Creating strategic advantage with dynamic scenarios

by Anika Savage (formerly Audrey Schriefer) and Michael Sales

Anika Savage and Michael Sales are founding principals of Art of the Future (www.artofthefuture.com), a strategic management consulting firm located in Waltham, Massachusetts (anika@artofthefuture.com and michael@artofthefuture.com ).  This article provides the latest thinking and applications of the concept of Dynamic Scenarios that Audrey presented in Learning from the Future: competitive foresight scenarios, edited by Liam Fahey and Robert M. Randall (Wiley, 1998).

Introduction

Media guru and futurist, Marshall McLuhan, observed that “We drive into the future looking through the rear view mirror,” and this is as true in our strategic thinking about the future of work as in any other domain.  Because of the expectation that the future will be like the past, economic and social discontinuities frequently seem startlingly abrupt to those who are unaware of potential changes and are, therefore, unprepared. When this happens they discover too late that the rules of the game have changed permanently. 

By taking a structured approach to analyzing emerging trends, such unpleasant surprises can be avoided.  The Dynamic Scenario Learning Process™ (DSLP) is a tool executives can use to turn their attention toward the future.  This approach surfaces explicit and implicit assumptions, unconsidered myths, and unexplored possibilities.  It weaves information into usable narratives to guide business decision-making regardless of how the future unfolds. 

Elements of the DSLP will be familiar to any strategist with a background in futures thinking or in system dynamics.  However, the Dynamic Scenario approach represents a unique integration of these analytical frameworks that yields a powerful combination of insight and rigor.  The result: a set of compelling, influential stories that mobilize widespread support for clear, actionable strategies.  The approach has been successfully applied in a wide range of industries to many different types of business problems.

This article outlines the structure of the DSLP and then applies it to a composite case in the financial services industry. We will demonstrate how dynamic scenarios yield insights that may be counterintuitive but position the companies to take advantage of trends and uncertainties that competitors may be missing. 

Overview of the DSLP process

The Dynamic Scenario Learning Process (DSLP) consists of four interrelated phases:

• Analysis --  Examining the organizational context to identify and articulate a decision issue around which DSLP will be focused.
• Scenarios -- Gathering and assessing data, which are rigorously debated and crafted into scenarios.  We do this by identifying critical uncertainties, defining relevant trends over time and then examining the causal relationships between these key variables. 
• Dynamic Scenario Generator – Integrating causal relationships into a Dynamic Scenario Generator (DSG).  Using the DSG to identify key leverage points and generate scenario logics for plausibility and consistency.  Applying the DSG in the Strategy phase to understand clearly the dynamic impact of proposed actions by the company and its competitors.
• Strategies – Articulating and testing possible strategic actions within the context of the scenarios having the greatest potential for shaping a desired future and robustness in a wide range of future conditions.

Then, looping back to the analysis phase to monitor events in the external environment and assess the impact of strategic initiatives and competitive responses. 

Exhibit 1 shows that the DSLP process starts at the level of discrete observable events.  These events are put into context over time to identify the underlying patterns in the variables under consideration and the structure of these patterns.[i] For example: an observer might experience a series of earthquake tremors as discrete events, but in context they reveal a pattern of instability occurring along a fault line.  The structure is deep within the earth causing the fault line to appear on the surface.  The DSLP process is designed to see beyond events to discern their interrelationships and to understand how our actions will impact the system.

Exhibit 1:

Case study:  Forward Bank

A composite case study of several actual financial services industry projects illustrates how the Dynamic Scenario Learning Process works in practice. In this case –“Forward Bank” – the application of the DSLP was critical to the organization’s ability to thrive in difficult times. 

In 2000, Forward Bank was enjoying steady growth in its core business of regional banking and explosive growth in its investment banking business and key foreign markets; for the moment Forward was on a roll.  Forward’s Strategic Planning Group could sense from events in the financial services world that this situation was likely to change dramatically although they couldn’t say when or if it would be a smooth evolution or a dramatic discontinuity.  While it is never easy to convince an organization that their future operating environment may be radically different from the present, it is particularly difficult when times are good.  And yet, the Strategic Planning Group knew that this was precisely the right time to undertake such an initiative.  By the time disruptions start a chain of precipitous reactions, thoughtful long range planning is nearly impossible.

