Forecasting Change in Support of Innovation
Scenarios are structured narratives that explore possible futures based on
varying assumptions, trends, and driving forces. As Ogilvy (2015) suggests,
scenarios are possible futures in which the choices—sometimes referred to as strategies—made
currently could unfold. In this context, two well-known planning strategies
provide unique frameworks to support innovation and decision-making: scenario
planning and standard forecasting. While each of these planning
frameworks serves the function of informed decision-making, they differ
significantly in their structure to support the planning process and potential
outcomes. This paper examines various planning strategies and uses
Blockbuster's rise and fall as an example of how critical these concepts are to
maintaining relevance in rapidly evolving social-technical environments.
Planning Strategies
Scenario
Planning
Scenario planning is a methodology that constructs multiple, plausible futures
for entities by examining how different approaches to uncertainties and
complexities might unfold. Unlike standard forecasting, which typically
projects the future based on historical data, scenario planning acknowledges
that the future is uncertain and complex, requiring a degree of acceptable risk
and inherent flexibility. This notion is illustrated by Schoemaker (2004),
stating that scenario planning is a practical tool for handling
high-uncertainty, high-complexity environments. This suggests that scenario
planning is a suitable framework for handling innovative and disruptive
changes, as it acknowledges that futures are unpredictable and may not
materialize at all (Deloitte, 2022). Conversely, it also provides a roadmap for
entities to make informed predictions about potential futures and pivot
accordingly.
A recent study by Deloitte examines scenario planning and how the framework not
only reduces uncertainty in business environments but also increases
resilience. The research provides six reasons why entities should consider
scenario planning to avoid being caught off guard by disruptive shifts in
evolving environments (Deloitte, 2022).
- Supports
and enhances strategic decision-making in uncertain environments.
- Aids
in the innovation process by anticipating market shifts.
- Creates
a more sustainable and long-term strategy.
- Helps
generate a culture of flexibility and creativity.
- Aligns
key stakeholders under unified visions to help ensure business success.
- Gives
entities the agility to "course-correct" in shifting
environments.
While
scenario planning offers these unique advantages, it also presents challenges
as the method can be time-consuming, reliant on subjective assumptions, and
does not produce a single definitive outcome (Ogilvy, 2015). As a result,
translating scenarios into concrete actions—such as planning, resource
allocation, and implementing deliberate functional shifts—can be complex,
convoluted, and seemingly ambiguous.
Standard
Forecasting
Standard forecasting is a forward-looking process that aids decision-making by
identifying the most probable future outcome(s), supported by historical data,
to help guide entity efforts (see Figure 1). Ogilvy (2015)
differentiates between strategic planning and standard forecasting on the
futurist continuum by using a poker analogy where strategic planning is akin to
preparing for multiple hands to be dealt, while standard forecasting is an
attempt to predict how a player will respond to a specific hand, knowing the
previous actions of that player. This distinction highlights the role of
standard forecasting in narrowing down uncertainties through historical data to
inform a strategy, such as a mixed research strategy that confirms qualitative
findings through quantifiable means. Similarly, the London Premier Centre
(2023) reinforces this perspective by emphasizing that standard forecasting
helps organizations bridge the gap between current realities and future
aspirations. In doing so, standard forecasting translates conceptual visions
into actionable strategies, which enables organizations to make informed,
timely, and effective decisions.
Standard forecasting provides a structured, data-driven approach that is
particularly effective in stable environments, where historical data trends can
effectively inform future outcomes. The strength of this method lies in its
ability to generate actionable insights across various business strategies and
functions, thereby supporting informed decision-making. However, standard
forecasting is not without its limitations, as overlooking disruptive events
that do not follow historical patterns can leave an entity vulnerable to
unexpected changes. Additionally, overreliance on quantifiable data can lead to
significant gaps in the strategies' ability to forecast effectively.
Nevertheless, employing standard forecasting can be an effective planning tool
for entities that understand how data-driven approaches help inform actionable
plans.
Figure
1
Scenario
Planning and Standard Forecasting
Note. From Scenario Planning: A Useful
Tool for FP&A, by Piyush Handa, 2021 (url:
https://fpa-trends.com/report/scenario-planning-useful-tool-fpa)
Forces
of Scenario Planning and Strategic Forecasting
Social and technological forces have a profound influence on scenario planning
and standard forecasting by shaping their relevance and effectiveness in
strategic decision-making. According to Nowak and Vallacher (2018), shifting
social dynamics, such as consumer values, demographic trends, or regulatory
changes, are inherently unpredictable and often exhibit nonlinear behavior.
