Decisions are part of our every-day life. It’s not only in work that we are expected to make good decisions, those are desirable in private life as well. So do we think we make good decisions? Are you sometimes misled by cognitive biases? Have you ever heard of the two different cognitive systems underlying our reasoning and thinking? There is enough evidence so far to support the view that we need to be data driven in order to make better choices.
Data is no longer something reserved for business intelligence, data warehousing or BigData departments. Data is prerequisite of making the right choice – use it to understand a trend, find a weak spot, measure a success or better understand a failure. Surprisingly enough, gathering and retrieving information that is helpful in day-to-day work can be very easy. Below are just a few examples on different organizational levels.
→ How do you know that you have failed or succeeded?
Ask for feedback, it will certainly help.
→ How fast and effective your team is at delivering features?
Track lead time and percentage of “touch time” activities within the process – aggregate historic data to see the trend.
→ Is the discussion on retrospective meetings focused on most important problem?
Collect impediments and blockers and create a Pareto diagram as one of the ways to verify that.
→ How do you know that you’ve correctly assessed a candidate during recruitment interview?
(If hired) Link his 360 feedback score with recruitment score, this way you also verify the fairness of your hiring activities.
→ Where is it possible to improve the delivery process within your department?
Gather and visualize data in the form of a value stream map, use it to better understand and visualize waste activities.
→ Want to open new development center abroad and you are eager to understand cultural differences?
It looks like you don’t need to be data scientist to become data driven.
Additionally, being data driven includes promoting similar attitude among coworkers. Start challenging solutions by asking the right questions, i.e. “do you have data to support your proposal?”, “how are we going to measure the success of this experiment?” This way we build a culture that understands the meaning of data and is more likely to make better decisions.
Data is very powerful tool which if used wisely can boost the success rate of decisions you make. But like with any tool you need to watch out for risks. Being too attached to data, measurements and numbers can lead to loosing track of real problems that in long term can lead to disaster. Keep in mind the cost of data collection compared to the cost of a bad decision making without data. Moreover, sometimes having less data creates predictions as good as the those made with all possible data. Also in many cases trusting gut feeling is perfectly fine, as we need to keep common sense between decisions we should back with data and those we don’t, not everything can be measured – and that is just fine.