By David Dundas
Company History – Inventory Locator Service
The origins of Inventory Locator Service LLC (ILS) date back to 1979 in Memphis, Tennessee, when John Williams, founder of The Memphis Group, established a business-to-business marketplace that allowed aviation parts buyers and sellers to search inventory, connect with suppliers, and negotiate orders more efficiently. At a time when much of the aviation aftermarket still depended on phone calls, paper catalogues, and fragmented supplier relationships, ILS helped pioneer a more transparent and searchable approach to aircraft parts sourcing.
Over the decades, ILS evolved alongside the aviation aftermarket itself. The company became part of Aviall, later came under Boeing ownership, and in 2019 was acquired by CAMP Systems, a Hearst company. That progression reflects a broader industry shift: from basic inventory location to a more connected aviation software and services ecosystem, where marketplace visibility, data quality, supplier intelligence, and digital commerce increasingly influence how buyers and sellers operate.
Today, ILS remains rooted in its marketplace heritage while serving a broader role in the global aviation aftermarket. Its history as an early digital parts marketplace gives it a distinctive position: ILS is both a long-standing sourcing platform and a growing intelligence layer for customers navigating a more complex, data-driven supply environment.
Operational Services
ILS provides a global digital marketplace and aerospace business intelligence services for buyers and sellers of parts, equipment, and services across the aviation aftermarket. The platform supports Commercial, OEM, MRO, Trader, Defence, Business Aviation, and General Aviation customers by helping them identify available inventory, evaluate sourcing options, understand market activity, and make faster, more informed purchasing decisions.
The marketplace includes access to OEM, USM, PMA, Airworthiness Directive, MRO services, and unapproved parts information, along with aftermarket supply, demand, and pricing data. With more than 298,000 users across over 165 countries, ILS provides broad visibility into verified global aerospace parts inventory and market activity.
ILS also supports suppliers through SalesEdge Commerceâ„¢, a fully integrated eCommerce solution designed for the aviation aftermarket. The platform enables aviation parts and services suppliers to promote their businesses through branded eCommerce storefronts, helping connect marketplace visibility with digital commerce.
More broadly, ILS operates as part of a wider aviation software and services ecosystem that includes airframe and engine health management systems, ERP platforms, business and general aviation services, and trip logistics capabilities. Within that ecosystem, ILS helps customers connect sourcing visibility, market intelligence, and transaction enablement in a way that supports both day-to-day purchasing and longer-term inventory strategy.
These capabilities are increasingly relevant as aviation companies rethink how they manage parts availability, working capital, supplier responsiveness, and operational risk. In an environment shaped by supply chain volatility, longer lead times, repair constraints, and continued pressure to avoid AOG disruption, inventory optimisation depends on more than what a company owns. It also depends on what it can see, source, forecast, and act on across the wider market.
That context formed the basis of AviTrader’s discussion with several ILS leaders, who shared their perspectives on how inventory strategies are changing and how data, visibility, pooling, and AI-enabled intelligence are influencing the future of aviation aftermarket planning.
AviTrader: How has the post-pandemic recovery and supply chain volatility changed inventory strategies?
Ashley Neeley, VP of Product Services: Post-pandemic supply chain volatility has pushed some airlines away from lean, just-in-time inventory models toward more resilient, buffer-based strategies…or “just-in-case availability without just-in-case ownership. To balance out the added cost and risk of holding more stock, airlines are getting creative. Some are offloading certain parts packages or using consignment models, so they can access what they need without tying up as much capital. At the same time, there’s a shift toward shared, network-based inventory, where suppliers and MROs manage pooled stock across multiple operators. Overall, I believe the priority has shifted. It’s no longer just about minimising inventory. It’s about making sure the right parts are available when and where they’re needed to keep operations running smoothly.
What data inputs are most critical for accurate demand forecasting?
James Scott, VP of Information Services: The most critical inputs for accurate demand forecasting start with buyer intent data. Search activity, including part-number lookups, keyword trends, and repeated searches for the same components, often provides the earliest signal of rising market interest. RFQ volume is equally important because it reflects stronger buying intent, especially when measured by part number, condition, quantity, and urgency. In an aviation industry where many transactions still move offline through phone, fax, and email, these marketplace signals are especially valuable because they reveal demand patterns even when final order data is not fully visible. Just as important are the supply-side and market-response inputs that help explain whether demand can be met. Quote activity, including no-quote rates, supplier response times, and price variation, can indicate tightening supply or growing urgency in the market. The number of active suppliers per part, visible inventory, lead times, and inventory updates—especially decreases in available quantity that may suggest fulfilment—also provide important forecasting context. To make these signals accurate, they must be supported by clean part master data such as normalised part numbers, interchangeability, condition codes, and aircraft applicability. Together, these inputs can provide a clearer view of demand by combining buyer behaviour, supplier responsiveness, and market availability
What are the biggest inefficiencies today: overstocking, understocking, misallocation, or data quality?
