Journal of Business Forecasting Articles Issues

This article is a revision of one written almost twenty years ago in the JBF, “Forecasting Heroes Catch Turning Points” published in the Summer 2001 issue. While the ideas are largely the same, it is particularly relevant for today’s forecasters and planners. The U.S. has experienced a long-running period of economic growth and pundits are speculating about an economic downturn. After all, “what-goes-up, must come down” and “what goes down must come up” and we are at a point in the economic cycle where things are likely to go down. For too long, business forecasters and planners have had a relatively easy job forecasting continual growth. A potential downturn is much harder to forecast. This first column of a two-part series deals with potential ways to forecast turning points and get organizational support for them. A second column will deal with selling and surviving in an organization and living through a ‘bad news’ forecast.

This article discusses the importance of establishing strong links between demand planning and inventory management processes. Several steps in the Sales & Operations Planning (S&OP) process can be more effective if this relationship is managed well. For example, linking expected demand patterns with a review of stocking risks and an evaluation of the best stocking strategy. It shows “how-to” examples for integrating demand planning with inventory control to gain a better overall balance across objectives leading to improved financial performance.

Excel spreadsheets have long been a valuable resource to professionals the world over, including Demand Planners. However, spreadsheets cannot scale in today’s digital economy where data streams into repositories every second from mobile devices, websites and IoT connected devices. Over the last decade, a wide variety of other, non-spreadsheet-based forecasting and planning tools, applications, and enterprise solutions have become available that can handle this Big Data. Here I reveal that to succeed in our roles in the digital economy, we need to move away from spreadsheets and towards these more sophisticated, scalable solutions.

The COVID-19 pandemic has quickly disrupted global business operations by impacting resources at multiple points in a complex, interconnected process. From suppliers to transportation, and including huge spikes and deep declines in demand, there are varying degrees of disruption in virtually all industries. While it is impossible to predict a crisis like COVID-19, this article outlines a path to combat volatility with vitality by harnessing the power of AI with best-fit internal and external data to model and better predict demand across short- to long-term horizons.

Demand planning for the e-Commerce channel presents some unique challenges. Success in planning for this channel requires a different perspective on planning and a different approach to managing the planning process. It may also require a different organizational structure. In this article I share some of my experiences with planning demand for this channel, with the hope that others that are new to planning for this channel can avoid some of the mistakes I made when I first started.

Since 2011, Philip has been the Annenberg University Professor at the University of Pennsylvania, with cross-appointments in Psychology, Political Science and the Wharton School. He has received awards from the American Psychological Association, American Political Science Association, American Association for the Advancement of Science, International Society of Political Psychology, the Carnegie Foundation and many more. He leads the Good Judgement Project which aims to identify ‘superforecasters’. He co-authored the best-selling book Superforecasting: The Art and Science of Prediction which explores the project’s findings and is regarded as one of the most important works on decision making.

While many of us understand the importance of engaging the Commercial function in the S&OP process, less is understood about the benefits of engaging the Finance Function. In this article I discuss why engaging Finance is not only an advantage but a core requirement for a sustained S&OP process. Their experience in cross-functional collaboration, reporting and data-driven decision making means they are ideal business partners. When S&OP is sponsored by the CFO, Finance’s involvement can drive real and lasting change, and be a catalyst towards S&OP and IBP maturity.

Garry Ridge is the CEO and chairman of WD-40 Company, a San Diego-based manufacturer of lubricants and household cleaning products where he has worked for 33 years. He is the co-author of Helping People Win at Work and is a prolific speaker and leadership coach. He is a key proponent of servant leadership, an approach that revolutionizes the role of senior business leaders. Garry is an adjunct professor at The University of San Diego where he teaches Talent Management.

Implementing S&OP is as much a change management process as it is a technical supply chain process, and yet many process owners fail to manage the critical nuances of change required for success. Often times, in excited exuberance, process owners publish positive metrics without understanding the negative impact it can have on the success and sustainability of the process. The poor handling of early metric improvements can stall or damage the S&OP implementation project. In this article, I focus on how to finesse the communication of these positive results, the appropriate metrics to use when gauging success, and key factors to be aware of throughout the process.

Dr. Simos is Director of Forecasting and Predictive Analytics at e-forecasting.com, a division of Infometrica’s Data Center, 65 Newmarket Road, Durham, NH 03824, U.S.A. and professor of economics at Paul College, University of New Hampshire, www.infometrica.com, eosimos@e-forecasting.com. This report does not purport to be a complete description of global economic conditions and financial markets. Neither the Journal nor Infometrica, Inc. guarantee the accuracy of the projections, nor do they warrant in any way that the use of information or data appearing herein will enhance operational or investment performance of individuals or companies who use it. The views presented here are those of the author, and in no way represent the views, analysis, or models of Infometrica, Inc. or any organization that the author may be associated with.

Dr. Nahavandi is Associate Professor of economics at Pfeiffer University School of Graduate Studies, specializing in Business Economics, International Business, and Healthcare Economics. The information in these forecasts is gathered by the Journalfrom sources it considers reliable. Neither the Journal nor the individual institutions providing the data guarantee accuracy, nor do they claim that use of the data appearing herein will enhance the business or investment performance of companies or individuals who use them.

This article describes a 5-step process about how the philosophy of Lean Manufacturing can be applied to demand planning. The steps include what customers truly value (valuable products being those customers are willing to pay for); mapping the value stream (i.e., how a product is delivered to the customer); evaluating opportunities for improvement; working on activities that are requested by customers; and aiming for continuous improvement.

Dr. Nahavandi is Associate Professor of economics at Pfeiffer University School of Graduate Studies, specializing in Business Economics, International Business, and Healthcare Economics. The information in these forecasts is gathered by the Journal from sources it considers reliable. Neither the Journal nor the individual institutions providing the data guarantee accuracy, nor do they claim that use of the data appearing herein will enhance the business or investment performance of companies or individuals who use them.

Dr. Simos is Director of Forecasting and Predictive Analytics at e-forecasting.com, a division of Infometrica’s Data Center, 65 Newmarket Road, Durham, NH 03824, U.S.A. and professor of economics at Paul College, University of New Hampshire, www.infometrica.com, eosimos@e-forecasting.com. This report does not purport to be a complete description of global economic conditions and financial markets. Neither the Journal nor Infometrica, Inc. guarantee the accuracy of the projections, nor do they warrant in any way that the use of information or data appearing herein will enhance operational or investment performance of individuals or companies who use it. The views presented here are those of the author, and in no way represent the views, analysis, or models of Infometrica, Inc. or any organization that the author may be associated with.

Doug is credited with originating the field of infonomics, developing methods to quantify information’s value. He put forward these ideas in the best-selling book, Infonomics: Monetizing, Managing and Measuring Information as a Competitive Advantage, and lectures on the topic at the University of Illinois Gies School of Business. Formerly, Doug led the Deloitte Analytics Institute and worked as an analyst at Gartner’s research and advisory practice. When he is not teaching, Doug leads the data and analytics strategy practice at the consultancy firm Caserta.