A Sociotechnical Plan: Brain-Computer Interface

 Introduction: A Blackberry Story

In 1984, two engineering students with a passion for innovation founded a software and computer science consulting company known as Research in Motion (RIM) (Choi, 2023). In its early days, RIM was involved with a variety of technology projects in search of a viable market niche. Unbeknownst to RIM, this pivotal moment came in 1989 when a Canadian telecommunication company (i.e., Rogers) contracted RIM to help build a mobile text network explicitly designed for mobile messaging (Adit, 2023). This initial exposure to the mobile communications industry gave RIM a significant competitive edge. Roughly seven years later, in 1996, RIM introduced a groundbreaking two-way pager with an integrated email service; this device was the first to bear the now-iconic “Blackberry” name. Recognizing that digital communication would soon surpass fax, RIM focused its strategy on email capabilities, which became central to success in the business market (Time for Designs, 2023). Combined with its physical novelties, such as the QWERTY keyboard, and unconventional marketing techniques, Blackberry quickly captured a dominant share of the enterprise mobile device market.

Blackberry’s early success is a textbook example of a sociotechnical design as it integrated a transformative device into the social ecosystem and achieved initial success. However, the company’s fall from grace did not come from poor planning or execution, but from innovative competitors that entered the market and a failure to anticipate social norms and adapt quickly enough to this changing environment. As noted by Adit (2023), if “Blackberry had recognized the potential of touch features in smartphones and altered their design by eliminating the physical keyboard,” the company could have capitalized on this shifting trend in an attempt to maintain their mobile dominance. The launch of the iPhone in 2007 represented a paradigm shift in the mobile computing industry that introduced a prominent touchscreen, robust application store, better operating system (OS), greater media capabilities, and much more (Choi, 2023). Suddenly, users wanted faster OSs, touchscreens, integrated applications, and seamless interfaces, which were not at the forefront of BlackBerry’s design. As such, Blackberry underestimated this social transition and continued pushing its design on users (i.e., physical keyboard and sluggish OS) rather than listening to user needs, which, ultimately, led Blackberry to fall behind and never recover.

Sociotechnical Relevance

The Blackberry exemplar is relevant to my sociotechnical plan, which centers on brain-computer interfaces (BCI) as a new modality of communication and control between humans and hardware. Like Blackberry during its dominance, the sociotechnical plan assumes a well-defined social need for such an advanced technology, which is a wireless capability to control devices with neural-linked gizmos for purposes such as medical, accessibility, and potentially leading to productivity enhancements. Take, for example, a recent article showcasing Apple’s new BCI, which allowed a man with Amyotrophic Lateral Sclerosis (ALS)—a disease that affects the nerve cells controlling voluntary motor functions—to control an iPad using his brain signals (Salman, 2025) however, as we have learned with Blackberry, a revolutionary technology today could be obsolete tomorrow. As advancements continue, the sociotechnical environment may shift unexpectedly due to external forces beyond the innovator’s control. This signaling shift could show itself in various ways, such as a mass transformation in social ethics or an innovation that challenges the initial design and social acceptance of BCIs. Taking a lesson from BlackBerry’s history book, anticipating these sociotechnical shifts can serve as a technological safeguard against premature obsolescence.

Forces of Impacting Brain-Computer Interfaces

Two forces, though not inclusive, shape the BCI industry: technical limitations and ethical considerations. Technically, BCIs face persistent challenges such as neural signal variability, frequent decoder training due to neural plasticity or electrode micromovements, and the complexity of acquiring accurate, high-resolution brain data, which is especially difficult in non-invasive applications (Maiseli et al., 2023). These concerns of data reliability, device convenience, and user adoption could hinder the social acceptance of these devices. Furthermore, invasive BCI types introduce additional safety concerns, such as the risk of infection, tissue damage, and biocompatibility issues, where the body could reject a foreign device. Ethically, BCIs raise profound questions about cognitive privacy, informed consent, data ownership, and device security. The lack of standardized BCI regulations has allowed some BCI applications to access and process sensitive brain signals without clear user awareness or control, signaling significant concerns with privacy and possibly user autonomy (Maiseli et al., 2023). Without advanced encryption, access protocols, as well as regulatory and ethical oversight, these systems risk breaching personal mental data or becoming targets of cyberattacks. The public concern over security, privacy, and accountability could influence regulatory policy and social trust, which will undoubtedly have a significant impact on defining how, and whether, BCI technology can be integrated into society.

