Smart use of information technology can allow for frequent and faster iterations between the design and operating environments, improving experimentation efficiency.
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Managers have used business analytics to inform their decision making for years. Numerous studies have pointed to its growing importance, not only in analyzing past performance but also in identifying opportunities to improve future performance.1 As business environments become more complex and competitive, managers need to be able to detect or, even better, predict trends and respond to them early.2 Companies are giving business analytics increasingly high priority in hopes of gaining an edge on their competitors. Few companies would yet qualify as being what management innovation and strategy expert Thomas H. Davenport has dubbed “analytic competitors,” but more and more businesses are moving in that direction.3
Against this backdrop, we set out to examine what characterizes the most experienced project managers involved in business analytics projects. Which best practices do they employ, and how would they advise their less experienced peers? Our goal was to fill in gaps in management’s understanding of how project managers involved in analytics projects can contribute to the new intelligent enterprise. (See “About the Research.”) We found that project managers’ most important qualities can be sorted into five areas: (1) having a delivery orientation and a bias toward execution, (2) seeing value in use and value of learning, (3) working to gain commitment, (4) relying on intelligent experimentation and (5) promoting smart use of information technology.
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Excellent article, immediately brought to mind 2 keys to the “test”/analytics parts. Firstly, my experience has been that as you noted test planning should be as detailed as reasonable. My noted problems in this area is that the people who are testing, like to continue to test and need a definitive stopping point (the point is that good program management has to be reasonably objetive about getting data and completing analysis). Secondly, as a program manager it has been my experience that the analytics part is typically more expensive than anyone thinks and it too suffers from inertia (bodies in motion want to stay in motion). The most difficult part is to be flexible, but know that some discipline will be required and timely recognition and use of discipline is key.