Market Perspectives

ISG Research is happy to share insights gleaned from our latest Buyers Guide, an assessment of how well software providers’ offerings meet buyers’ requirements. The Supply Chain Planning : ISG Research Buyers Guide is the distillation of a year of market and product research by ISG Research.

ISG Software Research defines supply chain planning (SCP) as the business discipline of coordinating the future supply of materials and services used in the creation of specific products and services with the expected demand for them. The purpose of planning is to optimize the flow of goods and materials with related services from suppliers to customers.

Supply chain planning is a relatively new field of business activity. It began in a rudimentary form in the early 20th century as the scope and complexity of industrial enterprises and their products grew to a point where a casual approach was no longer competitive. World War II spurred the need for better coordination of supply chain activities in the creation of complex armaments such as aircraft and ships. Operations research and the mathematical modeling required to solve complex logistical problems across the vast distances of the theaters of war laid the groundwork for modern SCP. The use of techniques such as linear programming and inventory management models became increasingly common in the 1950s and 1960s. Faster and more interconnected methods of communication expanded the geographical scope of suppliers and markets and, as a result, the need to deal with more complex logistical webs. The rapid evolution of technical innovations led to faster product cycles and a greater cost of obsolescence that could only be managed with better forecasting and planning techniques.

Business computing capabilities evolved significantly in the 1970s and 1980s, enabling the use of Material Requirements Planning (MRP) systems that allowed enterprises to better manage their inventory and production schedules. MRP systems used computer algorithms to determine the materials needed for production and the timing of their purchase. In the 1990s, more robust Enterprise Resource Planning (ERP) systems emerged, with the ability to integrate a wide range of what had once been discretely managed business functions on a single platform. At the same time, the development of online analytical processing (OLAP) data processing systems made more sophisticated analysis and planning of complex systems like supply and demand chains feasible. The rapidly improving performance-cost characteristics of these computing systems pushed the boundaries of the scope and complexity of SCP while making these systems increasingly affordable for smaller enterprises.

Accelerating trade integration, supported by more efficient transportation methods and the rapid adoption of the internet, caused enterprises to 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. As this happened, more capable planning and optimization tools became essential. 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 better-informed decisions and respond more quickly to changes in demand and supply.

Over the past decade, advances in application programming interfaces (APIs) have made rapid integration of data from source systems feasible, heightening situational awareness and allowing for faster 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 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 SCP software in multiple ways. The most important is through improved demand forecast accuracy. Increasingly, this software uses advanced algorithms and machine learning (ML) to achieve greater accuracy, which helps companies better anticipate customer needs and reduce the risk of overstocking or stock-outs. Achieving superior order fulfillment promotes customer satisfaction. Another is better collaboration, which is critical because of the cross-functional and geographically distributed nature of enterprises and their physical resources. The software helps ensure that everyone is aligned and working towards common goals. Because these tools provide real-time data and insights, it enables enterprises to make informed decisions faster, allowing them to respond quickly 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 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) and generative AI (GenAI). AI can facilitate the process of continuous SCP 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 will significantly 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, shortening planning and execution cycle times to make enterprises more agile and efficient. Rather than having to focus almost all their time on mechanical tasks, supply chain 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 in 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 the pace of business has never been faster, 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 has changed are the tools for doing business, providing those enterprises that successfully adapt and learn how to use these tools with a competitive advantage. AI 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.

The ISG Buyers Guide™ for Supply Chain Planning evaluates products based on their support for the capability model including AI/GenAI, demand planning, demand sensing, logistics planning, planning analytics, production planning, replenishment planning, supply planning and planning platform. The software must be able to manage and reconcile demand and supply plans, manage the planning process, support cross-functional collaboration, support sales and operations planning, model data for analysis, analyze data using a variety of techniques and communicate the results in a variety of ways in support of data and analytical processes.

This research evaluates the following 22 software providers that offer products that address key elements of SCP as we define it: Anaplan, Blue Ridge, Blue Yonder, Board, Dassault Systems, e2Open, FuturMaster, ICRON, Infor, John Galt Solutions, Kinaxis, Logility Solutions, Manhattan Associates, o9 Solutions, OMP, Oracle, Pigment, QAD, RELEX, SAP, Slimstock and ToolsGroup.

This research-based index evaluates the full business and information technology value of supply chain planning software offerings. We encourage you to learn more about our Buyers Guide and its effectiveness as a provider selection and RFI/RFP tool.

We urge organizations to do a thorough job of evaluating supply chain planning offerings in this Buyers Guide as both the results of our in-depth analysis of these software providers and as an evaluation methodology. The Buyers Guide can be used to evaluate existing suppliers, plus provides evaluation criteria for new projects. Using it can shorten the cycle time for an RFP and the definition of an RFI.

The Buyers Guide for Supply Chain Planning in 2025 finds Anaplan first on the list, followed by Kinaxis and Oracle.

Software providers that rated in the top three of any category ﹘ including the product and customer experience dimensions ﹘ earn the designation of Leader.

The Leaders in Product Experience are:

• Kinaxis.
• Anaplan.
• Oracle.

The Leaders in Customer Experience are:

• Anaplan.
• Board.
• Oracle.

The Leaders across any of the seven categories are:

• Anaplan, which has achieved this rating in six of the seven categories.
• Board in five categories.
• Oracle and Kinaxis in four categories.
• SAP and o9 Solutions in one category.

The overall performance chart provides a visual representation of how providers rate across product and customer experience. Software providers with products scoring higher in a weighted rating of the five product experience categories place farther to the right. The combination of ratings for the two customer experience categories determines their placement on the vertical axis. As a result, providers that place closer to the upper-right are “exemplary” and rated higher than those closer to the lower-left and identified as providers of “merit.” Software providers that excelled at customer experience over product experience have an “assurance” rating, and those excelling instead in product experience have an “innovative” rating.

Note that close provider scores should not be taken to imply that the packages evaluated are functionally identical or equally well-suited for use by every enterprise or process. Although there is a high degree of commonality in how organizations handle supply chain planning, there are many idiosyncrasies and differences that can make one provider’s offering a better fit than another.

ISG Research has made every effort to encompass in this Buyers Guide the overall product and customer experience from our supply chain planning blueprint, which we believe reflects what a well-crafted RFP should contain. Even so, there may be additional areas that affect which software provider and products best fit an enterprise’s particular requirements. Therefore, while this research is complete as it stands, utilizing it in your own organizational context is critical to ensure that products deliver the highest level of support for your projects.

You can find more details on our community as well as on our expertise in the research for this Buyers Guide.