The IMD Wrap: Taking stock of inventory management

Most financial firms that consume market data will have an inventory management system. These unsung tools track the data services a company uses. They count how many people use these services—and, for some systems, how much an individual uses them. They alert users to upcoming expirations and renewals. They can also help monitor changes to terms and reconcile vendor invoices against what the firm is owed.

At home, I employ a similarly sophisticated system for our household inventory. It’s called the FreezerMax 2000. My wife asks me things like, “Do we need pizzas? Cheese? Pepper?” and I go root around in the pantry and freezer to see what we have, assess rates of consumption, and how soon they’ll need to be replenished. She then inputs the order into Fresh Direct or Amazon Fresh, and we sit back and wait for the grocery delivery, which will be Tetris-ed into the freezer. And for two adults, two kids and a cockapoo, that’s fine. But that’s not sustainable once you reach any kind of scale. Say you’re also living with—and cooking for—grandparents, aunts, uncles, cousins, and a larger brood. That would become a daily situation to keep track of, and costs—as well as the time involved every day—would skyrocket.

So now imagine any financial firm with an array of data providers, delivering price data—both exchange and over-the-counter—across multiple asset classes and regions, research, news, analytics, and an ever-growing myriad of alternative datasets.

And clarity around what data is what, who uses it, how much it costs, what one dataset allows you to do with it compared to another, is critical. Mess that up, get an invoice wrong, report something incorrectly, or mistake which data you’re allowed to redistribute and to whom, and you’re looking at some very costly errors. To return to my sophisticated FreezerMax 2000, the process becomes even more manual and labor-intensive when you ask, “Which pizza? French bread pizza? Kids’ pizza? My supreme pizza with extra onions and peppers from Dollar Tree?” Or, “Which cheese? Cheese slices for burgers? Cheddar for crackers? Aged parmesan for my Cacio e Pepe? Or cheesy treats for the dog?”

The choices and combinations are deliciously overwhelming, and specifics matter. A lot.

Just as American cheese singles won’t work for my Cacio e Pepe, fixed income data from the Mongolian Stock Exchange won’t help someone trading equities on Nasdaq. You need clear and consistent codes and nomenclatures. Even if you use internal naming conventions within your firm—such as, “Dave’s Bloomberg”—they can be mapped to central controls that correspond with a data supplier’s own naming conventions for their products.

Inventory management practices have largely remained the same for the past 20 years, says Richard Mundell, who until recently was chief product officer at inventory management software vendor TRG Screen, where he spent the past 13 years. This, he says, isn’t for want of innovation among inventory specialists, but rather that data vendors don’t make it easy.

In short, there’s no incentive for data vendors to standardize how their datasets are named and described because while it would make them easier for user firms to manage, it would also make it easier for user firms to make apples-to-apples comparisons between comparable products from rival data providers and potentially replace them with cheaper or more comprehensive alternatives.

Of course, there has been plenty of change in this space over the past two decades. TRG Screen, for example, is the result of a merger between New York-based The Roberts Group, provider of the FITS platform, and Dutch vendor Screen Consultants, which sold its InfoMatch system. UK-based MDSL, provider of the MDM (Market Data Manager) and TEM (Telecom Expense Manager) platforms, was acquired by Calero, a telecoms expense management software vendor, in 2019.

And the inventory management providers themselves certainly aren’t stagnant: Aside from the “big two,” there are new and old players doing new things. For example, San Francisco-based VendEx Solutions, which is building out a suite of data management services, will soon unveil a new product, dubbed VPort Essentials. Though it’s not a cost allocation tool with integration to HR systems to show spend by an individual, and it will not have many features of heavyweight inventory platforms, VPort Essentials will offer a “light” version of a vendor relationship management tool—essentially a lightweight inventory platform—aimed at smaller firms and a broader audience outside of financial services, says CEO Richard Clements.

