Futures Friday: Foresight Driven Decision Making
Using Foresight and Data in Your Organization
In my company we focus on projects for clients around DDDM, Data-driven decision making. In a nutshell, this is the capability of using data to help inform key areas inside of an organization. It can range from real-time data for situations that require quick or even automated actions, aggregate data showing trends and outliers, or long term “big data” to help inform strategy.
Many organizations today use DDDM, and while our company offers strategic advice and custom implementation, we are not unique, and there are many services and articles out there to help organizations implement DDDM. Data has become big business and DDDM is now more or less table stakes for a successful organizations.
But what about foresight or futures research? Why are so many companies unaware of this practice that gives them an advantage? Why are more people familiar with data-driven organizations than foresight-enabled strategies? I have my own theories I will share in a moment, but first let’s take a look at what foresight-driven decision making (FDDM) is.
So first of all, foresight-driven decision making is not a common term…yet. However, the concept is not new, and at its core it is relatively simple and intuitive. In foresight, we do specialized research and analyze trends, programs, drivers, implications, policies, etc. to extract images of possible futures that could have an impact on the organization. All of this is to help reduce uncertainties and to not be surprised.
We then use this information to help organizations be better prepared and make key strategies, plans, and long term decisions (often impacting ten or more years ahead). In a way, FDDM is an extension of DDDM. Foresight requires research and data, and the more quality and accessible data there is, the better. If an organization has a mature DDDM practice already, it is a natural candidate for foresight.
So how is FDDM different than DDDM, besides the time spans that foresight generally deals with? Foresight tends to be a bit more fluid. While based on data, it also uses a heavy amount of creative and critical thinking. It is both an art and a science. Foresight can deploy rigorous methodology or be more speculative in nature, and the futurists that practice foresight come in many different flavors.
And this may be the reason why many organizations have not yet adopted or even heard of foresight to help with decision making. DDDM offers hard facts and allows us to build rules to run an organization. It can shield the decision maker and reduce their responsibility by relying on facts and evidence. This is of course not really true. Data, algorithms, rules, etc. are all subject to bias, inaccuracies, and false assumptions, but DDDM does provide a quantifiable way of making decisions and provides a more secure feeling that the decision is the right one.
Foresight also relies on data, but often uses a much more qualitative approach. The goal of foresight is not to develop a series of rules, but rather to aid the very important skill of critical thinking in decision making by allowing the decision makers to be prepared and better informed. So why wouldn’t more organizations want to do this? Here are some theories I have on that…
- Many organizations do not know what professional foresight or futures research is. They may have heard of it, but the field is not necessarily consistent on terms, methodologies, and marketing itself to have a consistent and well understood view in the larger world.
- Foresight can seem messy. As I mentioned above, DDDM may be a technically complicated discipline (lots of data expertise required), but it is based largely on quantifiable information aimed not just at providing insights, but usually some level of automation. Foresight — not so much. Foresight requires a different skill set from the practitioner that uses skills related to social and political sciences as much as data science. A futurist will rarely (or ever) provide a definitive answer or specific odds. We will give you plausible options. Many in the data trade are not as comfortable with fluidity and more than one answer.
- Most people are not as good at critical thinking as we might want to believe. Foresight requires critical thinking. Exploring implications, analysis of qualitative research, understanding holistic ecosystems, systems thinking, and understanding social change — these are all part of the futurist’s trade. Most learning institutions lack proper critical thinking curriculums. There are exceptions (science fairs and exception educators) but social discorse seems to have fallen off the critical thinking train. If an organization does not have a culture of critical thinking, then adopting foresight, or even DDDM, can be a hard adjustment to make.
I am sure there are many more reasons, but you can see with these few examples how foresight has its challenges as being accepted organizational discipline. It helps to think of foresight as not about definitive answers, but about a way of thinking. It is an approach to help us better understand what lies ahead. Let’s take a look at some of the practical ways foresight can help in decision making.
Thinking Through Scenarios
One of the most common tools futurists use is scenarios. These are a series of possible futures, distinct from one another, that offer a glimpse into what might lie ahead. They are based on the foresight research that futurists do. Scenarios are not meant to be taken as an either/or choice. Instead they offer a means to talk about the preferable futures that an organization envisions. It reveals what elements outside of the organization’s control to look for, challenges in the organization, and potential new opportunities. More than a plan for a future, scenarios are a way of communicating futures. They should include a high level of participation and discussion with stakeholders and decision makers.
