Haas@Work Blog

  • Seeing Beyond the Headlights Foresight work in the era of exponential change

    by Dave Rochlin

    Seeing Beyond the Headlights

    Foresight work in the era of exponential change

    foresight blog post photo 1 

    It is becoming widely acknowledged that we are moving into an era of disruption driven by exponential technology change. As John Hagel and John Seely Brown describe it, “The cost-performance of three core digital technology building blocks—computing power, storage, and bandwidth—has been improving at an exponential rate for many years. As the rate of improvement accelerates, we are experiencing rapid advances in the innovations built on top of these core technologies. The current pace of technological advance is unprecedented in history and shows no signs of stabilizing as other historical technological innovations, such as electricity, eventually did.”[1]

    This creates significant near-term disruptive potential, as industries  become increasingly digital dependent and traditional boundaries between industries and specializations dissolve.

    If true, this represents an emerging existential threat for many firms, since the ability to see and act on this sort of transformational change has not moved at the same speed. Traditional innovation and strategy tools may leave firms following linear models that do not positioning them to adapt to rapidly changing value delivery or shape their industries.

    Granted, not everyone is a believer. As Thomas Kuhn pointed out, even in science, paradigm shifting evidence is often discounted – and refuted – in favor of incremental discovery.[2]  But among the converted, the question that has come up most often to me is “OK I’m convinced…so now what?”

    One answer is the use of foresight work, which focuses on understanding potential long term external shifts in relation to internal capabilities. Future-gazing is not new, but it’s moving from the peripheral domain of the futurist-provocateur to a vital tool for developing strategy.

    Foresight work goes hand in hand with exponential thinking – I would call it the connective tissue between belief and action. So along with several colleagues, I recently led a group of 250 Berkeley MBA students and 20 innovation executives through a foresight sprint in order to explore how effective this approach is in identifying and addressing change and opportunity.

    A Foresight Design Sprint Takes Shape

    In developing our foresight ‘sprint’ methodology, we consulted foresight thought leaders at Institute for the Future, Deloitte Center for the Edge, Singularity University, Arup, and Idea Couture.  Rather than guessing at the future, they all use methodologies rooted in the present. This is consistent with both Peter Drucker and Gary Hamel’s views that the future can be imagined based on changes that are already underway.

    A basic premise of foresight work is to “leap into the future” using the signals around us to identify significant drivers of change.

    So, a basic premise of foresight work is to “leap into the future” using the signals around us to identify significant drivers of change.

    To prepare, we held a set of “pre-sprint” student and company sessions to develop signals, which we defined as “small or local innovations or events that catch our attention, and potentially point to larger scalable implications.” Because of the large size of the group, we very quickly generated 500. Clusters of signals start to tell a bigger story about the future[3] – referred to as likely drivers of change – and we curated the signal clusters into key drivers for our sprint work.

    As an example, Amazon Echo, Google’s Android voice and push platform capabilities, and “employee-free” stores,  were identified as signals that “more automated and predictive consumer interfaces” are on the horizon. This driver crosses industries, and has largescale implications on the economics of a variety firms and how they will compete. Some of the technology drivers that emerged from the signaling work focused (perhaps unsurprisingly) on artificial intelligence, IoT, robotics/automation, and predictive analytics.

    For our actual design sprint, teams were assigned to work with different corporate partners. They focused first on using the drivers to identify potential new opportunities and market demand that may emerge by the year 2027. Teams then designed future state offerings to tap into these.  In some cases, these connected back to the company’s current capabilities and interests, and in others they imagined that change would be driven by new entrants. What was most surprising was the myriad of potential ways in which the student teams envisioned emerging technology platforms and capabilities transforming and disrupting medicine, transportation, food, retail, energy, entertainment, and other industries in the years ahead. Most of the partner executives, already anxious about the speed of change, left with a heightened urgency.

    foresight blog post photo 2

    Photo Credit:    Jim Block

     

    Gazing “Beyond the Headlights”

    An apt metaphor for what is now occurring (e.g. exponential/accelerating change) is to think in terms of a car driving at night.  Car headlights are specifically designed to allow you to see ahead safely based on traveling a normal speed, and react to obstacles and turns as needed. But what works at 60 mph does not work at 200mph. What if we are already traveling at this higher speed and have not realized it yet? We can still see ahead – but no far enough to react to the changes before they are upon us. New types of headlights (tools) are needed to cover the necessary extra distance.