Summary

The use of the Blackberry case study as a sociotechnical exemplar is to draw lessons for the development of BCIs by examining Blackberry’s early success in its innovative and socially accepted product, while also examining its failure to adapt to the shifting social trends and expectations. Similarly, BCIs showcase promising medical, accessibility, and productivity applications, but face external forces that could hinder their adoption. The technical forces challenging BCIs originate from factors such as signal variability and device risks, which affect usability, reliability, and acceptance. These forces give way to the ethical concerns about privacy, security, and transparency, which become increasingly important as technology becomes more deeply embedded in cognition and other biological functions. As with Blackberry, failing to anticipate social and technological shifts could render groundbreaking technologies obsolete. This, in turn, emphasizes that BCIs must not only remain technologically and ethically grounded but also adaptable to the evolving social landscape.

 

References

Adit, S. (2023, April 27). The importance of evolving product design: A case study of blackberry's rise and fall. Retrieved August 06, 2025, from www.medium.com: https://medium.com/design-bootcamp/the-importance-of-evolving-product-design-a-case-study-of-blackberrys-rise-and-fall-5c21ceaf395a

Choi, A. (2023, March 26). Case study: The demise of blackberry. Retrieved August 06, 2025, from www.alfredchoi.ca: https://www.alfredchoi.ca/blog/case-study-the-demise-of-blackberry

Maiseli, B., Abdalla, A. T., Massawe, L. V., Mbise, M., Mkocha, K., Nassor, N. A., . . . Kimambo, S. (2023). Brain-computer interface: Trend, challenges, and threats. Brain Informatics, 10(1). doi:10.1186/s40708-023-00199-3

Salman, A. (2025, August 06). Apple's brain-computer interface lets man with als control an ipad using only his thoughts in groundbreaking accessibility and neural technology breakthrough. Retrieved August 06, 2025, from www.wccftech.com: https://wccftech.com/apple-brain-computer-interface-man-controls-ipad-using-thoughts/

Time for Designs. (2023, October 10). The fall of blackberry: How ignoring innovation led to decline. Retrieved August 06, 2025, from www.timefordesigns.com: https://www.timefordesigns.com/blog/2023/10/10/the-fall-of-blackberry-how-ignoring-innovation-led-to-decline/

 

 

 Introduction

Admittedly, I was not prepared for such a reflective post, as being unconstrained by time, money, and physical and mental abilities opens many possibilities to consider. In this scenario, it is easy to define what you have (i.e., time, money, and talent), but it becomes increasingly complex when we step back and consider how we will use these resources and what we will use them for. The concept of what the resources will be used for is grounded in whether the areas of choice serve the self, are selfless, or strike a delicate balance between the two. This, in turn, affects how these resources are used not just in scope, but in our intentions. If unconstrained by the concept of limited resources, it inherently forces us to ask more profound questions: What matters the most? What brings fulfillment? Where can we make the most significant impact? By reflecting on these different categories, I found that each contains a risk of selfish overindulgence, but also opportunities to grow, connect, and change the world.

Unconstrained Resources and Limitless Possibilities

If I had all the time, money, and talent in the world, I would, and in no order,

Education

·         Learn to play a musical instrument—likely a guitar.

·         Become fluent in Old Norse.

·         Earn a second doctorate in economics or psychology.

·         Write and teach a course on creative problem solving.

·         Enroll in flight school to become a pilot.

·         Learn how to weld.

·         Become fluent in the intricacies of offensive security.

·         Learn deep-sea diving in hopes of studying the depths of the ocean.

·         Study game theory and its application in strategic decision-making.

·         Learn advanced mountaineering techniques.

Job or Research

·         Start a research institution for next-generation military equipment.

·         Lead a planning program for Mars colonization.

·         Serve as the director of a university’s cybersecurity or research program.

·         Create a venture fund for startups in artificial intelligence.

·         Design predictive models for next-generation threat hunting.

