Dealing with uncertainty Dealing with uncertainty

With the right levels of analysis in place, executives can strengthen their foresight and business decision making skills.

Most of us 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 all do wish that we have the gift and wisdom of foresight.

For those that are not familiar with the American idiom hindsight is 20/20, it means that when you look back at something that happened in the past, it is much easier to see how something could have been done differently, or how a wrong decision could have been prevented because we have more of the facts after the outcome of the decision, therefore one has a clearer 20/20 vision of the event.

So, how do we 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 available to managers to aid in their decision making. However, any discussion of strategy or uncertainties always brings to mind for me, an excellent McKinsey Quarterly article that I read about a decade or so ago on levels and types of uncertainty. The approach and conclusions drawn by the author/s of this article has had a profound influence the way I look at uncertainty in my personal or professional life.

In essence, the article stated that most strategically relevant information fell into two categories. Often it is possible to identify clear trends like demographics and macro economic data. With the right level of due diligence and analysis, most remaining unknown factors like technology risks, market risks, financial risks and other risks associated with supply and demand side factors  are among many others that could be determined through structured analysis. The uncertainty that remains after the best possible analysis has been undertaken, is what they called 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 types of uncertaincies are divided into four levels.

Level one: Outcome is known

In level one uncertainty the possible outcome is known, so no multi scenario analysis is required. However you have to be sure that decision making required on a residual uncertainty is really a level one.

Due to the fast moving pace of the telecommunications industry, I personally feel that that most business decisions or strategies in the fast moving telecommunications industry are facing uncertainties beyond level one. However most telecommunications managers limit the strategic analysis to level one uncertainty and often draw wrong conclusions.

Level two: Alternative outcomes

In  a level two uncertainty, the authors described it as “as one of a few discrete scenarios”. In essence, any analysis cannot predict which outcomes will happen but rather would require us to assign probabilities based on the best information, tools and knowledge available.

A classic level two situation is when a telecoms operator decides whether to invest in a new technology which usually costs them billions of dollars. These are choices that were grappled by the telecom players in most developed and developing markets as to whether to invest in upgrading from 2G to 3G or even now whether to invest in 4G. The telecom players are normally forced to make the high stake investments, even if the previous generation technology investments have not generated the desired returns. The value of this type of established (standardised) new technology investments are dependent on their same 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 minimise their opportunity costs of 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: Multiple possible outcomes

In level three, there are a range of possible outcomes that can be identified. There are very few variables to range the multitude of options.

Examples of level three uncertainties are when a telecom player had to decide on the type of technology to enhance performance and speed of the network. For example, many telecom operators are deciding whether and when to invest in 4G technologies and which technology to choose from (HSPA+,  LTE or wait for other technological advancements happening in the industry). This is a difficult decision today, as it entails billions of dollars of investments at a time when no reasonable returns have been generated from prior upgrades in the network. Further, all this investment decisions have to be made in an era of rapid price and margin erosion.

Another example is when a telecom operator in a small market have to make a choice as to,  if and when to align with Mobile Virtual Network Operators (MVNOs). 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 cannibalisation 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. As you will have noted, this will require a detailed, structured and multi scenario analysis to address this complex and often an arduous task to predict the outcome of this type of uncertainties.

Any scenario development should facilitate easy decision making. Therefore, it is recommended that the number of scenarios be limited and the scenarios should have unique implications and should not overlap. At the very least, developing a set of scenarios should at the least enable managers to assess the wisdom of their existing or planned status quo strategies.

Level four : Outcome is unpredictable

A level four uncertainty is truly ambiguous. It is hard to predict the outcomes. These uncertainties are rare in most industries, but exist in the fast moving telecommunications industry.

For example, if you are in the telecommunications industry, it behooves upon the management to have a structured and purposeful strategy to address the emergence of the multiple VOIP players like Skype, Rebtel and other new age companies like Google, Facebook and other networks having millions of customers. No amount of analysis could have actually predicted in the early part of 2002 or 2003, the outcome of how and when they will wreck the telecom player’s voice business.Today, the outcomes seem a little too obvious. Yes, hindsight is indeed 20/20.

Shape or be shaped

Assigning informed and reasonable probabilities will help them to develop investment and pricing and product portfolio rebalancing strategies that are phased to ensure that they don’t end up being the proverbial dumb pipe.

Addressing level four uncertainties requires a player to shape or be shaped, be prepared to adapt and or reserve the right to play. The choice of strategies to address level four uncertainties are dependent on the competitive leverage, risk averseness of the management, financial strength and a multitude of other factors like investor appetite, organisational capability, innovation orientation and others.

Foresight framework

As you can see, the range of the levels of uncertainty can range from a broad spectrum of one of a two possible outcomes to a wholly unknown and ambiguous set of variables.

Knowing the levels of uncertainty, thinking purposefully and in a structured way the multiple scenarios and probabilities and the strategies to address the uncertainties is essential for any manager.

Understanding and addressing the levels of uncertainty is the only way to avoid Monday morning quarter backing (critiquing the situation after the fact). The deliberate framework and tool described here can be applied to both your professional and personal life.


John Lincoln has over 20 years telecommunications experience in the USA, Japan, Europe, India, Dubai, Malaysia, Latin America and various other countries. He has extensive senior expertise in international telecommunications sales, marketing, business development and customer service delivery. John also has executive experience with general management, marketing, P&L, product development and revenue management responsibilities in both consumer and enterprise segments for both the fixed and mobile sectors. In addition John has an impressive operational and management portfolio of

John Lincoln

established proven expertise in incremental business value creation and management of large multi-cultural teams in Vodafone Global in the UK, Japan Telecom in Tokyo, AirTouch and Pacific Bell (now AT&T) in San Francisco and Tokyo, Airtel in Delhi and other telecom and technology companies. Additionally he has extensive large scale business development, M&A and operational project experience across the USA, Europe, Asia and Latin America. John has an MBA and MS in Telecommunications from the Golden Gate University in San Francisco, California, USA. You can find John’s personal blog at com. He can be contacted via:, Twitter: @lincolnjc.

At present John is in the final stages of finishing a book which explores how businesses can grow and achieve sustainability and which is scheduled for publication by February 2012.

Rushika Bhatia Editor

Rushika Bhatia is one of the region’s leading commentators on business and current affairs issues. She is the Editor of SME Advisor magazine - the flagship title of CPI Business. She is passionate about infographics – with special emphasis on data, research and statistics. Rushika has a Bachelor’s Degree from Indiana University, USA and is also CIMA qualified.

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