How to Make Strategic Choices in Uncertain Conditions

Leaders must get comfortable with the discomfort that comes from the inherent uncertainty of strategic decision-making. What does that take? How can they get better at navigating through fog and towards good decisions? 

By looking at the best strategy and decision-making research, we can give leaders two pieces of advice:

1. Balance comfort and discomfort to make the best possible decision at the time; and
2. Give people clarity even when you can’t give them certainty.

Enacting these two pieces of advice requires leaders—and particularly CHROs—to equip organizations with new mindsets and skill sets that they may not traditionally have had. It’s important to identify these and to understand what it takes to develop them. 

Facing deep uncertainty, the most effective leaders learn to be simultaneously comfortable and uncomfortable in their decision-making. First, they need to become sufficiently comfortable to be able to simply make decisions, rather than being paralyzed by the scale of the unknowns. But they also need to be uncomfortable enough with these decisions to ensure that they are regularly challenging, testing and validating them. Such leaders remain open to changing their minds as events unfold and new data becomes available. But simultaneously, they are also confident enough to communicate their current decision in a way that spurs momentum and motivates their organization to act.

How can leaders gain sufficient comfort to be able to make initial decisions—even if these are only temporary? A useful concept here is that of emergent strategy,¹ facilitated by incremental decision-making.² This asks leaders to accept that, rather than making decisions about the final shape of a strategy or proposition at the start, they will have to navigate their way towards a “best” answer over time. 

This is sometimes referred to as point-to-point navigation—a phrase attributed to Abraham Lincoln’s description of how boats sailed down the winding and often fog-bound Mississippi River during the American Civil War. Whatever its genesis, it’s a nice image that helps us see how incremental decision-making works in practice. The sailors knew in general terms where they wanted to get to (the end of the river) but could not see precisely how to get there. They navigated from their current point of the river to the next point that they could see. Once they’d reached that point, they could see further down the river—just as leaders have more data and insight once they’ve taken some action and moved further on into a process. By going from point to point, we are able to navigate the best route even when we can’t see it at the start of the journey. 

Incremental decision-making and emergent strategy are, in many ways, antithetical to the traditional view of how strategy decisions should be made. Indeed some would consider this to be too tactical an approach to even count as “strategy.” The key distinction, though, is that each stage of the incremental journey is in service of the ultimate destination, rather than being merely a reaction to events. This ultimate destination is the outcome(s) the strategy is targeting—for example, a certain market share, a certain cost-ratio or, in the case of a pandemic, keeping deaths below a certain level. By being clear about these outcome-level objectives, leaders can be strategic while embracing the inherent unpredictability of their situation. 

To help organizations, and the people within them, become more incremental and iterative in how they “do” strategy takes two important shifts in mindset. The first is that leaders need to accept that their strategy will be wrong—at least in some ways. 

The second mindset shift is that leaders must accept that they have to learn from the things that don’t go as planned—rather than merely working to fix them. This means framing problems as learning exercises, rather than merely execution exercises, and giving equal time and attention to what can be learned for next time, as is given to how to fix it this time.

One business leader demonstrates both these new mindsets in the way he leads his company’s strategic planning process. First, he always pointedly asks questions such as “What will go wrong with this new strategy?” and “What do we think won’t happen as we’re planning?” These inherently disconfirming questions force everyone involved to test and challenge their own assumptions—and to start thinking about how to mitigate the risks within them. But these questions also signal to people, however subtly, that strategies won’t go as planned and this is to be expected. He then embeds this lesson by revisiting the original assumptions after the strategy has had a chance to play out. Now the questions are: “What did we get wrong and why?” and “Given what we’ve learned, what do we plan to do differently this year?” The mindset that underpins these questions is that, because strategies will not go as planned, we ought to be getting better over time at making less inaccurate assumptions and therefore having more realistic plans. If strategy will always be wrong, let’s at least try to make it less wrong next time.

As for the new skill sets required, organizations still need smart, analytical, articulate people. They could, however, do with more who are versed in running great experiments and then putting the resulting insights into practice. A great experiment uses the least amount of time and budget to learn the most about what will work—or not. Manufacturers have been good at this for years, regularly using learning loops to get incrementally better (the Japanese concept of kaizen is a good example). Software developers increasingly take an iterative, agile approach to writing code, rather than the traditional linear, so-called “waterfall” process. But all businesses need to become more skilled at implementing learning loops—something that CHROs and learning and development teams can champion and fund. 

