How to plan best for a Retail distribution center – Multi Echelon Replenishment in SAP Forecasting and Replenishment – Engage with us!

We would like to invite you to work with us and get your feedback about requirements and experiences for Multi Echelon Replenishment in SAP F&R.

It is key for today’s retailers to bring the right amount of merchandise to the consumer at the right point in time. Right amount means from a consumer perspective obviously not too little but at the same time it shouldn’t be too much as well from an internal company cost perspective. This is the typical replenishment balance challenge.

A great help in that context is having a precise idea of what is needed – this is what demand forecasting is needed for. When we look at the demand of a product in a store or e-com channel, there are many influencing factors that play a role: promotions, events, seasonal effects, price changes, weather impact – all these make up at the end what consumers are likely going to buy. So, the better you can model this demand, the better the basis for your subsequent replenishment decisions. This is where sophisticated machine learning forecasting algorithms such as SAP Forecasting and Replenishment along with SAP’s Unified Demand Forecast can help: All these factors are already included out of the box in the model and trained each time new information is available.

But what about levels higher up in a retailer’s supply chain such as regional or national distribution centers? How can you forecast their demand to achieve good replenishment results? The DC is surely driven by the demand of the underlying level (stores for example) but also their current inventory position.

A common approach is to have an independent DC forecast based on aggregated data, e.g. historical shipments out of the DC to stores. Or sometimes aggregated store orders as forecasting basis to account for unavailability situations at the DC. But how to consider all the different sales influences that happen at store level? A DC may deliver to many stores, not all of them having the same type of promotion at the same time. Also, there are regional differences, different holidays maybe – and many more differences on a product-store level when you look at it in detail. How would you model these kinds of ‘blurred’ effect that are no longer visible in the aggregated DC history? This is almost impossible.

A more advanced approach, that is also used in SAP Forecasting and Replenishment, is the so-called Multi-Echelon Replenishment (MER) where upstream levels of the supply chain balance their needs for inventories with lower levels they must supply. Demand at each level of the echelon is used to influence the forecasting and ordering at the next level of the echelon.

How is this done? To calculate the demand of the supplying location, MER uses the aggregated future demand of the assigned receiving locations, that means it considers the demand of the next lower level:

• Store sales forecast represents the future customer demand in the stores. This sales forecast includes all known demand influencing factors on the most granular level.
• Future store ordering requirements depend on this sales forecast but in addition on current and future inventory position, order and deliver schedules and logistical units in the ordering process. The result is an order forecasts for a product that represents what a store is likely to order in the future from a certain supplying Location
• The results are streamlined and demand-driven requirements along the supply chain that lead to less inventory and higher fulfillment rates.These future order forecasts are now aggregated across stores and can be used instead of a separate, disconnected DC forecast – no need for complicated DC forecasting parameter settings.

Do you know this process and are using it already?

We want to get your feedback on the current SAP Forecasting and Replenishment multi-echelon replenishment scenario.

Questions which should be answered are:

• Is the process working as you expect it?’
• Which features are meeting your requirements?’
• Which features are useless to you?’
• Which features are missing?’
• How would your ideal MER process look like?’

Are you curious?

There is a new Customer Engagement Initiative research project available on SAP’s Customer Influence Page where registration is open from June 3-28, 2019:

Requirements for Multi-echelon Replenishment Scenario, SAP Forecasting and Replenishment for Retail

https://influence.sap.com/sap/ino/#/campaign/1913

The goal is to collect feedback from customers or partners, consultants about the current solution but also to get general remarks/requirements.

How will this engagement be set up?

• Initial Call: one hour (starting in August)
• Feedback concerning the current process and your requirements through a questionnaire
• Further feedback iterations: depending on progress of evaluating the feedback, designing a new concept and participant’s availability
• No onsite activities
• Closing Call: one hour
• Estimated effort: maximum 1-2 hours per month.

We are looking forward to your registrations and Feedback!