Ignore the Data at Your Own Risk
As an undergraduate psychology major heading for a career in psychology research (or so I thought), I took a course in experimental methods from a professor who frequently told us, "The data are trying to tell you something."
The professor was talking about data in the context of behavioral research, but this statement proved to be a lesson that applies to everyday life and work. It emphasizes the importance of paying attention to situations that might appear to be minor matters but could turn serious—the leaky roof, the medical symptom, the squealing tire, the contractor who doesn't return calls. These might be situations of no consequence. On the other hand, brushing them off as no big deal could prove to be disastrous.
At work, the evidence of something worth paying attention to is often front and center, and yet we miss it, or, worse, dismiss it. My professor's statement reinforces the idea that if we ignore the data—negative survey results, team member absences, an increase in bugs, stakeholders who repeatedly miss meetings, etc.—we could be overlooking signs of trouble and find ourselves in a fix that could have been avoided.
Therefore, if you deliver services to customers, it's important to continually gather and assess data so that you're aware of evolving patterns and can make adjustments in a timely fashion. Note: I said gather and assess, because buckets of data about budgets, timelines, schedules, resources, and other key project variables are of no use at all if you're not paying attention.
But even gathering and assessing isn't enough, because no matter what data you routinely collect, you need to be alert to situations that are exceptions to the rule, such as a gradual increase in calls about one particular problem. When an incident occurs that clearly deviates from the norm, it’s wise to view it as a signal that something is wrong, or at least unaccountably different. At that point, it could a serious mistake not to ask, “What's going on here?”
The absence of an expected pattern or trend is also data. For example, if a major upgrade to your ERP system routinely results in a spike in customer complaints, and just a few complaints have dribbled in since last week's upgrade, that absence of complaints is itself data. It could mean customers were so disgruntled by a history of flawed upgrades that they no longer bother to complain. Or, on a more optimistic note, it could mean the preparation for the upgrade was first-rate, leaving customers with no cause to complain. The first of these explanations is wholeheartedly depressing. The second is cause for celebration. It seems best to know which of these explanations (or any other) is the right one.
Ignorance of data is not bliss. Stay alert. The data you haven't paid attention to may be trying to tell you something.
