Behavior engineering


Instituting an analytics program in which actionable insight is delivered to a business consumer will be successful if those consumers are aware of what they need to do to improve their processes and reap the benefits. As we have explored over the past few posts, success in the use of analytics actually relies on three aspects of the program:

  • Technical – designing, developing and implementing the analytics applications.
  • Operational – engaging the business consumers and ensuring that they are willing and able to make use of the analytical results.
  • Management – providing guidance and support for both the application developers and the targeted business consumers to ensure proper incentives, training and oversight are provided to facilitate change management.

This last bullet item suggests that you don’t have to wait until after the applications are developed to ease the transition. In other words, the management of change can be eased through behavior engineering. What does it mean to "engineer behavior"? You might say that it is one part socialization, one part incentive and one part habit. When the practical value of changing behavior is clarified and an incentive for change is presented, training for repetitive transition from the undesirable behaviors to the desired ones is a matter of learning new habits.

Oversee those transitions as part of the change management initiative. Knowing that there will be a need for behavioral change means that you can plan for those changes by specifying what the expected modifications will be and align the training and motivation with the development and deployment. This can lead to more rapid uptake of the analytical results and faster time to value.



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 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 . David is also the author of The Practitioner’s Guide to Data Quality Improvement. He can be reached at

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