A Support System for the Strategic Scenario Process

A Support System for the Strategic Scenario Process

Hannu Kivijärvi, Markku Tuominen, Kalle Elfvengren, Kalle Piirainen, Samuli Kortelainen
Copyright: © 2008 |Pages: 15
DOI: 10.4018/978-1-59904-843-7.ch093
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In modern day business, management of uncertainty in the environment has become a vital part in building success. The increasing speed of changes in the field of business and shortening product lifecycles are being discussed right up to the point where these concepts are becoming clichés (e.g., Teece, Pisano, & Shuen, 1997; Wiggins & Ruefli, 2005). The problem of uncertain conditions boils down to the question: how can a business develop reasonable strategies for steering the company in the long run (Mintzberg, 1994)? Strategic planning and decision making in some form or another is seen as an important part of modern corporate management. Traditional techniques and tools have been criticized for being too rigid from the perspective of managing the environment (Mintzberg, 1994; Schoemaker, 1995). In many instances, the analysis that fuels the development of corporate strategies is a snapshot of the surrounding world and does not perceive possible anomalies in the development of situations. In the traditional sense, management is all about knowing the relevant decision parameters and forecasting the result of each decision. In contrast, scenario planning has gained attention as a structured method for interfacing strategic planning with the evolving operating conditions (e.g., Mintzberg, Ahlstrand, & Lampel, 1998; Walsh, 2005). Scenarios are not a single point prediction of a defined time-space in some point of future, and multiple scenarios have conventionally been used to map the borders of plausible futures (Schwartz, 1996; Schoemaker, 1995; van der Heijden, Bradfield, George, Cairns, & Wright, 2002), which aims at avoiding problems that arise if carefully conducted forecast of future business proves to be faulty.

Key Terms in this Chapter

Driver(s) of Change, Driver(s): The drivers create movement in the operational field, which can be reduced to a chain of related events. It is not assumed that a driver has one defined state, but multiple possible states in different scenarios. Thus, a driver can influence multiple events, which may or may not be inconsistent in a given set of scenarios, but according to the definition of a scenario, not in a single scenario (see: A scenario).

Cognitive Map: The map consists of nodes similar to causal map, but the relationships do not have specified strength, just the polarity is included. The relations are illustrated with arrows or connectors, which are assigned with either a plus or a minus sign to depict the polarity of the relationship (see Causal map).

A Scenario, Scenarios: Scenarios are a set of separate, logical paths of development, which lead from the present to a defined state in the future. These separate scenarios are chains of events leading from the present status quo to the defined end state during the defined time span. Furthermore, scenarios are not descriptions of a certain situation some time in the future, nor are they a simple extrapolation of past and present trends.

Groupware: Both groupware and GSS are computerized systems designed for facilitating group work. This study adopts the narrow definition of GSS as a system that is used to aid decision making in a defined situation, between certain individuals assembled for a particular task, during a specified time, and groupware as a system that is used to mediate and facilitate the workflow of a wider audience in an undisclosed timeframe (see: Group Support System).

Scenario Method, Scenario Methodology: The scenario method contains the set of assumptions, rules, and tools, including but not limited to the process outline, which govern the process of scenario planning. The scenario method describes the basic assumptions and process model, how the future is to be captured in the scenarios, and the method through which the scenarios are formed, including the recommended support systems, modeling techniques, and data sources (see: A scenario, Driver(s) of change).

Concept Map: Concept maps are built of nodes connected by connectors, which have written descriptions called linking phrases instead of polarity of strength. Concept maps can be used to describe conceptual structures and relations in them and the concept maps suit also aggregation and preservation of knowledge (see Causal map, Cognitive map).

Cluster Analysis, Clustering: Generally, cluster analysis, or clustering, comprises a wide array of mathematical methods and algorithms for grouping similar items in a sample to create classifications and hierarchies through statistical manipulation of given measures of samples from the population being clustered.

Mind Map: A mind map consists of a central concept which acts as a headline for the map and the branches that represent the aspects of the main concept. A mind map allows summarizing and decomposition of the key aspects of a complex problem or issue.

Group Support System (GSS): By definition, group support systems are a collection of applications aimed at facilitating group work and communication similar to groupware. In the general hierarchy of decision support systems (DSS), GSS is placed in the branch of communication driven DSSs. GSS implementations generally feature tools for idea generation, prioritization, commenting, and discussion, packaged into a software suite.

Causal Map: Causal maps include elements called nodes, which are allowed to have causal relationships of different strengths of positive or negative loading depicted with a number, usually in the range of from 1 (weak) to 3 (strong). The relationships of the nodes are depicted with arcs or links labeled with the assumed polarity and loading factor or strength of causality, Links with positive polarity refer to dependency (when A increases B increases proportionally to the loading factor) and negative to inverse dependency (when A increases, B decreases).

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