Release Notes: January 2023 We are excited to announce the latest upgrade to EazyStock. With this release, we continue to enhance and improve your experience by incorporating new features and addressing feedback. As always, we are committed to providing the best possible service and support. If you have any questions or further assistance, please don’t hesitate to contact your Customer Success Manager. They’re always happy to help. All the best and happy optimising! Ranveer Singh Customer Success Director, EazyStock email@example.com New features Respond to demand pattern shifts with step change detection Understand supply chain and BOM relations with Propagation graph Understanding your item behaviour with demand type propagation Expedite purchase orders with Supplier Portal’s delivery monitoring Detect missing data with new Unprocessed interface data Achieve your service levels with forecast uncertainty propagation Optimise carbon emission with CO2 emission simulation 1. Respond to demand pattern shifts with step change detection Today, most businesses are facing unexpected changes in their demand patterns. It’s very important to accurately handle those demand changes in your forecasts so you can respond correctly. New step change detection is useful in working around big demand pattern shifts. Who is it for? Available in all versions. Why did we do this? Changing market conditions often lead to changes in demand . Usually, it’s difficult to answer the question “is this just an outlier or the beginning of a new normal? Is this sudden change in demand permanent?” It can often take several periods for an algorithm to adjust forecast values for a change of this type. Solving this manually was cumbersome but not taking any action could result in a drop in forecast accuracy and even stockouts or a build-up of excess stock. What did we do? EazyStock now automatically detects a step change in demand. It is based on the “X outliers in Y periods” rule. You can specify how many outliers (X) have to be detected within (Y) consecutive periods to be classified as a step change. Look at an example of an item with the step change detected. The forecast (marked with a green line) is calculated considering only the most recent demand history, as specified. Why should you care? Step change detection allows you to increase forecast accuracy. You no longer have to manually adjust for items that have sudden changes in their demand pattern. Also, you have better overall visibility in demand pattern changes. How to get started How to configure the Step change in demand: Go to Demand & forecast → Configuration → Forecasting configuration. In the Demand analysis → Demand outliers → Step change section, Set Enable step change detection to Yes and specify two parameters: Periods for step change detection Number of outliers for step change detection 2. Understand supply chain and BOM relations with Propagation graph Sometimes, an item’s forecast can depend on hundreds of other items. To make this easier and to understand these dependencies, we added the propagation graph. Who is it for? Available in all versions. Why did we do this? Customers reported they needed a way to see what dependencies there were between an item’s forecast and its supplied items or BOM dependencies. To understand the structure behind the item, you had to navigate through multiple screens and several pieces of information. This was frustrating and inefficient. What did we do? With the new propagation graph, you get one view where all the relevant information is stored in one place. Every item has its own graph showing the supply chain and BOM relations that propagate demand and forecast to it. The graph is available for customers using unified demand and forecast propagation. You can view the graph within EazyStock or download and analyse it offline. Why should you care? This new screen allows you to quickly get an insight into how different item relations impact your forecasts. The propagation graph will improve efficiency and reduce the time it takes to investigate planning structure. How to get started Go to Items > Worksheet > Demand > Forecast graph. To see the graph, click Show propagation graph. To download the graph, click Download propagation graph. 3. Understanding your item behaviour with demand type propagation Classical demand types work well for “isolated” items downstream in the supply chain. However, when items are located in the upstream (supplying) warehouses and/or are part of the bill of materials, the full demand picture might not be clear. In such cases, demand type propagation ensures accurate demand type and product lifecycle classification. Who is it for? Available in all versions. Why did we do this? In some cases, customers were concerned that items might not be classified correctly. For example, an item with a non-zero forecast (aggregated from their supplied items and/or BOM parent items) were classed as non-moving or obsolete because the full picture wasn’t being assessed. What have we done? When using the new unified demand and forecast propagation feature, target items receive more information than before. Along with the propagation of demand and/or forecast, the demand type of source is propagated. From now, each item has two demand types calculated: Combined demand type – this value takes into account demand type propagation. It ensures that the item’s demand type that you see in the system considers the “big picture” (not only local demand information, but