ARC was briefed by John Galt Associates not long ago. They used the phrase ‘planning at the edge of chaos.” I love that. That is a very good phrase for describing the increasing complexity and need for speed large organizations face. John Galt Solutions has focused product development on helping companies to ameliorate this chaos. This involves the use of new technologies on their platform. Data fabrics, knowledge graphs, a digital thread, and digital twin technologies are critical.

The Need for Speed

When you talk to supply chain planning software suppliers, they identify similar trends. However, Alex Pradhan, the global product strategy leader at John Galt Solutions, talks differently about what her company sees in the market. And the trends they are focused on have a direct impact on their product development plans. John Galt Solutions is a provider of supply chain planning solutions. Their solution is known as Atlas.

“Companies need to innovate and make decisions very quickly. They need to adopt new capabilities as they mature, Ms. Pradhan said. “This is not surprising. But what we’re seeing is that the speed has to be a lot quicker!”

The need for speed increases the complexity of an already very complex environment. The original plan developed in a month-long integrated business process can quickly become irrelevant as conditions change. Then, a new plan must be quickly generated. However, generating these short-term response plans in large companies is difficult because “companies need to coordinate and automate processes across multiple stakeholders, who often have competing objectives. Those stakeholders include planners; supply chain, manufacturing, and logistics executives; sales and marketing; finance or regional or business unit leaders; and suppliers and other partners.

“Many companies are planning at the edge of chaos,” Ms. Pradhan ex-claimed. “Where they need to balance stability with continuous change and support networks of decision makers across and beyond their own enterprise.”

“Our technology enables us to create ‘moments of truth’ and get the right information you need, when you need it, and personalized to you,” said Ms. Pradhan. The composable UX layer and platform enables John Galt to fine tune the different type of decisions and link these to the right decision maker.

“The technology is more advanced than the business process.” Based on this trend, John Galt is focused on three main areas in its product roadmap: decision intelligence – the ability to make and analyze decision tradeoffs at the right time; process orchestration – being able to connect, align and synchronize processes; and visibility – the ability to see what is going on across the extended supply chain and transform data into knowledge.

Supply Chain Planning Suppliers Embrace Generative AI

Supply chain planning (SCP) is one of the most complex applications. But to support the increased uncertainty and the need for quick, high quality answers to supply chain disruptions or opportunities, it is getting even more complex.

Most SCP suppliers are talking about adding generative AI. John Galt is no exception. Technology, particularly generative AI, adds to planning uncertainty. Most executives don’t fully understand it.

Ms. Pradhan makes an analogy between GenAI and a beehive. “There are different types of bees and they have different roles.” There are queen bees, drones, and worker bees. All are necessary. Their roles can be explained and the way they cooperate to produce honey is not that difficult to under-stand.

Similarly, GenAI employs multiple agents. Those “agents mimic the structure of an enterprise and define roles in the enterprise. But, “how do we think about the decision roles of not just humans but also machines?” When the machine is given autonomy to make certain decisions, transparency and trust in AI become essential.

However, John Galt Solutions is also working to add other technologies that get far less attention but are, in ARC’s view, more powerful technologies in the short term than GenAI.

Supply Chain Planning is a Complex Application

There are new technologies that a planning engine needs to incorporate to enable the application to see what is going on in an extended supply chain, understand the implications of what is going on, act once a solid understanding of the situation has occurred, and learn from experience.

John Galt is using a variety of techniques and technologies to improve their planning platform. In this Brief, ARC will discuss only a few that, in its view, are particularly important.

John Galt’s Supply Chain Planning Platform

John Galt is right to single out data fabrics as an increasingly important technology. A “data fabric” is an approach to data integration that allows access to data across various systems without physically moving it. This creates a unified view by stitching together data sources in real time. Traditional integration involves moving data into a centralized repository like a data warehouse. That requires more complex data extraction, transformation, and loading processes.

Some of the capabilities John Galt Solutions highlights have been part of supply planning applications for some years. Planning suppliers now speak of digital supply chain twins. A digital supply chain twin is a new vocabulary for describing a capacitated supply chain model. That has always been the core of supply planning engines. However, what is new is that the models are now being extended beyond the four walls of an enterprise to include suppliers, trading partners, and sometimes customers.

A digital thread is a flow of information that tracks a product from design to disposal, including production, sale, use, and maintenance. Historically, supply chain planning has not spanned the whole product lifecycle. Supply models have been focused on source, make, and fulfill. With a growing emphasis on sustainability, supply chain models need to become more granular. It is unrealistic to think that supply models will ever fully encompass product design. However, supplier components in a bill of mate-rial, facility, and transportation assets used in supply models should more fully incorporate sustainability data.

Most planning applications don’t use knowledge graphs. However, there is an increasing awareness that knowledge graphs provide a deeper understanding of linkages between supply chain facilities, assets, products, suppliers, and customers. To more fully model a supply chain in all its granularity and depth, this is a critical technology.

In summary, John Galt is focused on three main areas in its product roadmap: decision intelligence – the ability to analyze tradeoffs at the right time; process orchestration – being able to connect, align, and synchronize processes; and visibility – the ability to see what is going on across the extended supply chain and transform data into knowledge. Their roadmap is poised to support companies with better decision making as they go beyond embracing complexity to help them influence and re-imagine their decision network. To support this, new technologies are being incorporated into their Atlas Planning Platform.

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