Posted by andreag

I recently wrote a blog post that has gained quite a bit of traction with our readers. It seemed it would be a valuable newsletter edition as well, since the two publications reach out to a different audience. My post covered the error of many managers in making decisions without the data to back them up. First, a couple definitions:

Fact: a real occurrence, event

Opinion: a belief or conclusion held with confidence but not substantiated by positive knowledge or proof.

The dangerous waters of decision-making

W. Edwards Deming, the father of continuous quality improvement, was a statistician who believed management decisions should be driven by data. He opined that there are only two mistakes a manager can make, making a decision when one shouldn’t and not making a decision when one should.

Deming urged that one should look at data and determine trends and the nature of the changes observed in data. That is, is the change in data an outlier or one time event, or is the condition or fact replicated over 3 reporting periods? If the latter, the data represents a change in condition that warrants investigation and potential action.

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Deming held that if you react and make decisions/changes based on a single data point, you could do more damage to the system than doing nothing at all. That is because there is variation in all that occurs in the physical universe and the data point could be the result of weather, a single human error that is a one-time occurrence, a glitch in machinery that does not repeat itself, etc. Changing one’s process or method in reaction to such an occurrence could worsen performance over time.

Facts vs Opinions

Deming addressed the need for data, the reliance upon data to make decisions and how to interpret data. His intent was that leadership would know when to make changes as well as when to avoid making them, i.e., when the change could do harm. Sadly, Deming’s philosophy and methods never really caught fire here in the U.S. to the extent that they did in Japan. Currently, Six Sigma and “lean” methodologies approximate this, but are far from universal in U.S. companies.

Instead, there is an underlying and more disturbing practice in management. That practice involves relying on opinion vs. facts to make decisions.

A common scenario

For example, let’s suppose that your sales manager reports “our customers are becoming increasingly upset with our pricing relative to our competitors’. I think we need to reduce our prices to compete.” Fact? No, it is an opinion. How many customers? Over what period? What did they actually say? How do our prices compare? What changes in pricing did our competitors make? When?

Certainly his assertions may be an accurate reflection of what is happening, and his ideas warranted. But without data, it is impossible to tell. The reality may be that the sales manager’s numbers are down due to his own failure or that of his salesmen. Or it could be a system issue in that he and his staff are incentivized based on units sold and not profitability. So, there is an incentive to create as many sales as possible without regard to impact upon the bottom line of the company.

You get the idea?

The reasoning

Now, this seems rather obvious, so why is decision making based on opinion so rampant? Here are some reasons:

  1. It’s easier. I can be lazy and not impose discipline on myself or others to gather and faithfully present the facts.
  2. Dismissing the opinions of trusted team members is held as an invalidation, e.g. “you don’t trust me” or “you don’t think I am being honest”, and managers don’t want to do that sort of damage to fellow team members.
  3. Getting seduced into the notion that there is a crisis, and we have to act now.

Now, take the example above and extrapolate that out to the countless number of decisions being made in your organization every day. Scary, right?

Instill discipline to have only facts presented to you, and base decisions only on those facts. Opinions should be reserved to what individuals believe would be the best course of action to correct what the facts are telling you needs to be handled.

What measures are relevant?

The caveat to all this measuring is that the data must be relevant to be effective. For example, simply measuring that an important project is being completed on time is far less effective than measuring whether or not the project is creating the intended impact – i.e., are sales going up, customer complaints decreasing or morale improving?

Get your feet wet with a few simple measures that will show the effectiveness or impact of your work, then continue digging into more meaningful measures. And require the same of your direct reports. If you would like some help creating measures that get you the facts,
send us an e-mail and we can step you through the process.