Forecasts and Vision

Forecasts are strategic business tools that help organizations navigate the future, but they also help create plausible and reasoned material when articulating business and product visions or aspirations. A vision is a strategic tool that paints the picture of a desired future state for an organization, a product line or an individual product. Visions are what companies aspire to. Visions are much less volatile than forecasts because they are based on a desire to take the company, the employee or a market to a future state. Visions paint a promise without making one.

Forecasts inform vision by creating a canvas that calls out gaps between the current state and the future state across many potential futures. The vision is not likely one of the future states, but an amalgam of them, even a reaction against others.

Scenarios can also play a role in vision when one scenario does presents a particularly inspired view of the future. In Microsoft’s set , the Freelance Planet world represents a place where many want to take the work experience in the future, with plenty of surface level evidence and press coverage to reinforce that’s future’s appeal. Discussing this future provides a context for much that is going on with the Millennial generation, the penetration of consumer technology, in particular, social networking, into the work experience. But it is not all ideal, as an independently crafted vision might be. Freelance planet is also a world where workers pretty much have to fend for themselves when it comes to healthcare and pensions. In Freelance Planet most companies divest their core competencies of everything except financial management, partner management and brand management (money, people – external, and brand).

Discussing the scenarios with customers creates a thought leadership platform, as the combination of the process and analysis of implications demonstrate a mature approach to an uncertain market, and it reinforces the altruistic nature of thought leaderships by providing customers with value that goes beyond that expected by their software licenses. The scenarios and their accompanying forecasts also create a platform for learning and dialog, which takes them well beyond outward bound communication. The rich narratives of scenarios act as a canvas that people can react to, and therefore help co-create. The vision becomes better refined, the points of discussion better resolved, because customers can look at alternatives in the scenarios that reveal, at least their current inclinations, to a wide range of business and technology issues. As organizations seek new ways to keep customers close, scenarios offer a new form of inclusion that can powerfully inform the business, provide insight for the customer and help guide the market.

Acting on the Future

A good forecast is one that forces an organization to accept possibilities it might not otherwise consider, and to create plans more resilient to change than it might be made for an assumed future. The first action when incorporating robust forecasting into a long range planning model is applying what is learned directly to current plans. Many plans fail because of an organization’s inordinate belief that even for some period of time an individual or team has foreknowledge meaningful enough to anticipate what will come, and thus take short-cuts and imposes rigidity in architectures, processes or markets. Those choices may prove detrimental when the future unfolds in even subtly different ways than anticipated.

Even though organizations cannot afford to create plans that account for all contingencies, what they can do is take actions that permit their plans to survive in light of the contingencies. Software is perhaps one of the most malleable inventions, but like clay, it can be used to build walls or walkways. Choices can be made to lock a design into a very narrow framework, or it can be used deliver a platform, open to reinterpretation by its end users.

Collaboration software applications illustrate flexibility well. Microsoft maintains four very different versions of the future that range from government-business cooperation on a grand scale, to devolved economies to geopolitically fractured markets, to open markets where freelance principles dominate.[i] Collaboration software plays a role in each of these futures, but in a very different way. In Freelance Planet, collaboration software becomes the connective tissue of business, it exudes from a social computing fabric as a way to share information and communicate with peers and colleagues around the world. It is organic and self-organizing. In the geopolitically bounded world called Continental Drift, collaboration software becomes a tool of the state, limiting communication and tracking activity. It becomes a constraint rather than an empowering tool. Yet at the core, the concepts of e-mail, shared work spaces, instant messaging, expertise discovery and other features exist in much the same way. By adopting software for Freelance Planet, an organization receives the more flexible platform, one that can easily be expanded to include any necessary constraints or impose levels of control and tracking. It is easier, architecturally, to create flexibility and then add constraint than it is to open up something that is functionally constrained.

Another way of acting on the future is to place the organization within the context, conceptual and temporal, of the revolution with which they feel most associated. Electricity, television and the Internet all took time to meet the anticipated goals of their most enthusiastic early adopters. Finding a place in the s-curve of early adoption helps define vision and set goals because the business exists within a framework of movement, informed by multiple scenario-outcomes.

