Enterprise Agility in Today's Era of Complexity

Enterprise Agility in Today's Era of Complexity

Rama P. Varanasi
DOI: 10.4018/978-1-5225-3906-3.ch001
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Abstract

This chapter delves into some of the facets surrounding complexity and determining solutions for a globalized future, both in the context of the fourth industrial revolution and changing socio-economic dynamics where humanity has been witness to more shifts in a decade than in the previous four centuries. It has therefore come to be an era where the only certainty seems to be constant uncertainty. The two principal entities standing at the forefront of such uncertainty are governments and corporations. The author addresses key facets influencing complexity and agility in corporations.
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Background

For two decades now, the world has seen numerous shifts – transformational in nature and fundamentally game-changing in their impacts. Most such shifts have been possible thanks to significant progresses made in the fields of Science, Engineering, Medicine, and Technology. Sub-disciplines like Material Sciences, Nanotechnology, Biosciences, organ farms, laboratory-grown meat, gene sequencing, gesture-based computing, machine learning and others contend for mind-space with human trends around increased isolation, instant gratification, reduced attention spans, pastism, rising rage, contextual deficit, and related aspects. Enterprises built around traditional command-and-control structures have for long endeavored at creating value, for themselves - most visibly in the form of shareholder value - and for customers - mostly in the form of competitiveness and comparative distinctiveness. Early years of this century resulted in aggressive adoption of capitalist endeavors manifested in corporations, ably supported by forward-looking policy making governments.

Times have now changed dramatically. Organizational structures have moved from owned-and-operated models to collaborative partnering. Such dramatic shifts have resulted in added uncertainty, as traditional boundaries have been breached, management theories – for long held as holy grail – discarded, dependencies – hitherto manifested in the form of production and consumption (read traditional economics) – have changed form distinctly. Models defined traditionally within the context of the “Employer-Employee-Customer” triad are no longer seen as useful or sustainable. Replacement models have delivered upon unfulfilled promises, while adding new layers to existing models. It is highly appropriate to quote observations made by Jared Weiner1 recently who says, quote “economies do not replace each other with each disruptive transition. They layer on top of each other. Hence the old remains in the system though they may be lesser in their impacts” unquote. Panning the globe one can clearly stand witness to a variety of transitions, from democracies to theocracies, capitalist to managed, family-run to crony models, all vying to make sense of emerging trends that do not seem to have any historical precedent. Contending with such uncertain futures is not only difficult, but scary at times. The former is influenced by shifting boundary conditions, while the latter is compounded by conflicting views on the future one wants to be a part of.

It therefore becomes pertinent to understand the root causes for such shifts in behavior, and marketplace expectations if one has to put a handle on understanding and deciphering complexity. Going back to the beginning of the industrial age, Nickolai Kondratiev2 articulated six major shifts the world has been witness to, as in Figure 1.

Figure 1.

Kondratiev waves

978-1-5225-3906-3.ch001.f01

It is pertinent to note that while economists like to describe various shifts in the world as a function of six distinct trends, broader consensus emerging in the past two years has resulted in usage of the term Industrial Revolution, to describe these very shifts. The author believes that the terms used to describe these shifts are unimportant. What is relevant is to appreciate some key outcomes emanating from each shift. Distinctively, a few of these outcomes are:

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