Strategic thinking in the past few decades has been largely driven by tools and paradigms from economics and its sub disciplines. Such an approach has facilitated acute understanding of positional power in terms of developing and retaining competitive advantage and the competencies required to be flexible and create new products and services for firms and organisations. However, strategy development and execution has undergone significant change in the past decade-and-a-half as organisations are subject to multiple influences not only from within their sectors of business, but also from converging technology trends, rapidly changing customer demands, increasing state actions in terms of deregulation, stake sale, privatisation to name a few, and increasing effect of a connected globalised economy. Thus the earlier understanding based on creating positional power to be profitable is no longer tenable and businesses need to seek out newer approaches for survival, growth and profitability.
Newer approaches to achieve competitive advantage would rely on data, use nonlinear models and be inter-disciplinary in nature to try and comprehend the large data that could be available on customer trends, economic indicators, global trade swings, international policy decision impacts, local regulatory issues and so on. This would lead the very nature of analysis to look for deep-seated patterns from seemingly unconnected events, ferret out influences from deep mining of data, and integrate these insights into tangible indices. These indices would then constitute a dashboard for use by senior managers to navigate through uncertain business landscape. This is the expectation from complexity science.
How could businesses benefit from complexity science?
Businesses could benefit in three broad ways by harnessing the power of complexity science.
- Derive deep insights from large datasets: Advanced data-mining techniques could be used to develop deep insights from customers, suppliers, macro-economic indicators, industry factors, country issues and others. The continuous stream of data could be mined to understand the usage pattern, component behaviour under different conditions of usage and other aspects one may be interested to know for preventive maintenance and future product innovation.
- Map influences that could unravel uncertainty: Event flow mapping approaches could be used to map the key issues within and without organisations to arrive at possible intervention points for them to move to a high growth trajectory.
- Develop organisational indices: The insights from data flow, as in the case of the first approach, and insights from the events flow as in the case of the second approach could be combined to develop multi-dimensional indices for use at the corporate level. The different dimensions could be economic, financial, product related etc. obtained from data flow and political, environmental, regulatory and local issues from events flow.