I remember cautioning people at Hughes Aircraft about the irrational exuberance of the Internet startups who had one degree different models than their competitors, but more importantly, had a small pool of customers to draw from. I likened it to dropping the late 20^th century yellow pages, and all of various services, fully into 1920. Imagine phones and an advertising delivery model but with one flaw: only 30% of American household had a phone.[ii] There would be too many businesses to support the people who owned the technology. The dot-com bust occurred as the market realized that even massive amounts of users did not support such a diversity of offerings and business models. As an analyst at the Giga Information Group I usually started new client sessions with one important question about forecasting: what is your exist strategy? The executives were usually dismayed and a bit upset paying my firm money to help them make money only to be greeted by a question about their demise. But that was a strategic test question. Any organization that said it didn’t have an exit strategy was either lying or was deluded, neither of which was healthy.

Perhaps the best advice to those who wish to forecast more accurately is to forecast often. Good forecasters prove adept at sensing change. Tracking change cannot be a periodic exercise; it needs to be ongoing investment in agility. Organizations must not simply listen to the future as it unfolds, but they must hear it and act on it.

[i] Listening to the Future

[ii]Universal Service, Page 148 http://books.google.com/books?id=GrEZQHQ5-ncC&pg=PA148&lpg=PA148&dq=telephone+penetration+in+1920&source=bl&ots=-awQFEYXYS&sig=6IlcSpatqsBTRPl71A1UCaaRD-w&hl=en&ei=t1XSSbq2CJO8swO2sbzGAw&sa=X&oi=book_result&resnum=2&ct=result#PPA148,M1

Hearing the Future

If trends and extrapolations are our only inputs for future scenarios, how do we go from the process of gathering evidence, to the process of actively listening to the evidence? The constant movement to the future and the perceived momentum of the status quo are common problems that befall any long range planning effort as current action seems more important that future considerations. The Obama administration is facing such a dilemma in their first months in office. Regardless of campaign promises, many Americans and many in Congress want to concentrate on the immediate issue of the distressed economy, placing issues like the environment, education and healthcare into the background.

Hearing the future means placing current analysis in the context of future factors in a way that informs direction. As Obama has stated several times, the current economic crisis cannot be solved without understanding and applying the insights into its fundamental cause. On the surface, that includes the revamping of regulatory policy around investment banking, but he implies a holistic approach to the underlying economic structures like healthcare, energy, education, the environment and the political standing of the United States on the world stage. To a scenario planner the interaction of these elements in future narratives shouts about linkages that risk being broken if short term solutions do not take into account the long term affects. The uncertainties facing the administration must be placed into a context where future states have the ability to inform current action.

The evolution of whole systems, economic or evolutionary, can be misrepresented if trend readings are taken without account for expansion or contraction of a system (Gould famously argues that the extinction of the .400 hitter in baseball is the result of an overall improvement in baseball as system, not a trend toward poorer batting or betting pitching).[i]

For forecasts to be effective, it is important that the forecaster create what Paul Saffo refers to as a cone of uncertainty[ii]. This cone starts with a selected starting point in the past, and moves out in time, creating a playing field within which uncertainty can be related to current events.

Many trend watchers map additive data points along a trajectory without mapping the currents around the trend that will reinforce or drive a trend off course. Adding cross-relationships and integration into the cone of uncertainty unveils a more dynamic playing field (see figure 2).

Influences are subjective and intuitive. It is important to say this as we must remain cautious of false correlations. Correlations, as Taleb reminds us, have “no significance outside the Gaussian.[iii]” When looking for disruptions as Saffo and Taleb do, the S-curves and power laws dominate, and normal statistical analysis, including correlation and regression fail. For many during the economic crisis, models failed because they were built on assumptions that no longer held true. The lack of statistical correlation does not mean that influences do not exist, it means that mathematical representations using standard statistical methods don’t apply—thus the need to reason about uncertainty with evidence and intuition combined.

For strategic level forecasting, then, the cone of uncertainty must be expanded and contracted on a regular basis in order to encompass important potential influences. When something falls outside the cone, but is likely to exert influence on an uncertainty within it, then the cone should expand to include that element. I have found it important to draw maps and relationships, to categorize items in multiple buckets to try and tease out relationships where none may be apparent. Forecasting, in the sense of scenarios, is about imagining the impact of wild cards, and mitigating their effect (or leveraging an advantage they create). As Taleb argues, rare events can be given a sense of the possible—that leaves us with the completely unexpected, which even when given a name and placed on a set of scenarios, may be so hard for people to imagine that they ignore it like cross traffic to a driver with poor peripheral vision.

When creating models of the future, they must include non- arbitrary, seriously disruptive scenarios that challenge prevailing assumptions to the point of breaking. If they don’t, then the probability that a scenario set is inclusive of key uncertainties should be seriously in doubt. A set of safe scenarios does not extend the strategic dialog, it cripples it.

