In this time of frequent and intense disruption, it’s clear that organizations must be prepared to act nimbly and strategically on any unlikely scenario the future throws their way. Yet while executives have long sought a way to reliably plot the future, traditional forecasting techniques frequently come up short as leaders focus on dealing with immediate crises, fail to spot potential disruptors as they arise, and struggle with linking long-term scenarios to short-term actions.
As the Managing Director and Principal of New Markets Advisors, a boutique consulting firm specializing in innovation opportunities and capabilities, Stephen Wunker and Charlotte Desprat have deep experience in helping companies design distinctive strategies, craft creative business models, and create new ways to compete.
In today's episode of BTG Insights on Demand, Stephen and Charlotte join BTG's Jennifer Napier to discuss their recent working paper, "Navigating Uncertainty with FutureCasting," which lays out a rigorous, four-step process to help organizations better prepare for all types of uncertainty. Listen to the episode or read our lightly edited transcript of the chat below.
Hi Stephen and Charlotte, it's such a pleasure to speak with you today.
It's great to be here.
I feel like this is a perfect time for us to discuss FutureCasting as we're just in this whole new wave of uncertainty around the latest variant, and what it means for businesses who have already had to innovate and adapt so much over the last few years. Many companies were caught by surprise by the pandemic, as I was, as you were, and had to act so fast just to survive. And in many cases, the quick fixes left them little room to think about long-term strategy or emerging opportunities.
You argue that FutureCasting can help business leaders not only prepare for an uncertain future, but really to shape it. So, I'd like to kick off by just, what is FutureCasting and why is it so important right now?
Yeah, absolutely. FutureCasting and other scenario planning methods have definitely been very top of mind since COVID hit. And really, our idea for FutureCasting came from looking at our clients’, our own clients’ struggle with using existing methods.
At the same time, even though it's born out of a certain dissatisfaction with current techniques, we're certainly using a lot of different elements from these existing techniques—simply packaging them differently with a different set of objectives in mind to make this as useful as possible.
So, the real challenge we saw with today's techniques is the fact that scenario planning and war gaming, we have a rough idea of what they're for. Plotting the future, understanding our place in it, but there's no clear path as to how you're supposed to do that. Very often, there doesn't seem to be a very clear process for either collecting the data that you're supposed to analyze or making sense of it in the end.
There's no clear understanding of how you're supposed to prioritize trends that you identify, especially given that not every trend is as easily quantifiable as the next. So, how do you try and sift through that as the company looking at this? More importantly really, at the very end of this exercise, partially because again there is this lack of process behind it, it's not very clear what the action implications are in the end.
So, a lot of companies that we've seen will go through that process, through those different steps, they will try to wrangle with different kinds of data, different sources before them. But then at the very end, it's not clear what they're supposed to do about it, what the action implications are.
So, we looked at this situation and decided that we wanted to find ways to improve the overall approach—give this both more rigor and more practical usability—so that anyone can take this, pick this up, and just implement in their own company, in their own context, and make this as useful as any future-oriented work like scenario planning tries to be. So, that's really the overall reasoning behind the process we devised here.
It's really about bringing process, rigor, structured thinking to the whole idea of thinking about the future. I like that. Okay. So, let's talk about how it starts off. You said that there's four steps.
So, the first is knowing your environment. That's the first step, correct, in preparing for the future? But how can organizations map out such an uncertain landscape in a way that captures the big pictures of all the risks and opportunities and potential disruptions? So, walk me through the first step of the process.
So, I'll tell you what people often do, which is wrong, and then what we do, which I think is the right way to do it. They will often either just focus on one scenario based upon facts that have been in house or that they purchased through some secondary market research like Gartner or Frost & Sullivan, and they'll set a trajectory that, "This is the way the world is going to be. So, let's go plan for it."
Or maybe they'll have a base case, best case, and worst case—and all the time, they will just focus on the base case. That ignores a whole lot of uncertainty out there and treats all facts as being on an equal playing field, and they're not.
What we do is borrow a tool and adapt it from the US Department of Defense, which we call the Uncertainty Matrix. What we do is disaggregate facts into four quadrants, and the quadrants are defined by the certainty that you have around a certain risk or assumption and the accessibility of data that you have around that.
