As we approach the end-game for BREXIT (or is it?), politicians lament the lack of contingency planning in UK businesses ("Boris's Game of Chicken" Economist 3 August 2019). However much they may urge companies to get on with it, the truth is that indecision is a complex phenomena. Businesses operate in a volatile, uncertain, complex and ambiguous (VUCA) environment which makes classic strategic planning difficult and often pointless. In this article I strip away the confusion surrounding planning paralysis and explain the elements of indecision, and explain how Decision Science helps.
The Roots of Indecision
Halfway Up The Economist (3rd Aug 19) points out that many businesses are suffering from "Duke of York" syndrome. Having written contingency plans for a no-deal Brexit in Spring; having ordered and stored extra inventory and warehousing, they are reluctant to go through the same costly process, especially when the chances of a no-deal Brexit are "a million to one" (Boris Johnson quoted in the same periodical). Having marched to the top and back again, the King's Men are hill-fatigued and who can blame them? Many business plans are reliant on knowing when things will happen. In the VUCA business environment many plans may have nailed the what but there is often less certainty about when. Contingency plans are meant to be taken off the shelf when needed but the ups and downs of Brexit have created a number of false alarms. The problem with false alarms is that they make real alarms less credible. Many business decisions are time-critical because resources vary in cost over time. Somehow businesses need to know exactly when to initiate their plans. This is not easy but agile decision making helps, having multiple courses of action really helps. Decision Science links data to decision makers allowing flexible contingency planning. That also means making contingency plans a part of living strategy and not stored behind glass.
Data Bound One of the biggest problems in strategic decision making today is the sheer volume of information. Actually increased data should lead to better decisions, so how is too much data such a prevalent problem in the 21st Century? The reason so many decision makers are data bound is because they are using an outmoded leadership model (see http://bit.ly/dec1isionscience). Traditional approaches to leadership view leaders as heroic figures who must know everything and then make decisions. In the age of data, leaders who attempt this will soon find themselves paralysed and unable to make decisions. There are two solutions. The first is to adopt a networked decision structure, delegating decisions throughout the organisation and taking the load of high level executives. Another strategy is optimise the Information Supply Chain to ensure the right data is in the right place at the right time, and the irrelevant data is filtered out. Needless to say, both strategies should work together. This is also not easy. Many firms have layers of technology overlapping but not communicating with each other. Often numerous data bases exist in different areas of an organisation dating back 20 or 30 years and procured to solve a specific problem rather than to integrate with existing systems. As a Decision Scientist I know if I see employees exporting data via Excel and manually entering the same data in a different system, I have my work cut out. Such a company has probably not spent as much time on its Information Supply Chain as its materiel supply chain.
Weaponised Information If BREXIT has taught us nothing else, it is the way information can be subtly twisted to serve a specific agenda. The same can be said for any number of recent political events and on all sides. From a decision making point of view, this makes it very difficult to know what information to trust. On a strategic level companies can be badly affected by this as the current inertia over BREXIT demonstrates. Nobody knows what will happen, not because analysis hasn't been conducted, but because there is so much conflicting analysis based on political agendas. Within companies too, employees often have a narrative of 'how we do things around here' or why certain behaviours and cultures are the best. They are often untrue and they constrain decision making. For this, I have developed the SWAN leadership model. SWAN stands for Start With Another Narrative and it encourages leaders to challenge the fallacious narratives which abound in any workplace. The model is more complicated than that, but at the heart of it, it's about looking for alternative solutions to business problems.
Integration of information Decision Science is about getting the right data to the right people at the right time. Data is the new oil but like crude oil, data must be refined and pumped to where it is needed; otherwise it is worthless. A common problem I find is that technology is bought in with little thought about how to integrate it with existing information systems. Like a shoddy painter, new software is loaded on old systems like layers of paint with no preparation. I made the point earlier that data can be seen as an Information Supply Chain, if lean principles are applied with the same fervour as many companies apply to their logistics, this supply chain will be fully integrated. The company will be ready for data operations and enjoy significant competitive advantage.
The planning paradox The planning paradox occurs when outmoded strategy tools are applied to business plans. Most of the oft quoted strategy tools in business and taught in many business schools were devised in the mid to late 20th Century. This was a period of relative calm where future scenarios were more predictable than today. Planning tools emphasised the need to collect as much data as possible and then apply specific methods to devise a grand strategy. The problem with this approach is that the decisions are made when least is known; this is the planning paradox. 21st Century business environments are simply too unpredictable to sustain this approach. Many strategy experts now advocate a more exploratory approach. This approach takes full advantage of modern data and communication systems to hop from strategy to strategy as new information becomes available. In short, successful firms have switched from the efficiency of the Industrial Age to the agility of the information Age.
It is often said that the world has never experienced the current pace of change. I am not sure if that is actually true, the early Greek philosopher, Heraclitus was so impressed by the pace of change in the Bronze Age that he stated change was the only constant and that everything is consumed by it. Sound familiar? It is more a question of what type of change. For Heraclitus the iron hoe was a game-changer. In the 21st Century, data is the game-changer recently taking over from technology as the most influential force in society. The old heroic leadership model where decisions are made by one or few people is leading to the paralysis and indecision. Daunted by the sheer volume of information, not knowing who to believe the Industrial Age leader can only look blankly at the screen. Decision Science and Data Science are very necessary tools for the modern business to become data savvy and agile.