Bold enough to use the “solutions” tech industry label that every enterprise software vendor is so fond of inside its core naming designation, o9 Solutions is a company known for its demand planning software platform and extended toolsets. Aiming to explain where digital planning tools go next in a world of spiralling cloud complexity, advancing agentic AI automation and abstracted orchestrion, the company used its aim10x Americas event this month in Dallas, Texas, to host a media and analyst day that really drilled into the smörgåsbord of planning software functionalities that the company is currently weaving together.
Spanning the planning smörgåsbord
How many major functions, sub-functions and disciplines of enterprise planning software are there? A lot. The company straddles the spectrum, including Integrated Business Planning (IBP); Sales & Operations Planning (S&OP) software; AI/ML demand forecasting; Supply Chain Control Tower; Supplier Relationship Management (SRM) functions, sustainability solutions and Revenue Growth Management (RGM) services.
The company also straddles key vertical industries, including automotive suppliers; consumer electronics;, food & beverage; high tech & electronics; home & personal care; medical devices; retail and telecom operators.
Content for the show itself was billed as an opportunity for IT teams focused on digital demand planning products to learn how to tackle real-world scenarios such as tariffs, demand spikes, supply disruptions etc. In terms of o9’s new AI-powered capabilities, the company showcased developments and extensions in its o9 Digital Brain™ Platform, driven by AI agents and self-learning models.
o9 Experience Center
Located on the fabulously named Lyndon B. Johnson Freeway, the company has reflected what a number of firms are doing now (like NTT today… and like Microsoft since the 1990s to be honest) and created the o9 Experience Center for customers, users, partners and others to get up close with o9’s software.
In a session devoted to examining what o9 is doing with agentic AI today, o9 Solutions chief product officer Umesh Arasu spoke to press and analysts and said that business itself in this digital age is becoming inherently more complex because of five key growth factors across disconnected, disaggregated functions:
- Product portfolios are growing
- Market segments are expanding
- Customer segments are splintering outwards
- Supply chain models are evolving
- Sales channels are diversifying
Added to those factors, there is so much volatility in world markets due to socio-economic and political factors… and we find that firms have what he calls “late visibility” into how their business is running, which is leading to a) firefighting and b) value leakage. All of these factors have been behind o9’s thinking as it has built its current technology proposition in its o9 Digital Brain platform.
Adaptive thinking & post-game analysis
“Adaptive capabilities are – traditionally – missing in so many modern enterprises’ IT stacks… and, really, even post-game analysis (PGA) has been missing,” said Arasu. “Copilots can help firms to overcome these shortfalls and perform a higher degree of self-service for business operations.”
Reminding us that human-led AI-augmented business operations are a productive way for firms to get to a process known as Fast Response Execution (FPE) today, he says that skilled AI agents can help in this field, specifically in the area of business simulators (which can incorporate the use of Enterprise Knowledge Graph models) that create new operational models so that firms can explore new markets and methods of operations with zero learning time for humans and less risk.
Because agentic AI can be so much more goal-oriented than the previous ages of generative and (before that) predictive AI, teams need to make sure that the domain knowledge of agentic services is rich enough… and this is where Enterprise Knowledge Graph technology plays a key role in terms of allowing agents to contextualise their reasoning models and act effectively inside the business.
High-agency atomic agents orgs
As we get to a point where we start to see “high-agency organizations” (i.e. obviously a term that means firms with a high degree of agents deployed and ones that are rich in their horizontal functions and those with a key vertical span in terms of their ability) we are – as we stand today – at a point where even firms like o9 Solutions (which builds tools for these functions at the core of its stack) would find it hard to know how to task human planners in the future. To be clear, the horizontal span of agents means ones that can work in commercial, finance, supply chain, procurement and so on.
This discussion moved forward to use of technologies such as so-called “atomic agents” and this is a technology that o9 Solutions has been building alongside its composite agent framework.
Operating system company for AI and data on AWS Shakudo defines them as follows: “Atomic Agents is a modular framework for building and deploying AI agent systems that breaks down complex workflows into specialised components that work together seamlessly. It enables precise control over each agent’s functionality while providing standardised interfaces for agent communication and tool integration. For example, a financial services company used Atomic Agents to create a system where one agent monitors real-time market data, another analyses trading patterns and a third executes trades – reducing their transaction processing time from hours to minutes while maintaining complete audit trails and compliance checks.”
Moving forward, we will start to look to use more of the unstructured knowledge that exists inside a business and digitally track and analyse what those data resources might mean for the business. These could be video chats across geographically distributed teams, telephone calls, meeting notes and so on i.e. all information resources that businesses have traditionally failed to inject into end-to-end demand planning and resource management. These are complex tasks, so the more automated the analysis of these data flows (and the resultant management reports that they generate), the better.
