Model Implementation: On The Psychology Of Large-Scale Technical Interventions
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Model Implementation: On The Psychology Of Large-Scale Technical Interventions

Thomas Fletcher, PhD, VP Data Analytics, North America Life, PartnerRe
Thomas Fletcher, PhD, VP Data Analytics, North America Life, PartnerRe

Thomas Fletcher, PhD, VP Data Analytics, North America Life, PartnerRe

When 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 Start

You 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 momentum. This person will ideally understand the business problem and how the model will solve that problem, and be familiar with the outputs, workflow implications and impact on those affected.

Third, one should make note of the relative size of the business problem to the company and impact to be delivered. Often, small segments of a business do not resonate with the larger organization and smallish problems don’t garner the implementation resources necessary to see success (small distractions don’t get traction).

Measures of success, or what I refer to as the hallmarks of a good implementation, are related to the above three considerations. If any, or all, of these considerations are not met, then the timing is not right, and success is unlikely. An effective implementation will have clearly stated goals (related to the business problem to be solved), have a change champion and matter in relative terms to the company.

Be Change Ready

With respect to planning for change, key considerations are a must. What is the core content of the change? What people, processes, systems, etc. will be impacted? What is the change management strategy to be implemented? That is, careful attention should be given to the process of change, how we go about changing. Considerations in the process include: the content, the role of the change champion, inclusivity of key stakeholders, planned communications (there should be many) including timing, proper storytelling, and the like. However, most critical to change management are the identification and addressing of resistance and ensuring change readiness. The most well-intended interventions will fail if the organization is not made ready for the change.

"The ‘best laid plans of mice and men often go astray,’ is as relevant today in the hyper-modern tech world as when it was written many years ago"

processes, systems, etc. will be impacted? What is the change management strategy to be implemented? That is, careful attention should be given to the process of change, how we go about changing. Considerations in the process include: the content, the role of the change champion, inclusivity of key stakeholders, planned communications (there should be many) including timing, proper storytelling, and the like. However, most critical to change management are the identification and addressing of resistance and ensuring change readiness. The most well-intended interventions will fail if the organization is not made ready for the change.

Culture Eats Strategy for Breakfast

Strategy is important, but ignoring culture is tantamount to failure. The “best laid plans of mice and men often go astray,” is as relevant today in the hyper-modern tech world as when it was written many years ago. Careful consideration must be given to the underlying assumptions that people hold, the values and beliefs that they share and the normal way of behaving. Introduction of a new work design implies change, and that impact should be acknowledged. Some key questions to ask with respect to the intervention’s impact on culture include:

• Does the implementation work in concert with or in contradiction to the prevailing culture?

• Do people believe that they will be rewarded or inadvertently punished by model usage?

• What values are impacted or challenged?

• Have new norms been established? What are the “best practices” given the model results?

Don’t Reduce Motivation in a Quest to be Efficient

The impact on the motivation of those affected is perhaps the most critical and most often overlooked factor. Careful consideration should be given to the workflow changes. While there are many well established theories of motivation to draw upon, a few key concepts are worthy of highlighting.

Models that create efficiencies can also impact the design of work in unintended ways. Autonomy, a fundamental psychological need, could be threatened. The new work design may limit skill variety or otherwise limit challenges. The sense of joy and focus one obtains in work—“flow”—could be hampered. In general, models should supplement performance by reducing monotony and enabling greater attention to complexity (not the reverse). Here are some key questions to ask with respect to the impact on motivation. Does the new work design:

• Remove autonomy?

• Make the work boring or otherwise less motivating?

• Make the work more interesting (can focus on more valued actions)?

• Provide opportunities to otherwise be better in a specific role?

Planning and Psychology in Tandem

In summary, much of the pessimism surrounding real experiences in implementing technological interventions such as predictive models, can be attributed to limited attention to people issues. Picking a winner is a good first step. Strive to recognize limitations early on and ameliorate those or patiently wait for the right opportunity. Plan for change effectively, but don’t discount the culture in which the change is to take place. There will always be resistance, so look for it and be prepared with a change champion or transformational leadership. Finally, recognize that while intentions may be valid, some change undermines the motivation of those who are intended to benefit—don’t reduce motivation in a quest to be efficient, but craft careful discussions with those impacted.

 

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