Data convenience!

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Data convenience! / 067, 18 Mar 2023

We are bang in the middle of the information age. Data about everything and anything is available, and in real-time at that. Decision making is more and more data driven, or so we read everywhere. But with so much data to choose from, selection of data points for a specific decision is still subjective and depends on the person involved. For example, a young professional just starting her/his career and a senior professional with just a few years left will choose differently from the same available investment options, because one critical parameter – time horizon for ROI – varies greatly for both.

Similarly, in organisations, professionals prefer to choose the data points based on how well they have worked in the past, and a certain sense of what will be ‘acceptable’ to others. This is what I call “Data Convenience”, or the repetitive use of certain data points based on our preferences for decision making. I had earlier written about Cognitive biases in decision making; but Data Convenience is different because it goes beyond bias, to safety, convenience, or acceptability. We choose data points that we think will not fail, or will not shock other people, and in general will find acceptability or least resistance amongst them. Leaders today need to avoid Data Convenience, simply because the quality of new data emerging is profound and if we are limited in our choices by ‘Data convenience’ then we may miss out on the future.

Like any working professional, I have experienced both pros and cons of my own ‘Data Convenience’ in Decision-making – they worked in some cases and didn’t in some others. But whether they worked or not, I found out in retrospect that my quality of choosing the data points could have been better had I followed s few critical steps:

• Suspend decision making until the end, because I used to form a decision initially but communicate it at the end. Now I really remain undecided until I have read, listened, and debated all points
• Research – much as we all think, what we are trying to do has probably been attempted already. We can learn valuable lessons from others’ hits and misses. Reading up on the topic and its related areas, typically where surprises spring from will help us avoid poor decisions based on wrong choice of data points
• Encourage playing Devil’s advocate, ask for deliberate and wide-ranging criticism over the choice of data points. In this simulated environment, we can refine our choice of data points by roasting them in the fire of diverse and rational thinking

With these steps, we can avoid ‘data convenience’ and improve our choices by choosing the relevant data for our decision making.

I hope you enjoyed reading this one, and as always, I request you to share your own thoughts and experiences in the comments section. Let us build a conversation on this topic!

Warm regards, Krishnakumar.

Image courtesy:

Marketing the Future: How Data Analytics Is Changing - Knowledge at Wharton (upenn.edu)

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