also the overall demand situation of the items within the supply chain and BOM structure). The Combined demand type is the one used in reporting and summaries. Local demand type – calculated exactly as before, using only the demand that is considered when performing statistical forecast calculations for a given item. Local demand type determines which forecasting algorithm to use (moving average or exponential smoothing). An item’s Combined demand type is based on: Item demand Item forecast Item forecast uncertainty Item picks forecast (probability of zero picks in next period) Demand type of source items (supplied items and BOM parent items) Why should you care? Demand types are a fundamental part of classifying items. Accurate demand type classification is crucial for visibility, policy and reporting reasons. With demand type classification, EazyStock now ensures that all items (including items planned as parts of a complex supply chain and BOM structures) get accurate demand types, correctly reflecting their lifecycle stage and demand characteristics. With this new approach, it is possible even when no local demand information is available. 4. Expedite purchase orders with Supplier Portal’s delivery monitoring The new delivery monitoring screen in the Supplier Portal is a useful tool for managing open purchase orders and communicating with suppliers about updating delivery dates. You can see critical purchase orders that may require expediting because of predicted stock outages. Instead of adding additional rush orders, you can negotiate earlier delivery dates with suppliers. You can also give your suppliers the ability to log into this screen and keep communication clear. Who is it for? Available in Premium and Global Planner versions only. Why did we do this? Customers were spending huge parts of their day analysing the risk of run out data. They wanted to negotiate delivery dates with suppliers for critical purchase orders to prevent running out of stock. Communication about purchase orders was managed outside of the EazyStock system – typically by phone or email. This was inefficient and prone to error. What did we do? Previously, the screen displayed a report for open purchase orders on the order line level, showing the predicted shortfall/stock-out before the order’s delivery date. This was based on risk of run-out data. Now, planners (buyers) and suppliers can cooperate and expedite orders in these run-out situations. Now you can: Create Supplier users and give them specific, limited access to your data. They can see only the Delivery monitoring screen and only the data needed to identify the right product on the order. Their access can’t be extended to any other screen. Negotiate the expected time of delivery. Planners can request to expedite, or de-expedite orders and suppliers can reply by confirming or rejecting the request. Both parties can communicate by adding comments. Get suggested delivery dates that consider business calendars to help avoid run outs, incorporating your agreed schedules that may limit available delivery dates. You are also able to review recent changes and update your purchase order line again. Why should you care? You can avoid run-out situations by expediting orders, and this screen makes it quicker and easier. Communication with suppliers is easier than ever and you access messages and notes related to an order in one click. Tests with early adopters have shown that teams can save up to one hour a day on this screen. How to get started Go to Orders > Delivery monitoring. Find a purchase order you’d like to expedite. To prioritise, you could use: Risk of run-out minimum value Minimum run-out time Item picks class Item VAU class Next, click the pencil icon next to the requested delivery date. Then: Fill in the new requested date. Add a comment to your supplier, if needed. Add an internal note as well, if needed – it will be only shared with other buyers that can see the purchase order line. Click Update. How do your suppliers confirm or reject delivery dates? Go to Orders > Delivery monitoring screen. Check for recently updated lines; for that, you can use the Last update by buyer field. To reply to a request, click on the pencil icon next to the Confirmed delivery date. In the modal, you can check the details of the order line and set a new confirmed delivery date. Finally, click Update. 5. Detect missing data with new Unprocessed interface data The new Unprocessed interface data screen is a tool that detects and displays unprocessed records connected with invalid warehouse codes or group codes. You will be able to quickly find issues, analyse, and fix them. Who is it for? Available in Global Planner version only. Why did we do this? Previously, if you sent an incorrect warehouse group code, the system couldn’t process it and didn’t provide information about it. Data problems needed to be self-diagnosed and/or troubleshooted with the support team. In the worst case scenario, this could lead to important orders not being created or incomplete data. What did we do? There is now a new screen that displays unprocessed records. The unprocessed interface data screen displays records imported to EazyStock that failed to be processed successfully. In most cases, such data can’t be processed because of a spelling error, configuration mismatch or white space in the warehouse group code name. Another problem could be caused by skipping data processing, or that your setup only allows loading data for the current date. This new screen will show you what data is missing and expedite the troubleshooting process with Support. Why should you care? Typically, this will help during the beginning of your integration with EazyStock or during a new warehouse roll-out. Any data issues can be investigated quickly and fixed. How to get started From the new unprocessed interface data screen, choose an interface type, set a date range or choose one of three possible reasons for failure. Click search and you will see records that have not been processed. The file causing the error will be specified. 