Organizations today face increasing pressures to integrate their processes across disparate divisions and functional units, in order to remove inefficiencies as well as to enhance manageability. Process integration involves two major types of changes to process structure: (1) synthesizing processes from separate but interdependent subprocesses, and (2) decomposing aggregate processes into distinct subprocesses that are more manageable. We present an approach to facilitate this type of synthesis and decomposition through formal analysis of process structure using a mathematical structure called a metagraph.
Agile manufacturing, fast-response micromarketing, and the rise of the virtual organization have led managers to focus on cross-functional business processes that link various divisions and organizations. These processes may be realized as one or more workflows, each of which is an instantiation of a process under certain conditions. Because an ability to adapt processes to workflow conditions is essential for organizational responsiveness, identifying and analyzing significant workflows is an important activity for managers, organization designers, and information systems specialists. A variety of software systems have been developed to aid in the structuring and implementation of workflow systems, but they are mostly visualization tools with few analytical capabilities. For example, they do not allow their users to easily determine which information elements are needed to compute other information elements, whether certain tasks depend on other tasks, and how resource availability affects information and tasks. Analyses of this type can be performed by inspection, but this gives rise to the possibility of error, especially in large systems. In this paper, we show how a mathematical construct called a metagraph can be used to represent workflows, so that such questions can be addressed through formal operations, leading to more effective design of organizational processes.
The availability of a large and diverse collection of stored modules such as data relations and decision models is a desirable feature in a decision support system (DSS). however. it is usually infeasible to design a DSS in which every problem instance can he solved using a single module. Instead, it may he necessary to combine several stored modules into an integrated model that is sufficient to solve the given problem. We show that modules such as data files and decision models in a DSS can be usefully represented by a metagraph, a graph-theoretic construct that captures relationships between pairs of sets of elements. In addition to the visualization benefits that graphical representation oilers, we show that many useful questions faced by the designers and users of DSS can he addressed by exploiting analytical properties of metagraphs. In particular. we show that the process of model integration can he significantly facilitated by exploiting certain connectivity propel-ties in metagraphs.