8APRIL 2025IN MY OPINIONWhen it comes to large-scale technical interventions, such as the implementation of a predictive model, pessimism is relatively easy to encounter. Studies, opinions, and observations abound and are consistent in suggesting that fewer than 1 in 6 such projects reach their stated finish line. While technical reasons for this exist (data limitations, systems readiness, timing), more often the issues lie in the more mundane--people issues. With some careful attention to the psychology of large-scale interventions and the impact to the people, one can increase the likelihood of success. A professional practitioner should be able to gauge the environment, understand the people, and ultimately understand when an opportunity for large-scale technical intervention exists. Pick a Winner from the StartYou can't push a string. Choose wisely. What makes a good candidate for an analytic product (or other technical intervention)? There are at least three primary considerations. First, there should be a clear line of sight to a business problem. The problems that statistical models often impact the most include one or more of the following: creating consistency, driving efficiency, making better [risk] decisions, and/or seeking opportunities. These problems may not be clear at the outset of a project but should be stated early enough that a clear line of sight to success is articulated. Second, an organization must be open to change, and that positive momentum must be maintained long enough for success. For this, ideally a person is identified to serve as the champion for change, seeing the project through from start to finish, helping to develop openness to change (a transformational leader) and keeping up the necessary change MODEL IMPLEMENTATION: ON THE PSYCHOLOGY OF LARGE-SCALE TECHNICAL INTERVENTIONSBy Thomas D. Fletcher, PhD, SVP and Global Head of Data Science Consulting (Life and Health), PartnerReThomas D. Fletcher
< Page 7 | Page 9 >