That said, it integrates with VendEx’s data catalog and V-Key document digitization solution. This means that it can extract and digitize fields from vendor contracts, and allows users to visualize all the vendors whose services they subscribe to, and how much they spend with each. VendEx has a partnership with TRG Screen to make elements of its suite available via TRG Screen’s Optimize Spend platform. But VPort Essentials offers an option for firms beyond the reach of the larger players, or which have more modest needs from an inventory platform. “There’s a need for inventory management among smaller firms, but they only need a speedboat, not an aircraft carrier,” Clements says.

Integration with other parts of the data ecosystem—as per VendEx’s blueprint—will prove critical to eliminating friction across the flow of data from vendor to user, and reporting and payment back from user to vendor. One key point of integration, I believe, will be the use of data catalogs, such as VendEx’s own VSource, 3D Innovations’ (3Di) Profiler tool, and Expand Research’s new data catalog, developed for a number of bank clients.

And then there’s an older player that nevertheless has a youthful spring in its step. Though not as well known as its larger rivals, Swiss provider BST Software is still around, though these days it goes by the same name as its platform: FinOffice. In fact, FinOffice has a busy year ahead.

In Q1 this year, the vendor focused on fixing design inefficiencies, adding “enriched logic” to its wizards, and improving its user experience and operational efficiency. In Q2, it will roll out an “advanced order management module” to streamline order approvals and integrate with firms’ existing procurement tools. In Q3, FinOffice plans to integrate vendor profiles and product information from UK-based 3Di to enable comparisons between competing products. And in Q4, it will introduce automated invoice reconciliation, using AI and natural-language processing to automate matching invoices with purchase orders and receipts, which the vendor says will reduce inefficiencies and operational costs associated with manual reconciliations.

Indeed, cost—and the cost (and savings) of managing costs—can be a compelling factor in how firms approach inventory management: Simply installing (or, more likely, in a software-as-a-service world, subscribing to) inventory management systems can anecdotally save 10% or more on data costs—easily paying for the cost of the platform itself—by identifying areas of duplication, overspend, or inefficient licenses. Is that sustainable year-on-year? Probably not, but if used effectively, it will help prevent those costs from creeping back up.

And just as software has moved to a subscription model, vendors are augmenting their tech platforms with consulting models to give firms fresh eyes on their data spend. There are also advantages of scale: as a data manager, you may fully understand your firm’s spending challenges, but as a vendor serving multiple clients, you have visibility into all those clients’ challenges and know how to solve them when you experience them at another client.

That knowledge is all well and good, but there’s a big element of friction that remains in this process. And here’s where the industry could perhaps learn from others. Jeremy Baksht, former head of alternative data at Bloomberg, and head of strategy at Walmart Data Ventures, recently co-founded Catena Clearing, which aims to make the supply chain for retail goods and stores as automated and data-rich as the supply chain for data in financial markets. Catena will build connectors between all the parties involved in the retail supply chain—manufacturers, logistics and shipping companies, and retail stores—giving retailers a view of their supply, and supply chain, faster and more precisely than previous manual monitoring and ordering processes.

Beyond retail, the data generated could also be of interest to traders and analysts looking for advance information on all these companies. But it could also serve as a blueprint for someone looking to shake up the usage monitoring, inventory management, permissioning and procurement arena.

Additionally, there’s room for automation in the inventory management process: Mundell suggests vendors could use generative AI tools to extract contractual terms from license agreements, such as which datasets allow or prohibit redistribution of the data.

And here’s my personal take: vendors are already running these systems in the cloud. Data providers are distributing data via the cloud. Why not give both sides—supplier and consumer—access to the same system, operated and mediated by the inventory management platform vendor? That way, each side can see pricing and usage, as well as terms and conditions. This would remove the process of reconciling invoices, because they could be automatically generated based on transparent usage statistics, visible to both sides. Onboarding and permissioning would be centralized and seamless, and procurement and delivery would be two sides of the same coin. And with those efficiencies—not to mention the ability to spot any divergences, under-reporting or cost discrepancies easier and sooner—that could save both sides some serious coin.

If you’d like to share your thoughts on this topic—either privately with us, or publicly with our audience—or if you’d like to franchise my patent-pending cloud inventory idea or get my recipe for Cacio e Pepe, you can contact me at max.bowie@infopro-digital.com