The Growing Strategic Importance of Sales and Operations Planning

The growing strategic importance of sales and operations planning (S&OP) reflects the confluence of two major trends evolving outside of enterprise operations. One is the ongoing disintegration of the post-World War 2 liberal trade environment that began in the early 2010s and has accelerated since. The second is the increasing sophistication and approachability of S&OP software. These applications are designed to align an enterprise’s sales and marketing objectives with its operating environment (including its production and distribution assets as well as its supplier ecosystem) while respecting financial constraints. The availability of more accurate and nuanced machine learning (ML)-based forecasting systems and the growing availability of agents that shorten planning and execution cycles will enable enterprises using software to better adapt to change, anticipate risks and evaluate trade-offs to determine the best course of action faster with greater intelligence. These two trends have raised the importance and value of agility while making the software more powerful and easier to use. That noted, I expect the uptake of S&OP software will be slow. We assert that through 2027, only one-third of enterprises will have adequate technology to support S&OP requirements to achieve a competitive advantage.

S&OP is aligned with supply chain planning (SCP) but with a broader, strategic focus: eliminating planning silos by using an enterprise-wide approach that balances supply and demand while considering customer satisfaction and financial and corporate strategy objectives. This process ensures that all departments within an enterprise are working towards the same objectives and optimizing overall business performance. The result is a plan that coordinates sales, production, inventory, product, customer or channel lead time, and financial plans observing the best set of trade-offs.

The increasing strategic importance of S&OP has arrived after decades of evolving economic and technology trends. Greater global economic integration in the last decades of the 20^th century broadened the need for robust SCP. Accelerating trade integration, supported by more efficient transportation methods (such as containerization) along with the rapid adoption of the internet, caused enterprises to increasingly source and sell materials and manufacture products globally, leading to more complex and extended supply chains. The internet facilitated real-time communication and data exchange, enabling better coordination and collaboration among supply chain partners and an expanded set of potential buyers. As this happened, more capable planning and optimization tools became essential. For example, Advanced Planning and Scheduling (APS) systems emerged, offering sophisticated algorithms and models to optimize various aspects of the supply chain, such as demand forecasting, production scheduling and transportation planning. These tools helped companies make more informed decisions and respond more quickly to changes in demand and supply.

Technology continues to push the boundaries of what’s possible, broadening its scope to improve enterprise performance. Over the past decade, advances in application programming interfaces (APIs) have made rapid data integration from multiple source systems feasible, heightening situational awareness and allowing for faster forecasting cycles and response times. Meanwhile, the speed and scope of data processing continued to rise, enabling enterprises to analyze and plan in near real time rather than performing work in batches. And rather than having to laboriously plan in iterative steps to arrive at an optimal or even acceptable solution, results could be calculated concurrently. This shortens cycle times, potentially increasing agility in responding to market developments.

Enterprises benefit from S&OP software in multiple ways. The most important is through improved demand forecast results. Increasingly, this software uses advanced algorithms and ML to achieve greater forecast accuracy over simple time-series analysis, which helps companies to improve their planning by anticipating customer needs and reducing the risk of overstocking or stock-outs. Achieving superior order fulfillment promotes customer satisfaction. Another is better collaboration within an enterprise and across supply chains, which is critical because of the cross-functional and geographically distributed nature of organizations and their physical resources. The software promotes alignment while minimizing and mediating conflicting objectives. Because these tools provide real-time data and insights, they enable enterprises to make informed decisions faster, allowing them to respond sooner to changes in markets, economies or any factor that can disrupt conditions. Similarly, the software can help identify potential risks and disruptions in the supply chain. By simulating various scenarios and planning for contingencies, companies can mitigate risks and better ensure business continuity. All of which promotes enhanced efficiency and productivity, thereby reducing costs, especially for inventory holding costs, transportation, logistics and production.

We stand at a watershed in enterprise planning activities as a result of the availability of artificial intelligence (AI), generative AI (GenAI) and agents. AI can facilitate the process of continuous S&OP through better cross-functional coordination, significantly shortening the time it takes to iteratively juggle and resolve supply and demand chain objectives and constraints across multiple time horizons. It is already beginning to reduce the manual steps of supply and demand planning under dynamic business conditions, which occupies much of the time of the people involved in planning and execution management. AI and GenAI have the potential to substantially reduce the time required to perform these steps in order to make enterprises more agile and efficient. In the case of GenAI, ISG Research asserts that by 2027, all providers of sales and operations planning software will differentiate their offerings by the capabilities and accuracy of their GenAI functionality. Rather than having to focus almost all their time on mechanical tasks, analysts and managers will have time to consider multiple scenarios and their impacts. In ultimate form, systems should be able to apply event-driven analysis and suggestions that trigger actions to stay ahead of events.

AI will have an increasingly profound impact on enterprises that adopt the technology through the end of the decade. For most companies, the process of embedding AI in their supply chain activities will be gradual, starting with the easiest, most obvious and least risky aspects of planning and execution. As a first step, investments into data capture, orchestration and management will provide a foundation for more rapid analysis and reporting that promotes agility and deeper insight.

While it is common to hear that doing business is more challenging than ever, business challenges remain essentially the same. Enterprises must be able to create products and services that meet market requirements, market and sell those products effectively, operate efficiently and profitably, as well as attract and retain the human capital necessary to sustainably achieve those aims. What does change are the tools for doing business, providing those enterprises that successfully adapt and learn how to use these tools with a competitive advantage. AI in all of its forms is a powerful tool that will separate winners from also-rans. Enterprises with even moderately complex and lengthy supply chains must have a strategy and an evolving timeline for applying AI and GenAI to their planning processes. Those that do will have a cumulative strategic advantage over rivals that do not. Choosing the right software provider with the ability to provide AI-enabled tools will be important to facilitating adoption of this technology.

Regards,

Robert Kugel