[i] Gould. Op cit. Page 77.

[ii] Saffo, Paul. Six Rule for Effective Forecasting. Harvard Business Review. July-August 2007. Page 22.

[iii] The Black Swan, page 239

Understanding Trends

The late evolutionary biologist Stephen Jay Gould was confounded that equine evolution became the standard illustration of evolution in biology texts. The primitive little horse marches inevitably to the complex and robust Equus that pulls beer through the streets of St. Louis and carries cowboys in roundups. But the trend to Equus was not nearly as linear as the biology texts describe. In fact, the standard image for the progression horses, or for that matter man, collapses the bush of evolution into a single line. Equus, and humanity, when compared to rats, bats and antelopes are the final representations of once much more diverse groups. Success in evolution comes from radiation and local adaptation, thus many more species of rats, bats and antelopes exist than do humans or horses, but, as Gould argues, our bias toward progress clouds how we represent the facts. Humans and horses are evolutionary failures, as the diversity of their heritage becomes a single, tenuous branch.

A trend, then, as defined by Gould, “is not a march along a path, but a complex series of branching events, or episodes or speciation.[i]” So when we look to trends, it is not the single path that must be examined to understand the influence of biology or technology, but the radiation and adaption within the model.

A bias toward progress clouds how we represent the facts in business trends as well. Consider the trend toward globalization. If you examine supply chains, tariffs, trade deficits, foreign investment and other factors (see Riezman and Whally for a deep examination of globalization metrics[ii]) what you find bias in much of the reporting toward the inevitability of globalization at the macro level. A forecasting bias is not necessarily incorrect, but it misrepresents the complexity of the data, much as the march toward progress misrepresents the actually evolutionary history of the horse. Technology examples of triumphant evolution include the operating systems (Microsoft Windows) the digital media player (Apple’s iPod) and the Internet (Ethernet and TCI/IP). Whereas historical retrospectives may make these appear the inevitable end points of an progressive evolution, The Black Swan’s Nassim Nicholas Taleb would attribute their success to luck and randomness rather than to inevitability and design.

The failure of trends alone as an indicator can be seen currently unfolding in Detroit as the automotive industry faces its toughest challenge, much of it brought about by a bias toward progress. Faster, more efficient internal combustion engines combined with affordable luxury created an industry of me-too automobiles and trucks. The disruptive elements from ecological sensitivity to a credit crunch precipitated by the US housing crisis interrupted the seeming trend that led to the Hummer and the Lincoln Navigator.

A trend, to most business forecasts, then, is something to bet on, much like the evolutionarily challenged horse. We can draw its progress all the way to triumphant success. The role of most forecasters, then, is to point toward those few things that will create high payoff. As Taleb informs us incessantly in the Black Swan, the inevitability of this success being widespread is negligible. Most businesses will miss an opportunity, even if they see it. Gould discusses this in Full House when he explores how politicians exploit the mean to describe economic policy, rather than the mode, which represents the more realistic reflection of economic distribution.

Scenario planning treats trends very differently. Scenario planners concentrate on process; they seek a robust examination of critical factors across a wide playing field of narrative logics about the future. Although the scenario stories may be informed by trends, the trends are not seen as predictors of outcomes, but rather actors within the narrative—capable of surprising actions across a range of outcomes constrained only by a focal question, or point of inquiry.

My latest book, Listening to the Future, focuses on the future of work. Although our team speculated about the future of various industries, we viewed those industries through the lens of external factors that influenced the shape of the workplace experience. Scenarios do not claim to forecast precisely, but to create a map for navigation. If you think about shooting the rapids, the level of water in the river changes the character of a run. As currents whip boats through various pathways, they encounter different conditions. Scenarios are intended to, as the skipper of a rapids runner will tell you, prepare the organization for various conditions they may encounter, not for the conditions they hope to encounter.

Gould is not universal in his repudiation for common errors in trend analysis. He writes, “I am not saying that all trends fall victim to this error (genuine “things” do move somewhere sometimes), or that this “fallacy of reified variations” exceeds in importance the two more commonly recognize errors of confusing trends with random sequences, or conflating correlations with causality.”[iii]

This last point bring forecasting back to risk. It is risky to bet on forecasts that claim certainty, because no matter how smart a person is, his or her ability to know for certain the outcome of a factor over which they have no control is based on luck, not knowledge. Well-prepared adventurers navigating the rapids would likely ascribe to the adage: you make your own luck.

[i] Gould, Stephen Jay. Full House. Page 63.

