Trends and Issues

Collaborative Demand Forecasting in Supply Chain Management

/>Modern supply chains are complex, with many interrelated participants who must work together to deliver products and services to customers as promised. Collaborative demand forecasting between buyers and suppliers is a powerful tool that can significantly streamline this process. - BY Sharon Ross

Supply chain collaboration brings internal and external partners together to optimize operations, and collaborative demand forecasting is an important element. Demand forecasting is estimating future demand for products and services based on data drawn from multiple sources. The traditional methods of forecasting demand are often inadequate in today’s complex and volatile global business environment.

A supply chain may have hundreds or thousands of suppliers working in constantly changing business environments, making matching supply and demand extremely challenging, especially when suppliers are located in diverse locations and multiple products and services are sold across various channels. The result is that many companies are prone to store surplus inventory, increasing costs without the assurance that the inventory is aligned with customer demand or that the inventory level will be able to meet demand. Collaborative demand forecasting brings internal and external entities together to share real-time intelligence. It is a proactive approach to aligning stakeholders through end-to-end visibility in the supply chain, using collaborative forecasting platforms.

Wanted: Data From Multiple Sources
Data is king in demand forecasting. Data must be available from multiple sources, and there must be effective ways to share the data with suppliers and others involved in the forecasting process. A corporate sourcing and procurement function shares data and data analytics with suppliers, and suppliers share their data and information in return. However, the exchange should also include sharing information that is important to forecasting to improve planning for manufacturing, inventory levels, logistics, and more. That includes information and insights about market conditions, customer needs, sales data, anticipated demand disruptions, and other relevant information that improves forecasting.

While collaborative demand forecasting relies heavily on integrated technology, engaging in joint planning sessions with critical suppliers and including operational people, like sales and marketing representatives, is important. Advanced demand forecasting platforms, such as ERP or Enterprise Resource Planning cloud-based software, can automate much of the demand forecasting process, supplementing the system with collaboration tools for easy real-time communication with suppliers.

During the COVID-19 pandemic, auto manufacturers experienced serious issues, like a shortage of semiconductor chips. The Toyota Production System shows how effective collaborative demand forecasting can help a company manage even a significant market disruption. Toyota proved resilient during the pandemic and continued to manufacture vehicles by using a strategic approach to inventory planning.

The strategic approach considers inventory sizes in the right locations and safety stock to cover disruptions and lead times. Lead times, requiring forecasting, mainly play a major role in keeping operations going because it ensures inventory is available for the locations and during disruptions. Toyota used usage rates and patterns for parts, collaborating with suppliers. In the winter, additional parts inventory is maintained to reflect forecasted weather interruptions in logistics. This example demonstrates the practical application of collaborative demand forecasting in a real-world scenario, showing its potential benefits and effectiveness.

Toyota shows that collaborative demand forecasting involves more than running a program and producing data analytics. Toyota works closely with suppliers and develops relationships built on trust so that suppliers are willing to invest in the facilities and technologies needed.

Demand Forecasting Platforms

Simplify Collaboration
Coupa Software Incorporated is a global technology platform and expert in supply chain management. Coupa describes three types of supply chain collaboration: vertical, horizontal, and full. Vertical collaboration is between the up and downstream members of the supply chain, i.e., suppliers, manufacturers, and buyers. Collaboration enables alignment of production schedules, inventory levels, and demand forecasting to maximize efficiencies and lower costs. Horizontal collaboration is between businesses in the same industry. They share resources, like warehousing, to reduce costs and optimize logistics. Full collaboration is the optimal supply chain collaboration. It is the collaboration of all stakeholders, including suppliers, manufacturers, distributors, businesses, and customers.

Though there are different supply chain collaboration models, Coupa points out that all three collaboration models can improve forecasting and demand planning. The goal is to forecast demand accurately, identify the risk of bottlenecks, and anticipate and manage demand changes, given changing variables. Collaboration improves inventory management because real-time data is shared concerning things like production schedules, demand forecasts, and inventory levels using an integrated digital platform. The platform supports communication, including rapid response to disruptions in the supply chain. Coupa’s collaboration tools include digital twin technology. This digital model of a real supply chain utilizes real-time operational data. The digital twin tests scenarios, predicts outcomes, and uses AI for time-series and demand-gap analysis to forecast demand.

Impact Analytics offers state-of-the-art demand planning software and points out that Collaborative demand planning is not just traditional forecasting. It is a strategic approach that has diverse stakeholders sharing data and information to forecast demand and optimize supply chains. The strategy synchronizes activities from supplier to customer to reduce inefficiencies, combines diverse perspectives to mitigate and manage demand volatility risks, and supports business decision-making.

Impact Analytics explains that collaborative demand planning involves internal and external stakeholders. While it is usually viewed as a sourcing and procurement strategy, a comprehensive collaboration involves various people and functions. For example, sales and marketing provide market trends and customer preferences data, operations and production offer information on the capabilities and constraints of the supply chain, financial professionals evaluate the financial implications of forecasts, suppliers offer insights into market performance, potential market disruptions, and capacity constraints, and logistics and transportation providers contribute insights into delivery capabilities and constraints. Customers, industry analysts, and market research firms provide additional data and information.

Strengthening Supplier Relationships
Collaborative demand forecasting improves forecast accuracy and strengthens supplier-buyer relationships, leading to improved efficiency and reduced costs across the supply chain. However, it is important to remember that demand forecasting requires continuous monitoring to ensure it remains effective as a competitive tool and process, keeping supply chain professionals proactive in managing their operations.

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