The organization of the Digital Equipment Operator will usually be very different than that of the Digital OEM. The focus is much less on development but mostly on integrating the solution with the existing assets and the existing business processes. This will be discussed in the following.
This part of the organization will heavily depend on the make vs. buy decision. In many cases, the AIoT-enabled solution will be sourced externally (or from a dedicated IT unit in the same company). In this case, the organization required will be relatively lightweight, focusing on requirements and provider management. If the decision is made to develop the solution with one's own resources, the picture obviously looks different.
An interesting example for solution provisioning is discussed in the Bosch Chassis Systems Control (CC) case study. In this example, a dedicated team for building AIoT-enabled solutions for manufacturing optimization is established. This central team supports manufacturing experts in the different Bosch CC factories. The central team has AI and analytics experts who then team up with the manufacturing experts in the different locations to provide customized AIoT solutions.
Particularly in cases where new hardware (e.g. sensor packs) must be deployed to existing assets, solution retrofitting becomes a huge issue, and must be supported with the right organizational setup. Take, for example, the railway operator who wants to roll out the escalator monitoring solutions to thousands of escalators in different train stations around the country. For this rollout, a dedicated rollout/retrofit organization will have to be established.
Depending on the complexity of the assets -- how they are operationally utilized, and the scale of the rollout -- this can be quite a significant organization. Of course, key questions include: for how long the rollout/solution retrofit organization must exist, and how the peak load during the initial rollout should be dealt with. Take, for example, an AIoT solution that needs to be retrofitted to all the trains in the railway operator's network. Each train might only get a couple of hours of extra maintenance time every year. This will be quite a challenge for the team responsible for applying the retrofit to a fleet of thousands of trains.
Ultimately, the utilization of the AIoT-enabled solution is indeed the aspect that is of most interest to the Digital Equipment Operator, as it is where the business benefit is generated. Depending on the nature of the solution, this can involve a dedicated organizational unit, or be supported by an existing unit. New, AIoT-enabled analytics features might feed into an existing MRO (maintenance, repair and operations) organization. More advanced features, such as predictive maintenance, may already require some changes to the organizational setup because they will most likely have a more profound impact on the processes. For example, if the predictive maintenance solution actually predicts a potential failure, then the MRO organization must pick up this information and react to it. This process could be completely different than the traditional, reactive maintenance process.
If the AIoT solution offers a broader set of features to support Asset Performance Management (APM), then this will require a dedicated APM team to continually execute the performance optimizations.
Finally, if the AIoT solution feeds into other business processes, then business process re-engineering must be performed, and the new target processes must be supported by a suitable organizational setup. Take, for example, the AIoT-enabled flight path optimization system explained earlier. The introduction of such a system will have a significant impact on how the airline operates and touch many of its core processes.