STATERGIC AND OPERATIONAL DECISION MAKING
The performance of contracting any firm or an organization is firmly bounded to the quality of operational decisions at the strategic level. Business intelligence (BI) software is applied at three different levels in the enterprise: strategic, tactical and operational. At the strategic level, BI provides performance metrics to management and executives, often in conjunction with a formal management methodology such as Balanced Scorecard or Six Sigma. Strategic business intelligence, one of the latest crazes, is generally called performance management (PM). Depending upon which analyst firm you subscribe to, PM might be preceded by a C for corporate performance management, an E for enterprise performance management or a B for business performance management (not to be confused with BPM, the acronym for business process management).
WHAT IS STRATEGIC AND OPERATIONAL DECISION MAKING
Modern organisations operate in an increasingly complex environment and the magnitude of the consequences of decisions at the strategic level demands high quality responses from the management. The ever-changing and turbulent internal and external environments of the organisation demands extreme sensitivity from the management in their reactions towards change. This often requires rapid response and the consequence of one course of action could be dramatically different from an alternative course of action. Strategic decisions are a reflection of the attitude, values and expectations of the decision-makers at the top level. They have a long term effect on the direction and future activity of the organisation, and have resource implications, affecting decisions at the lower levels and initiating a wave of other, often lesser decisions (Hickson et al. 1986). The uncertainties and complexities of strategic decisions direct the decision makers to reduce the infinitely large problem into a manageable one. This conversion to a manageable model of reality inherently involves a great number of assumptions, many of which, rely on the judgement of the decision maker. But the scale of the complexity and variety of variables surrounding the decision is such that some of the assumptions are ill-defined and possibly wrong. To combat these problems the managers categorise the uncertain decisions into a number of criteria: Laplace, insufficient reason to believe otherwise; Minimax, making the best out of worst possible conditions; Maximax, the best out of the best alternatives; Savage, the best of the regrets for not taking the right actions; and Hurwicz, giving a range of attitudes from optimistic to most pessimistic (Turban 1993). The choice of the approach is linked to decision-maker’s conservatism. The strategic decisions such as expansion, consolidation, diversification, revision, etc., require an extensive analysis of numerous issues independently and in combination. The industry has been somewhat conservative, resisting to explore and exploit a range of available techniques and apply them at higher decision making levels. This is partly due to management’s reluctance to recognise the need for scientific management. Also, there is a lack of appreciation as to the extent to which the application of management science can be useful. This often leads to a poor allocation of resources to areas of management science, hence, the technical capabilities to implement the science does not develop adequately. Where applied, the management science techniques are poorly located within the organisation. Their use is often scattered and undefined rather than being integrated as part of organisation's structure and culture. Indeed, there have been formidable forces of opposition to the management science activity within many organisations (Forgionne, 1983). “The Five Ps for Strategy: plan, ploy, pattern, position and perspective. * Strategy is a plan or a guideline to deal with a situation. Implicit in...
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