Data isn’t important in decision-making. What? Shocking! Then why aren’t we shocked when someone says that all decisions must be totally data driven? Perhaps it depends what we mean by data, which is usually something quantitative.
We need to get out into the world and gather data by watching, observing, listening, asking – qualitative data. We don’t live in a binary world – it’s not either-or, it’s and-both. We need quantitative and qualitative data. We need to consider both equally valid forms of data. After all, as the sociologist William Bruce Cameron said (guess Einstein didn’t *),
Quantitative data needs to be part of the equation, part, not all. More and more I see companies defining “data” as purely quantitative, dismissing or minimizing, at their peril, the importance of the qualitative. Quantitative data can tell us a lot. It an also tell us little. Quantitative data has limitations – as does everything. These limitations are because the data usually is…
- About existing “stuff”. It tells us about our current features, functions, customers and markets. It tells us what customers are [stuck] using now, not what they really want. It doesn’t tell us what our “stuff” could become or what new customers, markets and applications are out there;
- Based in the present or the past. We don’t have much ‘future’ data: what will, could, should or might be and what we could do to make that happen;
- A glimpse in time. It can be a year, five years, ten years, but it’s always piece of the bigger picture;
- About the what, where, why and maybe even how, but rarely the why. Data usually doesn’t tell us much about fringe factors or trends that impact it. It’s hard to have data show us the subtle societal, cultural, behavioral “whys” of influence;
- Used to make things more efficient instead of more effective. Yes, efficiency (or optimization to be more eloquent) still rules for most of business today. Data helps us figure out to eliminate unnecessary steps, improve productivity, reduce costs, etc. Data doesn’t necessarily tell us why things need to be improved in the first place or new, different ways of doing, period.
As I like to tell my engineering students, most of today’s wicked problems aren’t optimization problems; they are system and design problems. Think of the remote controls on your den table! Optimization issues are a symptom, not a root cause. Data doesn’t necessarily tell us how to make the problem go away because it doesn’t tell us why the problem is there in the first place. We have to actually get out of the office and look at how the problem is being addressed, not addressed, or not well enough by human beings. We need to see how things are organized, structured, laid out, used, not used and under what conditions, circumstances and contexts.
Data can tell us a whole lot about how our sites and stores and companies are working or not working, but data can’t necessarily tell us the whys – why it is or isn’t working, or working well enough. Without getting out and observing reality first-hand with all our five senses, we risk optimizing our organization into extinction.