The other skillset missing in many organizations is the ability to operate both in the details and at a high level. This enables a leader or team to focus on getting to the next point on the river, while simultaneously knowing that the end point is what really matters. A CEO with whom I worked more than a decade ago was terrific at this. She ran one of the largest banks in India and could go from 10,000 feet (her strategy goals) down to the detail (what the latest customer complaint data told her about potential issues in the branch network) and then, critically, back up again. I call this the “laddering” skill—the ability to go up and down the ladder, from strategy to execution, while never forgetting the view from the top rung. It’s this skill that helps people understand how their businesses really work—and how a new strategy gets implemented.

But even with these new mindsets and skill sets, in times of great uncertainty leaders will still be asked for answers. This brings us to the second piece of advice.

When navigating the fog, that is, where outcomes are impossible to predict, leaders shouldn’t kid themselves, or the people they lead, that they can ever provide certainty. That sounds obvious, but it’s a sentence that leaders would still do well to internalize. However, you can—and must—give people clarity. That clarity might only be temporary—a view held until new data suggests a different approach is needed. But leaders need to be clear about what people should do in the short term, even if they can’t provide certainty about what will happen in the long term.

There’s a distinction here between issues that are complex and those that are merely ambiguous—although many organizations use these terms almost interchangeably. Ambiguous issues—where the meaning isn’t yet clear enough—can and should be analyzed until that meaning become clearer. To help this effort, leaders may need to address the reasons why ambiguity continues to exist in their organization. 

In my experience, the failure to move from ambiguity to clarity happens for three reasons. First, because getting to clarity will require leaders to choose one course of action rather than another, and leaders frequently want to hedge their position on a decision for as long as possible. Second, because making choices invariably generates some measure of conflict within the organization, and many people prefer a quiet life where conflicts are not just minimized but avoided altogether. The third reason is more basic: a failure to devote the necessary time and effort to thinking about, and properly analyzing, something that is perfectly capable of being analyzed. 

Complexity is different from mere ambiguity. Leaders need to accept that complex issues (or phenomena) can’t be understood through traditional analysis, such as spreadsheets or net present value calculations, so more of those skills won’t help. That’s because, by its very nature, a complex issue is a system: it contains within it interdependencies that produce two particular features. First, a system has long-dated causal links—that’s where the result of an action is difficult to discern because it happens too long after the action that may have caused it. For example, the full consequences of Brexit will play out decades after the referendum that prompted it. Second, a system contains within it the possibility for unintended consequences—that’s where an action that might have seemed like a good idea at the time goes on to produce unforeseen adverse effects. An example is where a seemingly smart but short-term fix to a problem produces bigger and more serious problems down the road.

As a result, complex issues require a different approach. First, leaders need to accept the impossibility of understanding a complex issue in full—at least in the short term—precisely because it is a system with features that make this impossible. But I’m not suggesting that leaders are passive here; they shouldn’t hold up their hands and think “I can’t do anything to improve my current understanding of this, so I’ll wait until somebody else makes a decision.” Rather, leaders need to respond actively by recognizing:

• I can try to understand this new phenomenon by first exploring one particular aspect of it to see what that tells me. 
• From that growing understanding, I can then start to generate more specific questions with which to investigate it further.
• I need to be checking that the questions I’m asking are the right ones.
• Gradually, through this iterative process, I will build up my understanding of this strange, new phenomena to the point where I can start collecting the right data and analyzing it in the traditional way. 

In other words, by following the process shown in Figure 1, leaders can transform a complex issue that they don’t (and can’t) understand into one that is capable of being analyzed.

To do this well, organizations must not only embrace the practice of experimentation, but also demonstrate the patience and persistence to truly understand the problem before they rush to a solution. The LEGO turn-around is a good example of how to do this. Believing that the growth of gaming meant children would no longer have the inclination or patience to play with LEGO’s famous bricks, the company had made several unsuccessful acquisitions and had failed to break into new markets. By 2004, it was close to bankruptcy. LEGO’s leaders decided they needed to properly understand the complex reasons why and how modern children played. 

They spent time studying families who were LEGO fans and seeing how these children used the bricks and what they took from the experience. “Data” here came not in the form of consumer surveys or trend analysis, but rather from direct observation of children playing and by asking parents to keep photo and video diaries. From this data, LEGO learned that children enjoyed mastering new LEGO projects and were prepared to invest time and effort to build something amazing. They also learned that parents felt nostalgia for LEGO, remembering it from their own childhoods. 

