Thank you IBM for putting on YET another great TechXchange conference, this time in Orlando FL. The great thing about the TechXchange conference is that the content is tailored to technical people, so we are free to be ourselves, knowing that no one will judge us for getting enthusiastic about a snippet of Python code, or writing our first AI agent!
Many IBM Champions (and others) have already written eloquently about the Big Announcements - Agentic AI, Project Bob, Anthropic+Claude and more – so instead I would like to talk about all the connections I made during the week!
Even though my current “lane” is planning, forecasting, finance, sustainability and climate risk, I am very curious about technology in general, and I love it when an enthusiast takes the time to explain their passion to a newbie.
Read on if you are interested in the connections I made at IBM TechXChange 2025 between IBM Planning Analytics (PA/TM1) and Envizi (my “lane”) and Maximo (ALM/Asset Lifecycle Management), Rhapsody/Doors NEXT/EWM (ELM/Engineering Lifecycle Management), and (last but not least) IBM Pure Storage!
Finding Connections between Maximo, Planning Analytics, and Envizi
Thanks to fellow IBM Champion @Jan-Willem Steur I learned that Maximo (MAS) the Asset Lifecycle Management (ALM) tool, keeps track not only of each asset (e.g. a train or a building) but also all the constituents of the asset, all the way down to its parts that might require maintenance or replacement (e.g. a train seat or a component within the building’s cooling system). In addition to tracking defects and work orders to fix them, Maximo also spits out predictive maintenance plans and keeps track of financials including maintenance and repair labor costs, and depreciation expense.
Here’s how the lightbulb went off! PA can use Maximo as a starting point for all sorts of applications including:
- a fixed assets planning model, providing detailed information about existing assets, to which can be added (in PA) planned acquisitions (and disposals) to get a unified view of capital expense plans and depreciation as part of the overall financial plan.
- To get Direct Labor hours and costs at a detailed level to more accurately report on departmental or functional profitability, AND to use as a basis for allocations and AI-driven predictive forecasting
Assets (by geography) are also the foundational input to the IBM Envizi Climate Risk Insights module (CRI), which I demonstrated during my presentation on Tuesday October 7. Once you know your asset valuations and where they are located CRI applies climate science modeling to show you the the financial impact of climate risk across multiple climate scenarios in P&L format, all built on the powerful (and customizable) IBM PA platform. Having easy access to a data source for your assets is a great way to automate CRI model maintenance, and keep it relevant!
More Maximo Connections, this time with ELM (and PA)
One session I took a chance on (since it was quite far outside my “lane”) was the joint session by @Walter van der Heiden (another distinguished IBM Champion) and Jan-Willem, and I was SO glad I did. In the session, “Bridging the Gap between ALM and ELM”, Walter and Jan-Villem provided a great overview of how ALM and ELM complement each other, and how the fact that the business processes around them are often siloed and separated, when in fact a lot of efficiency and business value could be gained through collaboration. A point they made was that while the workflows of the ALM and ELM technologies could (and should) certainly be integrated using the OSLC (Open Services for Lifecycle Collaboration) framework (yay! a new acronym), it is important for the people who work in maintenance and engineering to be ready to talk to each other.
One example might be a car owner going to a dealership with an obscure technical defect that gets noted in an ALM. In a collaborative process, the engineers (and ELM users) responsible for designing the car part may be brought into the loop early to investigate the defect in direct collaboration with the dealership technicians rather than (as often happens) getting some disembodied defect reports at the end of a business cycle. The technology would support this process by automatically conveying the results of the technicians’ troubleshooting and diagnostics to the engineers in real-time, but that capability would not be of much use if the business process, incentives and cultural aspects were not also in place. The result could be earlier detection and resolution of engineering design issues, leading to faster interventions, reduced negative impact (and cost), and happier customers.
Suppose you were a car manufacturer that was interested in increased collaboration between ALM and ELM processes, but needed to make a business case for making the change, and then to redesign the incentive model for dealerships and engineering to support the adoption of the new business processes. If you had historical financial data in IBM PA that included dealer-level revenue and expense data, the cost of servicing cars under warranty and the cost of recall campaigns, you might access this data from a spreadsheet using Planning Analytics for Excel (PAfE) or – if you wished to leverage larger amounts of data for statistical or predictive analysis – you might even pull incident data into a PA model and work with it there!
Plus IBM Storage …
The final lightbulb flash came courtesy of Rob Young whom I met in the IBM Champions lounge one afternoon. Rob is a storage architect, and unabashedly passionate about what he does! In recent years storage has become so easy “in the cloud” that I have stopped paying attention but OF COURSE, as I learned from Rob, there’s a lot that goes on behind the scenes to keep all our data safe and accessible, and at the low price point we have become accustomed to. I learned, for example, about the difference between “cold storage” (that’s basically off-line until you need it) and “warm storage” (that you can get to any time). One thing that blew my mind was that tape storage on big round tape spools (like in old movies from the 1950s) is alive and well! This brought back memories because many years ago when I was a Computer Science graduate student, I had a part-time job switching spools on the departmental backup system. Nowadays I believe robots often do that job, but TAPE! Who knew? (Everyone except me it seems).
The first connection I saw was the realization that optimizing cold vs warm storage would have a clear expense optimization (IBM PA) component, as well as a sustainability optimization aspect (Envizi). At TechXchange 2024 last year I talked about how the challenges large technology companies were facing in managing data center costs and meeting greenhouse gas emission reduction commitments with the growth in AI (watch a replay here). I wasn’t considering storage, but since generative AI feeds on data, storage is just as much a part of this story as large language models (LLMs). Since we are talking about massive investments and operating costs, not to mention social and governance implications in the location of these facilities, I hope these companies are building models to explore the various strategic planning scenarios thoroughly before they make big decisions. IBM PA and Envizi can both be deployed usefully for this.
In Conclusion
These conversations with @Walter van der Heiden, @Jan-Willem Steur and Rob were exactly what I looked forward to when I signed up for TechXchange 2025. They were so generous with their knowledge and time! All of us share a passion for technology, and a desire to use technology for good.
The IBM Champions program is so valuable because it creates a framework and a space (literally – the IBM Champion’s Lounge) for these conversations to be had! While these conversations and connections may not be the central story of the conference, I think they are just as important. I can’t wait until next time!
Contact me @Ann-Grete Tan if you’d like to make another connection and if you are interested in the IBM Champions program, nominations for the class of 2026 are open through November 21, 2025.