·         Operate a high-risk, high-reward, DARPA-style research unit.

·         Lead a deep-sea or high-altitude exploration company.

·         Create and fund a search and rescue group.

·         Launch a global AI governance initiative.

·         Run an academy for innovators and next-generation security professionals.

Philosophical or Religious

·         Visit sacred sites aligned with historical battlefields.

·         Study the bible and visit religious sites.

·         Temporarily live and meditate with the Tibetan Buddhists.

·         Study Old Norse spiritual practices.

·         Create a podcast that weaves cyber-ethics with philosophy.

·         Host discussions on purpose, mortality, and ethics.

·         Create a sanctuary space that offers deep reflection.

·         Conduct a comparative study on different warrior ethos (e.g., Spartans and Vikings).

·         Build a digital archive of philosophical literature for security professionals.

·         Participate in a martial arts program that focuses on mind, body, and spirit.

Travel

·         Sail across the major seas on a wind-powered ship.

·         Explore the north and south poles.

·         Visit all the ancient wonders of the world.

·         Hike the Appalachian Trail and climb to the summit of Mount Everest.

·         Take a zero-gravity flight.

·         Explore the depths of the Mariana Trench.

·         Live among the Maasai people of Africa.

·         Explore ancient settlements.

·         Travel to an active volcano and explore extreme environments.

·         Live for six months in a remote location.

Home

·         Build a “study” that promotes innovation and research.

·         Construct a climate-controlled observatory called the Eagles Nest.

·         Add a meditation garden.

·         Develop a virtual reality room for immersive studies.

·         Design and build a workshop for ad hoc experiments.

·         Design a server room for cybersecurity research.

·         Create an archival-quality library for rare books, maps, and items.

·         Build a 3-mile-long heated lazy river around the house.

·         Construct a wind tunnel for artificial skydiving.

·         Add an aquarium with unique aquatic animals that are big enough for scuba diving.

Summary

These constructed realities reveal a deep commitment to exploration, innovation, and legacy, which is grounded in intentional design rather than excess, presumably. The pursuit of knowledge—old and new—and the mastery of physical and spiritual depths reflect a desire to understand and push personal limits while building an environment to help elevate others. Whether through launching bold research initiatives, studying ancient philosophies, or crafting immersive virtual reality environments at home, the underlying motivation is to help shape the future where intellect, occupation, and morality converge. This approach is about contributing to oneself and society, fulfilling personal curiosity, and constructing systems, experiences, and institutions that leave a meaningful and enduring impact on the world.

 

 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).

1. Supports and enhances strategic decision-making in uncertain environments.
2. Aids in the innovation process by anticipating market shifts.
3. Creates a more sustainable and long-term strategy.
4. Helps generate a culture of flexibility and creativity.
5. Aligns key stakeholders under unified visions to help ensure business success.
6. 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

 Introduction

Socio-technology theory is constructed upon the paradigm that people are more than mere extensions of machines, but rather complementary. As proposed by Abbas and Michael (2025), the purpose of a socio-technical plan is to conceptualize the underlying forces influencing both the social and technical aspects, and then optimize this relationship to achieve system success. These forces are distinguished through the concept of subsystems, which are interconnected, self-contained systems within a broader system. In a socio-technical system, Trist et al. (2016) identify three primary subsystems: the social, the technical, and the environmental. The social subsystem refers to the people; the technical subsystem refers to the "artifact;" and the environmental subsystem refers to the interaction between the social and technical subsystems. Conceptually, the social and the technical subsystems collectively operate within an environmental subsystem (i.e., surroundings, contexts, and conditions), which represents the effective interactions between the social and technical systems. These interconnected dimensions of socio-technical theory enable researchers to understand the distinct roles of each system and subsystem, as well as how they interact within a larger system, as discussed in the following socio-technical research on educational technologies.

