Dr. Aly, O,
Computer Science

Introduction

Scenario planning first emerged for application to businesses in a company set up for researching new forms of weapons technology in the RAND Corporation (Chermack, Lynham, & Ruona, 2001).  Kahn of RAND corporation pioneered a technique titled “future-now” thinking (Chermack et al., 2001).  Scenario planning encourages organizational leaders to think the unthinkable (Chermack et al., 2001).  It has been identified as a useful means of conducting strategic organization planning (Chermack et al., 2001).  With a focus on long-term and short-term future, scenario planning forces the organizational planners to consider paradigms which challenge their current thinking (Chermack et al., 2001).  

In (Wade, 2012), scenario planning is described as a productive, creative, and existing way to develop the groundwork for a strategic plan which does not bet the future on the company on a single most likely scenario.  Scenario planning challenges the idea of a single future but an array of possible future which could potentially unfold (Wade, 2012).  The outcome of the scenario planning process is a portfolio of future scenarios, each of which represents a different way the business landscape could look in a few years, and not just the landscape, but also the players who involve in the business such as competitors, suppliers, customers, employees and other stakeholders (Wade, 2012).  Scenario planning is considered to be a critical tool for anyone who is not just managing, but also leading (Wade, 2012).  It enables the leader to create a realistic vision for the future and craft the strategies which will make the leader successful (Wade, 2012). 

The good scenario planning goes beyond just high-low projections (Schoemaker, 1991).  In (Peterson, Cumming, & Carpenter, 2003), scenario planning is described as a systematic method for thinking creatively about possible complex and uncertain futures.  The underlying concept of the scenario planning is to consider a variety of possible futures which include many of the important uncertainties in the system instead of focusing on accurate prediction of a single outcome (Peterson et al., 2003).  There are many approaches to scenario planning such qualitative approach,

The applications of scenario planning can be organized by their use of qualitative or quantitative methods and their approach toward the uncertainty (Peterson et al., 2003).  Most scenario planning incorporates both qualitative and quantitative details, and the relative mix of these two aspects distinguish different scenarios exercises (Peterson et al., 2003). Some scenario planning is intended to facilitate the management uncertainty, while others are used to discover it (Peterson et al., 2003).  Three examples of scenarios which have been used to approach problems which were beyond the read of the traditional predictive methods include “Shell Oil,” “Monte Fleur, South Africa,” and  “Northern Highland Lake District, Wisconsin” (Peterson et al., 2003).  In the Shell Oil, the traditional forecasting was found inappropriate, and scenario planning was used to allow well-defined actor “Shell” with a clear goal to maximize shareholder value to develop a strategy for an uncertain future (Peterson et al., 2003).  In Monte Fleur, scenario planning is used by bringing a group of disconnected people with divergent goals together to create a shared understanding of the uncertainties surrounding the transition to democracy (Peterson et al., 2003).  In Northern Highland Lake District in Wisconson, a team of scientists created an initial set of scenarios to begin a scenario-planning process among a broad group of stakeholders (Peterson et al., 2003).  These examples demonstrate that scenario planning can be modified in a multitude of ways to fit a particular context (Peterson et al., 2003). 

Scenario Planning Could Have Saved Blockbuster

Blockbuster is a very good example of the business which did not do the proper scenario-type planning and only relied on standard forecasting.  Blockbuster Inc. was an American-based DVD and video game rental service.  It was founded by David Cook, who used his experience with managing large database networks as the foundation for the retail distribution model of the Blockbuster (Albarran, 2013).  In 2009, Blockbuster had an estimated 7,100 retail stores in the US with additional locations in 17 countries worldwide, and had over 60,000 employees in the US and worldwide (Albarran, 2013).  The headquarter of the company was in McKinney, Texas (Albarran, 2013).  Blockbuster filed for bankruptcy just prior its 25^th anniversary on September 22, 2010, and on April 11, Blockbuster was acquired by satellite television service provider Dish Network at an auction price of $233 million and the assumption of $87 million in liabilities and other obligations (Albarran, 2013). 

            The innovation is not about developing new products, but it is about reinventing business process and building entirely new markets to meet untapped customer needs (Albarran, 2013).  For some businesses, innovation is deliberative and planned, while for others innovation is the direct result of a triggering event such as a change in external market conditions or internal performance which forces a change in business strategy (Gershon).  Three main types of innovations:  product innovation, process innovation, and business model innovation.  Blockbuster followed the traditional forecasting model without paying attention to any innovation and the impact of the technology on its business.  If Blockbuster had implemented scenario-typed planning in their Business Process, it would not have failed.   The Blockbuster retail model was going to be difficult to sustain in the presence of advancing technology (Albarran, 2013).  Figure 1 illustrates a Scenario Planning Model.