Evaluating the situation 

At that time, Forward was a $20B institution company involved in retail and commercial banking, investment services, including underwriting technology IPO’s, and capital equipment leasing.  It had about 70,000 employees worldwide working in approximately 32 million square feet of real estate. 

Regional banking, the core business of the enterprise, was pursuing a strategy of growing “wallet share” of existing retail and commercial customers in a mature market. Forward enjoyed a competitive advantage in technology applications through its extensive and sophisticated network of ATM’s, on-line banking applications for retail and commercial customers, advanced check-processing capability and excellent customer service response times. 

Forward’s investment banking business had been growing at double digit rates throughout most of the 1990’s due to it focus on technology.  Projections for this part of the business showed continuous expansion off the charts, ignoring any possible limits to growth.  Any suggestion that explosive growth might not continue was not culturally acceptable. This business line was eyeing significant expansion in very pricey markets including San Francisco, New York and London.  Forward’s real estate executives were ready to pay top dollar to secure prime office real estate to support the growth projections

The Bank allowed employees to work from home although there was no official policy.  As a result, everyone had an assigned workspace in a corporate facility, even those who came into the office infrequently.  Most functions and business lines felt strongly that they needed to maintain a significant presence at Forward’s headquarters to be near the seat of power.  Due to optimistic growth expectations, managers were extremely reluctant to give up any assigned space, even if floors were honeycombed with empty workspaces due to merger-related layoffs, home-based work and frequent travel requirements. Forward’s real estate group had calculated that they could save the bank $14 million annually in occupancy costs if they were able to improve the space utilization rate from 70 percent to 85 percent in the corporate headquarters city alone.

Leaders and managers in this go-go context saw no need to step back to take a long view.  In this case, Forward’s Strategic Planning Director risked her credibility by posing the following challenge to senior executives:

We are a large company and expect to be in business for a long time. We need to understand the conditions in which we will be operating and how we should be responding to them.

Through persistence and persuasion, she eventually succeeded in gaining the support of the CEO and the senior leadership team to initiate a scenario initiative.

Scenario planning, including the Dynamic Scenario Learning Process, embraces and thrives on divergent opinions and contrarian views.  Forward’s Strategic Planning Group and their consultants identified strategic thinkers from all parts of the business at all levels to comprise the scenario team.  This team of twenty included senior leaders and other key decision makers, junior employees with freshly minted MBA’s from top business schools, middle managers and individual contributors noted by their peers for their ability to think well beyond the current situation as well as their connections within the organization. In order that the scenario team could bring a broad perspective to the process, one that took into consideration the attitudes of the customer base, its composition was intentionally diverse in terms of race, gender, age, sexual orientation and national origin. 

In their first meeting, the scenario team shaped the following decision issue:

How should Forward’s long-term investments in real estate accommodate turbulence in the business environment due to shifts in economic cycles, composition of the workforce, new work styles, globalization, hyper-competition, mergers, partnering, outsourcing, off-shoring, and rapid developments in technology

Because the decision issue focused on long-term investments, 2010 became the endpoint for the timeframe under consideration.  A ten-year period would enable the team to assess the effects of decisions made in the present. 

Generating events

The scenario team and their consultants prepared for the Dynamic Scenario workshop by scanning news sources, conducting interviews with senior leaders, and using rapid ethnography [ii] to better understand some of forces at play in the current environment.   As the workshop got underway, the scenario team identified 100 events, which, if they occurred, would have a significant impact on the decision issue.  See Exhibit 4 for a sample of these events. 

From the full list, the team considered whether any events were foreseeable -- that is, with sufficient research they could safely predict how the underlying variable would perform in the future.  For example, the team found that by 2010 oldest baby boomers would begin to retire and there would not be enough young people entering the workforce to replace these skilled and knowledgeable workers [iii].  Such events reveal “facts” about the future that the team would weave into all the scenarios. 

