Journal of Business Forecasting Articles Issues

Mature demand planning is a complex affair and difficult to achieve for even the most well-resourced organizations. One emerging solution to this challenge is outsourced demand planning, known as Third- Party Planning, that can handle one or more planning activities. Companies can rely on such providers to generate forecasts, develop materials for Consensus meetings, provide performance metric and give advice on how to improve. This article reveals how such providers fill a crucial skills gap, allowing companies to level up their planning capabilities in a flexible way that meets their specific requirements.

Technology innovations are poised to dramatically improve the value and effectiveness of S&OP and IBP processes, in both small and large manufacturers. New solutions are combining these traditional pro- cesses into fully integrated financial and operational planning and performance management. What results are incre- mental capabilities that can reduce the cost of planning by up to 50%, while simultaneously improving profits by up to 5% of sales. In this article, I make the case for leveraging these new technologies to fully integrate all elements of plan- ning across geographies and legal entities for a better view of business performance.

Since the pandemic, S&OP has seen further adoption and is increasingly recognized as a proven method to manage demand and supply variability. But have we stretched the scope of this planning process too far? Recently, many articles have been published that advocate for S&OP’s management of FP&A, Master Planning, New Product Development, and even commercial strategy. In this article I make the case that S&OP is designed to be the connective tissue between different planning processes and that S&OP adds the most value by integrating stand- alone functions and facilitating transfer of information, rather than setting the agenda for the entire enterprise.

The agricultural chemical marketplace is very complex. The end customers—growers— require a highly responsive and localized supply chain while suppliers must make purchase and production decisions long before variations in weather, pricing, pestilence, or prevalence of crops are known. The inherent conflict of long lead times and responsiveness is a nearly intractable supply chain problem. In this article, I outline how successful Agri- science suppliers try to optimize supply, demand and other influences to improve these crucial decisions, which ulti- mately impacts how produce is being brought “to the table”.

Despite increasing pressure to reduce working capital across many industries, many multinationals still set their safety stock targets as a number of weeks of demand depending on an item’s ABC/XYZ- segment, ignoring important aspects like lead time and replenishment quantities. This leaves room for improving costs, customer service and working capital. This article explains how to set up ABC/XYZ-segmentation in the right way and how to successfully implement inventory policies and service level differentiation in your organization. A real- life case study of a manufacturer of cargo securing systems is used to highlight best practices and the benefits gained.

Implementing planning software is a wide-reaching project that touches many individuals and functions. It represents a transformation in the way the business works, and it is safe to say that not everybody will support such a change. In fact, one or more individuals may be strongly resistant to change, even if the benefits are self- evident. In this article I discuss why digital transformations fail, drawing on first-hand experience at multiple organiza- tions. I reveal how to overcome common barriers to change and the key elements of a successful digital transformation, including assigning a change champion, defining the future state and educating users.

The current hype in Artificial Intelligence (AI), has compelled me to update my AI-related column from 4 years and a half years ago, titled “Artificial Intelligence: Decision Maker or Supporter?”. This update addresses whether AI-based decision-making should be the last word in making final decisions in forecasting and planning processes. To address this, two type types of cognitive thinking are discussed. While pre-supposing that AI will surely be useful in a decision support role, it looks at roles it may play in making decisions for the two types, without intervention from managers. Moreover, it warns against using AI output at face-value for the most impactful and strategic decisions.

Hiring in the US was stronger than expected in May with 272,000 jobs added, although unemployment simultaneously rose to 4.00% for the first time since Jan 2022. The increase in jobs is an indication that employers remain undaunted despite pressure from high interest rates and slowing consumer spending. Additionally, in May, the US economy experienced a slight cooling of inflation as consumer prices rose at an annual rate of 3.30%, prompting Fed officials to set out a future path for interest rates.

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.