Defining the Study

The research, "Affectability in Educational Technologies: A Socio-Technical Perspective for Design," introduces a socio-technical plan built around the "Semiotic Onion" framework. This framework integrates and embeds informal, formal, and technical modes to better conceptualize the introduction and adoption of technology, specifically the XO laptop from the One Laptop Per Child (OLPC) initiative, within a Brazilian public school (Hayashi & Baranauskas, 2013). The Semiotic Onion model reinforces the notion of systems and interconnected subsystems by acknowledging that each layer represents a critical piece to understanding how the entirety of the system functions. Rooted in qualitative research, the study's conceptual design explores the affectability dimension, which emphasizes participants' emotional, cultural, and affective responses to the technological artifact. The purpose of the study extends beyond simply distributing computing devices into an educational system; it aims to embed digital artifacts into the culture of Brazilian schools and document the results through a participatory approach. Through this lens, the research enables a nuanced understanding of how educational technologies are received, resisted, or redefined by the participants.

Description of the Study

The study employed a qualitative research methodology that combined participatory workshops, field observations by participant observers, and informal interviews. To help quantify the results and bolster the study's rigor, the researchers used the Self-Assessment Manikin (SAM) technique, which is a pictographic evaluation tool used to capture the participants' effective states when interacting with an object or in a situation (Bradley & Lang, 1994, as cited in Hayashi & Baranauskas, 2013). By using this method, the researchers verified their previous recordings of positive emotional responses between the participants and the XO laptop. This comprehensive approach, along with the involvement of more than 500 participants—including students, teachers, and school staff—significantly increased the validity of the findings. While discussing each scenario is outside the scope of this post, the researchers provided four key use-cases of how technology can be inserted into internal school environments and external settings for more meaningful practices (Hayashi & Baranauskas, 2013): (1) transforming homework into in-class experiences, (2) integrating the school in interdisciplinary activities, (3) extending learning to transcend beyond school boundaries using the same device, and (4) empowering "student monitors" to address technical issues. Each scenario illustrates how technology can affect not only the population involved but also the local culture, which helps develop a deeper social engagement, collaborative effort, and developmental environment.

Critical Evaluation

The socio-technical plan presented is commendable for aligning with socio-technical theory, which recognizes that technology alone cannot transform learning. Instead, it is the alignment of technological tools (i.e., the "artifact") with human values (i.e., the "social") and how they are interconnected in current contexts and environments that drives meaningful adoption. This research approach is distinguished by its focus on affectability, which examines how learners "feel" about the technology they use. However, the research plan is not without its limitations. While the scenarios demonstrate positive emotional responses and increased engagement from teachers and school staff, additional challenges, such as teacher resistance, infrastructure limitations, and safety concerns, highlight the technological implementation's dependency on broader systemic support (Hayashi & Baranauskas, 2013). For example, one issue recorded during the qualitative study was the limited network resources, which did not allow all students to have stable, simultaneous connections, resulting in slow and intermittent internet access. This, along with the aforementioned dependencies, could indicate a broader, extensible issue, such as funding. Additionally, despite the inclusive participatory approach, the scalability and replicability of this qualitative research remain uncertain. Lastly, while the study provides valuable insights into the participant researchers' approach expanding over a year, it could also benefit from a more robust longitudinal approach to measure the long-term outcome on educational impacts.

Summary

Socio-technical theory provides a framework for understanding how people, technology, and environmental subsystems interact within a larger system. In the study above, the underpinnings of socio-technical theory inform the qualitative research approach used to examine the integration of laptops into a Brazilian public school. The research explores the concept of affectability, which aims to capture emotional and cultural responses through participatory methods, while validating the findings using pictographic tools (i.e., the SAM method). The study's findings show that aligning technology with local values enhances engagement and collaboration, but also introduces unique challenges. Nevertheless, the socio-technical plan effectively links theory to practice, emphasizing that successful technology adoption must consider both human and contextual factors.