[ii] Riezman, Raymond, Whalley, John and Zhang, Shunming. Metrics Capturing the Degree to Which Individual Economies are Globalized. December 20, 2004. http://www.biz.uiowa.edu/faculty/rriezman/papers/RWZ.pdf

[iii] Gould. Op. cit. Page 38.

Listening to the Future

Listening to the future begins with an understanding of what is important: focal question to solve for and a set of uncertainties and important, but more predictable elements. Unlike scenario planning, less open planning processes charge individuals with the curse of expertise, forcing them to guess and then defend their guesses. Van der Heijden discloses the trap of certainty when he write that for rationalist: “there is one right answer to the strategy question and the art of strategizing is to get as close as possible to it.”[i]

I always recommend not only indentifying uncertainties, but giving them a name. Naming uncertainty attempts to remove ego, bias and other prejudice from the planning process by creating an initially dispassionate list of uncertainties. Naming uncertainty wraps the negative elements of human bias around a concept they no longer need to defend with the rightness of opinion. And in an anthropomorphic way, the uncertainties settle into the model and listening becomes easier as they grow into mature characters within the scenario narratives. Passion then returns based on a collective interpretation of the uncertainties and their outcomes, not from preconceived notions about them.

It is important to better define uncertainty before proceeding further. First, risk and uncertainty are not the same thing. In his book Risk, Uncertainty and Profit, University of Chicago-economist Frank Knight sees risk as something with a fixed set of possible outcomes, whereas uncertainty has unlimited choices and unique context. In other words, uncertainty does not increase risk, uncertainty reflects a different circumstance than risk, and needs different tools for managing it.

In a Morgan Stanley report titled Navigating in the Midst of More Uncertainty and Risk, the report’s authors state that “many asset and financial risks resist quantification. In fact, many asset and financial risk these days appear to be non-normally distributed and not independent. They conclude that “what we once thought of as “risks” are turning out to be uncertainties. Eamonn Kelly of the Monitor Group reinforces that position in his book Powerful Times when he writes: “…the entire world—has surely never been more uncertain. As our systems—technological, social, economic, cultural, and political—become more complex, more global, more interdependent and develop at an accelerating pace, increasing (and increasingly widespread) uncertainty is an inevitable and ongoing consequence.”[ii]

Given the increase in uncertainty, Microsoft’s Business Division applied scenario planning to the examination of the future of work. Despite some presumed trends about work, like it is getting more digital, more automated, and therefore, becoming more easily distributed. Many other elements about the future of work can’t be predetermined. Let me use workforce demographics to illustrate the point.

If you go the US Census Bureau, the population pyramids are available for any country, for any year (See Figure 1). Population pyramids illustrate the male and female portions of the populations by bands over time. The aggregation of bands become generations (e.g., Baby Boomers, GenerationX the Millennials). The size of each of these population cohorts is determined, and given certain factors about life expectancy, and their composition is extrapolated forward pretty accurately (taking out factors like war, or a major catastrophes like pandemic or global ecological disaster). So we can, with good confidence, know the age range of our potential candidate pools.

What we don’t know, and can’t predict with any certainty, fits directly within the framework presented by Knight— namely, a unique circumstance and a wide range of options: how people will work together when the generations join up within a workplace. So the certainty of the population, doesn’t provide any insight into how the generation will perform, how long individuals or groups are likely to stay employed or the social environment that will be created when bringing together this disparate groups.

When it comes to forecasting, traditional quantitative methods suffice for risks. When it comes to uncertainty, listening to the future requires an investment in the collection, reflection and collation of information from a wide variety of sources to create reasonable hypotheses for what might occur. Scenarios provide a framework that helps those performing the analysis avoid the straightjacket of linear trend extension by forcing the evidence to play out against multiple social, economic, political, environmental and technological backdrops. The way these elements are shaped by the scenario narratives can provide input to executives seeking ways to make plans more resilient by eliminating rigidity, fragility and brittleness.

Before we continue on to hearing the future, it is important to better understand trends, what they are, and how they are applied.

[i] Van der Heijden, Kees. Scenarios.

[ii] Kelly, Eamon. Powerful Times. Page 14.

To engage in more discussions about the future of business, please join the Listening to the Future community on facebook.

The National Academy of Engineering has launched its open innovation project to start thinking about how to address the new Grand Challenges that a select committee believe are crucial to the century ahead.

