Understanding McKinsey’s ‘residual uncertainty’ theory and applying it in real life
Business owners, investors and managers can be faced with a multitude of options and choices and many of us will have made major or minor decisions at some point in our business or personal life that we have regretted later.
Be it an investment choice, a major purchase, a hiring choice, a major price cut, a key strategic investment or other daily business or personal decisions or strategies, we will all from time to time with that we have the gift and wisdom of foresight.
In the US it’s referred to as 20/20 hindsight. The notion is that by looking back to the past (hindsight), we can see what and how something went wrong – and hopefully learn from that experience and understand how to tackle the situation better next time. In the same way, that perfect vision is 20/20, with 20/20 hindsight we are able to see perfectly what should have been done to produce the best outcome.
So how does this help us deal with uncertainty in the business world?
Most business schools teach some level of managerial decision-making, as well as how to use the various tools and frameworks that aid in decision making. On a personal level, any discussion of strategy or uncertainties always brings to mind an excellent McKinsey Quarterly article of a decade or so ago that dealt with different levels and types of uncertainty. This article had a profound influence on the way I look at uncertainty in my personal or professional life.
In essence, the article stated that most strategically relevant information falls into one of two categories of structured and residual factors.
- Often it is possible to identify clear trends like demographics and macroeconomic data. Further, with the right level of due diligence and analysis, most remaining unknown factors could be determined through structured analysis. These include the likes of technology risks, market risks, financial risks and other risks like supply and demand-side factors such as competitor responses, customer adoption rates including potential elasticity to price reduction, and financing coverage capability from cash flows generated.
- The uncertainty that remains after the best possible analysis has been undertaken, is what McKinsey calls residual uncertainty. Examples of this include the outcome of a legal suit, outcomes of regulatory changes, or the performance attributes of a nascent technology that has not been fully deployed or adopted, or one that is still under development. These residual uncertainties can be classified into four levels.
The uncertainty that remains after the best possible analysis has been undertaken, is what McKinsey calls residual uncertainty.”john lincoln, author
Level 1 uncertainty – Easy choices
In level 1 uncertainty the possible outcome is known, so no multi-scenario analysis is required. But we must be sure that decision-making required on a residual uncertainty is really a level one uncertainty. In the telecommunications industry, for instance, most business decisions or strategies are facing uncertainties beyond level 1 simply because of the fast pace of change in that sector. By limiting their strategic analysis to
level 1 uncertainty, telecommunications managers are therefore in danger of drawing the wrong conclusions.
Level 2 uncertainty – Multiple choices and alternative outcomes
In level 2 uncertainty, we can expect one of a few discrete scenarios. In essence it accepts that any analysis cannot predict absolute outcomes, and requires us to assign probabilities of alternative outcomes based on the best information, tools and knowledge available.
A classic level 2 situation is currently playing out in several telecom sectors as operators decide on how best to invest in the upgrades from 2G to full 3G and then onto 4G. In this scenario, telecom players are being forced to make the high stake multi-billion investments, even when the previous generation technologies have not generated the desired returns. The value of this type of investments is partly dependent on their market competitors’ investment strategies, which cannot yet be observed or predicted.
If the first mover invests in a higher performance technology, others in the market will be forced to invest to minimize their opportunity costs or face a high probability of customer churn and rapid per unit revenue degradation.
The possible outcomes and moves of the competitor are discrete and clear – Will they invest, yes or no, and if yes, when? The best strategy depends on which one does, and when it happens.
Level three – Array of choices
In level 3, there are a range of possible outcomes that can be identified, with very few variables. A good example of a level 3 uncertainty is when a telecom operator in a small market has to make a choice as to, if and when to align with Mobile Virtual Network Operators (MVNOs are companies that provide mobile phone services but do not have their own spectrum and usually do not have their own network infrastructure).
The significant factors that determine this sort of strategy have multiple levels of uncertainty – ranging from the decision to align with an MVNO or not to, to the level of pricing, the cannibalization of revenue and customer issues, whether to limit the sales to a niche segment or to the broader market.
Additional considerations could include the level of costs and customer control to be transferred to the MVNO. It will require a detailed, structured and multi-scenario analysis to address this, and it will often be a complex and arduous task to predict the outcome of this type of uncertainty.
Any scenario development should facilitate easy decision making. Therefore, it is recommended that the number of scenarios is limited, should not overlap and each has unique implications. Developing a set of scenarios should at the least enable managers to assess the wisdom of their existing or planned status quo strategies.
Level 4 – True uncertainty
A level 4 uncertainty is truly ambiguous. It is hard to predict the outcomes. Level 4 uncertainties are rare in most industries but do exist in fast-moving sectors like media, ICT and the telecommunications industry where the emergence of the multiple VoIP players like Skype or Rebtel and other digital media companies like Google and Facebook are proving hugely disruptive. No amount of analysis could have actually predicted in 2002 or 2003, the outcome of how and when they will wreck the telecom player’s voice business (the real gravy for the telecoms industry and the killer app of all time). Today, the outcomes seem a little too obvious. Yes, hindsight is indeed 20/20.
Level 4 uncertainty in practise
Take a company like Vodafone. Its Western European revenues are declining. It has invested billions in 3G and next generation networks and acquired many developing market telecom players to offset the anticipated decline in revenue from its developed markets portfolio. The cash fl ow growths in these newly acquired companies are coming under heavy pressure due to the signifi cant price reductions as the operators try to boost market adoption. Additionally, all the players in the telecommunications value chain are forcing them to expend or reinvest their free cash fl ow.
The processor core and network vendors are upgrading their network equipment. Further, all it takes is an “irrational” player in any of their markets to force them to prematurely invest billions in the network.
The advent of new smartphones like the iPhone is forcing them to subsidize the handsets and the network just to retain their existing base. The MVNOs are forcing them to drop prices just to stay competitive. Multiple content players are forcing them to rethink and invest heavily in their networks and data strategy. The new media players like Skype and Google are forcing them to reduce their voice prices. The regulators are pressurizing them to reduce prices on their high-margin roaming propositions. Informed individual customers and enterprises are demanding the best deal and the lowest prices. On top of all these factors, imagine the range of new organizational capabilities required to transform the company into a nimble new age media player.
- How does the company justify the growth assumptions that have been baked into its enterprise valuation?
- How and where does it shape, adapt or reserve the right to play?
- What are the portfolio of strategies, initiatives, actions, big bet moves, options and no regret plays that Vodafone should be embarking on?
Vodafone’s management and shareholders are surely facing a level 4 uncertainty.
Shape or be shaped!
Addressing level 4 uncertainties requires a player to shape or be shaped, be prepared to adapt or reserve the right to play. The choice of strategies to address level 4 uncertainties are dependent on the extent of competitive leverage, the risk averseness of the management and its financial strength, and a multitude of other factors like investor appetite, organizational capability, innovation orientation and so on. Assigning informed and reasonable probabilities will help us develop investment and pricing plans and product portfolio rebalancing strategies, that are phased to ensure that they don’t end up being the proverbial ’dumb pipe’.
Don’t let your foresight be blind!
The range of the levels of uncertainty can stretch from a broad spectrum of one of two possible outcomes to a wholly unknown and ambiguous set of variables.
Knowing the levels of uncertainty, and being able to think purposefully and in a structured way through the multiple scenarios and probabilities and the strategies to address these uncertainties, is an essential skill for any manager.
Understanding and addressing the levels of uncertainty is the only way to avoid Monday morning quarterbacking… The methods described here can be applied to both your professional and personal life… Hindsight is 20/20. Don’t let your foresight be blind!
JohnLincoln.one –The business growth hacker