References

Abbas, R., & Michael, K. (2025). Socio-technical theory. Retrieved July 21, 2025, from www.open.ncl.ac.uk: https://open.ncl.ac.uk/theories/9/socio-technical-theory/

Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self assessment manikin and the semantic differential. Journal of Behavioral Therapy and Experimental Psychiatry, 25, 49-59. Retrieved July 21, 2025

Hayashi, E. C., & Baranauskas, M. C. (2013). Affectability in educational technologies: A socio-technical perspective for design. Educational Technology and Society, 16(1), 57-68. Retrieved July 21, 2025

Trist, B., Murray, H., & Trist, E. (2016). Characteristics of socio-technical systems. The Social Engagement of Social Science, a Tavistock Anthology, 2, 157-186. Retrieved July 21, 2025

 

 

 Introduction

Forecasting is a critical tool for businesses as it guides strategic planning, investments, and the overall direction of the organization. Tidd and Bessant (2024) note that forecasting is not merely an assumption but a comprehensive process that leverages quantifiable metrics to make informed decisions about future directions. It is essential to note that forecasting is an educated prediction, which does not guarantee 100% accuracy in the projection. Organizations should acknowledge these connections to avoid "putting all their eggs in one basket." That said, even highly experienced industry leaders can misread the trajectory of innovation. When misapplied or excessively influenced by bias, short-term reasoning, or other factors, forecasts can miss transformational shifts, resulting in missed opportunities and reputational damage. One of the most infamous examples of a failed forecast in the technology industry is Microsoft's dismissal of the smartphone revolution, which is a prediction that dramatically underestimated the potential impact of mobile computing.

Microsoft and the iPhone

In 2007, shortly after Apple unveiled the first-generation iPhone, Microsoft's Chief Executive Officer (CEO), Steve Ballmer, publicly dismissed the user-centric mobile device by predicting that it would never gain significant market share. In an interview with USA Today, Ballmer stated, "There's no chance that the iPhone is going to get any significant market share. No Chance" (Wired, 2007). At the time, Microsoft was heavily invested in its Windows mobile platform and viewed enterprise-focused business devices, such as the BlackBerry, as the future (Microsoft, 2007). Ballmer's forecast suggested that smartphones without physical keyboards, running a new operating system (OS), and targeting general consumers rather than specific business users, would be a niche product at best. However, this prediction is considered one of the most infamous miscalculations in the mobile technology industry. The iPhone not only gained a significant market share but also redefined the mobile phone industry by ushering in an era of application-based ecosystems, which ultimately led to the downfall of competitors who failed to adapt (e.g., Nokia).

Forces Behind the Missed Forecast

The primary factor contributing to Microsoft's gross misjudgment and Apple's success was a lack of technological foresight resulting from limited visibility into the mobile domain. During this era, Microsoft focused on developing business-specific mobile solutions, which overbalanced the entire mobile industry and failed to recognize the growing consumer demand for integrated, user-friendly mobile experiences. The company's internal culture focused on productivity and compatibility with existing Windows systems, whereas Apple's approach emphasized design, touch interaction, and a user-friendly experience. The business-consumer disconnect led Microsoft to underestimate the disruptive potential of the iPhone's touch-based mobile interface and the application store model.

A secondary influential force was economic, stemming from strategic inactivity and inflexibility. Microsoft was heavily invested in its existing product lines and the licensing model, making it difficult to pivot without cannibalizing its software ecosystem (Srikanth, 2025). Moreover, the high price point of the iPhone led many, including Ballmer, to believe it lacked economic sustainability. However, the market rapidly accepted Apple's strategy, with consumers willing to pay a premium for innovation, and developers quickly recognizing the new revenue streams in mobile application development. Meanwhile, Microsoft's Windows phone platform failed to gain traction, and by the mid-2010s, it was officially discontinued (Savov, 2017).

Summary

Forecasting can be a powerful business tool. However, when grounded in outdated assumptions or constrained by organizational limitations, it can lead to costly errors. The prediction that the iPhone would fail exemplifies how even seasoned leaders can make infamous forecasts that miss monumental shifts in technology. This example underscores the importance of continually challenging beliefs, embracing emerging trends, and remaining open to disruptive technologies, especially when they challenge the status quo. In the fast-paced world of technology, being wrong about the future can be more damaging than failing to predict it altogether.