Here are the Grand Challenges for engineering as determined by a committee of the National Academy of Engineering:

• Make solar energy economical
• Provide energy from fusion
• Develop carbon sequestration methods
• Manage the nitrogen cycle
• Provide access to clean water
• Restore and improve urban infrastructure
• Advance health informatics
• Engineer better medicines
• Reverse-engineer the brain
• Prevent nuclear terror
• Secure cyberspace
• Enhance virtual reality
• Advance personalized learning
• Engineer the tools of scientific discovery

They are taking open comments on these ideas. Here was my first post:

I think we need a more distributed, organic method that integrates public policy makers, citizens and the organizations that co-exist in a given area. Rather than pushing the burden to over burdened government, we need bring together stakeholders in a way that may drive this to a very very local level - not just streets, but community association, even individuals. Yes, there are grand needs for large improvement, but even those can be more effectively handled in an organic way by seeking emergent planning and construction methods.

Think about putting a city's infrastructure into a computer, modeling the current needs and then projecting, using scenario planning, along multiple different futures, and then have the system evolve, using genetic algorithms or some other process, a plausible plan within the constraints. In this way, science can help depoliticize the planning process and providing transparency into how various constraints: natural, technological and political, were handled in the various models. The system could even look at financial capabilities and search for funding models from available sources, and while also suggesting a timeline.

This does beg the issues of many science fiction stories in which a computer plans the future and people simply accept its dominion over them. I am suggesting here, that software is capable of being an effective tool in negotiating human issues often fraught by imperfect information. Not only does the software provide emergent views of the future, but it can provide the forum for negotiation and cooperation – perhaps brokering an auction among interested parties for paying for various portions of a project – those who choose to live on an island end up disproportionately paying for a bridge, but may have little to do with a rural road hundreds of miles from them. The model can also look at things like wealth distribution and wear, so that perhaps the rural road, given less traffic, doesn’t get addressed as often unless there is a natural disaster.

If all the power lies with the political infrastructure, they physical infrastructure will always suffer. We need to find ways to bring rational alternatives to the table that go well beyond competitive bidding by several interested contractors who are never as apolitical as they may seem. And then of course, we will need to write the software to look for bias in software models, which isn’t on the list of big challenges, but may be one of the next ones.

I encourage you to get involved. I don't know where this will go, but they have raised important issues, and, as I mention in my post, they may have missed a few implications. They need to ask the question: if we solve this, what new challenges does the solution create? An important question to any quest like this.

A futurists work is never done :)

After my lengthy commentary on the BusinessWeek Future of Work series (see their articles here: The Future of Work) I think it is only fair that I put down my expectations for an article that purports to forecast the future.

1. Tell people what you don’t know. This creates a great list of items for multiple outcomes and it really make it look like you did your homework. Pretty simple: here are the areas where prediction leaves use with near complete uncertainty, and here is a range of possible outcomes.
2. Don’t just write the article. Too hard to find the forecast. Have multiple industry  pundits and other knowledgeable people comment on how things might turn out, and then use the those fancy print capabilities to visually map the possibilities for people. Be sure to include, in the commentary, the trigger events that people think will cause their forecast to happen (or not to happen)
3. Disclose the framework for the forecasts. A long list of articles with no connective tissue is useless for decision making. If everybody isn’t using the same framework (say a shared set of scenarios) then the predictive power, and decision making ability of the forecasts again, are nearly useless.
4. Highlight disagreement. On some topics (and I know print media is limited compared to the web) print opposing points of view. Give people information about the reasons that people believe what they do and make it clear that the consensus is or isn’t there on a particular forecast.
5. For polling, don’t ask people what they think will happen. Interesting, but not that useful. Rather, design the survey so that the answers indicate certain characteristics about the future that may be different than the questions themselves. Remember, questioning people about the future from a finite list of choices means the survey has systematically eliminated innovation, because only the things they thought about are in the survey. Also, most surveys presuppose a single future, and therefore do not provide any insight about alternative futures based on trigger events that would shift the entire context (open global markets vs. a sustained economic cold war, vs. a real war, vs. some regional mix – answers to questions would be different if the future was different. For instance, the survey said most people were worried about China. In a particular future, the quality issues facing China may lead to a decline in their economic strength. If that future is presented as an alternative, the survey results are likely to be very different than the current commonly held belief that China will be the economic superpower of the 21^st Century.

So if you are forecasting, or reading a forecast, take this as a high level  list of things to look for. If you don’t see them, then take the forecast with a grain of salt (all forecasts should be taken with a grain of salt, but if you follow this list, at least the underlying faults in the forecast will be transparent.)