The 5 Stages of Data Denial

Data is often used to confirm the truth or disperse myths. So it pretty much goes without saying that people love it when data proves what they have been saying or doing all along. As Dan Holowack states in his blog: "Change often costs money, change is hard, change sometimes means admitting mistakes". So it makes sense that if you need to initiate change in your organization, an activity often met with a little resistance, then wielding data that proves the need for change seems like an appropriate way to begin.

Adapted from a presentation presented by Brian Postl, President and CEO of the Winnipeg Regional Health Authority, here are the 5 stages of data denial.

1. The Data is Wrong

A lot of the time your initial reaction can be: "the data must be wrong". If this is what springs to mind, it is advisable to take a step back and take a look at the overall result. Is it at least close to what it should be? If so, this could be enough to leverage action; don't spend too much time worrying over the finer details.

2. The Data is Old

Another classic excuse. Does the data really need to be up-to-the-minute, real time data? That all depends on your industry and what you are doing with your data. But chances are, that data that is a little dated still holds some value and truth. Don't dismiss it just yet.

3. We Have Already Changed

As long as you can show that the changes have been made, this one does not count as a denial. At least the organization has acknowledged the fact that they need to improvements and have started to think about, if not implement, actionable changes. Questions to ask yourself: What changes have we made? How are these reflected in the data? Make sure you can confirm the changes in the new data.

4. This is a Different Place

Just because your organization does not fall into a particular area, or does or doesn't outsource work to another country, don't think you can escape by playing the location card. Make use of data by trying to find commonalities to support best practices instead of comparing where you both fell down.

5. We Already Tried That

As we said before, it is hard to get an organization to initiate change, let alone get it right the first time. Especially if previous attempts at change were unsuccessful. Look at your data carefully - are there things you missed last time, or things that have changed that can give you more insight or opportunities?

The best way to deal with data denial - start with a small change, something you can measure, share and celebrate the success. Or the other alternative is to try to avoid it completely - start analyzing your data early on with a BI solution like Bime. Because you can ask any question you want, you are able to quickly uncover where things are going wrong before you have to enter the denial stages.