Can You Be Data-Discerning, Not Data-Driven?

Everyone says we must be data-driven.  I have trouble with that phrase, as discussed before.   Too often, we're making decisions based on the data presented...as is.  We're not asking the hard questions behind the data.

When I was at Bell Labs, we used to ask, "How much did you pay for that data?"  You can get data to say whatever you wanted depending on how it is presented and calculated, on what you show and what you don't.  

Before you start making decisions on the data in front of you, ask why it is the way it is, what's driving those numbers, what was the context, the constraints, the demographics, the sample size, the timeframe and frequency, etc. 

For instance, a company says it promotes more of its people than its competitors,  but perhaps it's 50yrs older? Perhaps its twice as large so the overall numbers are bigger? Perhaps it hasn't  in the past 5 yrs but given the number it had the previous 30, the overall number is still big.  Perhaps, perhaps - if you don't ask, you won't know and you could make decisions that are yes, based on the data in front of you, but not on the story behind that data. 

"Be Data-Discerning, Not Data-Driven"

I propose we start being data-discerning, not data-driven.... you may be surprised at what new insights you discover! 

Death by Data

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 *),

“Not everything that can be counted counts. Not everything that counts can be counted.”

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;At the Edge (Pemaquid Point, ME)
• 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. 

* http://quoteinvestigator.com/2010/05/26/everything-counts-einstein/

Should we worry about a Digital Landfill?

Our society has made significant progress on reducing landfills.  From companies like Subaru’s Zero Landfill Plant in Indiana to the many trash and recycling bins on campuses, shopping areas and homes, we are conscious of not wasting our physical resources.

So, I’ve wondered if we are creating the equivalent of a digital landfill? I’m not talking about the plethora of physical computer equipment (and precious, rare-earth minerals) in landfills but the actual concept of wasted, unused bits and bytes.  It is so easy to write an app, a software program and create data (like photos, music, e-records, analyses, etc.), that we do it without thinking. 

How many times do you take a picture of the same thing to get it right? We used to take just one in the physical film days but with a digital camera/phone, we can take 20 to get the one we want.  How many apps do you have on your phone or iPad that you don’t use anymore, and probably just used once or twice? And if you delete it, what’s really ‘gone’?

Innovation requires many “at-bats” before we get it right.  We have an idea, test, learn, apply and iterate.  That's how we create meaningful and valuable solutions to problems. I’m not recommending we don’t keep trying.  Yet, I do wonder if we are becoming habituated to wasting the resources associated with the digital world: time, effort, thought, money.  After all, these are not as tangible and visible as soda cans, paper cups and plastic utensils, but they aren’t infinite.  Somehow it seems ‘ok’ to buy and/or download more ‘stuff’ and use up more ‘space’ with every picture, sound, video ever taken.

As we try to increase our consciousness of what and how we consume in the physical world, so we are better stewards of our natural resources, does the limitlessness of the digital world mean we over-consume? Does it mean we’ll just download apps and keep saving data because we ‘can’, because there is no tangible landfill or obvious sign of waste?  Are we merely transferring our consumerism from physical to digital? And is that ok? What are the 2^nd and 3^rd order consequences of that?

I don’t have the answers – I just have the questions.  What do you think?

Thank you again, Denise Fletcher, for telling me to write this!