BackgroundForecasting and demand planning are essential to business operations and will be especially important for project-based industrial companies in the near term. Capital expenditures by S&P 500 companies have grown by about 20 percent in 2022. As a result, project-based businesses must contend with the complex planning and supply chain issues that are inherent to investments in plant, property and equipment updates, and acquisitions.Planning is no easy task for these companies as global supply chains are reoriented. Poor planning can result in wasted time, and more importantly wasted money, as labor waits idly. The challenges are most pronounced in areas where demand is underpinned by advanced industries and large-scale deployments, such as supply chain automation, defense industrial assets, biologics, specialty chemicals, precision control, electrification systems, and infrastructure.The challenge of forecasting and demand planningForecasts and demand plans are often nebulous because of unpredictable sales cycles, unique project-specific needs, and changing customer requirements. Resource needs are also difficult to integrate across disciplines and can rely too much on individual judgment. Sales or induction processes can quickly get out of alignment with what the business can actually deliver, and supply capacity can be constrained or lack resiliency when disruptions inevitably occur. Beyond the internal challenges, ever-changing engineering specifications and requirements increase the difficulty in accurately forecasting demand.The core questions of risk and uncertainty—what’s needed and when—are the root of the forecasting challenge. Leading companies understand and shape demand to create a lasting competitive advantage by focusing on three types of approaches (see figure).Demand forecasting analyticsThe first challenge is how to forecast demand with granularity and accuracy.Leading project companies establish robust forecasts of their resource needs, using data and analytics to develop an integrated view of their business needs. They tie analytics directly to both front-end load plans and execution processes, uncovering insights into uncertainties and trade-offs around project scope, timing, and the use of capital.Many companies adapt common packages, such as SAP APO, Kinaxis RapidResponse, or o9 Solutions, or more advanced Bayesian or machine-learning approaches to work with their operating models, often systematizing the most important data to make the best judgments. This data can include internal and external sources, such as advanced indicators for macroeconomic conditions or demand-influencing supply chain risks.The leaders incorporate unique domain knowledge—such as execution history, statistical aggregations, joint business planning, supply relationships, and unique constraints—in their predictive forecasts, enabling them to use data to create a competitive advantage.Example:the power of analytics. A leading industrial maintenance, repair, and overhaul (MRO) operation developed a predictive demand forecasting capability and integrated it into its maintenance planning processes. The process entailed 30 to 50 percent unplanned and late identified work that had been causing material shortages The solution allowed for different maintenance schemes, trade-offs between working capital and execution risk, and a strategy to improve its material and inventory posture by having the right material available across its network of sites. This analytics capability resulted in 50 percent more material identified prior to the start of execution, resulting in less schedule churn and greater on-time delivery. In addition, the operation improved working capital by having the right material on the shelf at the right time.Demand sensing and shapingAnother challenge is how to plan and execute large projects in the face of an uncertain scope. The need for flexibility is vital in an evolving market environment.Leading project companies systematize how they engage their customers and internal business stakeholders (such as design and engineering teams)—both to sense shifts in demand, considering internal data points (such as design specification changes, sales history, and field data) as well as external elements (such as macroeconomic indicators, weather patterns, and competitor moves) and how to make changes for effective delivery on cost, schedule, safety, or effectiveness. They also connect on-demand sensing with their delivery, project management, and supply planning capabilities in a way that allows the organization to be agile and flexible, and they address trade-offs to time and capital, often using resource-loaded schedules or time-phased resource plans.At the same time, these companies actively shape demand by moving their customers toward better solutions and more strategic outcomes.Example: the power of the pivot. A leading semiconductor manufacturer implemented an advanced data and intelligence layer on top of its traditional integrated business planning system, allowing it to quickly sense demand and pivot toward a more optimal stocking of parts. This included placing purchase orders for long-lead critical parts 12 to 18 months in advance to minimize supply risk. The result was better delivery performance, even in the face of market volatility.A program manager-oriented operations modelThe final challenge is how to run an operation that incorporates demand, supply, customer, and financial perspectives across programs and projects.Leading companies develop governance and operations with a program manager (PM) who is empowered to innovate, develop solutions, and solve problems. A PM-oriented operations model lessens a company’s risk with robust planning and forecasting. The PM serves as the organization’s focal point and establishes a common operating plan across the various functions or sites involved. The PM often oversees change management and contract management processes to control for specification creep and customer driven schedule changes. The PM also owns forecasting, planning, execution, and reporting of programs, acting as a constant and steady hand to make sure the organization’s activities are able to accomplish what has been promised to the customer.Example: the power of the PM. A leading defense industrial company restructured its sales, inventory, and operations planning processes to incorporate a PM-oriented operations model. The enhanced approach led to better delivery, including consistent, sitewide views of demand, supply, and reconciliation around delivery schedules.Unlock value with an innovative approachAs projects become more complex, many companies that support advanced industries will find their businesses under even more pressure to deliver on schedule, cost, safety, and technical effectiveness. Novel ways of forecasting and demand planning lead to more effective ways of delivering value for customers while also mitigating internal risks.