Journal of Business Forecasting Articles Issues

I've never been a fan of forecasting approaches to intermittent de- mand. With intermittent demand — or other situations (like new products) where we have little hope of reasonably accurate forecasts — my thinking is “why bother with trying to forecast?”. But just because we can’t expect to solve a business problem with forecasting, it doesn’t mean there is no solution. It just means we need to find a different approach. This same kind of mindset — this openness to look beyond just throwing more sophisticated models at a problem — is displayed in the new book Intermittent Demand Forecasting: Content, Methods and Applications by John Boylan and Aris Syntetos.

This book has, once again, reminded me of what I admire most about Charlie Chase: He discusses forecasting in a language that everyone can understand, from the most junior data analyst to C-level executives, and teaches them something important about the topic that is directly relevant to them. In his latest book, Consumption-Based Forecasting and Planning, Charlie explains how Predictive Analytics and Machine Learning can help firms improve their forecasting and demand planning processes.

It is with a heavy heart that we announce the passing of a much loved IBF team member. Gina Ribeiro, Director of Education Programs at the Institute of Business Forecasting, died on October 19, 2021 surrounded by her loving family. Gina joined IBF in 2015 to lead IBF’s corporate training programs and, during her time with the company, oversaw the delivery of industry leading training for a variety of companies across the globe. Gina played a key role in developing IBF’s eLearning program and was committed to delivering value to her clients, ensuring IBF programs aligned with industry recognized corporate training standards and met the challenges that companies face in demand planning, forecasting and S&OP.

Several key economic factors including a strong labor market, high consumer demand, and historically high household savings (that would cushion any potential downturn) contribute to the sense of hope for 2022. Unemployment stood at 4.2 percent in November, compared with the pre-pandemic 3.5 percent in February 2020. The stubborn mismatch between job vacancies and the unemployed suggests that the natural rate of unemployment has shifted and long-term investment in public goods is the only way to realize unlocked GDP potential. The number of unemployed workers stood at 6.9 million, almost two million more than the pre-pandemic level in February 2020.

The Demand Review is a crucial part of the S&OP process because it’s where different functions align on forecasts and demand plans, and identify any challenges in meeting demand, or any opportunities to be exploited. The aims of this process step are simple enough, but all too often the Demand Review fails in these goals by focusing too much on historical performance and reporting instead of looking forward. Here I reveal the 4 cornerstones of an effective Demand Review that drive focus on what really matters to the business, including understanding what factors are impacting demand both now and in the near future and, most importantly, understanding the gap between the demand plan and financial plans.

Product or service strategy, and the ability of different functions to serve that strategy, makes or breaks a company. It stands to reason then, that S&OP should be designed to specifically support the enterprisewide goals of your business. Most companies have one of three overarching strategies: Product Leadership, Customer Intimacy or Operational Excellence. This article reveals how to identify which category your company falls into and how to adapt your S&OP to each strategy (with segmentation underlying each approach), along with practical tips for the Product Management Review and Executive S&OP steps.

S&OP is a cross-functional, collaborative forum that acts as the ‘operating system’ for a company. In this article I discuss how involvement of Finance in this process allows us to understand the financial implications of the demand plan, facilitating fully costed and financially viable demand management responses. It also allows us to know inventory and production costs and to develop accurate revenue and earnings estimates. I also reveal how Finance’s involvement leads to a robust Annual Operating Plan, avoiding the issue of disconnects between the plan and what actually occurs.

There are three components to effective S&OP implementations. When in place and implemented well, they will be mutually reinforcing and will help ensure long-term benefits to an organization. The first component is “thought leadership”, which provides a north star to S&OP implementations. The second is “structured deployment”, which ensures results will scale and adequate resources will be in place to support S&OP practitioners. The third is “governance”, which is critical for closing the loop and ensuring accountability over results achieved by S&OP over time.

This column deals with the role of the Sales and Operations Planning (S&OP) process when there are uncertainties in a supply chain, the likes of which emerge under extreme situations like the COVID-19 pandemic. I discuss how S&OP is designed to deal with risk, but not extreme volatility like we are experiencing now. In such cases, we need a temporary ‘Quick Response’ operational planning process that sits alongside the regular, formalized process of S&OP. I explain how such a tactical framework allows us to react quicker to demand and supply shocks in a way that S&OP cannot.

Executive sponsorship is key to successful S&OP deployment and an ongoing, sustainable process. In this article I reveal what is required from C-suite sponsors and what their specific role and responsibilities should be. I discuss how to secure their support by connecting the benefits of S&OP to strategic priorities, as well as tips to secure the support of managers to deliver the cross-functional collaboration so critical to S&OP success.

S&OP allows an organization to balance demand and supply, thereby cutting operational costs, freeing up cash, and improving customer service. The benefits are clear — effective implementation, however, remains more elusive and, for many companies, the first steps are often the hardest. In this article I reveal how to get started with S&OP by indentifying the appropriate function, channel, business unit, brand, or product to launch from. I discuss the criticality of starting small and securing sustainable, quick wins before attempting to launch a mature, enterprise wide process. I also dive into how using a maturity model identifies areas to improve and how securing allies in senior leadershop faciliates buy in.

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. Evangelos Otto Simos is head of predictive intelligence at Kefallonia, Inc., a private research and consulting firm, and professor at the University of New Hampshire. This report does not purport to be a complete description of global economic conditions and financial markets. Neither the Journal nor Kefallonia, 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 Kefallonia, Inc. or any organization that the author may be associated with. You can contact Evangelos at eosimos@e-forecasting.com

Stefan is a thought leader in the supply chain planning and forecasting domain with over 20 years’ experience. He has worked in many roles including technical and functional consulting, product design, product management, and development at multiple supply chain software companies, as well as serving as a planner and forecaster. He has applied his skills across many industries at companies such as Millennium Chemicals, Heineken, Beiersdorf, UCB, Biogen Idec, Valvoline, Kroger, Godiva, Ariat, and over a hundred more. In the process, Stefan realized that problems relating to accuracy, efficiency and stability, which he witnessed everywhere, were due to critical flawed assumptions. Over the last decade he has used his applied mathematics background to distill the root causes and design better approaches. He is a regular speaker, consultant, educator, blogger, and is writing his first book, “An introduction to Probabilistic Planning and Forecasting.”

Demand planning and supply chain management are essential platforms from which key business activities are launched throughout the company and must serve both the long-term business plans of the company and core financial metrics. This article reveals how Demand Planners can see their decision making through a financial lens which helps the business balance customer service and cost and cash efficiency. I reveal key financial questions to be asked and financial variables and relationships to be considered in order to balance these competing priorities. I also discuss the importance of return on assets and net income as key ways to understand how planning decisions are impacting your company’s performance.

When forecasting demand for a new product, we generally use cause-and-effect models but, owing to lack of data, forecast accuracy is generally poor, especially for brand new products that have no like items. In this article, I propose using a new heuristic model for new product forecasting. I argue that, though use cases are limited, forecast accuracy of this model may be significantly higher than that of analytic models. I will also reveal how we can generate range forecasts which changes uncertainty to risk which can subsequently be managed by supply chain management best practices.