Consumption-Based Forecasting and Planning

Predicting Changing Demand Patterns in the New Digital Economy

Charles W. Chase

• Publisher: Wiley
• Year: 2021
• Print ISBN: 9781119809869
• eBook ISBN: 9781119809876
• Edition: 1
• Topic: Business
• Subtopic: Business Strategy
• Index: Business

Discover a new, demand-centric framework for forecasting and demand planning

In Consumption-Based Forecasting and Planning, thought leader and forecasting expert Charles W. Chase delivers a practical and novel approach to retail and consumer goods companies demand planning process. The author demonstrates why a demand-centric approach relying on point-of-sale and syndicated scanner data is necessary for success in the new digital economy.

The book showcases short- and mid-term demand sensing and focuses on disruptions to the marketplace caused by the digital economy and COVID-19. You'll also learn:

• How to improve demand forecasting and planning accuracy, reduce inventory costs, and minimize waste and stock-outs
• What is driving shifting consumer demand patterns, including factors like price, promotions, in-store merchandising, and unplanned and unexpected events
• How to apply analytics and machine learning to your forecasting challenges using proven approaches and tactics described throughout the book via several case studies.

Perfect for executives, directors, and managers at retailers, consumer products companies, and other manufacturers, Consumption-Based Forecasting and Planning will also earn a place in the libraries of sales, marketing, supply chain, and finance professionals seeking to sharpen their understanding of how to predict future consumer demand.

CHAPTER 1
The Digital Economy and Unexpected Disruptions

We are experiencing unprecedented and unpredictable times where disruption has been felt globally by many companies, particularly retailers and consumer goods companies. The digital economy has had an impact on almost every aspect of our lives from banking and shopping to communication and learning. This incredible progress driven by digital technologies is affecting the world we live in by improving our lives, but also creating new challenges. The most successful organizations get ahead of an unpredictable future by being prepared for the unknown. There have been significant developments in the evolution of various disruptive technologies over the past two decades and this development brings new opportunities, both in terms of cost savings and overall value creation. The benefits of IoT, big data, advanced analytics, AI/machine learning, cloud computing, and other advanced technologies collectively can make an impact that companies can leverage to digitize their supply chains to address business challenges.

The world is changing at an accelerated pace and companies are seeing that the biggest benefits of digitization come from the ability to move faster, adapt quickly to disruptions, anticipate changes, and automatically execute information faster by managing large volumes of data more effectively—all resulting in speed of innovation and execution of those changes. As a result, companies are looking for real-time data collection across multiple media platforms that will provide actionable insights from the data to advanced analytics with easy-to-use user interfaces (UI). Additionally, these companies hope to remotely gather relevant information affecting day-to-day operations to monitor performance, make the right decisions at the right time, and improve the velocity of supply chain execution. Digital transformation will help companies establish that foundation by becoming more agile and flexible.

The consensus is that the overarching impact of digital transformation strategies and objectives will have significantly more influence than just cost savings. Companies are facing increased consumer demand for reasonably priced, high-quality products and cannot afford quality-related disruptions with their products and services. Visual depiction of a demand plan, graphical depictions of performance indicators, and better visibility of KPIs through dynamic searches and interactive dashboards and reports will enable seamless data discovery and visualization. Users need to easily compare multiple scenarios and visualize them fully for improved performance.

DISRUPTIONS DRIVING COMPLEX CONSUMER DYNAMICS

Over the past decade, consumers have been gaining power and control over the purchasing process. Unprecedented amounts of information and new digital technologies have enabled more consumer control, and now, instead of being in control, marketers have found themselves losing control. In the past several years, however, there's been a shift. Even as consumers continue to exert unprecedented control of purchasing decisions, power is swinging back toward marketers, with the help from technology and analytics that play a new and larger role in the decision-making process.

Consumers are turning increasingly to technology to help them make decisions. This has been enabled by four key disruptions.

1. Automated consumer engagement. A shift from active engagement to “automated engagement” where technology takes over tasks from information gathering to actual execution.
2. Digital technologies. An expanding IoT which embeds sensors almost anywhere to generate smart data regarding consumer preferences triggering actions offered by marketers.
3. Predictive analytics. Improved predictive analytics or “anticipatory” technology driven by artificial intelligence (AI) and machine learning (ML) that can accurately anticipate what consumers want or need before they even know it—based not just on past behavior but on real-time information and availability of alternatives that could alter consumer choices.
4. Faster, more powerful cloud computing. The availability of faster and more powerful on-demand availability of computer system resources, especially data storage (cloud storage) and computing power, without direct active management by the user. Cloud-based demand forecasting and planning solutions that crunches petabytes of data, filters it through super-sophisticated models, and helps analysts and planners gain previously unheard-of efficiencies in creating more accurate demand plans.

Instead of merely empowering consumers, technology is making decisions and acting for them. Analytics technology will be doing more and more of the work for companies by automating activities around demand forecasting and planning in real time.

It's no longer merely about predicting what consumers want. It's about anticipating—which includes the ability to adapt marketing offers and messages to alternatives based on data from hundreds of possible sources. By anticipating, we gain a greater chance of influencing outcomes. Consumer's phones or smartwatches can deliver recommendations and offers where to go, how to get there, and what to buy based on what they are about to do, not just what they've done in the past. Anticipation is about the short-term future, or even a specific day and time. Analytics provides marketers with the ability to create contextual engagements with their customers by delivering personalized, real-time responses.

