Balancing demand while maintaining minimal inventory costs is almost impossible these days. Accounting for volatile supply chains, high customer expectations, and unpredictable seasonality requires solutions that exceed traditional approaches. But with the help of Epicor IP&O’s powerful inventory optimization capabilities, you can create agile, customized stocking policies in a matter of minutes.
Epicor IP&O delivers cloud-based inventory policy decision support and the ability to share, collaborate, and track the impact of your inventory planning policy. It reconciles holding costs, ordering costs, and stockout costs to prescribe inventory policy and service levels that yield the total lowest cost. Through as-needed pressure testing, you can implement inventory management policies that lead to greater profitability.
Benefits
Stop using arbitrary service level targets. IP&O rigorously analyzes the simulated demands, holding, ordering, and stock out costs and prescribes optimal service level targets and inventory policies for each item that yields the lowest total costs.
IP&O generates thousands of realistic demand and lead time simulations for each item to reflect real-life uncertainties. It stress-tests current and proposed policies yielding accurate predictions of future costs, inventory value, and service levels that enable you to make fact-based inventory policy decisions.
Epicor IP&O integrates with your ERP platform using an “out of the box” connector that simplifies module implementation and support. Each module operates under the same common data model, meaning that when you implement one module, you are implementing for all. No new data acquisition effort is required, enabling you to seamlessly add new planning technology as your requirements grow.
To maximize the functionality and efficiency of Epicor IP&O, it integrates seamlessly with these products out of the box.
Epicor offers the ability to compute the Min/Max/Safety based on multiples of the average demand. Multiples of averages don’t account for demand or supply variability and will nearly always overestimate reorder points for predictable items and under-estimate for less predictable items. So, while standard Epicor ERPs are great for executing what to order, if you want to accurately risk adjust the stocking policies, account for intermittent demand, seasonality, trend, and conduct what if scenarios, then you’ll need IP&O. IP&O also supports what-if planning at scale so you don’t have to “wait and see” how a proposed change in policy will turn out. You can simulate how changes will impact key metrics like service levels and inventory value in just a few mouse-clicks before committing to it.
IP&O imports data from Epicor once each night and pulls in the latest shipments, sales orders, transfers, returns, and item master data such as product descriptors, unit costs, lead times, etc. Periodic refreshes may also be scheduled to pull multiple months of history. This is recommended if you are making corrections in Epicor because of ongoing data management/entry practices. Although the data is uploaded into IP&O nightly, the stocking policies are not computed daily.
You should do it once monthly or even once weekly. The specific cadence will be determined during your discovery. This way you are always adjusting the reorder points based on up-to-date demand, lead time, and cost changes. Using an outdated reorder point is guaranteed to trigger orders in Epicor too soon or too late and for the wrong quantities.
No. Like it or not the noise is already there in the form of demand and supplier lead time variability. Fixing replenishment parameters infrequently means you will be forced to react to problems rather than proactively identify them in advance and take corrective action. Modifying the policies once monthly with near term recalibrations ensures your inventory policies are adapting to a fluid situation and puts you in a better position to meet demand for a lower cost.
Service level is the percentage of the time you will fill customer demand 100% from available stock. Fill rate is the percentage of total units demanded that are filled. Service level defines probability of stockout while fill rate defines the magnitude of stockout.
Inventory management is risk management, and you can’t make good decisions about inventory without a full understanding of the stockout risk vs. cost. Each item has a different “tradeoff curve” and identifying this by item automatically and targeting stocking parameters accordingly ensures inventory will be properly allocated.
Yes, you can either target your choice of service levels and IP&O will recommend the required reorder points that are needed to achieve that service level or you can let IP&O use “optimization” to select the most profitable service level.
Epicor IP&O will conduct simulations of demand against a spectrum of stocking policies and it identifies the policies that generate the lowest total cost considering a) cost of holding inventory, b) cost of ordering inventory, and c) cost of stockout. So, if you generate more profit from carrying more inventory and capturing more sales, it will recommend a targeted stock increase and a higher service level. If additional inventory doesn’t justify the added cost, then it will recommend a targeted stock decrease and a lower service level.
Users define how much it costs the business for every unit that stocks out. Epicor IP&O simulates the stockout quantities associated with the policy and multiplies stockout quantity x unit cost per stockout.
IP&O will auto compute lead times for the preferred supplier for each item by determining the average period that passes between when an order is placed and when it is received. The average lead time is available in the “actuals tab” in the Item view of SIO under the “Avg LT” column. Users can choose the average lead time, ERP specified lead time, or users can enter a desired lead time. IP&O also offers an option to simulate lead times which is recommended since this accounts for all the possible lead times you are likely to face. SOA reports also detail historical lead times by supplier and product.