The Myth of the Bell Curve

According to Josh Bersin (Principal and Founder, Bersin by Deloitte), business has a lot to learn about understanding and evaluating human performance and achievement. Some of the standard tools that have been employed for decades cause managers to draw imprecise and unacceptable conclusions.

“There is a long standing belief in business that people performance follows the Bell Curve (also called the Normal Distribution). This belief has been embedded in many business practices: performance appraisals, compensation models, and even how we get graded in school. (Remember “grading by the curve?”)

“Research shows that this statistical model, while easy to understand, does not accurately reflect the way people perform. As a result, HR departments and business leaders inadvertently create agonizing problems with employee performance and happiness.”

Read Josh’s complete, and very interesting, comments here.

Rethinking Data

This analysis appeared April 30, 2013 in Cornerstone Information System’s “Insight & Opinion” section


Data and their application have been a travel industry fixation since ADS was discovered over 30 years ago. When it became practical to collect the specifics of what travel customers were buying, suddenly it was an essential management task, effective competition hinged on being the best data manipulator, and travel managers were left to wonder what they should do with the piles of reports TMCs were cheerfully offering.

Most people are still wondering. Making better decisions that are enabled by travel data is a goal industry experts, acknowledge, respect, desire to achieve, and find surprisingly elusive.

A correct and productive data strategy for the travel industry is not difficult to identify, but its successful implementation requires discarding several cherished ideas.

Big Data…Big Deal

Some years ago, the CEO of a major national TMC (herein nameless) was fond of telling industry groups that it once “came to me in a flash of light that I was really in the information business.”

As I worked for a major competitor, I was also fond of telling the same story–with full attribution to its author. I added that perhaps his next corporate account proposal would be successful if he offered just reports…and no tickets.

Travel is not an information business; it is a service business and many of the most indefensible and irrational travel products were conceived when people lost sight of that fact. Where data support the delivery of effective and affordable customer service, analysis has a role.

Analysis for its own sake has few uses and is something for which most travel managers have a difficult time writing a check.

The current hot topic in reporting circles is “big data,” (ten years ago it was “data warehousing”). Apart from the fact that big data means lots of data from multiple sources, most people are challenged to explain its business rationale.

Under most conditions, “big data” is a term without meaning in the travel industry. Effective managers in all sectors of the industry need realistic business analysis goals, without regard to the size or complexity of a data set. Collecting the most data sounds highly scientific to most people and from that they incorrectly infer that the exercise must be valuable and that ill-defined real-world applications are justified.

Big data might have a role in such predictions as what travelers will buy, but even there the variables are so complex as to confound all but the most determined and expert analysts.

Where’s Your Talent?

Decision support tools for the travel industry have proven difficult to build and maintain, and the few companies that produce truly good ones are highly underrated for the value they deliver. A successful decision support tool enables better, more informed business decisions that cannot necessarily be anticipated when the system and the databases that sustain it are conceived.

As essential to such a system’s success as the skill with which it was designed is the insight it enables for its human operator. Systems people are prone to highlight data, reports, and analysis while overlooking the fact that a skillful, insightful, talented operator is what moves decision support into action.

The system’s role is to make that talent productive.

Without recognizing the role and composition of decision support, travel data analysts are likely to dive down any number of rabbit holes looking for new projects. One good example is the current fascination with data analysis projects that have subjective outcomes.

Systems that contrive to use data for calculating such things as traveler dissatisfaction with policy are ill-conceived in my view. A “dissatisfaction” report cannot escape the subjective and occasionally irrational nature of what it attempt to measure, a problem which is compounded by dozens of other variables that combine to make the result about as meaningless as arguing that green is better than blue.

Successful corporate travel data analysis is built upon clear business goals, and supported by decision support tools that empower insight and better conclusions in their human users.

They recognize the elegance found in simplicity and employ the shortest, most efficient way to deliver their results, and the travel managers using them do well to require specific answers from them to their real-world problems.