Figure 1: Scenario Planning Model

Forces Driving Blockbuster Out of Business

The Internet made the future of e-commerce and “disruptive technologies” possible.  Netflix is one of these “disruptive technologies” which took the form of a unique business process innovation (Albarran, 2013).  Netflix is an online subscription-based DVD rental service founded by Reed Hastings in 1997during the emergent days of electronic commerce (EC) when companies like Amazon and Dell Computer were starting to gain prominence (Albarran, 2013).   Netflix provides greater value to the consumer when compared to the traditional video rental store which charges by the individual DVD rental unit, by offering two to three DVDs per week for a fixed monthly price (Albarran, 2013).  Moreover, Netflix offers greater convenience in the form of “no late fee.” (Albarran, 2013).  The success of Netflix is the direct result of personalized marketing which involves knowing more about the particular interest and viewing habits of the customers (Albarran, 2013).  Netflix utilizes the power of the Internet to promote a proprietary software recommendation system (Albarran, 2013).  This recommendation system solved the common complaints with Blockbuster when renting an unfamiliar movie, and the customer gets dissatisfied with the viewing experience later.  With this recommendation system, Netflix offers suggestions of other films that the customer might like based on the past selection and the brief evaluation filled by the customers (Albarran, 2013).

            Blockbuster failed to react to the competition and revise its business model (Albarran, 2013).  Blockbuster could have re-position itself strategically as early as 2011 (Albarran, 2013).  However, Blockbuster could have acquired Netflix or modified its strategy by duplicating many of the same EC efficiencies which Netflix’s business model had already demonstrated (Albarran, 2013).  Blockbuster chose to ignore the competitive threat posed by Netflix. 

Scenario Planning could have saved Blockbuster.  Scenario Planning offers a framework for resilient conservation policies when faced with uncontrollable, irreducible uncertainty (Peterson et al., 2003).  Scenario Planning consists of using a few contrasting scenarios to explore the uncertainty surrounding the future consequences of a decision.  Blockbuster could have benefitted from a few contrasting scenarios to explore the uncertainty that is resulted from the competition, the technology, and the presence of the Internet and e-Commerce.  The key benefit of the Scenario Planning process is that it reveals different ways of the future based on which more flexible and more thoughtful and better decision can be made today (Wade, 2012).  An additional benefit of scenario planning includes the increased understanding of key uncertainties, the incorporation of alternative perspectives into conservation planning, and greater resilience of decisions to surprise (Peterson et al., 2003).

In summary, the traditional forecast model did not help Blockbuster stay in business.  On the contrary, the traditional forecast model did not forecast the future of Blockbuster.  The forces such as the Internet, the emerging technologies supporting e-commerce, recommendation systems for customers, monthly rental for two to three DVDs, and no late fee have driven Blockbuster out of business.  Blockbuster could have saved itself if it has applied scenario planning strategically to protect itself from the uncertainty of the future, instead of following the same traditional forecasting model which worked perfectly in the past but became not applicable any longer in the presence of the Internet and other emerging technologies and innovations driven by these technologies.  

References

Albarran, A. B. (2013). Media management and economics research in a transmedia environment: Routledge.

Chermack, T. J., Lynham, S. A., & Ruona, W. E. (2001). A review of scenario planning literature. Futures Research Quarterly, 17(2), 7-32.

Gershon, R. A. MEDIA INNOVATION: Disruptive Technology and the Challenges of Business Reinvention: Kalamazoo, Western Michigan University.

Peterson, G. D., Cumming, G. S., & Carpenter, S. R. (2003). Scenario Planning: a Tool for Conservation in an Uncertain World. Conservation Biology, 17(2), 358-366.

Schoemaker, P. J. H. (1991). When and How to Use Scenario Planning: A Heuristic Approach with Illustration. Journal of Forecasting, 10(6), 549-564.

Wade, W. (2012). Scenario planning: A field guide to the future: John Wiley & Sons.

Dr. Aly, O.
Computer Science

Purpose:

The purpose of this discussion is to research the concepts of forecasting and predictions in a business or innovation context. The discussion will identify and document one infamous prediction that actually came true.

