In our example, the data entry clerks’ task only requires the loan contract data to be represented in the system. Digitalized tasks (i.e., tasks that are supported by a digital tool) that have a high degree of both dimensions are the most complex. The second dimension, semantic dependency, analyzes the degree to which users need to understand how the business logic of their task is implemented in the system. We found that two dimensions explain this difference: The first, system dependency, looks at how much of a user’s task is represented in the system - that is, how much of the task and the relevant environment is implemented in the system through data and algorithms. Clerks in the former group achieved effective use within six to eight weeks, but those in the latter group needed over six months to do their work effectively again.
FSUIPC ONE LEVER FOR MANY OPERATIONS HOW TO
In stark contrast, clerks who needed to make edits to loans in stock had a much harder time learning how to work with it.
For them, learning how to do their work with the new system was easy. For example, one group of clerks used the new SAP-based loan management system to enter new contracts. In our study, complexity-in-use led to vastly different digitalization journeys for different departments, even though they all used the same system for their respective tasks. Key findingsĬomplexity-in-use explains why learning and using a digital tool is easy and straightforward for users in one context and difficult and cumbersome in another. Analyzing these struggles allowed us to identify both the underlying mechanisms that constitute complexity-in-use and the responses to it that worked. We were particularly interested in the contrast between departments that managed to use the new system effectively and quickly and those that struggled for a prolonged period. We conducted over 60 interviews with stakeholders at various levels of the unit and closely observed day-to-day operations - starting with employees’ established work routines using a 30-year legacy system and ending when unit’s executives felt their teams were performing well with the new system. In our study, we focused on the different teams across the unit’s core departments, the differences in their approaches to digitalizing their work with the new system, and their success. We shadowed one of the bank’s business units that provides shared after-sales services connected to the bank’s mortgage and loan business. Our insights are based on a two-year research study at one of the leading banks in Europe, which replaced its core banking system. Once managers master this form of complexity, they’ll be able to plan and focus their digitalization efforts and deliver more effective transformations. These levers are rooted in the idea of complexity-in-use, a concept we developed to help understand the difficulties users face when trying to cope with the impacts of new digital tools on their work. While much progress has been made - from hardware and infrastructure to updated work processes and a rejuvenated corporate culture - many organizations are confronting the question of how to integrate fragmented and often makeshift digitalization efforts in a way that’s sustainable.įor any digitalization effort, whether the goal is to safeguard business continuity or enable digital innovations, one of the key questions for managers remains: Are there ways to speed up digitalization and make outcomes more predictable? This is particularly pertinent for small and medium-sized organizations that need to be more targeted in their efforts and may not have the resources to engage in the “fail fast” approach often heralded by the larger poster children of the digitalization movement.īased on our research, we recommend three levers for accelerating digitalization projects that will help organizations of any size reap the benefits of true transformations. The pandemic has given many organizations an unexpected crash course in digitalization.
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