Technology is helping both marketers and customers take the next evolutionary step. Instead of merely empowering customers, it's making decisions and acting for them. Analytics technology will be doing more and more of the work for companies by automating activities around research and making actual purchases.

IMPACT OF THE DIGITAL ECONOMY

The new digital economy has affected all aspects of business, including supply chains. The Internet of Things (IoT), with its network of devices embedded with sensors, is now connecting the consumer from the point of purchase to the factory. Technologies such as RFID, GPS, event stream processing (ESP), and advanced analytics and machine learning are combining to help companies to transform their existing supply chain networks into more flexible, open, agile, and collaborative digital-driven models. Digital supply chains enable business process automation, organizational flexibility, and digital management of corporate assets.

Crossing the “Digital Divide” requires a holistic approach to digital transformation of the supply chain that includes new skills and corporate behaviors. New capabilities are also required such as digitally connected processes, predictive analytics to sense demand using pattern recognition, and scalable technologies with the capability to process “big” data using in-memory processing and cloud computing.

WHAT DOES ALL THIS MEAN?

The gradual replacement of human judgment across the supply chain. Companies will use advanced analytics to optimize complex cross-functional trade-offs to facilitate value across the supply chain directly from the consumer back to the supplier. This new digital supply chain network allows companies to match the long tail of demand, supply, and production capabilities to create the ultimate customer/consumer fit and fulfillment.

Digitization will affect all supply chain IT systems including seamless integration across organizations, as well as real-time synchronization of data, global standardization of workflows, and rising demands of cybersecurity. This requires companies to evolve in order to best support areas such as automated data gathering, short-term tactical demand and supply planning, procurement, and execution. The challenges inherent in digital transformation are:

• Continual connectivity. We live in an always-on, always available world where customers/consumers expect to access information and execute any task from any device.
• Organizational speed. Those companies who recognize market change and opportunities will profit the most from digital transformation.
• Deluge of information. Information is being collected by companies from multiple channels, devices, and forms at incredible speeds with minimal latency.

Those companies who understand how to capture, store, and process this information will uncover business value and experience the most benefits.

Digital transformation crosses many facets of a company's business including collaboration platforms, cloud, mobile, social media, big data, and most of all, predictive analytics. Digital transformation hinges on big data and advanced analytics. The analytics process needs to be tied to distinct digital architectures that include data integration and management, robust visualization and advanced statistical models for discovery and prediction, as well as continuous delivery of insights as events unfold, which is vital to digital transformation.

According to the 2020 Consumer Goods Technology (CGT) Retail and Consumer Goods Analytics Study, retailers and consumer goods suppliers for the first time agree on the top three areas of focus over the next year (mainly as a result of the coronavirus pandemic). Those three areas are:

1. Demand Forecasting (57% retail and 67% CG, respectively);
2. Consumer Insights (43% and 50%); and
3. Inventory Planning (40% and 30%).

In addition, roughly one-third of retailers chose pricing as a top-of-mind area of focus followed by personalization and logistics optimization. Consumer goods companies felt that assortment planning followed by marketing mix optimization completed their top areas of focus for the next year. (See Figure 1.1.)

The myriad forces affecting the relationship between demand and supply are set to expand their influence as a result of the “automated consumer engagement” and the recent disruptions. The ability to collect real-time consumer demand through digital devices will force companies to digitize their supply chains. Finding ways to be better prepared means implementing a corporate culture and structure that brings together organizations and, most of all, data from different sources. The analytics and technology capability are now available, so organizational changes and skills must transition to the next generation demand management with a renewed focus on people, process, analytics, and technology.¹ However, it also requires ongoing change management to not only gain adoption, but to sustain the new (normal) corporate culture.

Figure 1.1 Top 5 Analysis Areas of Focus

Source: Tim Denman and Alarice Rajagopal, “Retail and Consumer Good Analytics Study 2020,” Consumer Goods Technology, March 2020.

There is a more fluid distribution of goods today because customer purchase behavior has changed the way products are created and sold. The rise of omnichannel and new purchasing processes such as Amazon.com make inventory management more unpredictable. The influence of external factors, such as social media, Twitter, and mobile devices, makes it more challenging for distributors and retailers to plan deliveries and stock orders. Regardless, next-day or even same-day delivery is an expectation that consumer goods companies' supply chain processes are tasked to provide. These factors are making demand more volatile, and as a result, manufacturers can no longer operate using inventory buffer stock to protect against demand volatility, as it can too easily result in lost ...

Table of contents

• Cover
• Table of Contents
• Title Page
• Copyright
• Foreword
• Preface
• Acknowledgments
• About the Author
• Chapter 1: The Digital Economy and Unexpected Disruptions
• Chapter 2: A Wake‐up Call for Demand Management
• Chapter 3: Why Data and Analytics Are Important
• Chapter 4: Consumption‐Based Forecasting and Planning
• Chapter 5: AI/Machine Learning Is Disrupting Demand Forecasting
• Chapter 6: Intelligent Automation Is Disrupting Demand Planning
• Chapter 7: The Future Is Cloud Analytics and Analytics at the Edge
• Index
• End User License Agreement