Tell me if any of these scenarios sound familiar:

• You send quarterly reports to your entire team with charts, graphs and analytics that compare previous quarters - and nobody ever responds, so you’re not even sure if they’re looking at them.
• You have an executive dashboard that displays monthly numbers with red, yellow and green colors to indicate whether you’re on target, falling behind or at risk of falling behind. Often, even when the numbers are red, you ignore them because you think you can rationalize the dip for one reason or another.
• You receive daily alerts when any of your top three targets fall below a certain threshold. Unfortunately, your e-mail inbox is so bloated that you generally ignore them or delete them at the end of the day.

We are so inundated with information and so desensitized to reports and false alerts that we’re not paying attention anymore. In fact, we receive so many reports, alerts and signals that we’re no longer sure when we should pay attention. For many business leaders today, the reporting cycle has become one big game of The Boy Who Cried Wolf.

What if we applied quality control principles to our information flow?

Think about the way manufacturing systems used to work before total quality management and statistical process control became the norm. (Some of you may be old enough to remember. Others of you probably read about it in college.) Traditionally, manufacturing systems used heuristics and business rules to say, “If this happens, send me an alert.” The red lights on the manufacturing line were always buzzing, and workers were always ignoring them.

But then businesses applied quality control and realized variance matters. The big lesson? Now, we only ring the bell if the product goes out of natural variance. Essentially, quality control eliminated false alerts on the manufacturing floor, and workers started paying attention to the red lights and alert whistles again – because they meant something.

Well, guess what? Information flow is a manufacturing process. We should be evolving information management to follow the basic lessons that revolutionized manufacturing.

The problem with information flow today is that we don’t know our natural variance. When managers ignore the red numbers and false alerts, it’s because they think they know the explanation for the problem already, but they can’t statistically know if that variance is a natural part of the cycle we’re in. Maybe – as they’re guessing – there is a training cycle causing the change. Or maybe the change is just part of the natural process. Without calculating variance, we can’t know.

Let’s consider hospital reports for patient falls as an example. Normally, health care facilities report falls on a quarterly basis, so they can never really understand the process. When you apply statistical process control and look at the reports over time, however, you can see patterns. One hospital that did this found out that patient falls increased during new orderly training periods. If you only report on a quarterly basis, you’ll never see that. Only when you look at the information as a process can you find natural cycles so that answers become visible, and natural variances become clear.

What if you could apply the same process control methods to the reports you’re reviewing? Or the reports you’re creating? What if you could stop flooding managers with false positives and let them know that something valuable is in there? What if you could reduce interruptions in business process to only provide reports when really necessary? With quality control applied to the information process flow, you can.