نقشه های راهبردی شناختی فازی(نامشخص) درارزیابی عملکرد فرآیند تجاری

This paper elaborates on the application of Fuzzy Cognitive Maps (FCMs) in strategy maps (SMs). The limitations of the Balanced Scorecards (BSCs) and SMs are first discussed and analyzed. The need for simulated scenario based SMs is discussed and the use of FCMs as one of the best alternatives is presented. A software tool for the development, simulation and analysis of FCM based SMs is also presented. The effectiveness of the resulting software tool and FCM theory in SMs is experimented in two case studies in Banking.

Organizations are operating in a continuously changing environment. Market competition requires from management to continuously adapt their business objectives and revise strategic plans. Organizational performance measurement systems provide the linkage between strategic goals and daily operations. Traditional solely financial based performance measure systems cannot longer meet management expectations. For the last decade managers and academic researchers are focusing on frameworks, methodologies and tools that provide integrated performance measurement systems (PMSs) that analyze organizations from both financial and non-financial perspectives. The most notable example of this type of PMSs, is the Balanced Score Card (BSC) (Kaplan & Norton, 2004). It consists of four perspectives, financial perspective, customer perspective, internal process, and learning and innovation. Usually, 20 to 25 key performance indicators are allocated to each of perspective. The aim of the BSC is to link business objectives with operational objectives in a balanced way. The first version of BSC or also called First Generation of BSC has many limitations: for example it contains a too simplistic unidirectional causality mechanism, it neglects the notion of cause and effect relationships in time; and it presents high level of vagueness in linking strategic and operational goals. A big evolution for the BSC was the introduction of strategy maps (SMs) (Eccles & Pyburn, 1992). SMs focus on the causal-effect relationships even amongst measures of different perspectives and objectives, and the alignment of intangible assets. Strategy maps (SMs) represent visually relationships among the key components of an organization’s strategy (Eccles & Pyburn, 1992). We could argue that SMs describe strategy in a picture; they are powerful tools which show how value is created through cause and effect relationships. Kaplan and Norton argue that they create “the missing link between strategy formulation and strategy execution” (Kaplan & Norton, 2004). Strategy maps are particularly helpful for: • Promoting understanding and clarity of strategy. • Encouraging greater engagement and commitment to strategy. • Ensuring alignment of resources. • Identifying gaps or blind spots. • Making more effective and efficient use of resources. • Aligning remuneration with strategy – particularly in the soft areas and where objectives have a duration >12 months. A strategy map describes how an organization creates value by connecting strategic objectives in explicit cause and effect relationships. They provide an excellent snapshot of strategy and are supported by measurable objectives and initiatives. Strategy maps enable organizations to (Lawson & Desroches, 2007): • describe strategy in a single picture. • Clarify strategies and communicate them to employees. • Identify the key internal processes which drive success. • Align investments in people, technology and organizational, capital for maximum impact. • Expose gaps in strategies so that early corrective action can be taken. • Identify explicit customer value propositions. • Map the critical internal processes for creating and delivering. the value proposition • Align human resources, information technology and organization culture to internal processes. Strategy maps can be used for developing and reviewing strategy at organizational, departmental and even project level. The strategy map (Kaplan and Norton, 2000, Kaplan and Norton, 2004 and Kaplan and Norton, 2008) evolved from the four-perspective model of the balanced scorecard, adding a visual dimension which improves clarity and focus. There are five main principles behind strategy maps: • strategy balances contradictory forces. • Strategy is based on a differentiated customer value proposition. • Value is created through internal business processes. • Strategy consists of simultaneous complementary themes. • Strategic alignment determines the value of intangible assets. Strategy maps are used in many frameworks as part of their strategy and change management offerings an example of a strategy map can be seen in the picture below. The balanced scorecard (Kaplan and Norton, 2000, Kaplan and Norton, 2004 and Kaplan and Norton, 2008) is a performance management system that enables organizations to implement a business vision and strategy.

This paper presented a supplement to SMs based on FCMs. This decision aid mechanism proposes a new approach to supplementing current status analysis and objectives composition phases of typical strategy formulation projects, by supporting fuzzy cognitive modeling and “intelligent” reasoning of the anticipated impact of strategic change initiatives to business performance. The mechanism utilizes the fuzzy causal characteristics of FCMs as a new modeling technique to develop a causal representation of dynamic SM principles in order to generate a hierarchical network of linked performance indicators based on critical success factors. This paper discussed the FCM approach in putting realistic and measurable objectives in strategic planning projects and presented sample maps with causal relationships. Preliminary experiments indicate that the mechanism does not provide fundamentally different estimates than expert decisions. Moreover, the decomposition of financial metrics into their constituent parts supported reasoning of the strategic performance roadmap. The main purpose of the mechanism is to drive strategic change activities rather than limit itself to qualitative simulations. Moreover, the proposed mechanism should not be seen as a “one-off” decision aid. It should be a means for setting a course for continuous improvement (Langbert & Friedman, 2002). Future research will focus on conducting further real life experiments to test and promote the usability of the tool, but also to identify potential pitfalls. Furthermore, future research will focus on the automatic determination of appropriate fuzzy sets (e.g. utilizing pattern recognition, mass assignments, empirical data, etc) for the representation of linguistic variables to suit each particular project domain. Finally, further research will focus on implementing backward map traversal, a form of adbuctive reasoning (Flach & Kakas, 1998). This feature offers the functionality of determining the condition(s) Cij that should hold in order to infer the desired Cj in the causal relationship View the MathML sourceCij→wjkCk. Incorporating performance integrity constraints reduces the search space and eliminates combinatory search explosion. Backward reasoning has been tested extensively in other applications and its integration in the proposed methodology framework may prove beneficiary.