Discussion

Prediction:  The goal of prediction is to obtain a significant estimate of what the value of the dependent variable will be by known independent variable value (Bateh & Heyliger, 2014).  However, as indicated in (Garrett, 2013), the prediction is rough and is subject to a large error of the estimate.  Prediction means different things to different technical disciplines and different people (Peterson, Cumming, & Carpenter, 2003).  The prediction is understood to be the best possible estimate of future conditions (Peterson et al., 2003).   The less sensitive the prediction is to drivers the better (Peterson et al., 2003).  Whereas scientists understand that predictions are probabilistic conditional statements, non-scientists often understand them as things that will happen no matter what they do (Peterson et al., 2003).

The historical and technological records contain various and numerous examples of predictions that came true (Dreher, n.d.; Sterbenz, 2013).  Some of these predictions that came true include the following as indicated in (Dreher, n.d.; Sterbenz, 2013). 

• Jules Verne predicted a man on the moon in 1865.
• Ray Bradbury foretold earbuds in 1953.
• Edward Bellamy envisaged the debit card in 1888.
• Robert Boyle predicted organ transplants in the 1660s.
• Arthur C. Clark imagined the iPad in 1968.
• Nikola Tesla predicted personal wireless devices in 1909.
• H. G. Wells predicted the atomic bomb in 1914.
• Roger Ebert predicted video-on-demand services Netflix and Hulu in 1987.
• Isaac Asimov predicted the use of the Internet for learning in 1988.

For this discussion, the focus is on the prediction of Nikola Tesla for the personal wireless devices in 1909.  

Nikola Tesla’s Prediction of Personal Wireless Devices in 1909:  In 1891, Nikola Tesla developed a type of resonant transformer called the Tesla coil, which achieved a major breakthrough in his work by transmitting 100 million volts of electric power wirelessly over a distance of 26 miles to light up a bank of 200 light bulbs and run one electric motor (Bhutkar & Sapre, 2009).  Tesla claimed to have achieved 95% efficiency, but the technology had to be shelved because the effects of transmitting such high voltages in electric arcs would have been disastrous to humans and electrical equipment in the vicinity (Bhutkar & Sapre, 2009).  This technology has been neglected in obscurity for several years. However, the advent of portable devices such as mobiles, laptops, smartphones, MP3 players brought this technology into life and Tesla’s prediction of the wireless in 1909, which came true. 

Tesla was called as a visionary as well as “charlatan” (Lumpkins, 2014).  However, many attest that his early vision of alternating current transmission systems and wireless power were the precursors of today’s energy-harvesting technology (Lumpkins, 2014).  He is regarded as a prolific inventor (Marincic, 1982).  Tesla believed that by transmitting waves of alternating radio-frequency (RF) energy, devices such as electric vehicles and even flying dirigibles, could reuse this energy for consistent operation (Lumpkins, 2014).   Tesla experimented with large-scale wireless power distribution by building the world’s first power station in Long Island, New York (Xie, Shi, Hou, & Lou, 2013).  He planned to use the power station called Wardenclyffe Tower to transmit not only signals but also wireless electricity (Xie et al., 2013).  However, due to its large electric fields, which significantly diminished the power transfer efficiency, Tesla’s invention was not successful and was never put into practical use (Xie et al., 2013).

The field of wireless power has been growing over the past sixty years, from conceptual ideas such as collecting solar power in space and “beaming” it back to Earth-based collectors, like a Dyson sphere, to the reality of charging Philips Sonicare electric toothbrush with an inductive charger (Lumpkins, 2014).  The impact of the Tesla’s innovation and prediction is observed in every minute of our lives.

References

Bateh, J., & Heyliger, W. (2014). Academic Administrator Leadership Styles and the Impact on Faculty Job Satisfaction. Journal of leadership Education, 13(3).

Bhutkar, R., & Sapre, S. (2009). Wireless energy transfer using magnetic resonance. Paper presented at the Computer and Electrical Engineering, 2009. ICCEE’09. Second International Conference On.

Dreher, B. (n.d.). 9 Incredible Historical Predictions That Came True. Retrieved Jan 27, 2018, from https://www.rd.com/culture/historical-predictions-that-came-true/.

Garrett, M. (2013). Traditional Forecasting Leads to Traditional Results … Failure. Retrieved Jan 27, 2018, from https://www.forbes.com/sites/matthewgarrett/2013/08/22/traditional-forecasting-leads-to-traditional-results-failure/#4a0c95e0bebc, Forbes.

Lumpkins, W. (2014). Nikola Tesla’s Dream Realized: Wireless power energy harvesting. IEEE Consumer Electronics Magazine, 3(1), 39-42.