     

    “Within the headlights”, the standard management tools for setting an innovation path are ‘sensing’ and ‘seizing’:  Sensing to identify opportunity and threats, and seizing to act on them.  There are actually three types of headlights typically used to watch the road ahead:

    • Fog Lights (looking roughly 1 year out) are usually in the domain of the business unit, and focus on short term incremental roadmaps and modifications to the business, using market signals and voice of customer.
    • Low Beams (looking 1-4 years out) are often the domain of innovation teams, looking at new offerings, business models, and platform shifts. Effective innovators use tools such as design thinking, technology scouting, and innovation funnel management to develop proof of concept, plans, and freedom to operate for the firm’s next big thing.
    • High Beams (3-5 years out) are in the realm of strategy teams – focusing on direction, competitive advantage, capabilities, and resources.

    foresight blog post photo 3

    Most planning and strategy work in large companies uses the current state of the business as an anchor point. This “present forward” mindset”[4] creates an innovation emphasis on extending the existing business paradigm – e.g.  looking “within the headlights” – focusing on the area ahead and to the side that is illuminated by traditional sensing tools.

     

    But as our sprint demonstrated, the horizon of future possibilities often contains many new market spaces not on the linear path. More radical transformation (organizational redesign, business model change, external shaping, etc.) is often required to address these longer term more disruptive shifts.

     

    Some of these spaces – from cloud computing/SaaS to sharing economy models – are already radically changing some industries. An accelerating rate of technological change means that traditional models need to be supplemented across almost all industries as these emerging white spaces multiply.

    Thinking Beyond Technology

    Of course there are also other non-technological factors that dictate technology adoption and diffusion.  As Ford puts it in their annual trends report[5], “In a world of constant, dramatic change, companies must keep one foot firmly grounded in the now and the other firmly grounded in the next…Ford look(s) beyond the auto industry to comprehend what’s happening in social, technological, economic, environmental and political arenas, and creates a blueprint to understand how these trends are expected to influence products and brands for the next year and beyond.”

    Like Ford, our foresight sprint used the common STEEP framework to identify a wide variety of significant drivers of change beyond just technology shifts. This covers Social, Technological, Economic, Environmental, and Political shifts. As with technology, the other drivers are developed by first identifying signals – those interesting changes that are rising above the noise to alert us of disruption – if we know where and how to look.

    Ford tracks a variety of non-technology drivers, such as time poverty, aging, and urbanization in order to understand shifting market opportunity.  Our MBAs identified these as well as many other thought-provoking drivers that may inform technological change. Some of the more interesting ones included de-monetization, radical transparency, and the growing bifurcation of markets between low-cost universal technology at the bottom of the pyramid and the more advanced technology for “the 1%”.  These other drivers had a significant impact on the use cases develop by teams.

    Other Lessons learned

    Achieving buy-in

    The Haas groups did most of the sensing work, and therefore had more ownership of the future-state inputs used for the concept work. Really believing /embracing the trend work is a key to believing and acting on the disruptive implications of the output.

    Identifying the right “distance”

    We set our Sprint at the year 2027 – ten years out. While gazing even further is more provocative, we felt that this would encourage disruptive but pragmatic thinking. But the challenge we faced was too much pragmatism – one of the key facilitation roles was to push the teams from safer linear/incremental concepts into more disruptive and less certain ones.

    Scenario planning similarities and differences

    Clearly, there can be many versions and visions of the future, and beyond the headlights lies a range of uncertainties which makes action difficult. The difference is that rather than imagining the future from the present as scenario planners often do, foresight work seeks to develop strategy working backwards from the future. As Mark Johnson points out, “The future back process yields a way to create strategies that look beyond what leaders can see now…Without it, there’s no real plan for a different future.”[6]  The idea is vision rather than probabilistic certainty, and consideration of where the firm’s opportunities and vulnerabilities may lie. This wide aperture goal needs to be explicitly stated.
    Conclusion

    The reality of corporate life is that we must “feed the beast” of incremental growth, even while looking out for more disruptive change. Ambidextrous organizations seek to “pioneer radical or disruptive innovations while also pursuing more incremental gains.”[7]  This is a difficult challenge, since doing so requires the need to pay attention to the firm’s key assets and capabilities for the latter, while ignoring them for the former.

