Structured approach for strategic planning in complex systems: methodology and company-based case study

Abstract

Recently the trend of studying large-scale companies and other social and political systems as complex systems has been growing. This approach comes from the difficulty of understanding completely the interactions between subsystems that together form the larger system. Nevertheless, this approach still lacks the capability of developing long-term strategies for the unified system, accounting simultaneously for all of its components. The decomposition itself, although indispensable, is only one of the stages. It may fall short in case it does not lead to specific plans of action (PA), focused on long-term goals and based on short and mediumterm actions suitable for each subsystem. This research proposes a methodology specifically focused on the generation of strategic PA, emphasizing the relevance of having a structured timeframe classification of the actions. Furthermore, the methodology is based on an explicit recognition that long-term actions are strategic and must insure that the complex system is pushed towards a predefined goal in a constructive manner. The proposed methodology complies with Intelligence Gathering, Design and Choice phases of the Simon’s Model of Decision making (Simon, 1960), and has been applied to an airline company in order to enable it to respond to the recent sudden changes in economic conditions. The information gathered on the airline business and the company itself allowed the decomposition of the company into several subsystems and the identification of the interactions among them, as well as the creation of a set of possible actions. The identified actions were clustered into PA. During the generation of PA, the alignment between these and the strategic goals was always ensured. The structuring of the different PAs took into account the actions’ timeframe classification, which made each upcoming action to be enhanced by its preceding action(s). Moreover, each PA was characterized by the properties (-ilities) it would bring to the system. An evaluation of the resulting PA was performed regarding the different stakeholders. The analysis tools were inspired on Saaty’s AHP analysis and flag model, both accounting for PESTE parameters. A sensitivity analysis was performed to ensure that the PA adopted was the most suited for likely scenarios. Yet, the selection of a PA does not restrict the actions to be adopted. In fact, due to the clear mapping of distinct actions allowed by the methodology; the decision maker can achieve the long-term goal through a dynamic matching between different timeframe actions and economic environment changes. By adopting this methodology the system is inherently gifted with the property of agility. In this case study, the airline was identified as a complex system and after an assessment of the company and the airline business it was possible to define 32 opportunities that can be turned into actions. These actions were formulated under the goal of improving performance indicators of the company. The proposed methodology reached a PA that will bestow the system with the properties of scalability and adaptability. This means that the airline will be more capable to adapt to the customer needs and will also be able to increase its market share. Implementing is not restricted only to the actions of the selected PA. Depending on the economy behavior (amongst other externalities), some actions that were studied can be implemented to improve the performance of this PA. The actions to be adopted are based on a periodical assessment of the PA implementation and company’s environment.