Earlier, we talked about content-specific interpretation: algorithms that detect patterns in narrowly defined areas like team effectiveness, technology adoption, innovation, or contract management. Over time, consultants will come to realize that these patterns do not stand alone.
For example, a team without an effective Plan-Do-Check-Act process will predictably score lower on technology adoption than, say, another group that has such a process but has a pattern of not celebrating successes. Consultants who harness these patterns in the first place and then know how to structure and correlate these patterns within an overarching taxonomy will undoubtedly thrive.
The expanded nudging alerts when nudging motivates managers insufficiently to take actions that matter. Conversely, the activity alerts tell consultants when managers take action, how they take action, and what it did to the bottom line (e.g., the number of priority list items discussed with the team in a workshop). Structuring these alerts and – again, aggregating their outcomes in a taxonomy – will significantly enhance the predictability of when and how the organization completes a transformation, the 'nec plus ultra' for every discerning consultant. Automated consultancy is about offering a large group of people as much self-service as possible. Activity alerts help to understand how to make that group bigger.
The progress alerts are related to their activity alert brethren and indicate when assessment scores are above or below par, longitudinally (so, in time). In combination with activity alerts, they form the basis for transformation prediction algorithms. Is an individual management style (activity) indicative for, say, faster adoption of technology?