So, you can imagine at the top left of that, you've got the Known Knowns: what you're sure you know, and you've got the facts in house to prove it. And there, we want to challenge those truths. Selectively, but a lot of companies get into trouble because they are so darn certain that something is the way it is, and they'll gravitate to hard numbers because hard typically drives out soft. And in an environment of rapid flux, you may not actually really know that, but you think you know that. So, we want to lay those out and then selectively drill in where we think they need to be challenged.
Next to that, you have what we call the Unknown Knowns: where the organization knows certain things, but that hasn't filtered to the strategy team or to the C-suite. So there, it's working with people who are actually interacting with the market on more of a day-to-day basis. They might be in sales or customer success. They might have come in from competitors, for instance. Let's try to surface what they know that might bring in a little bit of color or divergence into the picture. So there, that's all about collaboration to get those opinions or facts onto the table.
Then on the bottom left, we've got the Known Unknowns: these are the uncertainties, and let's get very specific about what is uncertain within that. Are there diverging assumptions that people have? Can we make those discoverable facts that we can go out and quickly lay to rest? There are some things that you're not going to know for a while, okay, but let's understand what those are, why we won't know them, and how ultimately we're going to be able to find those out.
Finally, there are what's called the Unknown Unknowns, and you've got a lot of danger there, right? What are those X factors that can come out and really surprise you? There you use things like scenario planning and wargaming to bring those out—much like the Department of Defense does—to find those Unknown Unknowns before they can torpedo your efforts.
So, four different quadrants, four different approaches to get at the facts or uncertainties in each to those.
You said that in the Known Known quadrant that oftentimes people focus on the hard numbers because the hard numbers drive off the soft. Can you explain that a little bit to me?
In environments of rapid change, people will still gravitate to trend lines and data that they may have from either their own market research or from secondary market research reports, which are often a couple years old and don't really reflect what's going on today, but they want the data.
So rather than doing a quick, easy survey—which can be fielded pretty rapidly actually—they will use this old data, and then they'll make tremendously faulty assumptions. Charlotte and I worked with a healthcare company that was looking at its China healthcare strategy.
People were asserting, "No. Chinese healthcare, it's all going to be very hospital-based. It's all about trust in the physician," and they were ignoring what was going on with Tencent and Alibaba and some of the big trends of virtualizing care. Then when COVID hit, some of the provinces really went hard at digitalizing care delivery very, very rapidly—which they can do in China. Looking at the historical data ignored the underlying trends, ignored the capability of Chinese healthcare to turn very rapidly on its delivery model. So, that client ended up getting cut out. They realized it thankfully and they were able to pivot, but data can be a very dangerous thing when you don't look at what's really underlying the data.
That's really helpful. Thank you for that. In your paper, when you were talking about the uncertainty matrix, you mentioned that you need to focus on knowing your environment and that always requires knowing yourself. What do you mean by know yourself?
So here, the idea is to essentially have companies really focus on asking the hard question of planning. That includes making sure you're looking at any inherent biases or assumptions that have long held sway inside your own organization. So, that could be assumptions about the market that have been widespread across the company or any biases, especially about your own position inside the market.
So, I'm thinking here of clients and companies we've seen that become enamored sometimes with their own company stories, your own strengths, where you think your value proposition lies, that sort of thing. It's very easy to get wrapped up in that without testing that over time it's still valid—and not only is it still valid, but is it also valid everywhere? There's definitely a geographic component to this.
Stephen mentioned the example with the client in China earlier. That's a very good example because we've definitely seen that in a lot of contexts with a lot of companies sometimes thinking in a more US-centric fashion, certainly when it comes to North American companies. But really with the idea of taking whatever assumption you have internally and making sure that it's valid across different contexts. So, the geography component is important, but also again, so is making sure your research is current—so not relying on dated market reports—and making sure that you're not staying too wrapped up in the company's own ideas about itself.
So really again, it's being able to ask the hard questions—which is not easy, especially in certain corporate cultures. And we'll talk about how to handle that in a minute. But also, being able to be comfortable with ambiguity and not just going where the data is immediately readily available. Sort of what we were talking about a little earlier.
That's great. Okay. Let's turn to step two in the four step process of FutureCasting, and that's about getting to know your customers. How would you recommend that organizations rethink the customer journey and customer behavior? How do you approach it with FutureCasting?