Of particular interest to the core team were those remaining events that would exert a significant impact on the decision issue and yet were highly unpredictable.  The team debated the potential impacts of various events and decided which were the most critical and which were the most uncertain.
 

Exhibit 4: Sample Events

For the key critical uncertainties, the team sketched the historic behavior of the underlying variable to create graphs depicting the trends over time, based on both data they gathered and on their experience. Where the variables were thought to be affecting each other, they were sketched on the same axis. See Exhibit 5 for an illustrative example of some of the interacting trends the design team studied.

Exhibit 5: Trends over time

Each of the key variables mapped as trends could exert a significant impact on Forward’s real estate decisions. 

Depicting cause and effect relationships

The trend-over-time graphs indicated cause and effect relationships between the variables.  Forward’s scenario team concentrated its analysis on the most critical and most uncertain variables they had identified.  The team produced cause and effect diagrams for each of these key variables that showed how other variables affected them and also those variables that were influenced by them. For an example, see Exhibit 6 for the cause and effect diagram described below:

• Cost of telecommunications goes down as innovative technical solutions emerge.  As the cost to communicate falls, virtual collaboration (remote work) is likely to increase, creating new demand for technologies and driving down the costs further.  Off-shoring increases virtual collaboration, and virtual collaboration introduces all sorts of spontaneous interactions. An arrow with an “o” indicates that the variables move in an opposite direction, e.g., as telecommunication costs decrease, virtual collaboration increases.  An arrow without an “o” indicates that the connected variables move in the same direction.  

The core team identified and sketched many causal relationships as preparation for considering the dynamics of the entire system.

Exhibit 6: Cost of Telecommunications

Constructing the Dynamic Scenario Generator™

Having diagramed the causal relationships between variables, the team created a Dynamic Scenario Generator (DSG) by linking variables that appeared in more than one cause and effect diagram. The DSG is a model of the system under consideration.  It can be used to generate multiple scenarios.  [See Exhibit 7]

Using the DSG, the Forward team discovered crucial inter-relationships that were not intuitively obvious because they were not directly related.   For example, they realized that a resurgence of physical collocation of workers could lead to the revitalization of cities. They also saw that soaring energy prices or a high level of security threats could also drive urbanization.

The Dynamic Scenario Generator is the heart of the Dynamic Scenario Learning Process.  It assures that the scenarios generated in the DSLP are logical and internally consistent because they derive directly from this causal analysis.

Exhibit 7: Forward Bank’s Dynamic Scenario Generator

Developing Scenario Themes

The DSG suggested very different futures that were equally plausible depending on assumptions posited about key variables.  For example, the constellation of variables around collocated workers seemed to suggest a theme of high powered interaction among knowledge workers based on spontaneous interaction and social relationships.  A trend toward greater collocation of highly skilled workers would impact other variables such as levels of knowledge sharing and innovation. 

By debating the effect of plausible and powerful “shocks” to key variables, the team selected three themes that would generate very distinct scenarios. 

o       Radical technical innovation – Here the team assumed that innovation was intense, leading to radical new products and processes. For example, the advent of very low cost, full-featured video terminals advanced the effectiveness of virtual collaboration.

o       Increased levels of terrorism, insurgency and crime in developed countries – the assumption here was that industrialized countries would have to face a new, harsher reality because of increased terrorism, insurgency and crime.

o       Resurgence of physical collocation of skilled workers – The team explored the implications of potential research findings indicating that physical collocation of skilled workers stimulated knowledge sharing and increased productivity.  They found this led to a resurgent trend toward collocation despite the capability of working remotely. 

The team traced the impact of these “shocks” to key variables throughout the system depicted in the DSG.

Developing scenario logics

In each scenario theme, the “shock” caused the other variables in the system to respond.  Tracing the impact of the shock throughout the DSG, the team documented the effect on every variable and, thus, created a set of logical frameworks for differing scenarios.  See Exhibit 8 for an example of the Scenario Logics that the Forward team developed. These logic frameworks became the basis for narrating the scenarios.  

