Tuesday, March 30, 2010

Avoid the Pitfalls of Innovation Data Analysis

C. Engdahl
The Big E of Big E Toys

A few months ago, in a post titled “Innovation Needs Information” I wrote about the basic importance of information in the innovation process. Voice of Customer, competitive intel, market studies, syndicated data, and more. It’s all important. But what happens when you get emotionally attached or intellectually numb to gathered information?

One of the classic pitfalls of data analysis for any individual is the propensity to develop an emotional attachment to the information itself. For reasons not always entirely clear (or rather for reasons that might take some psychological therapy to fully explore), an individual may react or become emotionally attached in some manner to a specific set of gathered information. This is especially true if the person in question performed the actual data gathering – as might be the case with investigative phone or personal interviews. Such reactions could manifest themselves in a variety of ways, including possessiveness or denial. When attachment occurs, a couple things might happen.

First, a person may place too much importance on certain data and/or ignore other sources of information. In doing so the information gathered may be viewed as the definitive answer to a particular question. Other alternatives may not be explored. Mild versions of this phenomenon are prevalent in almost all research studies, and in most cases nothing detrimental comes of it. People simply have a propensity to take ownership of and defend work for which they are personally responsible. Passion and a sense of accountability can be good things. But when feelings of ownership become possessive, when data are potentially horded, and latent motivations cloud one’s judgment about the true nature and importance of a given set of data, this phenomenon can become problematic. Share data. Discuss conclusions.

A second pitfall is sort of the opposite of the first. It occurs when the conclusions derived from a set of data aren’t all that appealing. Perhaps data suggest public perception or market share is waning for your products. Perhaps data suggest a completely new online strategy is warranted for your organization. Rather than take appropriate action based on the findings, people may choose deliberately or unconsciously to ignore and deny certain results derived from data. They’ll choose to formulate a different set of conclusions. These alternative ideas would likely be more akin to currently held beliefs or expected results. In this scenario, mindsets and current business processes can be preserved. The status quo can live on. It’s a classic example of a company simply unwilling to face existing facts because it might require additional effort or money to change the situation.

To combat against this potential problem, people must make a distinction between information and the conclusions resulting from information. Whether one likes the actionable elements derived from a set of data should have no bearing on one’s perception of, or belief in the data itself. Information isn’t inherently invested in itself. And although the integrity of information is important and worthy of protection, avoid creating and defending delusional data analysis.

Don’t think for a moment, because of these pitfalls, that information should be avoided or ignored. That would present even bigger problems. It’s not the fault of the information. Gather, gather, gather.

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