Journal of Business Forecasting Articles Issues

AI is a valuable tool, particularly in demand forecasting where machine learning can man- age large amounts of data and select the most effective models. It has its limitations, however, and overreliance on AI-generated outputs can emerge all too easily at the cost of human creativity. In this article I discuss how AI algorithms rely on existing ideas, information and methods instead of fostering new ways of doing things which, if not combined with human judgement, leads to mediocrity. I also examine how AI is prone to a phenomenon whereby models incorpo- rate their own biases and get worse over time, resulting in both poorer business decisions and entrenchment of societal problems.

Demand forecasting of new products has been a persistent challenge for many industries. Although attempts to use AI for new product forecasting in the manufacturing sector have increased in recent years, companies often struggle to see tangible results. I posit that in today’s VUCA environment, the goal is no longer forecast accuracy and that a paradigm shift is necessary. In this article I propose ‘sense-making demand forecasting’ supported by advanced technologies that enhance visibility into demand drivers. This new forecasting approach will not only pro- vide companies with the confidence to launch new products but also lead to creating new demand.

Are we too obsessed with forecast accuracy? My experience in the forecasting and planning domain leads me to question the widespread notion that accuracy is a good driver of corporate success. The M5 forecasting competition, which uses over 30,000 time series, uncovers unexpected insights. Contrary to common belief, it reveals that an exclusive emphasis on accuracy doesn’t consistently improve decision-making or economic outcomes. This analysis prompts a revaluation of the traditional pursuit of accuracy, advocating for a balanced approach prioritizing economic value in forecasting and decision-making practices.

In FMCG, different products can display very different demand characteristics, making categorizing them for segmentation challenging. One way to segment products is the ‘Animal Farm’ method whereby products are assigned an animal identity that best represents their demand behavior. This intuitive way of categorizing like products lays the groundwork to apply appropriate forecast models and tailored demand management approaches. In this article, we will delve into each method’s intricacies, from establishing a solid foundation with statistical forecasting to the nuanced art of forecast value-add. In so doing, I aim to provide insights into how companies can navigate their vast data and product landscapes with structure, precision and foresight.

There are several key success factors for effective Sales and Operations Planning , including visible executive leadership, alignment in objectives, interdepartmental collaboration, and discipline in implementation. This article is a practical guide to the important points of S&OP implementation with a real-life case study at a European office supplies retailer. I reveal the challenges faced, including the resistance of the commercial function to change, as well as how to conceptualize and communicate the value of S&OP, namely that it a business management model that facilitates decision making—and not just an operations process.

Consensus is a foundational element of the S&OP process, aligning stakeholders on core assumptions that underline decision making. But how we arrive at consensus can vary from organization to organization. It is all too easy to fall into the trap of believing there is a single source of truth and excluding the variety of perspectives from different functions that enrich the decision-making process. In this article I advocate for not shying away from constructive conflict and aiming for unity, not unanimity. I also provide practical tips for getting functions with disparate aims to agree and how to combine quantitative data with qualitative expertise.

Demand-supply uncertainties, and the severe supply shortages and surpluses experienced during the COVID-19 pandemic, provided a valuable lesson for Planners and Forecasters: that the S&OP process alone is not always sufficient for planning. This column recommends two operational planning teams to help address these concerns. First, the ‘Quick-Response’ planning team to manage operational planning during extreme uncertainties in demand and supply and, second, the ‘Supply-in-Mind’ planning team to identify supply issues and develop demand-shaping tactics to enhance demand-side performance.

Despite recent layoff announcements, US job growth totaled 275,000 in February with unemployment rising to 3.90% which, despite the increase, is still low. Inflation (3.20% in Feb) continues to be persistent and above the target rate of 2.00%. With climbing unemployment and steadfast inflation expected from Q2 of 2024 to Q1 of 2025, Consensus expects the nation’s GDP growth rate to increase by 1.33% which is a low but steady level of growth. Similarly, Wells Fargo expects real GDP to be about 1.40% by Q4-2024 amid stronger consumer spending, a firmer hiring environment and downward trending inflation.

This column reintroduces a supply-demand matching planning process that involves “demand shaping with supply in mind”. It was the type of process that was needed during the pandemic. When there were severe supply shortages, both supply and demand became uncertain. Also discussed is the projection that this process may need to be deployed more often during the looming Longevity Economy which might result in severe labor shortages, as well as result in other types of supply constraints. The process, however, could also be always useful for creating a role for supply-side Planners to help generate additional revenue and profits.

Supply chain plasticity is a novel concept borrowed from neuroscience whereby the brain reorganizes its neural pathways to restore function following injury. This concept is applicable to supply chains, whereby production can be safeguarded amid catastrophic events by realigning across unaffected pathways in the supply net- work. I offer two case studies of plasticity from my own experience: a beverages company faced with a heat wave and a CPG company faced with a hurricane damaging its production plant. In both scenarios I reveal the options available to switch operations to different pathways in the supply network to mitigate disruption and provide continuity. I also highlight the importance of not perceiving plasticity as reversion to the pre-crisis state; rather a permanent adaptation to the new reality.

The digital transformation of supply chain management, expedited by the pandemic, un- derscores the need to invest in automated forecasting and planning solutions to safeguard financial stability amid fluc- tuating costs and economic uncertainties. The pandemic highlighted the limitations of isolated supply chains, as disrup- tions rippled across supply networks, emphasizing the need for cross-enterprise collaboration. This article reveals the need to move beyond traditional data sharing, and how the future of collaborative forecasting involves a commitment to shared data, technology, process, and people—underlined by the digitalization of supply chains. We also discuss the challenges of cross-enterprise collaboration, keys to success, and the required skillsets to succeed in this environment, with a nod to the rise of the ‘Business Scientist’.

Despite the increasing pressure to reduce working capital across many industries, many multinationals still optimize their inventory in the end-to-end supply chain in siloes. This leaves room for improving costs, customer service and working capital. This article explains the concept of multi-echelon inventory optimization and how to successfully implement it in your organization, along with best practices and lessons learned from a real life MEIO implementation in the CPG industry.

Forseveraldecades,outsourcingproductiontothefarEasthasbeenhighlyeffective in reducing production costs for American firms. Recent events, however, have exposed the fragility of long, global supply chains and the rise of China as a middle-income country has eaten into profit margins. Reshoring and nearshoring is picking up pace amid a torrent of geopolitical tension, protectionist tariffs, and COVID. In a world where China is no longer the reliable and cost-effective workshop of the world, what options do US manufacturers have? In this article we discuss the merits and demerits of nearshoring to Mexico which, with its proximity to the US market, improving industrial base, affordable labor, and positive regulatory environment, presents a viable option for many US firms.