Exhibit 8: Sample of Forward Bank’s Scenario Logics

Crafting the scenario narratives

With the logics derived from the DSG in hand, it was easy for the team to generate scenario narratives with internal consistency.  Good scenarios involve variables interacting in plausible yet, often, surprising ways. The teams gave each scenario an appropriately memorable name.

Here’s a sample of the scenario narratives:

• Internet II (based on the “Technical Innovation” logic)

In 2008, a new powerful version of the Internet was launched enabling both virtual commerce and leisure activities and surpassing all but the wildest of imaginations that existed in 2000. Virtual presence--using a wide array of devices anywhere in the world, accompanied by instantaneous translation--all but negated the need for physical presence. This spurred further leaps in innovation, both social and technological.  For example, creative knowledge workers all over the world began to form new societies based on knowledge, skills and interests rather than geography.   Their “radical virtual collocation” initiated a long economic boom that undercut the appeal of terrorism and exponentially increased confidence in the global system’s ability to survive and thrive.

• Code Red (based on the “Terror, Crime & Insurgency” logic)

This scenario occurred in two stages. First, a wave of seemingly random terrorist attacks hit developed countries; then an upsurge in radical insurgency occurred, both in known “hot spots” and also in affluent countries with minorities that felt oppressed. When these attacks and uprisings were accompanied by looting and other crimes, confidence in “the system” eroded, and people throughout the developed world longed for security.  Investor confidence was shaken, business expansion suffered, and risk taking by business entrepreneurs declined. As a result, fewer skilled workers were needed.  By 2010, the U.S. was in a deep recession as wars between the West and several Islamic nations continued to drag down their economies.  Meanwhile, Japan and China thrived.

• Creative Beehive (based on the “Physical Collocation” logic)

In 2006, research jump-started this scenario by demonstrating that collocation of knowledge workers was essential to innovation and productivity.  Simultaneously, technological advances made it possible for geographically dispersed teams of coworkers to collaborate seamlessly.  Urban centers and towns were revitalized by these findings, which the federal government incorporated into its funding standards for all agencies by 2009.  As a result, of these incentives, vast sums of money went toward urban renewal, which led to even higher levels of innovation.  Because the threat of terrorism continued, security remained a paramount issue and people felt safer within protected cities and towns.

Proposing scenario strategies

The scenario team then broke into smaller groups, each one focusing on one of the scenarios.   While it is recommended that senior decision makers participate in the entire DSLP to get the full benefit, it is possible for them to join at this stage to review the scenarios, make suggestions for improving and deepening them and, then, get involved in the development, testing and implementation of strategies. 

Each small group proposed strategies that might work in their particular scenario.  They used the DSG to trace the effects of their proposed actions throughout the system and to model competitive reactions.  Those strategies that were deemed effective were designated “scenario strategies.”  In Code Red, for example, if unprepared competitors were caught up in a frenzy to unload seemingly excess properties, Forward might seek to obtain favorable lease terms.

Stress testing the strategies

To test the scenarios strategies in all the scenarios, each scenario group selected “ambassadors” to visit the other scenario worlds to explain their own group’s strategies and consider how they would play out in the alternate scenario worlds.  Again, the DSG was used to test the logic.  The team also stress tested all of Forward’s existing strategies in each scenario. The results of the stress testing were collected in a strategy matrix similar to the sample below in Exhibit 9.  The cells of the matrix provide brief descriptions of how well each strategy works in each scenario. 

Identifying robust strategies

By reading across the rows of the strategy matrix, the scenario team found some strategies that worked well in all scenarios worlds.  For example, the team recommended that Forward’s portfolio of leased space be a mix of short- and long-term leases to take advantage of market conditions and to allow the bank to expand or contract as the business required.  They also found that flexibile lease options were highly desirable and cost justified because of the turbulence anticipated in each of these scenarios.  They found that Functional Integration (by implementing a series of dialogues across HR, IT, RE, Finance, etc.) to address work/life issues was successful in all of the scenarios. Since none of their competitors was addressing work and workplace management in these strategic terms, the dialogues proved to be a significant source of competitive advantage.  Forward Bank chose to pursue these robust strategies with a high degree of confidence since they had proven to themselves that the strategies worked well in a wide range of plausible future conditions.