These two insights—impossible to obtain using traditional, analytical techniques—led to the “Back to the Brick” strategy. For children, LEGO started offering much more complex brick projects that took days to complete. And for the parental market, LEGO started offering brick projects such as its World Architecture range. These new insights about its consumers took time to develop (the study took six months to complete) and required different skills (they hired ethnographers to help them unearth the insights they needed). But by properly understanding the issue, LEGO found a strategy that would save the brick—and the company itself—and was able to implement it with confidence and at pace.³

This iterative process of first exploring and understanding the issue, and only then collecting data and analyzing it, takes significantly more time than many organizations think they can afford to spend on it. The process shown in Figure 1 doesn’t usually fit within the annual planning cycle that the strategy or finance department oversees. But when contrasted with the time (and money) the organization will spend fixing the consequences of mis-analyzing a complex issue—because it failed to commit the time to understand it properly before rushing to a solution—this is time well spent.

But even if leaders accept that they need to do the work in Figure 1 and that it will take more time, there’s another challenging reason it often doesn’t happen. In most organizations, there is an oversupply of certain skills and a significant undersupply of others.

The skills that are in abundance are those of the smart, analytical people with MBAs and predominantly quantitative backgrounds. These people are much more comfortable with a problem when they can dive straight into analyzing it. Given the opportunity to play to their strengths, the temptation is to see all problems as capable of being analyzed, even when they are not.

The skills that are undersupplied in most organizations are those of smart, curious people with backgrounds in the social sciences—subjects such as sociology and anthropology. These people learn to be comfortable with problems that first require exploration. And, critically, they have the skills to complete this essential step before they attempt any analysis.

My MIT colleague Professor John van Maanen describes ethnographers as people who “live with and live like” the people or phenomenon they are studying. As the LEGO executives did, ethnographers enter a new, often very different world (in LEGO’s case, the world of children at play) without preconceptions about how it works or what it means. Instead, they observe, notice, record and play back—all, initially at least, without interpreting what they see. These skills—very different from those acquired on a typical MBA program—are what enable people to gradually understand enough about a new world to know what questions they ought to be asking about it. Based on this new understanding, they can then decide what data to collect. At that point, they have transformed the problem into one that can safely be analyzed in the more traditional way.

To embrace a problem as complex, people—and especially leaders—need a mindset that admits the full extent of their ignorance, i.e., that not only do they not know the answer (yet) but they also aren’t even sure that they are posing the right question(s). That can make them, and others in the organization, profoundly uncomfortable. It requires leaders to communicate even more than usual about how they are approaching the problem and what progress is being made. Humility in the face of uncertainty, balanced with confidence in their ability to navigate it, requires leaders of high capability and low ego. 

Another critical mindset shift is to accept, and honestly believe, that there will be multiple possible answers and that the one chosen will be the product of a contested, political and therefore suboptimal process. In a complex situation, framing the right questions and forming the right hypotheses is often a fight. The decisions produced by that fight will be poor unless there is a decent level of psychological safety to enable open and rigorous debate.

The skill sets needed to deal with complex issues are those of the social scientist and ethnographer. Hiring, and then valuing, these people is a tall order, especially when the vast majority of problems a business will face are not complex and so require only traditional management and analytical skills to solve them. Which is why many leaders, rather than hiring such people, turn to specialist consultancies for the skills needed to solve complex issues. 

But this means leaders must have sufficient skill and experience to judge when something is complex—rather than the more normal, analyzable problem that can be solved using their existing internal talent. 

HR executives can help leaders and organizations build these sometimes-uncomfortable mindsets and skill sets. Critically, they can also make sure these are incorporated into their succession plans for future leaders.

In times of deep uncertainty, there are two things leaders need to get right. First, they need to balance comfort and discomfort in making their decisions. Second, they need to give people clarity even when they can’t give them certainty. That clarity might only be temporary—a view held until new data suggests a different approach. But defeating ambiguity while embracing complexity is an essential executive ability today. By doing this in a disciplined way, leadership is possible even when the fog seems at its thickest.

Elsbeth Johnson, Ph.D., is a Senior Lecturer at MIT’s Sloan School of Management and the Founder of SystemShift. She is the author of Step Up, Step Back: How to Really Deliver Strategic Change in Your Organization (2020, Bloomsbury). She can be reached on LinkedIn.  

References

1 Minzberg, H., Ahlstrand, B and Lampel, J., 2008, “Strategy Safari,” FT Publishing International.

2 Lindblom, C. E. 1959, “The Science of Muddling Through” Public Administration Review, 19, 79–88.

3 For more on this and other examples of using ethnography to inform strategy, see Madsbjerg and Rasmussen, 2014, “The Moment of Clarity,” HBS Press.