Marincic, A. (1982). Nikola Tesla and the wireless transmission of energy. IEEE Transactions on Power Apparatus and Systems(10), 4064-4068.

Peterson, G. D., Cumming, G. S., & Carpenter, S. R. (2003). Scenario Planning: a Tool for Conservation in an Uncertain World. Conservation Biology, 17(2), 358-366.

Sterbenz, C. (2013). 16 Of The Most Impressive Predictions Of All Time. Retrieved Jan 27, 2018, from http://www.businessinsider.com/predictions-from-the-past-that-came-true-2013-9.

Xie, L., Shi, Y., Hou, Y. T., & Lou, A. (2013). Wireless power transfer and applications to sensor networks. IEEE Wireless Communications, 20(4), 140-145.

Dr. Aly, O.
Computer Science

Purpose

The purpose of this discussion is to compare and contrast the concepts of scenario planning versus traditional forecasting.

Traditional Forecasting:   A forecast is described as the best estimate of a particular method, model, or individual (Peterson, Cumming, & Carpenter, 2003). The view toward the forecast is that a forecast may or may not turn out to be true (Peterson et al., 2003).  Forecast is uncertain (Peterson et al., 2003).  Prediction, on the other hand, means different things to different technical disciplines and different people (Peterson et al., 2003).  The prediction is understood to be the best possible estimate of future conditions (Peterson et al., 2003).  Forecast and prediction are closely tied to the notion of optimal decision making (Peterson et al., 2003).  The optimal decisions maximize the expected net benefits and minimize the expected net losses (Peterson et al., 2003).   

Traditional forecasting has different models and methods as indicated in (DSG, 2011).  The traditional forecasting methods involve trending, extrapolation and curve fitting methods, which are used when forecast time frame is short to medium term, and there is sufficient evidence that forecast inflection points do not exist in the time frame (DSG, 2011).  It also involves the Adoption and Penetration Model which is used when there is sufficient evidence that the historical and forecast time frame of the model will include inflection points (DSG, 2011).  The scope of these Adoption and Penetration Models is usually total market, and the objectives are to predict market penetration, the location of the inflection points, and take-up times (DSG, 2011).  The traditional forecasting methods also include the “Casual and Multivariate” methods which are used when multiple known causal influences are driving or constraining the market (DSG, 2011).  The two most common form of this approach include the Total Market models and the Market Share methods (DSG, 2011).  Other traditional forecasting models include Time-Series Analysis, Agent-Based Models, and Trackers & Bottom-Up Models (DSG, 2011). As indicated in (Garrett, 2013), traditional forecasting leads to traditional results and may be failures. Thus, the models of the traditional forecasting do not have to be applied in every business scenarios.   

Scenario Planning:  Scenario planning first emerged for application to businesses in a company set up for researching new forms of weapons technology in the RAND Corporation (Chermack, Lynham, & Ruona, 2001).  Kahn of RAND corporation pioneered a technique titled “future-now” thinking (Chermack et al., 2001). 

Scenario planning encourages organizational leaders to think the unthinkable (Chermack et al., 2001).  It has been identified as a useful means of conducting strategic organization planning (Chermack et al., 2001).  With a focus on long-term and short-term future, scenario planning forces the organizational planners to consider paradigms which challenge their current thinking (Chermack et al., 2001).  

As indicated in (Chermack et al., 2001), scenario planning has been defined in several ways.  Scenario planning was defined as “an internally consistent view of what the future might turn out to be -not a forecast, but one possible future outcome.”  Scenario planning is defined as “a tool for ordering one’s perceptions about alternative future environments in which one’s decisions might be played out” (Chermack et al., 2001). It was also defined as “that part of strategic planning which relates to the tools and technologies for managing the uncertainties of the future” (Chermack et al., 2001).  The major themes of the scenario planning include history, scenarios as stories, the theory of scenarios, the effect of scenarios on decision-making capabilities, creating “future memory” from scenarios, scenarios as tools for organizational learning, and the evaluation of scenario projects (Chermack et al., 2001).  Scenario planning offers a framework for developing more resilient conservation policies when confronted with uncontrollable, irreducible uncertainty (Peterson et al., 2003). 

In (Wade, 2012), scenario planning is described as a productive, creative, and even existing way to develop the groundwork for a strategic plan which does not bet the future on the company on a single most likely scenario.  Scenario planning challenges the idea of a single future but an array of possible future which could potentially unfold (Wade, 2012).  The outcome of the scenario planning process is a portfolio of future scenarios, each of which represents a different way the business landscape could look in a few years, and not just the landscape, but also the players who involve in the business such as competitors, suppliers, customers, employees and other stakeholders (Wade, 2012).  Scenario planning is considered to be a critical tool for anyone who is not just managing, but also leading (Wade, 2012).  It enables the leader to create a realistic vision for the future and craft the strategies which will make the leader successful (Wade, 2012). 