 

References

Microsoft. (2007, May 09). Steve ballmer: Software 2007. Retrieved from www.news.microsoft.com: https://news.microsoft.com/speeches/steve-ballmer-software-2007/

Savov, V. (2017, October 10). Windows phone was a glorious failure. Retrieved July 10, 2025, from www.theverge.com: https://www.theverge.com/2017/10/10/16452162/windows-phone-history-glorious-failure

Srikanth, R. (2025, January 02). Understanding market cannibalism in the software industry: Risks, examples, and mitigation strategies. Retrieved from www.linkedin.com: https://www.linkedin.com/pulse/understanding-market-cannibalism-software-industry-risks-srikanth-r-rpgbc/

Tidd, J., & Bessant, J. R. (2024). Managing innovation: Integrating technology, market and organizational change (8 ed.). John Wiley and Sons, Inc. Retrieved June 18, 2025, from https://coloradotech.vitalsource.com/reader/books/9781394252053/epubcfi/6/10[%3Bvnd.vst.idref%3DAf03]!/4/2

Wired. (2007, May 01). More ballmer madness: "There is no chance that the iphone is going to get any significant market share". Retrieved July 10, 2025, from www.wired.com: https://www.wired.com/2007/05/more-ballmer-ma/

 

 

 What Are Scenarios?

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 (i.e., strategies) made today could play out. In this context, scenarios do not provide a single outcome; instead, they provide a framework for considering a range of plausible developments. For example, rewinding to the era of Blockbuster's brick-and-mortar dominance, several plausible scenarios illustrate how the company might have altered its trajectory: 1) investing in digital innovation, 2) pursuing convergence through a partnership with emerging companies like Redbox or Netflix, or 3) maintaining the status quo. Blockbuster's downfall is well-documented, mainly resulting from its failure to adapt to the digital transformation—a reality reflected in the third scenario (Satell, 2014). Yet, alternative paths were available as the company could have embraced the digital shift earlier, formed strategic alliances, or pursued a hybrid approach. While these scenarios may underplay the full scope of uncertainty and complexity, they represent realistic strategies that, if explored, might have sustained Blockbuster's relevance in an evolving market. As examined in the Blockbuster example, scenarios help decision-makers envision alternative futures, understand the complexities, and prepare for the uncertainties, enabling greater adaptability and resilience in strategic planning and forecasting.

Scenario Planning

Scenario planning is a methodology that constructs multiple, plausible futures to examine how different approaches to uncertainties and complexities might unfold. Unlike traditional forecasting, which typically projects the future based on historical data, scenario planning acknowledges that the future is uncertain and complex. This notion is illustrated by Schoemaker (2004), who states that scenario planning is a practical tool for handling high-uncertainty, high-complexity environments. In a real-world context, a high-uncertainty, high-complexity scenario could correlate to making predictions about the outcome of the war on drugs or terrorism. While predictions of war are an extreme example, they help convey the effectiveness of overcoming the challenges that futurists face in creating coherent scenarios that can be used for strategic planning.

There are numerous structured methods for conducting scenario planning, including interactive future simulation (IFS) and trend impact analysis (TIA). These approaches enable organizations to anticipate and adapt to future uncertainties by examining potential futures. However, Heckl (2021) introduces a more straightforward and digestible alternative—a four-step process designed to simplify the strategic foresight approach while maintaining its effectiveness.

1.      Identify the driving forces.

2.      Identify the critical uncertainties.

3.      Develop plausible scenarios.

4.      Discuss the implications of paths.

To initiate the scenario planning process, organizations first identify key driving forces that will influence their future, which are often categorized under the following six forces: political, economic, social, technological, legal, and environmental (PESTLE). After compiling a list of the forces impacting the organization, the next step is to narrow them down by selecting the two most impactful forces—these become the foundation for scenario development. Then, for each of the two forces (i.e., critical uncertainties), define the extreme ends of the spectrum for each one. For example, if one of the key forces was ransomware attacks in the technology domain, then defining extremes could be: 1) effective solutions to completely block ransomware attacks, or 2) there are no cybersecurity solutions to block, prevent, or sustain data or systems after an attack. Additionally, Schoemaker (2004) defines uncertainty in these driving forces as the "degree of available knowledge about the target variable," emphasizing the importance of selecting variables that are both highly influential and unpredictable (p. 274). Using these two critical uncertainties, organizations construct a scenario matrix by placing each variable on an x-axis and a y-axis, creating four quadrants that represent distinct, plausible futures, ranging from highly favorable to highly adverse outcomes (e.g., effective cybersecurity vs. ineffective cybersecurity). Participants then engage in role-play or narrative discussions as if they have already experienced these futures, helping to explore the consequences, risks, and opportunities associated with each scenario. Finally, the group analyzes the strategic implications of each scenario to guide planning, assess organizational readiness, and inform more resilient decision-making strategies.