Exhibit 9: Sample of Forward Bank’s strategy matrix

Considering contingent scenarios

Often, the team found that strategies worked well in some scenarios but would have mixed results or be downright disastrous in others, for example, reducing the size of existing workspaces to save space.

The Forward team was particularly surprised to learn that the Bank’s current strategy of using Universal Plans (the offices, panels and furniture stay in place as groups move in and out) in all its newly renovated facilities had some validity only in the most economically austere scenario.  In other scenarios, the restraints imposed adversely affected productivity because employees needed to adapt their work processes and work styles to a pre-designed, fixed environment.

Implementing strategies and monitoring the environment

As implementation plans were developed, the team realized that they needed to monitor unfolding events in the external environment such as competitive response, technology innovations, and political, economic and social conditions.  For managers, this meant that reading the newspaper was never quite the same after experiencing the DSLP.  Relevant events became more obvious and the team could put them into the context of larger patterns of behavior and begin to perceive the underlying structure of an unfolding situation.  They were prepared to respond with carefully prepared strategies. In addition to workplace strategy, a number of decisions regarding “long horizon investments,” such as the recruitment and retention of personnel with highly sought after skill sets, became much more clearly framed as a result of the DSLP.  This created a significant advantage for Forward, especially when their competitors were caught by surprise by a sudden turn of events.

Evaluating the results

From the perspective of hindsight, the value of the Dynamic Scenario Learning Process for Forward was significant.  In 2000, at the time the DSLP started, the Director of Real Estate at Forward was having a very difficult time keeping up with the demands to expand the corporate footprint.  In fact, Forward was on the verge of making a commitment to a half million square feet of space under development in San Francisco when the dotcom bubble burst in March 2001.  Forward’s investment banking business crashed just as the Bay Area real estate market plunged. Overnight, the portfolio strategy switched from rapid growth and acquisition to urgent disposition.  Business line managers who had been screaming for more space were now in a panic to dump what they had, but there were no takers.  In the same year, Forward’s international operations took a nose-dive due to economic collapse in key markets.  Forward’s executives could see the bank’s stock price dropping on the elevator news video screens as they came into work each morning.

Although they did not offer specific predictions, Forward’s scenarios provided a year’s head start on understanding how to manage the dotcom collapse and the 9/11 attacks.  Because managers had considered how to implement the robust strategies and apply contingent strategies as unfolding events merited, they were better prepared.  For example, they had signed a number of short term deals as older leases expired to restructure the real estate portfolio. They had also vacated space a number of facilities at lease expiration in anticipation of a drop in space demand.  Having imagined the possibility of an economic downturn, they structured sale/leaseback deals to increase the percent of leased versus owned space (then 65 percent leased) to achieve a goal of 80 percent leased.  The terms of these deals allowed the Bank to phase out of these properties over time if they chose.  This provided additional opportunities to shrink the portfolio and, potentially, relocate to less expensive space in current markets or in near-shore or off-shore locations as business needs dictated. Some of the new spaces were located in revitalized urban cores that offered very attractive rents and plenty of activities to Internet II and Creative Beehive employees. The Functional Integration dialogue series they had initiated in 2000 between functional groups proved invaluable.  Because Real Estate, Human Resources, Finance and Information Technology executives had hammered out the details, Forward was able to quickly implement a telework policy that better supported remote workers and allowed Forward to recapture space in their facilities, saving nearly $7,000 annually for each home-based worker.

The power of dynamic scenarios

The DSLP process creates bonds within the organization as everyone from senior leaders to front line employees across business lines and functions share a common language to communicate their insights into future possibilities.  Narratives based on a DSG are easy to grasp and can be widely disseminated throughout the organization. 

Endnotes