate philosophy, and explain why everyone in the company no longer needs to have a “say” in everything, this one is the case. Asking your engineers about art direction is like inviting a turkey to Thanksgiving dinner.

But the issue is much broader than just conflicting politics, busy bodies, and concerns about transphobia and canceled culture. To do its job well, there is no doubt that your team needs the proper will, direction and data. It is a vital component of both innovation and iteration, which are the keys to progress. But sharing important and sensitive information is not a free invitation for everyone. People adding and adding their two cents in a way that everyone is doing their job is a formula for failure and chaos. The fact that they’re just trying to help may be an explanation, but it’s no excuse. The key is to give your people the resources they need and the tools to keep track of how they’re doing and then go out of their way as long as they stay in their streets. If they don’t, your job—among a million others—is to intervene and back down from the butt-in-ski.

To help your people do their jobs and perform their best, nothing is more essential than timely and relevant metrics. As management guru Peter Drucker said many years ago, you can’t do what you can’t measure and that’s still largely true. Even more, it is clear that what is measured is done and, in true learning organizations, what is measured and modified appropriately gets better over time. Constant repetition and gradual approximation mean that you are always improving.

But, as with everything in life, too much of a good thing for an organization may simply be too much to swallow and digest effectively. Bean counting, in itself, is never good for business. If you can’t quickly and successfully integrate the data you’re assembling, it’s just make-work. And frankly, even in today’s ultra-technical world, there are a lot of important but intangible concerns and ideas that you still can’t measure.

Unfortunately, when there is constant pressure for results and “accountability,” there is often a tendency to invent and massage facts and figures so that the numbers add up. In too many businesses, a fetish with lax loyalty to budgets and estimates and false accuracy and made-up metrics can spell disaster. When measurement and process become the goal, you can easily lose sight of the real objectives. If you insist on overdoing it, the act of measuring will change whatever you are trying to measure and often, not in a good way.

Examples of this type of make-believe management reporting abound in marketing. While direct mail marketing is purely quantitative, it is clear that the impact and outcome of most brand marketing is, at best, a poignant guess. Even the best planning in such areas is not an accurate estimate; It’s fencing in parameters within reason– taking your best shot at a realistic estimate and moving on. After the fact, when you have some real numbers and results, you can fine-tune your approach and strategy.

After all, the real job is much easier. 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 frequent complaints are personnel problems that have overwhelmed more startups than any other matter. Whatever the perceived benefit of widely sharing sensitive and highly personal content like salary or performance rankings, I assure you that the pain is never worth the expected gain.

So, how do you determine who really needs to know? Four simple questions.

1) Is the requested information available and readily available?

As mentioned above, it’s easy to obtain impact and effectiveness data for brand marketing, for example, but it’s mostly the product of wishful thinking. Call it “anecdote,” an intoxicating cocktail of facts and facts. While it may make people feel better, the data adds little to their future performance or results. Also understand that while the right data can inform ongoing decision-making, it will not ultimately make the right choice for your people. The final call and responsibility is theirs; Using data as a crutch for your decisions is like using a lamppost for support instead of a drunken light.

2) Do they need the specific requested information to do their job optimally?

Even if it’s good information, you still need to know the difference between being good (or interesting) and needing to be. Everyone likes to keep score. Listeners constantly complain that streaming services don’t tell them how their shows are doing until a renewal decision is made. But telling them some random and relative numbers after the production is over has nothing to do with the progress, quality or success of the next show they are working on. This is more likely to cause anxiety and anger, rather than any revenge or better behavior.

3) Can team members use it effectively and is it provided on time?

Here again, writers and teams that assemble 8-to-12 shows for Netflix or Hulu usually deliver the first episode or three-packs of already finished series before air. Therefore, telling them how specific episodes are displayed may make them feel better or worse, but this is not information they can use to modify their completed work. Producers in Hollywood are still primarily treated like mushrooms and management sees no reason to think about changing the rules.

4) Can the data be collected and provided at a reasonable cost?

Well, clean data isn’t cheap. It is essential to determine whether the potential benefits will outweigh the costs before you start down the path because – like rabbits – both the demands and dimensions of the undertaking will multiply in a relatively short time frame since the desire for more and better guidance is continuous. Progressive and relatively insatiable.

Nielsen Used to track home TV viewership and even its report as the only game in town was acknowledged by the industry for the reasonable price, and genuine quality of the guidance they provided. It was valuable enough. But then the world changed in two important ways: (1) a fearsome new competitor, comscore Entered the market with more advanced and accurate measurement technology in multiple media distribution platforms; and (2) the media marketplace fragmented and exploded with viewership both indoors and outdoors on cable, digital, desktop and mobile delivery systems.

Today, the average American home has twice as many smart phones as TV sets and each consumes media continuously. The challenges of capturing accurate usage and viewership data across an ever-increasing spectrum and the cost of users to acquire such data are both increasing exponentially.

Every use case in every industry has different data needs that will change regularly, but will never decrease. No one is likely to get the parameters exactly right and make the best choices on a consistent basis, but important negotiations and time-sensitive decisions are inevitable and imminent.

We know with absolutely certainty that data is the oil of the digital age and the amount of data being created and collected will grow exponentially forever. Each organization will need to develop strategies and firm but flexible guidelines for its information policies.

Having data is important, but knowing how to plan and interpret it is extremely important. Having more data is not the same as having better information, even if your people want it all.

The opinions expressed here by columnists are their own, not those of