Businesses have become remarkably good at planning and then executing plans across complex, global supply chains. Similarly, many governments increasingly excel at setting boldly progressive policies and executing large, ambitious programmes. The problem for both is, the world is shifting under their feet move in the trajectory of Globalisation 4.0: fragmented global order and escalated trade conflicts; Expanded individual (consumer) power; the Fourth Industrial Revolution.
No policy domain is immune to this fundamental shift. When setting economic policy, government leaders must account for the startlingly unpredictable ways technology can change how countries compete – for example, by making it possible to competitively produce many products anywhere in the world.
So, how can government practically reconcile its long-term mandate with the near-term dynamism of the operating environment? Here are some suggestions shared though the World Economic Forum.
Adaptive government is a fundamental shift of intent, as governments recognize that their core competency in large-scale planning and execution is no longer sufficient. The established “plan and execute” approach must be aggressively augmented with new “sense and respond” capabilities, which were described in a business context by Erik Brynjolfsson and Andrew McAfee in Harvard Business Review.
The goal is to institutionalize agility, by making government an instrument of adaptation, as well as a shaper and implementer of policies and plans.
Consequently, two foundational elements of these new government operating models are adaptive systems and adaptive people.
Adaptive systems – the capability to recognise change as it emerges, respond to it rapidly, and iteratively learn from each response. Technology will be a key enabler, opening a path to more adaptive government systems.
The adaptive systems driving government action capitalize on a data-saturated environment to capture real-time insight into how a given strategy or policy is actually performing. Applying these capabilities, governments can engage in iterative policy experimentation, learning and refinement within greatly accelerated cycles.
Economic ecosystems are another prime example of highly adaptive systems. Many countries will find it difficult, if not impossible, to cultivate all the capabilities required to effectively adapt to their rapidly changing environment while working in isolation. Hence, bringing together the diverse capabilities and expertise required to address increasingly complex challenges is the way to go.
Throughout the world, in fact, the high-tech industry, higher education institutions and venture capitalists tend to recognize their interdependence, and so form strong communities of self-interest which are, in essence, ecosystems that foster the healthy ‘coo-petition’ of ideas and solutions.
By emulating such precedents, governments can demonstrate that collaboration in ecosystems is a requirement of enhanced competitiveness, no longer merely an alternative.
Adaptive people – the people who execute policy must make varied, nuanced, and consequential choices, quickly, in response to rapidly changing conditions.
The solution is to distribute decision making further out from the traditional centres of control, while rapidly building requisite new skills and behaviours, and guiding and augmenting human decision making with new technologies, processes, rules, and analytics.
The most successful examples of adaptive government will make full and effective use of virtual and augmented reality based micro-learning, gamified learning systems, and artificial intelligence to enable personnel to execute their job in ways that benefit from having the necessary data to adapt in real time – just as modern GPS systems warn drivers of obstacles along their planned route and offer alternatives.
In sum, adaptive systems combined with people capable and empowered to adapt will enable governments to sense when course correction is required and drive informed, effective responses to ongoing short-term disruption.