6. Achieve your service levels with forecast uncertainty propagation The feature helps you deal with the uncertainty of future demand. With unified demand and forecast propagation, items now incorporate forecast uncertainty when calculating demand. This leads to more accurate buffer stocks and order levels in supplying warehouses. Who is it for? Available in Global Planner version only and designed for multi-site businesses that have internal supplying warehouses. Why did we do this? Setting replenishment parameters in supplying warehouses can be a struggle. In simple terms, point forecasting can be used to answer the question “How much, on average, will I sell?” We were doing well with this part of the puzzle. However, there is another part. Forecast uncertainty answers the question “How certain can I be that the amount I’ll sell will be close to my forecast?” Previously, when using aggregation features, forecast uncertainty was calculated in a simplified way which could lead to buffer stocks being too low or too high. We now do a much better job of incorporating the second question into forecasts. What did we do? We introduced a three-step algorithm to correctly estimate forecast uncertainty at the level of supplying item. It works like this: Transform end-customer demand pattern into internal demand pattern using constrained optimum order quantity (COOQ) to account for internal order sizes. Calculate the forecast uncertainty of the internal demand pattern. Combine forecast uncertainty from all sources (propagated and local). How long the item(s) will be out of stock before the planned delivery This diagram illustrates step one: In EazyStock, you will see the forecast uncertainty measure labeled as combined where your item uses forecast uncertainty propagation. Why should you care? When planning for your business, it’s important to consider two key things: what you predict will happen point forecast and the certainty of that prediction. Aggregation features are great for increasing your visibility but inaccuracies aren’t always easy to spot when supply chain and BOM structures are complex. Propagation of forecast uncertainty helps you to prepare supplying warehouses for uncertainty in the future. Buffer stock calculations are now more accurate, considering both order bating (COOQs) and BOM quantities. This results in supplying warehouses performing better and makes achieving your target service levels easier. 7. Optimise carbon emission with CO2 emission simulation Curbing CO2 emissions are a key target for many of our customers. Supply chain planning and inventory control is ultimately about making sure items are in the right place at the right time for the lowest cost. However, EazyStock now models the CO2 emissions caused by items transported from supplier warehouses to customer warehouses. This simulation shows how your inventory decisions impacts the environment and allows you to prioritise sustainability without compromising profitability. Who is it for? Available in Global Planner version only and for users with Supplier warehouses in EazyStock. Why did we do this? Customers lacked tools that provided insight into their CO2 emissions and how their actions increased or decreased emissions. They wanted more information available to make informed choices. What did we do? EazyStock’s inventory policy simulation and optimization functionality now allows you to simulate the expected annual CO2 emission caused by selected inventory policy configuration. You can visualise data, see percentage differences and a heat map view that shows emissions spread over the matrix. Everything is broken down to show which items and configurations are the most important to decrease emissions. Why should you care? By using CO2 emission simulation you get transparency and insights into how your inventory management decisions impact the environment. Then you can adjust them to reduce CO2 emissions. Customers as well as the primary supply chain drivers, e.g. OEMs, require a higher and higher focus on sustainability from all the players in the supply chain. With our solution, you can work towards reducing carbon emissions while maximising profit margins. You can make operational and sustainability improvements that also drive higher profitability. With CO2 emission simulation you can: Create Supplier users and give them specific, limited access to your data. They can see only the Delivery monitoring screen and only the data needed to identify the right product on the order. Their access can’t be extended to any other screen. Negotiate the expected time of delivery. Planners can request to expedite, or de-expedite orders and suppliers can reply by confirming or rejecting the request. Both parties can communicate by adding comments. Get suggested delivery dates that consider business calendars to help avoid run outs, incorporating your agreed schedules that may limit available delivery dates.