ABSTRACT
When faced with a complex problem, we typically tend to devise a high-level strategy to solve the problem and then as we work on the problem we evaluate the progress and course-correct our actions in the direction that would provide a higher, better, or faster chance of resolution. Besides facilitating spontaneous on demand collaboration, it is the adaptive nature of ACM solutions where the case workers are able to make choices about what next steps to take that make them (the ACM solution) a more natural fit for the way we humans solve complex problems. In fact without the ability for the case workers to enjoy the freedom of choosing a context-appropriate activity, whether it is already made available as part of the packaged solution or needs to be created at run time, how would the added benefit of on-demand collaboration and expert advice be incorporated into the problem resolution exercise? Given the importance of adaptivity of ACM systems, it is fitting that we delve a little deeper into the essential properties and considerations for adaptive systems. This will be one of the key topics we will discuss in this chapter, and our expectation is that such a discussion will strengthen our grasp of the fundamentals about designing ACM solutions. Additionally, in this chapter, we will take up short discussions on a few other topics related to either the concept or the implementation of ACM. In the literature, there has been a fair amount of discussion around different types of case management solutions-we will compare and contrast ACM, dynamic case management (DCM) and production case management (PCM). Since traditional BPM is another dominant way of designing and managing business activities, we will extend the comments we have already made regarding the differences and similarities between BPM and ACM paradigms.
