Maintaining optimal inventory levels is tricky. Over-provision and you run the risk of tying up precious capital that you could invest elsewhere. Understock and risk losing money on equipment downtime. Consequently, developing a reliable inventory management process is essential in ensuring long-term operational success. For facility managers, what’s the best way to accurately track, control, and optimize assets, spare parts and consumable inventories? With CMMS software, of course!
Adopt a Data Driven Approach
Maintaining the appropriate spare part inventory levels revolves around predicting demand for each spare part and matching available supply. While facility managers have typically estimated the need for spare parts based on experience, a data-driven approach is surely a more rigorous way to maintain inventory. Not only will data be available to back-up decisions, if sufficient data is gathered, projections can be made supported by machine learning models.
Just Tracking Inventory Levels
Inventory management starts with the most basic task of knowing the current inventory level of each spare part. Facility managers relying on manual approaches will struggle to report these numbers accurately, requiring frequent stock takes or check-in, check-out ledgers to track these numbers. Manual processes are prone to human error. Tracking inventory levels is a function clearly better performed with a CMMS system. CMMS systems can also automatically alert management if particular stock levels have run low.
Managing Multiple Locations
Inventory tracking complexity increases as the number and types of equipment increases. It is even more complex if multiple locations are involved. Decisions will need to be made whether to centralize spare part storage, or to keep essential spare parts on-site. Comparing spare parts utilization across multiple similar locations often reveal interesting insights on equipment conditions and utilization patterns. Detrimental or wasteful practices can often be revealed by such comparisons.
Predicting Demand of Consumables and Spare Parts
The key uncertainty driving inventory management is the demand for the consumables and spare parts. This demand is associated with equipment faults and preventive maintenance checks. Therefore, to adopt a data driven approach to predict demand, the inventory items need to be linked to the equipment and the equipment linked to fault reports and checklists.
Such relational data should be gathered within the CMMS system. Ideally, demand forecasts can be computed based on historic data and re-order thresholds adjusted accordingly based on anticipated demand and supply lag times.
Improved Inventory Management Lowers Costs
Ultimately, better inventory management should lead to lower costs, whether through lower storage costs or lower equipment downtime. Inventory data may also influence equipment purchase decisions, some equipment may require low capital expenditures, but incur high consumable or spare part replacement costs.
Data may also lead to better procurement decisions. For example, a vendor that can provide new spare parts more quickly may be preferred to vendors which have long procurement lead times.