Ashley Neeley: I believe the biggest inefficiency in aviation today is poor data quality, which drives many downstream problems across inventory and operations. Because systems are fragmented and data is inconsistent, companies can struggle with accurate forecasting and real-time visibility. This leads to misallocation, where parts exist within the network but are in the wrong locations, often causing costly AOG situations. To compensate for uncertainty, companies can overstock inventory, tying up capital, while still experiencing pockets of understocking when critical parts aren’t available where needed.
How do pooling agreements influence internal stocking levels?
Greg Creekmore, Regional Sales Manager: Pooling agreements fundamentally change how one might think about stocking. Instead of carrying deep inventory, they can rely on shared access to parts across a network. That lets you reduce internal stock levels without increasing risk.
Rob Suhs, VP of Global Sales: I see pooling as a tool for access, not a replacement for inventory strategy. Its real value is that it gives operators a way to access high-value, lower-frequency material without having to own every unit themselves. That can lower the capital tied up in inventory, but in the current environment, I do not think pooling is driving broad de-stocking. What I am seeing instead is a more selective approach to internal stocking. Operators still need to protect the parts that are truly dispatch-critical or time-sensitive, especially when supply conditions remain uneven. So, the stronger model today is a hybrid one: hold the inventory that directly protects the operation and use pooling to add flexibility where ownership is less efficient. That is also where market visibility becomes much more important. The better informed you are about supply options, the better decisions you can make about what to stock internally, what to source externally, and where pooling makes the most sense.
What are the operational risks of over-relying on external pools?
Greg Creekmore: One has to trust the performance of the pooling providers fill rates, response times and logistics. If that slips, your operation feels it immediately. So, while pooling reduces inventory burden, it raises the importance of vendor performance and contract structure.
Rob Suhs: In my view, the biggest risk is loss of control. A pool can work very well when conditions are stable, but when the market tightens, the question is no longer whether a part exists somewhere. The question becomes whether it is available in the right place, at the right time, with enough certainty to protect the operation. That is where over-reliance can become a problem. If too much of your strategy depends on outside access, you can end up exposed to slower response times, lower priority in a constrained environment, and higher AOG risk when multiple operators are competing for the same material. So, I think pooling is most effective when it is part of a broader resilience strategy, not the entire strategy. Operators still need enough internal protection, enough sourcing flexibility, and enough visibility into alternatives to avoid turning an external pool into a single point of failure.
How do you see AI influencing spare parts forecasting?
Greg Creekmore: I see AI taking a lot of the guesswork out of spare parts forecasting, which has always been part science, part experience. It builds on historical usage and seasonality but goes further by processing far more variables and surfacing patterns you’d otherwise miss, like failure trends, shifts in demand, and early reliability signals. That lets one forecast more accurately and adjust stocking before issues hit operations. It also helps strike a better balance between availability and cost, so operators can run leaner without increasing risk. Tools like ILS add another layer by bringing in real-time market data and sourcing visibility, strengthening both forecasting and supply decisions. That said, AI doesn’t replace experience. It’s a tool. You still need someone who understands the operation, the fleet, and AOG realities. The best results come from combining AI, trusted data sources like ILS, and practical judgment.
Rob Suhs: I think AI will have a meaningful impact on spare parts forecasting, but probably not just in the way people first describe it. The biggest value is not simply better prediction. It is better decision-making. Forecasting has always depended on the quality of the underlying signals. If your inventory data is incomplete, your lead times are moving, or your repair cycles are inconsistent, even a good forecasting model can only do so much. Where AI becomes powerful is in improving the signal itself by identifying patterns earlier, surfacing anomalies faster, and connecting maintenance, usage, and supply data in a way that helps teams act sooner. Over time, I think the real shift will be from static forecasting to more dynamic planning. Instead of asking what we used last quarter, teams will be better positioned to ask what we are likely to need next, where the risk is building, and what action we should take now. That is where the business value sits: less excess inventory, faster sourcing decisions, and fewer avoidable disruptions.