Humans-In-The-Loop
All of which perhaps begs the question, where will we need Humans-In-The-Loop next? Arasu says that humans will be vital in scenarios where we have not asked the right questions of agents in the first place. Although demand planning agents will work on the “routine tasks” that they are so good at, they will soon do more… and humans will also be crucial in terms of helping provide business context to the work that agents do carry out. This will help validate results and allow businesses to apply and execute judgment in the more complex and unpredictable business scenarios and situations.
Senior VP for revenue growth management and commercial planning Adam Ben-Yousef took over this “day-zero” session to explain how the o9 Solutions revenue growth management (RGM) capabilities – which are fully integrated into its Digital Brain platform – enable a company’s marketing, finance, supply chain and procurement teams to collaborate, plan more effectively and improve the profitability of its strategic commercial investments.
“Because so many RGM functions are essentially analogue (written down, or even just stored in people’s heads) it can be tough for firms looking to move forward in digital transformation – especially in retail and packaged goods businesses – it can be very tough to deconstruct the logic behind the decision-making that happens all the time,” said Ben-Yousef. “Traditional consumer companies are vulnerable to losses when facing simultaneous demand, supply and technological description.”
This leads firms to realise that they have a limited ability to connect silo-based planning constructs to decisions which should be steered by corporate strategy, tactical plans and execution. Ben-Yousef says that it’s not hard to see why this is such a complex business operations problem space… and this is why o9 has been investing so much time, effort and R&D into digitising these functions.
Out in the real world, 65% of trade promotions (special offers) do not break even and deliver on return on investment and there is a further 10% loss in profit due to poor capabilities that exist in terms of measuring and monitoring pricing. Because so much forecasting and demand planning in retail firms is analogue, the reality is that firms don’t understand with enough granularity what revenue generation activities they should engage in.
Sell-in & sell-out data
Tools for organisations to use here include “digital shelf data” (i.e. price scales of products across competing retailers) EPOS point of sale data, financial profit and loss data, weather data and key macroeconomic data. Organisations looking to build a comprehensive data universe here should include sell-out and sell-in data. Sell-out data is retailer sales data (often at the till or checkout itself) from a company to the customer. Conversely, sell-in data (also known as wholesale data) is defined as data that describes the amount of sales of products from manufacturers and suppliers to retailers. All of these data sources are needed for digital demand planning.
Moving onwards to wider implications for all these technologies… around 90% of the environmental impact of companies lies in their supply chains. As such, it’s essential to think about supply chains as a critical component on the path to a sustainable economy. Here we see that o9 is the first enterprise planning technology provider to integrate an end-to-end suite of Environmental, Social and Governance (ESG) solutions into its AI-powered integrated business planning platform to help companies manage sustainable data risks and operations within their supply chains and beyond.
Sustainability solutions & ESG
Keen to look to sustainability as a major element of all software deployments stemming from, through, in or around the demand planning space, the company looks to a positive future and says that the o9 platform enables organisations to measure their digital footprint and enable visibility across complete value chains.
“The transition to circular operations and revamp scenario planning with sustainability at the core. o9 helps close the knowledge gap on a sustainability journey. While sustainability legislation may face delays and productivity often takes priority, the global consequences of unsustainable supply chain practices remain constant. The impacts and the risks they bring will inevitably drive companies to act, especially as consumer preferences increasingly favour sustainable brands,” notes the company, on its dedicated sustainability portal.
What is/are circular operations?
A term that perhaps needs extra clarification, transitioning to circular operations means shifting from a traditional linear “take-make-waste” model in business towards a circular economy model, inside which resources are eminently reused, repaired and regenerated. The circular models mean that organisations can minimise waste and keep products and materials (and indeed services) in productive use for as long as possible. Achieving a transition to circular operations involves a comprehensive change and overhaul to supply chains, product design and business models to enable a “closed-loop system” that champions resource efficiency and sustainability throughout complete operational lifecycles.
According to Stanton Thomas, SVP of Sustainability Solutions at o9, “Technology is needed to support supply chain leaders in their efforts to set sustainability goals not only to protect brand reputation, but also to reduce their vulnerability to future supply chain disruptions related to climate change, taxes levied on carbon emissions and other ESG regulatory implications.”
He also underlines what he says his firm’s “deeply interconnected nature” when it comes to sustainability, optimal supply chain performance and technology. It seems clear that we need the world’s largest organisations to create environmentally and socially sustainable supply chains that will benefit all of humanity… and that, very arguably, has to be a positive note to end on.