“Something is not Right!” Don’t Ignore Your Gut When Analyzing Information

Know What You Don't KnowTraditional data warehousing and data analytics vendors often present their solutions as a way to make decisions ‘based on objective facts’ rather than relying on ’emotional gut feel’. The problem, however, is the known ‘objective facts’ may not provide a complete and accurate picture of what’s really going on.

Even worse, some organizations over-emphasize hard data to the point of employees feeling compelled to ignore their ‘gut’, their intuition, that something is not right.

That’s a big mistake, says best-selling business author and professor Michael Roberto, in his book Know What You Don’t Know: How Great Leaders Prevent Problems Before They Happen – a book I first mentioned here on this blog not long after it was published in 2009.

Please read the entire article on the Smart Data Collective site.

Business Managers Can Learn a Lot from Data Scientists

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In a recent thought-provoking TDWI article, David Champagne informed readers of The Rise of Data Science: a discipline of emulating the scientific method when analyzing data, in a conscious and laudable effort to ensure objectivity and avoid poor analytical practices.

As I had just recently blogged on the Texas Sharpshooter Fallacy, a type of flawed analytical logic business intelligence users might fall into, David Champagne’s article caught my attention.

 

From David Champagne’s article:

Back in the “good old days,” data was the stuff generated by scientific experiments. Remember the scientific method? First you ask a question, then you construct a hypothesis, and you design an experiment. You run your experiment, collect and analyze the data, and draw conclusions. Finally, you communicate your results and let other people throw rocks at them.

Nowadays, thanks largely to all of the newer tools and techniques available for handling ever-larger sets of data, we often start with the data, build models around the data, run the models, and see what happens.  This is less like science and more like panning for gold…Perhaps the term “data scientist” reflects a desire to see data analysis return to its scientific roots…

Barry Devlin, in his business-focused commentary on David Champagne’s article, noted the worlds of science and business have rather different goals and visions, which I interpreted as data science might offer limited benefit to business managers.  But perhaps the best practices of data scientists have a lot more in common with those of business managers after all, in light of some commentary I came across on effective business decision-making.  That commentary gave high praise to the manager who utilizes the scientific method in the decision-making process. The author was not a technologist, but rather: Peter Drucker, the father of modern business management.

Revisiting Peter Drucker’s writings on effective decision-making process will show surprising similarities to the best practices of data science, and yield beneficial insights for business managers seeking to make more effective, data-informed decisions.

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Combine Business Intelligence with Business Wisdom

I very much want to share a live presentation that especially resonated with me, and no doubt for those who had the good fortune to be in attendance: a TED talk by Barry Schwartz appealing for wisdom in the workplace and beyond.

The good news is you don’t have to be brilliant to be wise. The bad news is that without wisdom, brilliance isn’t enough. It’s as likely to get you and other people into trouble as anything else. — Barry Schwartz

I reflected on Barry Schwartz’s fine presentation from a business intelligence perspective. Consider Barry Schwartz’s compelling example of janitors who modify or skip their usual tasks for the benefit of patients and their families. Now imagine a supervisor, relying only on the numbers from time and attendance reports, who might reprimand these janitors for not completing their work tasks in a timely manner (rule enforcement)! Similarly, consider a supervisor, again relying on reports, has the epiphany to offer a wage incentive for janitors to complete their tasks ahead of schedule.

In both cases, supposedly justified by business intelligence, rules or incentives might be enforced that unwittingly discourage janitors from performing their tasks with empathy and in the long run will have a detrimental impact on patient care…

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