Behavior architecture

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In the past few weeks I have presented training sessions on data governance, master data management, data quality and analytics at three different venues. At each one of these events, during one of the breaks a variety of people in my course noted that the technical concepts of implementing programs for any of these practice areas seemed straightforward. However, many of them suggested that the value of implementing any one of these programs and delivering high quality data and analytical reporting appeared to be constrained by what I have frequently referred to as “the last mile” – getting the consumers of the data to take advantage of actionable information.

One perceived reason for this phenomenon was that the business users are somewhat detached from the production of the information product, and when presented with more trustworthy information or better analytics, they neither understood why the result was more desirable nor changed their processes in reaction to the information improvements.

As an example, consider a sales process analysis that scores sales prospects in relation to their perceived needs, their predisposition to purchase a product and an understanding of their funding cycle. Depending on the industry, the salesperson may have hundreds, if not thousands of prospects in the funnel, yet most salespeople naturally gravitate towards those prospects that they believe to be the most promising. That means that the analytical model may be presenting valuable insights, yet those insights are being ignored because the intended beneficiaries of those insights are not prepared to react to those suggestions.

In other words, achieving the desired outcome of instituting good data management and analytics practices is limited by the desire of the users to change their behavior to accommodate actionable knowledge. And during a conversation I had with a colleague at one of the training events about information architecture, my colleague coined the phrase “behavior architecture” to refer to the way to engineer the consumption of information and change the target’s behaviors to benefit from that information.

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About Author

David Loshin

President, Knowledge Integrity, Inc.

David Loshin, president of Knowledge Integrity, Inc., is a recognized thought leader and expert consultant in the areas of data quality, master data management and business intelligence. David is a prolific author regarding data management best practices, via the expert channel at b-eye-network.com and numerous books, white papers, and web seminars on a variety of data management best practices. His book, Business Intelligence: The Savvy Manager’s Guide (June 2003) has been hailed as a resource allowing readers to “gain an understanding of business intelligence, business management disciplines, data warehousing and how all of the pieces work together.” His book, Master Data Management, has been endorsed by data management industry leaders, and his valuable MDM insights can be reviewed at mdmbook.com . David is also the author of The Practitioner’s Guide to Data Quality Improvement. He can be reached at loshin@knowledge-integrity.com.

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