This exercise should be transformational in and of itself, even if no one ever read the scenarios after their initial release. But the real power of scenarios is that if they are kept alive in discussions and referenced, then they offer a common dialogue to discuss the path the organization is on.
A famous case of scenarios in use is the Mont Fleur Scenarios conducted for South Africa during apartheid. In the early 1990s, the country of South Africa was looking to what their futures might be in the midst of dramatic social and governmental change. They conducted a series of foresight exercises and came up with four distinct plausible and relevant scenarios that showed how South Africa might look after the transition. Each had a memorable name and narrative, allowing the decision makers as well as the public to discuss what futures of South Africa might look like and the paths to get there. Adam Kahane, the facilitator of the project from GBN, describes them as:
Ostrich, in which a negotiated settlement to the crisis in South Africa is not achieved, and the country’s government continues to be non-representative
Lame Duck, in which a settlement is achieved but the transition to a new dispensation is slow and indecisive
Icarus, in which transition is rapid but the new government unwisely pursues unsustainable, populist economic policies
Flight of the Flamingos, in which the government’s policies are sustainable and the country takes a path of inclusive growth and democracy
Not every use of foresight and scenarios needs to be as high profile or carry as much weight as the fate of a nation. Scenarios can be part of a regular process in an organization when making decisions affecting longer timespans, or an exercise to help an organization strengthen its long term strategies.
Another great tool is futures wheels. They are part speculative, part trend analysis way of thinking about futures. They can greatly help in the decision making process. It is also one of my favorite tools. I think of it as the “If You Give a Mouse a Cookie” tool. The concept is simple, but the skill level to make it meaningful and plausible, based in data, should not be underestimated. If you really want to see how far you can take this tool, check out Joel Barker’s Implications Wheel website. You take a premise or an assumption such as “more people are trying meat alternatives” and then, based on your research, you add several implications that one assumption would create, perhaps “more alternative meat startups go into business creating competition.” Then you can assess some probabilities and levels of impact, much like a risk analysis. You continue to do this until you have a very robust wheel.
Implication mapping can be rather simple and informal, or it can be an extensive data driven exercise involving many stakeholders. The example above is from a project that had over 250 implications and impact projections.
Decision makers can use implications to better understand the holistic and long term effects of not only their decisions, but changes that are outside of their control. Using implications, decision makers can see how their choices may hold up under varying circumstances, such as a recession or a trend towards Net-Zero construction.
OK, there is probably a better word for this tool, but it’s Friday and so I am going to leave it as is. One of the crucial functions of professional foresight is proving recommendations on what an organization will do with all the results (trends, scenarios, futures visions, implications, etc.) Foresight provides a strategy on how you choose your strategies. If you can look at an array of possibly futures, you can start to plan how you might strategically approach each one. Perhaps your organization is already prepared for one particular type of scenario (e.g., a recession), but you are not prepared at all for a prolonged trade war with China. Perhaps your overall strategy then would be to put more strategic resources towards a trade war possibility.
This practice can help allocate resources more efficiently inside your organization to prepare for long term success. It will also help you identify what things you might be able to do now.
Long term strategy is great, but how can foresight driven decision making have an impact today in your organization. Not only can foresight help you identify issues and opportunities, it can help you take action today to create your preferred future. First, by practicing foresight you can better define and communicate what your organization’s preferred futures are. Then by better understanding the various drivers and trends both in and out of your control, you can start to see the levers you can move today. Implications of course help you simulate decisions and actions you might take.
Much like DDDM, foresight-driven decision making can take many shapes and forms. It is an applied practice and also requires an organizational culture that will support critical thinking, analysis, and improving the practice and capabilities. It is not a replacement for DDDM, but rather an enhancement or maturity of decision making in an organization. Also like DDDM, organizations should look for experienced practitioners to consult and/or build their internal capabilities. Adding foresight to an organization, especially one that already has some familiarity with DDDM, can be quite economical and provide a great long term ROI.
There are a lot of resources available on futures research and foresight, though navigating the various practitioners, methods, and offerings can be confusing. Personally I am a bit biased toward the University of Houston’s Framework Foresight, though there are many great methods and resources out there. Institute for the Future also has some amazing resources and educational opportunities. In a future post I will share a more comprehensive list of resources to get started in foresight.
JT Mudge is a professional futurist and data consultant. He is a member of the Association of Professional Futurists and both writes and speaks about data and futures. He works as a Data Strategy Consultant at productOps.