Forecasting Tools and Techniques

Forecasts are educated assumptions about future trends and events. Forecasting is a complex activity because of factors such as technological innovation, cultural changes, new products, improved services, stronger competitors, shifts in government priorities, changing social values, unstable economic conditions, and unforeseen events. Managers often must rely on published forecasts to effectively identify key external opportunities and threats.

A sense of the future permeates all action and underlies every decision a person makes. People eat expecting to be satisfied and nourished in the future. People sleep assuming that in the future they will feel rested. They invest energy, money, and time because they believe their efforts will be rewarded in the future. They build highways assuming that automobiles and trucks will need them in the future. Parents educate children on the basis of forecasts that they will need certain skills, attitudes, and knowledge when they grow up. The truth is we all make implicit forecasts throughout our daily lives. The question, therefore, is not whether we should forecast but rather how we can best forecast to enable us to move beyond our ordinarily unarticu­lated assumptions about the future. Can we obtain information and then make educated assump­tions (forecasts) to better guide our current decisions to achieve a more desirable future state of affairs? Assumptions must be made based on facts, figures, trends, and research. Strive for the firm’s assumptions to be more accurate than rival firm’s assumptions.

Sometimes organizations must develop their own projections. Most organizations forecast (project) their own revenues and profits annually. Organizations sometimes forecast market share or customer loyalty in local areas. Because forecasting is so important in strategic management and because the ability to forecast (in contrast to the ability to use a forecast) is essential, selected forecasting tools are examined further here.

No forecast is perfect—some are even wildly inaccurate. This fact accents the need for strat­egists to devote sufficient time and effort to study the underlying bases for published forecasts and to develop internal forecasts of their own. Key external opportunities and threats can be effectively identified only through good forecasts. Accurate forecasts can provide major com­petitive advantages for organizations. Accurate forecasts are vital to the strategic-management process and to the success of organizations.

1. Making Assumptions

Planning would be impossible without assumptions. McConkey defines assumptions as the “best present estimates of the impact of major external factors, over which the manager has little if any control, but which may exert a significant impact on performance or the ability to achieve desired results.”13 Strategists are faced with countless variables and imponderables that can be neither controlled nor predicted with 100 percent accuracy. Wild guesses should never be made in formulating strategies, but reasonable assumptions based on available information must always be made.

By identifying future occurrences that could have a major effect on the firm and by mak­ing reasonable assumptions about those factors, strategists can carry the strategic-management process forward. Assumptions are needed only for future trends and events that are most likely to have a significant effect on the company’s business. Based on the best information at the time, assumptions serve as checkpoints on the validity of strategies. If future occurrences deviate significantly from assumptions, strategists know that corrective actions may be needed. Without reasonable assumptions, the strategy-formulation process could not proceed effectively. Firms that have the best information generally make the most accurate assumptions, which can lead to major competitive advantages.

2. Business Analytics

Business analytics is an MIS technique that involves using software to mine huge volumes of data to help executives make decisions. Sometimes called predictive analytics, machine learn­ing, or data mining, this software enables a researcher to assess and use the aggregate experience of an organization, which is a priceless strategic asset for a firm. The history of a firm’s interac­tion with its customers, suppliers, distributors, employees, rival firms, and more can all be tapped with data mining to generate predictive models. Business analytics is similar to the actuarial methods used by insurance companies to rate customers by the chance of positive or negative outcomes. Every business is basically a risk management endeavor! Therefore, like insurance companies, all businesses can benefit from measuring, tracking, and computing the risk associ­ated with hundreds of strategic and tactical decisions made every day. Business analytics enables a company to benefit from measuring and managing risk.

As more and more products become commoditized (so similar as to be indistinguishable), competitive advantage more and more hinges on improvements to business processes. Business analytics can provide a firm with proprietary business intelligence regarding, for example, which segment(s) of customers choose your firm versus those who defer, delay, or defect to a competi­tor and why. Business analytics can reveal where competitors are weak so that marketing and sales activities can be directly targeted to take advantage of resultant opportunities (knowledge). In addition to understanding consumer behavior better, which yields more effective and efficient marketing, business analytics also is being used to slash expenses by, for example, withholding retention offers from customers who are going to stay with the firm anyway, or managing fraudu­lent transactions involving invoices, credit-card purchases, tax returns, insurance claims, mobile phone calls, online ad clicks, and more.

A key distinguishing feature of business analytics is that it enables a firm to learn from expe­rience and to make current and future decisions based on prior information. Deriving robust pre­dictive models from data mining to support hundreds of commonly occurring business decisions is the essence of learning from experience. The mathematical models associated with business analytics can dramatically enhance decision making at all organizational levels and all stages of strategic management. In a sense, art becomes science with business analytics resulting from the mathematical generalization of thousands, millions, or even billions of prior data points to discover patterns of behavior for optimizing the deployment of resources.

Netflix has used business analytics lately to mount a comeback in the industry and to grow dramatically its customer base. Netflix uses data analysis increasingly to refine its movie rec­ommendations to particular customers as well as to identify which movies and television shows to license or develop. A recent article by Willhite defines business analytics as “the art and science of collecting and combing through vast amounts of information for insights that aren’t apparent on a smaller scale.”14 Data mining, and using an analytical approach to all phases of strategic management, is rapidly burgeoning into a necessary prerequisite for success in hundreds of firms globally. This book advocates a systematic, analytical approach to strategic planning because otherwise emotion, politics, “experience,” and subjectivity too often prevent identification and consideration of key facts, figures, and trends in choosing among numer­ous feasible alternative strategies, and implementing and monitoring the execution of those strategies.

The big data analytics firm, Splunk, reports ever-increasing revenues and profits as it capitalizes on a growing market for helping companies find better ways to manage increasing amounts of data coming in from mobile phones, PCs, global positioning systems, and other electronic devices. Splunk CEO Godfrey Sullivan says companies have “a massive thirst to bet­ter understand their customers, as well as the data coming through the enterprise from a variety of sources.”

IBM’s annual business analytics revenues of about $40 billion are growing about 15 percent every quarter, compared to the industry growing about 15 percent annually. IBM’s acquisition of SPSS for $1.2 billion, among other recent acquisitions, launched the firm heavily into the busi­ness analytics consulting business. Other business analytics firms are Oracle, Tableau Software, Rocket Fuel, and Cisco Systems.

Source: David Fred, David Forest (2016), Strategic Management: A Competitive Advantage Approach, Concepts and Cases, Pearson (16th Edition).

One thought on “Forecasting Tools and Techniques

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