So, about 20 years ago, I was working with Clayton Christensen, who was a professor at Harvard Business School who originated the theory of disruptive innovation and disruptive technologies. And he was grappling with, "Okay, I can describe how disruption riles markets, but how do we know what that next wave is? How do we know where the puck is going?"
He settled on this theory which he called "Jobs to Be Done," which holds that fundamentally people aren't out there to buy products and services. They're out to get certain things done in their lives. And that can apply to a consumer, it can apply in a B2B context as well.
You've really got to understand those fundamental motivations to see where the opportunity and threat lies, and be able to really widen the playing field, so you can discover these vectors that maybe your competitors haven't. We try to understand what is fundamentally changing in those motivations, or how can those motivations be satisfied in very different ways?
That certainly came into play here with COVID, right? Where you've got some of those core motivations shifting, but it's not just about that, right? We have to understand, "Where is there inertia baked in and where has..." Take COVID example, although it could apply to any sort of industry disruption. "Where is inertia broken? And what opportunities does this create?” Which may only be temporary before inertia resets, but let's go and follow up those motivations and be able to deliver in fundamentally new ways for people now.
So, you want to understand: how is your customer motivation, how is the behavior, how is the way they're judging solutions—how is that changing? That's going to open up all sorts of opportunities beyond just doing the same old.
How do you know which customer behaviors are here to stay? If you're looking at what's broken, what's shifting, and what may be temporary before it resets, how do you know which of the behaviors are here for good?
Right. So, that's the ultimate question we're trying to drive at here, for sure. This is where Jobs to Be Done is an especially useful framework to use in this context. Obviously if you ask customers to answer that question, "Which of your behaviors are going to persist?" They wouldn't be able to tell you, or their guesses would probably not be the most accurate way of getting at it.
But the good thing here is that you're not so much looking simply at the behavior or the trend itself, but more so at the underlying motivation or Job and context, or Job Drivers, that are driving this particular behavior. By looking at the foundations of it, "Why is it that this customer behavior even exists to begin with?" and by monitoring the prevalence of these different jobs and job drivers—which are certainly quantifiable—it's much easier to tell via interviews, via mass surveys, which of these behaviors are more likely to stick around.
There are also a few signals that you can monitor over time on top of testing for general prevalence of Jobs and Job Drivers, and we mention quite a few in the paper—we have a separate paper on that as well—anything from figuring out, looking at when new approaches start to be appealing. One customer behavior that might have been somewhat fringe at one point might suddenly become much more prevalent, because a solution that had been around for a long time suddenly became cheaper or more convenient. I'm thinking of a lot of examples in the tech industry, of course. That's an example of one behaviors being on the borders of prevalence suddenly becoming very central.
Certainly critical mass is a very important factor as well. Another important signal to look at is infrastructure. By that, I mean both the physical infrastructure—an example could be fuel cell vehicles, making sure that you have enough stations that are available to power those vehicles. If there are enough of those, then that infrastructure will lock in the change around making those vehicles much more usable and appealing to customers.
But it's not just physical infrastructure. You've got the business infrastructure as well. If you need to rely on certain vendors or partners for a solution to take off, if those partners or vendors are not very present or very common, then that's going to be much more difficult to make that solution more available to customers and really cement that behavior.
So, there are many signals you can look at, but overall the idea is by looking at Jobs, Job Drivers, and the context for these customer behaviors, you can really monitor that much more reliably than by simply looking at the behavior itself.
Okay. So, you've mapped your uncertainty matrix. You've looked at Jobs to Be Done and Job Drivers. You have all of this information to sift through. What do you do next? Where do you go from here?
Right. This is, typically, the part that's the most difficult for a lot of clients that we've seen use traditional methods. When you have all this data in front of you coming from a variety of sources, how do you make sense of the chaos? What do you start focusing on?
Especially given that these are typically people with other things on their plate, other priorities. How do you decide where to go next? Really our key guideline here is, essentially, focusing on the trends that are both the most uncertain and the most impactful to you as an organization. To the market as a whole, but by extension to you as an organization.