    My colleague David Teece points out that “In large established organizations, transformation… requires breaking conventional modes of thinking.” But he believes that it “often takes a crisis” to activate companies to do so.  Simply waiting for crisis does not seem to be the most practical method for ensuring future capabilities and viability. Traditional sensing and seizing work – whether based on design principles, iterative lean launchpad type methods, or other models – provides fuel for the traditional innovation funnel. By applying foresight tools – looking at signals and drivers of change, imagining new white space, and considering disruptive shifts – firms can also more effectively look beyond existing markets and business models. As technology catalyzes and accelerates change, this will be an equally critical skill.

     

    [1] https://www2.deloitte.com/content/dam/Deloitte/es/Documents/sector-publico/Deloitte_ES_Sector-Publico_From-exponential-technologies-to-exponential-innovation.pdf

    [2] The Structure of Scientific Revolutions – Thomas Kuhn

    [3] IFTF

    [4] Johnson and Davis – A Future Back Approach to Creating Your Growth Strategy

    [5] https://social.ford.com/content/dam/campaign/media-trends/pdf/Ford-Trends-Book-2016-Interive.pdf

    [6] Johnson and Davis – A Future Back Approach to Creating Your Growth Strategy

    [7] The Ambidextrous Organization – Harvard Business School  O’- Reilly and Tushman, April 2004

  • Does Early Success Inhibit Innovative Thinking?

    by Dave Rochlin

    I’ve helped run at least two dozen innovation tournaments here at UC Berkeley-Haas, as part of various applied innovation courses (including ten simultaneous ones we recently fielded during our MBA Mid Program Academic Review Course.

    The goal of the tournaments is to demonstrate to students the power of iterative thinking and experimentation, as a tool for more impactful and innovative solutions. This is consistent with our overall “diverge/converge model”, which encourages broad exploration of both insights and ideas, before settling on either the problem to solve or the possible solutions.

    Problem-Finding-Problem-Solving

    The tournament format is designed to encourage this: We assign a client challenge (such as “how to accelerate smart home adoption” or “how to get more fans to attend football games”) to a group of 4 to 8 competing student teams, which each typically gather data for several weeks prior to the tournament. At the actual event, the teams present ideas for both problem frames and solutions to their client over the course of 8-12 rapid iteration rounds, modifying and elaborating after each round of client feedback. In many cases, we actually score the students after each around, on variables ranging from a clear problem frame, to the value proposition underlying the proposed solution.

    An interesting pattern has emerged among teams that win these tournaments: Those teams that start the strongest tend to improve only marginally though the rounds of feedback (see team one, below), while a winning profile typically resembles the trajectory of team two. Teams that have a rockier and perhaps slower start peak at the right time, and usually prevail. Based on feedback patterns in the early rounds, I can now usually identify by the half way point which team will ultimately be selected by the client.

    Scoring

    What are we to make of this?  There are few lessons that would explain this team/data pattern:

    The danger of converging too soon.   Rather than explore the range of possibilities, a team that defines and solves the problem immediately will naturally come up with a better initial solution. But they have created a box that limits further exploration and iteration. This behavior is common among real world business teams, which inadvertently focus on executing against good but not great solutions, or develop the right solution to the wrong problem.

    Internal focus.  Teams that solve quickly often use an inside out rather than outside in approach. This is often a mistake among novice design thinkers, who believe that a group of smart people can close themselves in a room with a stack of post it notes and solve for anything. Problem frames and solutions need to be evaluated constantly against the outside world.

    Lack of urgency. Success breeds complacency. Groups with variable feedback and lower scores tend to have some added urgency that drives them to work harder and take chances.  This same drive is often missing from groups who feel that they have “cracked the case” early.

     

    Tips for leaders in search of more innovative problem solving

    When a more innovative approach/solution is desired, leaders need to push their teams to diverge broadly during both the problem definition and problem solving phases. This includes seeking out feedback throughout the process, avoiding faulty processes – such as the urge to pull together a single meeting to solve open ended problems – and exploring multiple solutions rather than going all-in once a “good” solution is developed.  Not all issues and challenges are appropriate for this approach, but when more innovative thinking is the goal, finding the answer too quickly can be the enemy.

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