The article develops a conceptualization of problem solving and decision making which synthesizes a number of models and approaches in the context of multi-methodological practice to process analysis and performance management. It also emphasizes the combining of hard and soft systems methodologies and the mutual complementarity of methods and tools incorporated into and associated with these methodologies. An important part in a search for feasible and desirable changes in business systems under complexity and uncertainty is given to the problem structuring at different levels of performance management. The developed overall framework of problem solving for performance improvement is based on Soft System Dynamics Methodology and the combined applications of logico-linguistic modelling, causal analysis, petri nets, process-centric modelling, network modelling, simulation and others. A loading-unloading process at warehouse (cargo terminal) has been taken to examine the application of the framework
Keywords: PROBLEM SOLVING, PROBLEM STRUCTURING, SYSTEMS APPROACHES, MODELLING AND SIMULATION, DECISION MAKING, PROCESS, PERFORMANCE MANAGEMENT.
Human activity system is a cultural mechanism, which finds and realizes ways of supporting desired relationships and eliminating unwanted ones . Due to instability of system and its environment and diversity of changes early defined ways lost their actuality and adequacy eventually, therefore the mechanism’s cycle has to be restarted to reach the new "good mode" of performance. Rules, regulations, standards and experience are reviewed periodically to reflect new knowledge and experiences. However these problems are often considered as very complex and difficult to track. Some theories of management and system control postulate that the complexity of social and economic facilities is just perception and inference, that is the complexity of thinking, but other theories (for example, system dynamics, chaos theory and the theory of adaptive systems) assign it to explored systems .
Numerous descriptive theories have been developed to describe how decisions are mad . But the gap between descriptive and normative decision making is extensive . Practitioners and academics are calling for better decision problem structuring in order to improve the quality of the decision outcome . There are such problematic areas in business performance management as follows :
1) The uncertainty of external environment and the low adequacy of information about it and its interactions with the system.
2) The gap between goals and actual results.
3) The discrepancy between strategic and operational levels of control and lack of coordination of decision making at them.
4) Situational analysis tools are isolated and narrow focused because reflection on system’s element(s) depends on one or several points of view.
5) Delayed responses to changes.
6) The presence of red tape hampering staff’s initiatives and responsibility.
7) The local nature of measures for the improvement and optimization of the system as well as opportunistic behaviour of agents notably resistance to innovation and changes, low responsibility, consciously and unconsciously improper involvement of other agents to implement decisions.
8) The hidden knowledge.
Problem structuring involves : a search for underlying structure of the system (processes); a fixing of facts; the identification of a problem situation, making it specific and the conversion to tasks of best choice; dealing with issues; the support of managerial goals and objectives setting; the specification of nature, options, and attributes for evaluating options.
Complexity of economic objects and situation nullifies efforts to get the best model of system and the method of problem solving. Untenability of hard methods of operational research (OR) for business management is explained by such reasons as follows : fundamental differences between physical and human activity systems; variety of desired performance criteria that interferes with the definition of objective system features, metrics and indicators; complexity of business systems; static and linear nature of methods; academism of methods, i.e. weak focus on practical problems and needs.
Failures in the system, e.g. refusal to fulfil a customer order or a monthly backlog, are adverse (negative) events and have its latent period, during which there is a sequence of controversial events that is perceived as weak signals of a possible threat. Weak signals remain undetected frequently or are not taken into account or improperly interpreted. System Failure Dynamic Model classifies failures into internal, predictable external and unpredictable external types . Failures of the first type could be generally fixed in a short time while events of the last two types require much more time. In this case, system failures of the second and the third types could be mistakenly interpreted as ones of the first type so that decision-making gets less effective.
Moreover it should be noted that individual goals are often not related to organizational values, tasks and strategies in business performance management systems. Agents' needs, aims and intents are hardly recognizable. There is a lack of efficacious models, which are able to handle with qualitative features analysing business processes, system state and perspectives. Modelling and control are mostly based on the top-down approach though the up-bottom approach allows of clarifying what tools and computer-aided decision support system are useful for troubleshooting .
Phenomena complexity and uncertainty encourage multi-methodological researches for performance improvement to progress further . There are five well-known systems approaches to managing complex issues : System Dynamics (established by Jay Forrester); Viable System Model (Stafford Beer); Strategic Options Development and Analysis (Colin Eden); Soft Systems Methodology (Peter Checkland); Critical Systems Heuristics (Werner Ulrich). Critical systemic thinking and total system intervention founded on systems methodologies use a range of decision making approaches and different views of managing. They also justify choice of those that are helpful in situation when problem are identified considering the principle of complementary applying . Soft System Methodology (SSM) focuses on the structuring of problems in social and business management by experts. But in order to reduce subjectivity there are system dynamics, discrete-event modelling, graphs, operational research and other tools that need to be applied to SSM.
Soft Systems Methodology has been combined with System Dynamics by R. Rodriguez-Ulloa and A. Paucar-Caceres . This so-called Soft System Dynamics Methodology (SSDM) has 10 steps across three worlds: Real World; the Problem-Situation Oriented System Thinking World; and the Solving-Situation Oriented System Thinking World.
Any problem could be represented by the hierarchically ordered sequence of questions and issues, complemented by methodological principles and settings on the basis of knowledge, experience and value orientations, which contain prohibitions, standards and guidelines. Generally, problem field structuring is aimed at the identification of key problems that give impetus to a set of other problems and challenges. Moreover the main causes must be found among them. It’s similar to the task of identification of root causes for the sequence of events, including deviations.
Thus, root causes, factors and events-causes, changes in the internal and external environments, conflicting events (weak signals) and outcomes, state and effects and side effects are to be determined to describe the overall pattern of the problem. It is also assumed that a complex problem situation may be described by the terms of elements and flows at bottom and top levels of management.
Article’s purpose is to elaborate integrated approach to problem solving and decision making in business performance management through the combination of systems approaches according to SSDM, hard and soft OR methods that focus on problem structuring, process analysis and modelling.