Ideally, once you've isolated those most uncertain and impactful trends, you can create a set of matrices where each trend becomes an axis. By using these different axes and toggling those different variables, you start to map out different possible futures depending on how each trend plays out.
So as you look at these different futures, you can then tease out what the threats and opportunities might be. And by extension—working your way backwards—what the action implications are for your company, and how you should strategize.
One example that we mentioned in the paper is around retail banking. There are many different trends that you could focus on, but here the idea was, "Let's build out a matrix where you focus on two possible variables. One is the importance of physical branches versus going solely digital, and the other is the extent to which banks would become more customer-centric or product-centric."
By looking at these two axes crossing together to form a matrix, in each of these four futures, you start to think about what the threats and opportunities are. And again, working your way backwards, what does that mean for you as a retail bank?
There are other examples, of course, but this is the one that we figured we would focus on in the paper. And the number of axes really varies depending on the trends that you're looking at. We've seen museums, for instance, focus on more than two trends throughout the pandemic, because they had multiple different priorities on their minds. It really depends on the specifics of your organization.
Is this process at all different than analyzing best- and worst-case scenarios?
Right, the intent is actually quite similar. The idea is to look at all possible outcomes. It can be very easy to gravitate towards what feels like the rosiest of futures, and just decide we're going to be working with that and try to strategize around that. But it's very important to keep an open mind to futures that are less than ideal.
So, working with best-, middle-, worst-case scenarios—it has a similar intent. The objective is the right one. However, that approach assumes that you've got a single type of best-case scenario, a single type of worst-case scenario, a single type of middle-case scenario. The reality is that you can have an infinite number of best- or worst-case scenarios that you would have to work with.
The idea here is focus on not just a single of each, but really look at what trends might conflate to create different scenarios of different levels of risk and opportunities for you. So, trying not to buck yourself in an arbitrary number of scenarios from the get-go.
I mean, it's one thing to focus on three, but you very well may be missing out on key opportunities or threats by doing so—so it's just course-correcting an approach that otherwise shares a very similar objective to ours.
People will often, in a best/worst-case scenario, they'll build it around a financial model, and then they'll just have different values for the various variables that are part of the model. But our point is that these scenarios are different. It's not always the same variables that are in play.
Sure, you can look at some things that might vary and that are common across scenarios, but the history—not just of the COVID world, but the pre-COVID world too—is that the world is changing in all sorts of ways. You have to push these scenarios to look at worlds that are all plausible, but just fundamentally different.
Okay. You have all of these scenarios after all of this research. Is this the list that you go forth with, or is there some other process or thinking that you need to do once you have your short list of scenarios?
Right, you're going to have a lot of possibilities out there and you really need to narrow it down. So first of all, you want to go back to that Uncertainty Matrix and think about, "Alright, why do we really know what's uncertain? How has our view of the world changed a little bit since we created that Uncertainty Matrix? But also, how does that matrix influence how we're looking at the potential responses? Are we just gravitating to what we know and ignoring the Unknown Unknowns? Can we reduce risks a little bit by doing some little experiments or creating an option for growth in an area?"
You'd also want to have a little bit of a portfolio plan about how much you're willing to take on. Before you start thinking about which investments in particular are the most attractive to you, you want to think through, "Are we looking for two things? Are we looking for five? What's our timeframe for realizing returns? How much risk—and what types of risk—are we willing to take on?"
That's really going to influence that list of potential investments. Then you can take what should be a pretty long list of potential things to do and put it into an idea funnel that should be wide at its mouth, but very rapidly narrow down to a handful of things you're going to pursue. And you use decision criteria about those that are influenced by the scenarios, that are influenced by the Uncertainty Matrix that you created, as well as your portfolio plan of what you're ultimately seeking to get out at the end of the funnel.
You have then a list of investments that are probably going to look pretty different, that are probably guaranteeing a future against different sorts of scenarios, but which will also hopefully play together in some way and create some synergy—so it's not just a disconnected series of bets, but it looks coherent as a whole portfolio of bets that you're going to place.
Thank you. So, we've now walked through the four steps: Uncertainty Matrix, customer behaviors, alternative futures, investment portfolio. Can you help me put it all together with perhaps a real world example, maybe one of your clients from the last two years? How did they use the idea, the principles, and the process of FutureCasting in the midst of the pandemic?