Strategic Forecasting

Strategic forecasting is a forward-looking process that aids decision-making by identifying the most probable future outcomes to guide organizational efforts. Ogilvy (2015) differentiates between planning and forecasting along the futurist continuum, using a poker analogy where planning is akin to preparing for multiple hands being dealt, while forecasting is an attempt to predict how a player will respond to specific hands. This distinction highlights the role of forecasting in narrowing down uncertainties to inform strategy. Similarly, the London Premier Centre (2023) reinforces this perspective by emphasizing that strategic forecasting helps organizations bridge the gap between current realities and future aspirations by pinpointing emerging opportunities and potential threats. In doing so, strategic forecasting translates conceptual visions into actionable strategies, which enables organizations to make more informed, timely, and effective decisions.

At its core, strategic forecasting relies on both quantitative and qualitative inputs to help organizations anticipate and formulate strategies in response to changes in the business environment, as illustrated in the Blockbuster example. Quantitative forecasting utilizes complex data, including market trends, seasonal variations, and other measurable variables, to produce data-driven strategies. This numerical approach is efficient in stable environments with reliable historical data. In contrast, qualitative forecasting draws on subjective insights and expert opinions, utilizing tools such as the Delphi method to forecast strategic directions that may be difficult to quantify (London Premier Centre, 2023). This method is beneficial when dealing with unprecedented events, emerging markets, or disruptive technologies where historical data may be lacking or nonexistent. Organizations can adopt a hybrid, mixed-methods approach that combines both quantitative and qualitative techniques. The hybrid model enhances strategic forecasting by balancing empirical analysis with human judgment (i.e., validating), ultimately leading to more comprehensive and adaptive strategies.

Advantages and Disadvantages

Scenario planning and strategic forecasting offer unique advantages and disadvantages in the context in which they are applied. Scenario planning, as suggested by Schoemaker (2004), excels in environments characterized by high uncertainty and high complexity. The great strength of this method lies in its ability to prepare organizations for a range of plausible futures by encouraging flexible, innovative, and creative exploration of opportunities to mitigate business risks and solidify their relevance in an evolving and volatile market. As demonstrated by the Blockbuster example, scenario planning could have helped the company envision and prepare for disruptive technological trends, such as the rise of digital media platforms like Netflix. However, scenario planning also presents particular challenges as it is 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, or implementing strategic business shifts, can be complex and potentially convoluted.

Strategic forecasting offers a more structured, data-driven approach that is particularly effective in stable environments where historical trends can seemingly inform future outcomes. The strength of this method lies in its ability to generate actionable insights across various business strategies and functions, thereby supporting the decision-making process. The London Premier Centre (2023) emphasizes that strategic forecasting helps organizations bridge the gap between current realities and future goals by identifying concrete opportunities and potential business threats. However, forecasting is not without its limitations. Take Blockbuster, for example, the organization had a significant profit revenue that drove it to dominance during the brick-and-mortar era (Satell, 2014). However, while this business design was efficient, it was not flexible and contributed to the downfall of the Blockbuster empire. Nevertheless, underestimating or overlooking disruptive events that do not follow historical patterns could leave organizations vulnerable to emerging technologies, as seen in the Blockbuster example. Additionally, overreliance on either qualitative or quantitative methods can lead to significant gaps in the strategic forecasting process, which could inform strategic decisions poorly. In closing, scenario planning is better suited for strategies that navigate uncertain environments, while strategic forecasting supports planning in more predictable environments. However, when used together, these two approaches can complement each other to provide a unique perspective on understanding uncertainty, while supporting strategic direction and decision-making with historical and expert data.

References

Heckl, J. (2021, February 11). The 4-step scenario planning process. Retrieved July 08, 2025, from www.smestrategy.net: https://www.smestrategy.net/blog/the-4-step-scenario-planning-process-with-examples

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

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 08, 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