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If The Shoe Fits: Quantitative Data and Self-Deception

by Miki Saxon

A Friday series exploring Startups and the people who make them go. Read all If the Shoe Fits posts here.

5726760809_bf0bf0f558_mThe following post is reprinted in full with Wally’s blessings. I e-met Wally when we both blogged for b5 Media — I think. It’s so long ago I’m not sure, but over the years I’ve read and appreciated Wally for both his insights and independence from accepted leadership-speak. I highly recommend adding his blog to your reading list.

Quantitative Data and Self-Deception

If you need someone to blame this on, it might as well be Rene Descartes. The 23-year-old Descartes was serving in the army when was visited in a dream by the Spirit of Truth who told him that “Conquest of nature is to come through number and measure.”

Numbers were power. That effect was amplified during the Industrial Revolution. That’s when the engineers took charge, measuring and calculating. Soon, Frederick Taylor and the efficiency experts showed up with their stopwatches and clipboards. Now we’re in the Digital Age, where computers spit out numbers by the mountain load.

Today, companies trumpet the claim that they’re “data-driven.” The Economist proclaims that “data is the new oil.” If there is a golden calf to worship today, it’s probably digitized.

We love numbers so much that we don’t think about where they come from or how we’re using them. We can summon them from our vast databases, manipulate them, and turn them into equations that give us “answers. It makes us feel like we’re in control. We’re not, really. We’re only in control of the data.

The map is not the territory and data is not reality

Data is not reality. At best, data can only represent reality. Reality is complex and messy and we can use data to simplify parts of it so we can understand it better. To do that we must leave out part of reality, assign numbers to things that aren’t inherently quantifiable, and approximate relationships with equations.

If, after all that, we treat data like reality we commit what Alfred North Whitehead called “the fallacy of misplaced concreteness.” We get lost in the wonder of our calculations and think we’re describing the elephant, when we’ve only got hold of one leg.

It’s a good idea to apply George Box’s observation about models to our data. All are flawed, but some are useful.

Quantitative data is not objective

No matter what you or your boss thinks, quantitative data is no more objective than qualitative data. Someone, somewhere, sometime decided what would be counted and tracked and what would not. Someone, somewhere, sometime decided how and how often data would be gathered and how it would be presented.

That’s obvious when you talk about qualitative data. We usually get qualitative data in the form of a story. This happened when we observed it this way. With quantitative data, the questions, assumptions, and decisions that lie behind the data are usually behind the curtain and invisible to the people who receive and use the data.

Dig into the history of things to find out why you use certain measures and not others, how the raw data is gathered and manipulated, and why it is presented in the way that it is.

Quantitative data is not enough

Quantitative data is important, it’s just not enough for a successful business or a satisfying life. The most important things in life and business can’t be counted or calculated. Relationships drive much that happens in business. More than half a century ago, Mason Haire demonstrated that emotions influence buying decisions of all kinds. Knowledge workers trade in conversations and tacit knowledge.

There’s one more thing about quantitative data. It’s easy for us to manipulate and “understand” quickly, so we’re likely to pay attention to what we can count and ignore what we can’t. That’s part of the reason why the long term is often sacrificed to the short term and why numerical accounting data gets more attention than “soft” human stuff. As one friend of mine said years ago, “When the pressure’s on to make the numbers, people almost always take a hit.”

Bottom Line

Quantitative data is important. You can’t run a successful operation today without paying attention to it. Remember that quantitative data is always a flawed representation of reality. Look behind the curtain to discover the whys and hows behind the data. Remember that human choices drive quantitative data as much as qualitative data. And, please, remember that the most important things in life and business cannot be force-fit into a dataset.

Copyright © 2017 Wally Bock, All rights reserved.

Image credit: HikingArtist

2 Responses to “If The Shoe Fits: Quantitative Data and Self-Deception”
  1. KGNo Gravatar Says:

    So true – excellent summation of today's self-delusional data culture. Since we no longer study philosophy, and the humanities in general are valued lowly, we forget the knowledge we've already gathered as a species. We have become data driven without a sense of history, with little understanding of people or societies, and almost none of nature.

    The question is, can we under these conditions think and make cogent decisions about values? About what's best for people, society and nature?

  2. Wally BockNo Gravatar Says:

    Thanks for the kind words. I know from my own personal experience that you are better-equipped to write good computer models if you’ve read some Plato. I agree that we over-value the data side of things and without a sense of history or exposure to other cultures and ideas we’re likely to make the same mistakes others have made. We make it worse by retreating into our own little belief-bubbles and never sharpening our ideas by having a real dialogue with others who are good people with different ideas and beliefs.

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