Sure, let's take something that's really topical for the pandemic. We can look at diagnostics. Lots of change in the diagnostics market. Certainly grew a lot, but how is it going to change in an ongoing way?
We worked with a big diagnostics company. First, we separated those facts from the assumptions. We did the Uncertainty Matrix. We can look at a bunch of revenue expansion opportunities to look at further, and things came out of that around telehealth, for instance.
"What do we know about telehealth? What don't we know? What do we think we know, but we're not quite sure? How does this play in different sorts of situations around, for instance, how do we engage with primary care doctors, differently than nurses, differently than specialists? What are our big assumptions and opportunities around each?"
So, creating a set of Uncertainty Matrices there, and then we have to understand related to that, "What are those coming customer behaviors?" So in that case, we undertook a few dozen interviews with target customers to understand how their behaviors are changing. What are the motivating Jobs to Be Done that are really influencing those behavior changes? What are the factors that create inertia or break inertia, create new infrastructure? Then we could evaluate the appeal of different ideas, with an understanding of how those behaviors are changing.
Third, we developed the alternative futures. We had different scenarios. In this case, we looked at the employee point of view, as well as an employer point of view, in the US healthcare market and how that differs in more government-directed healthcare markets.
For instance, from an employee point of view, you could say that a lot of on-site care for any workplace would be convenient. Whereas for an employer point of view, you might look at a scenario around healthcare as a tool for employee recruitment or that healthcare is just a cost you want to minimize.
As you look at how those converge, you can then have very different sorts of scenarios. In one, for instance, there would be full integration of a workplace and healthcare. Whereas for others, there might be off-site delivery of healthcare, but you'd still be willing as an employer to pay a premium for superior access to healthcare as a recruitment tool.
Then fourth, you create that portfolio plan. How many ventures were they willing to get behind? How does that react or influence their current product roadmap or the way they undertake their sales model? What their marketing messages should be? How does that impact what they're going to be developing in the future? Maybe it's M&A, maybe it's organic development. It's also things they wanted to get out of, because you can't do everything. That influenced that list of investments as well.
So, it's a step-by-step process. There's a lot of different elements. The reason we have the rigor is to orchestrate these different elements in a way that all build on each other and make sense together.
I'm curious, how long does this rigorous process typically take, or is it just completely variable?
It depends on how much they already know, and of course it depends on things like, "Is this global on scope? Or is it multi-market or not?" The key factor is really, "How many uncertainties do we need to lay to rest with some primary market research?" You can step through this whole thing in a period of six weeks if you've got a lot of facts on the table.
The most this would typically take would be, I'd say about four months, just because organizations don't have the patience to embark on humongous, long initiatives. We don't want this to be some academic exercise. It needs to be practical. It needs to relate to business priorities. So, that's typically the cycle time that's required in order to do that.
Most organizations or many organizations already have some kind of long-term vision in place. What advice do you have for leaders to incorporate a process like FutureCasting into their existing plans and processes?
This is where the point that Stephen made earlier about how much preexisting worth there is, is quite critical here. You don't want to give the impression that you're duplicating other people's work. So, starting with a really good lay of the land and understanding what already has been done by your fellow coworkers, by your team, is really important.
Then once you have that, making sure that whatever FutureCasting exercise, whatever parts of the process you decide to take on—because it's quite modular, you could start at phase two if you already have phase one done—so wherever you're starting, you are including your company's current assumptions and vision about the future in your work to pressure test.
The last thing you want is to end the exercise with results or a process that didn't tie into that vision or didn't include it as part of that work, because it essentially makes the results a lot less relevant to your team. If you come out of the process with results that directly either question or confirm or validate your company's ideas about the future, then people are certainly much more likely to listen to you and take that into account as part of the company's strategy. A lot of it is just honoring what's already been done, what's already in place, and accounting for existing ideas about the future.
I imagine that this new way of thinking may be met with some resistance, some organizational resistance or hesitancy. What advice would you give to overcome that organizational resistance?
Absolutely. Like you said, any large change or different kind of thinking is going to be met with some obstacles along the way. Each organization has its own unique hurdles to some extent, but there are a few general best practices that we've seen work across different organizations of all shapes and sizes.