The good scenario planning goes beyond just high-low projections (Schoemaker, 1991).  In (Peterson et al., 2003), scenario planning is described as a systematic method for thinking creatively about possible complex and uncertain futures.  The underlying concept of the scenario planning is to consider a variety of possible futures which include many of the important uncertainties in the system instead of focusing on accurate prediction of a single outcome (Peterson et al., 2003).  There are many approaches to scenario planning such qualitative approach,

There is no one-size-fits-all approach to scenario planning (Wade, 2012).  Six steps are proposed by (Wade, 2012) as a general guideline for scenario planning.  These six steps include:  framing the challenge, gathering information, identifying the driving forces, defining the future’s critical uncertainties, generating the scenarios, and fleshing them out and creating storylines. Four more steps follow these six steps including the validation, the implication assessment, the identification of signposts, and the monitoring and updating the scenario as the time moves (Wade, 2012). In (Peterson et al., 2003), a similar guideline is provided.  However, in (Peterson et al., 2003), the approach is described as a qualitative approach, presenting the process as a linear process, with iteration, where system assessment leads to a redefinition of the central question, and testing can reveal blind spots which require more assessment.  The process begins with the identification of a focal issue, followed by the assessment, identification of alternative, building scenarios, testing scenarios, and policy screening (Peterson et al., 2003). 

The applications of scenario planning can be organized by their use of qualitative or quantitative methods and their approach toward the uncertainty (Peterson et al., 2003).  Most scenario planning incorporates both qualitative and quantitative details, and the relative mix of these two aspects distinguish different scenarios exercises (Peterson et al., 2003). Some scenario planning is intended to facilitate the management uncertainty, while others are used to discover it (Peterson et al., 2003).  Three examples of scenarios which have been used to approach problems which were beyond the read of the traditional predictive methods include “Shell Oil,” “Monte Fleur, South Africa,” and  “Northern Highland Lake District, Wisconsin” (Peterson et al., 2003).  In the Shell Oil, the traditional forecasting was found inappropriate, and scenario planning was used to allow well-defined actor “Shell” with a clear goal to maximize shareholder value to develop a strategy for an uncertain future (Peterson et al., 2003).  In Monte Fleur, scenario planning is used by bringing a group of disconnected people with divergent goals together to create a shared understanding of the uncertainties surrounding the transition to democracy (Peterson et al., 2003).  In Northern Highland Lake District in Wisconson, a team of scientists created an initial set of scenarios to begin a scenario-planning process among a broad group of stakeholders (Peterson et al., 2003).  These examples demonstrate that scenario planning can be modified in a multitude of ways to fit a particular context (Peterson et al., 2003). 

The key benefit of the scenario planning process is that it reveals different ways of the future based on which more flexible and more thoughtful and better decision can be made today (Wade, 2012).  An additional benefit of scenario planning includes the increased understanding of key uncertainties, the incorporation of alternative perspectives into conservation planning, and greater resilience of decisions to surprise (Peterson et al., 2003).

References

Chermack, T. J., Lynham, S. A., & Ruona, W. E. (2001). A review of scenario planning literature. Futures Research Quarterly, 17(2), 7-32.

DSG. (2011). Traditional forecasting and modeling methods. Retrieved Jan 27, 2018, from http://www.danielresearchgroup.com/WhatWeDo/ForecastsandMarketModels/TraditionalForecasting.aspx, Daniel Research Group: Understanding the Future.

Garrett, M. (2013). Traditional Forecasting Leads to Traditional Results … Failure. Retrieved Jan 27, 2018, from https://www.forbes.com/sites/matthewgarrett/2013/08/22/traditional-forecasting-leads-to-traditional-results-failure/#4a0c95e0bebc, Forbes.

Peterson, G. D., Cumming, G. S., & Carpenter, S. R. (2003). Scenario Planning: a Tool for Conservation in an Uncertain World. Conservation Biology, 17(2), 358-366.

Schoemaker, P. J. H. (1991). When and How to Use Scenario Planning: A Heuristic Approach with Illustration. Journal of Forecasting, 10(6), 549-564.

Wade, W. (2012). Scenario planning: A field guide to the future: John Wiley & Sons.