Thus, planning frameworks that do not account for these societal shifts can be
misleading in the context of rapid social change. Scenario planning excels in
this context by enabling organizations to envision a range of plausible futures
that encompass a broad spectrum of societal outcomes. This flexibility enables
entities to better prepare for both gradual shifts and abrupt market
disruptions. In contrast, standard forecasting is inherently linear, as it
relies on historical data for scenario predictions, which can overlook and under
plan for sudden shifts in public sentiments or policy reforms. As a result,
standard forecasting can miss transformative social developments that do not
align with previous historical trends.
Technological changes are marked by rapid innovation and uncertainty, which
further differentiate scenario planning from standard forecasting. During the
COVID-19 pandemic, organizations were compelled to rapidly adapt to the
evolving economic shifts, healthcare concerns, and regulatory changes that
resulted from the virus's impact (Clipper, 2020). As such, information
technology solutions that offer work-from-home options have become critical for
business operations and success. Scenario planning is well-suited for exploring
the uncertain trajectories of emerging technologies, such as the adoption of
artificial intelligence (AI) during the COVID-19 pandemic, by modeling
diverging paths across different possibilities (Clipper, 2020). This type of
divergent planning enables organizations to remain agile in the face of
unforeseen disruptions, such as those experienced during the pandemic. Standard
forecasting, however, often fails to capture these nonlinear evolutions because
it assumes scenario continuity based on historical performance patterns. While
this method does provide actionable insights into a stable environment, its
utility is diminished when disruptive technological events occur. These
planning methods are best blended to enable entities to manage and plan for
both short-term and long-term scenarios, which are supported by data-driven
trends anticipated in response to market shifts.
Blockbuster: A Planning Case Study
Rewinding the clock to Blockbuster's dominance in the early 2000s, the case
study exemplifies how reliance on standard forecasting measures, grounded in
historical data, can severely inhibit an organization's ability to adapt to
disruptive technological change. During the peak of Blockbuster's reign, the
business model was heavily reliant on late fees and brick-and-mortar operations
(Davis & Higgins, 2013). At the time, these factors seemed profitable and
stable within the standard forecasting framework; however, at the turn of the
century, this all changed. In 2000, Netflix, now a $28 billion giant, proposed
a partnership with Blockbuster, where they would promote Blockbuster's brand
online through a subscription service. Sitting atop the rental retail market,
Blockbuster dismissed the offer because it viewed Netflix as marginal, but also
undermined Blockbuster's current business model, which relied heavily on
penalizing its customers (Satell, 2014). This decision was representative of a
standard forecasting approach, which emphasized historical continuity over
optimizing business for innovation. In the years to come, the threshold model
of innovation diffusion rapidly propelled Netflix, a small and seemingly niche
technology, into becoming a threat to Blockbuster's rental business, which
standard forecasting models would fail to predict. While Blockbuster attempted
to counter this threat by investing in video game platforms and online rentals,
it eventually went bankrupt, conceding to Netflix's innovative technology and
business model (Davis & Higgins, 2013). Netflix's model was to eliminate
late fees through a subscription-based model, which ultimately reshaped
consumer expectations, behaviors, and the video rental industry.
Stepping back in time, had Blockbuster employed a scenario planning framework
as a strategic tool, the business could have been better equipped to explore
plausible future alternatives for digital delivery mechanisms. Scenario
planning would have encouraged business leadership to consider the evolving
social and technological shifts, such as consumer tolerances, internet
adoption, or consumer habits. Additionally, scenario planning could have
fostered a more resilient decision-making environment by challenging the
current business model, thereby avoiding the risk of "putting all the
eggs in one basket." Instead, Blockbuster's internal resistance to
change and its seemingly rigid business model hindered the acceptance of
digital innovations, which ultimately contributed to its decline. The failure
to model divergent futures and account for disruptive technologies underscores
the limitations and catastrophic effects of standard forecasting when faced
with dynamic social-technical ecosystems.
Scenario Planning for Future
Innovations and Social Impacts
Scenario planning can serve as an essential framework that enables the
development of structured yet flexible situations that account for realistic,
divergent futures shaped by disruptive technology and evolving social impacts.
For instance, the Department of Commerce's (DOC) Office of Information and
Communications Technology and Services (OICTS), where the author is currently
employed, publishes an annual technical prioritization table that guides the
offices' technical initiatives (Department of Commerce, 2024). By employing the
scenario planning framework in this strategic environment, the federal
government can effectively forecast new and disruptive technologies, preparing
the legislative space for possible actions against transactions that pose a
significant threat to the United States. Rather than relying on historical
trends, scenario planning facilitates the exploration of futures, each of which
reflects varying degrees of uncertainty, disruption, and innovation. This
approach has proven helpful in environments that attempt to navigate a complex
and evolving space where linear forecasting methods are insufficient.
Nevertheless, by anticipating a range of possible outcomes, scenario planning
supports strategic decision-making that is resilient, forward-looking, and
resistant to unexpected shifts in the social and technical environments.