One obvious practice is to make sure you're involving the right stakeholders at the right time. Whether it's just letting them know what you're doing or really giving them the opportunity to be involved in some key points of the process—whatever it is, just making sure you secure the right internal buy-in at key points during your FutureCasting exercise. That's one.
Another approach is making sure that whatever results you come out with, you can craft them, you can weave them in a really compelling story that you can share around and that will be memorable and inspiring to your fellow coworkers. There's a little bit of a storytelling component for sure. Generally you want people to want to hear more about it and run with it. Making sure that it breeds an interesting and shareable story is important.
Finally, one other method that we've seen really work in a variety of contexts—even including outside of FutureCasting, but in terms of general innovation—is setting up a system that rewards both decisive action and inexpensive ways of moving forward and making progress.
One example would be incentivizing teams to cut their losses early when you're exploring different trends. Putting a system in place that really rewards making relatively rapid forward action. Because again, very few companies have the patience to sit through a year plus of this kind of work, so you really want to show people that this is not just a zombie project going on. You have to keep things moving forward.
You mentioned the importance of getting the right stakeholders involved. Are there certain people, departments, or functions that you would recommend be part of the FutureCasting exercise?
So, you certainly want people to be involved who are customer-facing, but you should have R&D there for instance—and push them to think not only what are they doing, but what are their suppliers doing for instance. Or what do they see competitively? What's some of the patent action that's happening, right? Use ways to peek around corners that those folks might have as well.
You'd want find some people who are fairly recently joining the company, because they might have a different perspective. You could use some people who are pretty new to their career, but are unafraid to challenge the status quo. Fresh thinking is important.
Now obviously as Charlotte said, we want to have people there, too, who are going to catch the ball and who are going to have to be involved in the implementation of what comes out. But you're trying to get some fresh oxygen in the room here, so having that range of perspectives is really quite useful.
You mentioned fresh thinking. I would imagine that it's helpful to have an outside perspective such as an on-demand independent consultant or boutique firm like New Markets Advisors. Is that something that you recommend for an exercise like FutureCasting?
I do. Look, there are situations where internal work can really do everything you need to, but if you're trying to step back and ask really hard questions in a structured way, frame scenarios, think about these things from different perspectives, bring in external sorts of trends, potentially do some primary market research as well, then outside help is extremely useful. It allows you to get this done in a way that is objective, that brings in that perspective, that proceeds relatively quickly, and that can make sense of all these different strands, and put it together into a really cohesive, easily disseminated, actionable set of recommendations.
Any parting advice for leaders who are faced with the daunting task of looking at an uncertain future? Any last bits of advice you want to give to leaders at this moment in time?
I think you need to step back and think in the last five or 10 years of your career, what surprised you and why has it surprised you? Can you take steps now to remove those sources of surprise, right? The surprises vary. The sources of surprise often don't, and the reasons you get surprised often don't. So, that's really important.
I think now, as you say Jen, we're at a time of huge transition—economically and in terms of organizational and customer behavior. So rather than just let it swirl together, try to disaggregate those things. Try to understand what you are most uncertain about and what are the consequences? That at least I think will get you going to about what your responses might be.
Thanks, Steve. Charlotte, anything from you?
I would say along the lines of what we've been talking about when it comes to making sure those efforts have impact within your organization, just finding others within your organization—or outside and peer groups that are also looking to think about these things differently—and just fostering those exchanges. It's very easy for people to feel—especially in a remote setting as we all continue to work from home—that we're working and operating in different silos. But you're certainly not alone in working through these challenging issues, and I think really trying to find peers that you can exchange with and build a greater desire to change your company's vision for the future is important. That would be a reminder I would want make to folks out there.
Thanks, Charlotte. I think that's a perfect ending: just a reminder, you are not alone. Thank you, Stephen and Charlotte. It just has been an incredible time talking to you today. I have learned so much, so thank you so, so much for your time.
As a reminder, our guests today have been Stephen Wunker and Charlotte Desprat, New Markets Advisors. And I'm Jennifer Napier, Chief Marketing Officer for Business Talent Group.
To start a project with New Markets Advisors or thousands of other highly skilled independent consultants, visit businesstalentgroup.com. You can subscribe for more of our conversations with on-demand experts and future of work thought leaders wherever you find your podcasts.
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