Scenario planning inherently accounts for the social impact of change by
integrating potential futures into a flexible business model, and therefore, is
better equipped to adapt to evolving social norms, behaviors, and expectations.
This framework transitions from viewing societies and technologies as static,
predictable entities that can be accounted for through quantifiable means into
dynamic and evolving spaces that require divergent futures to account for
unexpected, unanticipated changes. As public sentiment, regulatory
environments, and consumer values shift, scenario planning ensures that
strategic models remain responsive and alert. This type of dynamic
responsiveness enables organizations to proactively assess the implications of
disruptions and innovations, not only from a technological or economic
standpoint, but also from a societal perspective, thereby fostering more
sustainable and ethically informed innovation outcomes.
Conclusion
Scenario planning and standard forecasting are applied planning frameworks that
enable entities to forecast possible futures, supporting the decision-making
process. Scenario planning constructs multiple, plausible futures that enable
entities to navigate uncertainty and complexity, which makes it effective in
anticipating disruptive innovations and shifting societal norms. In contrast,
standard forecasting relies on historical data to predict the most probable
future, offering a more structured approach in stable environments but lacking
adaptability in the face of sudden technological or societal shifts. Through
the case study of Blockbuster's decline and Netflix's rise, this paper
illustrates how overreliance on standard forecasting creates a rigid business
model that is inadequate for adapting to technological disruptions and shifting
consumer behavior. The analysis underscores that scenario planning could have
enabled Blockbuster to model alternative futures and respond more effectively to
social and technological shifts. Additionally, scenario planning is not limited
to business environments, but has a place in the regulatory space—as
illustrated by the DOC example. Scenario planning positions itself as a
forward-looking adaptive framework that not only supports innovation but also
accounts for evolving technology and social trends.
References
Clipper,
B. (2020). The influence of the covid-19 pandemic on technology: Adoption in
health care. National center for biotechnology information, 18(5),
500-503. doi:10.1016/j.mnl.2020.06.008
Davis, T., & Higgins, J. (2013). A blockbuster failure: How an
outdated business model destroyed a giant. Retrieved July 27, 2025, from
www.ir.law.utk.edu:
https://ir.law.utk.edu/cgi/viewcontent.cgi?article=1010&context=utk_studlawbankruptcy
Deloitte. (2022, June 23). Scenario planning reduces uncertainty,
increases resilience. Retrieved July 26, 2025, from
www.action.deloitte.com:
https://action.deloitte.com/insight/2230/scenario-planning-reduces-uncertainty-increases-resilience
Department of Commerce. (2024). Commerce department prohibits certain
connected vehicle technologies with a nexus to the prc and russia.
Retrieved July 27, 2025, from www.bis.gov:
https://www.bis.gov/OICTS#2024TechnologyPrioritization
Handa, P. (2021, May 24). Scenario planning: A useful tool for
fp&a. Retrieved July 27, 2025, from www.fpa-trends.com:
https://fpa-trends.com/report/scenario-planning-useful-tool-fpa
London Premier Centre. (2023, November 20). Strategic forecasting: A
guide to better decision-making in organizations. Retrieved July 08,
2025, from www.lpcentre.com:
https://www.lpcentre.com/articles/strategic-forecasting-a-guide-to-better-decision-making-in-organizations
Nowak, A., & Vallacher, R. R. (2018, August 22). Nonlinear societal
change: The perpsective of dynamicla systems. British journal of social
psychology, 58(1), 105-128. doi:10.1111/bjso.12271
Ogilvy, J. (2015, January 08). Scenario planning and strategic
forecasting. Retrieved July 08, 2025, from www.forbes.com:
https://www.forbes.com/sites/stratfor/2015/01/08/scenario-planning-and-strategic-forecasting/
Satell, G. (2014, September 05). A look back at why blockbuster
really failed and why it didn't have to. Retrieved July 27, 2025, from
www.forbes.com:
https://www.forbes.com/sites/gregsatell/2014/09/05/a-look-back-at-why-blockbuster-really-failed-and-why-it-didnt-have-to/
Schoemaker, P. J. (2004). Forecasting and scenario planning: The
challenges of uncertainty and complexity. In D. J. Koehler, & N. Harvey, Blackwell
handbook of judgement and decision making (pp. 274-296). Blackwell
Publishing. Retrieved July 08, 2025, from
https://books.google.com/books?hl=en&lr=&id=s73eYl1DRHUC&oi=fnd&pg=PA274&dq=scenario+planning+and+strategic+forecasting&ots=ngOxhCnnkp&sig=C25x4DpaJgK0myXXV2K--SkpWco#v=onepage&q=scenario%20planning%20and%20strategic%20forecasting&f=false
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