Executing Demand-Driven Replenishment in SAP S/4HANA

MRP has been around for over 50 years and this postwar engine is still the core of ERP systems.

The logic behind MRP is simple. Based on your master production schedule (MPS), you explode your bill of materials, netting and time-phasing the requirements at each intermediate level, and end up with the raw materials requirements. In essence, it is the perfect just-in-time (JIT) system, because its goal is zero inventory at each level.

This was a preferred strategy when plants had insufficient capacity for demand, but now, extra capacity is the norm. The decision about what, how much, and when to produce is more critical than ever.

The primary objective of DDMRP is to enable material FLOW. FLOW is key where demand is volatile (driven by promotions, innovation, shortening product life cycles, competition…) and there are rigidities in supply (long lead-times, large batches, capacity constraints…) which result in challenges in service, inventory, speed to market, and ultimately cost.

FLOW is based on these core principles:

• Dampening the effect of variation on the supply chain by decoupling lead-times. This is done through buffers. Identifying where to buffer, and how much to buffer to ensure a) the shortest possible lead-time and b) the most optimum amount of inventory to deal with variation at minimum cost across the chain.
• Driving replenishment on actual demand, not forecasts. The best use of our assets is to make what is needed (for example, what sells). Increasing volatility in demand makes accurate forecasting challenging, even where we have good customer collaboration.
• Achieving visibility and prioritization by exposing downstream inventory and demand status to upstream sources to facilitate demand-driven prioritization of supply.

Demand-driven material requirements planning (DDMRP) helps you plan and manage supply chains efficiently based on customer demand or consumptions rather than through traditional MRP procedures.

Demand-driven MRP offers the following advantages:

• Permanently optimize the process flow
• Produce only for real demand
• Dampen variability by decoupling with inventory buffers
• Work event-driven
• Provide real-time prioritization based on demand
• Empower teams to make local decisions

DDMRP is ONE method used both for planning and execution control by defining:

• Where to stock → Inventory positioning
• How much to stock → Buffer profiles
• In a dynamic way → Dynamic buffer adjustments
• Generate supply orders according to average daily usage → Demand-driven planning
• Guided by an alert execution → Highly visible and collaborative execution

DDR is the SAP solution to support the DDMRP philosophy in your company using SAP S/4HANA. It has received certification from the Demand Driven Institute.

• It focuses on real customer demand (for example, not plan against forecast).
• It executes strategic buffer positioning at selected Decoupling Points (DPs).
• It utilizes continuous buffer (re-)sizing based on real data analytics / feedback loops, to adjust the buffers to an ever-changing reality.
• It improves customer service levels.
• I leads to a smooth and sustainable material flow.
• It reduces inventory levels and bound capital.

Demand-Driven Replenishment (DDR) in SAP S/4HANA is aimed at improving supply chain management and ensuring that inventory levels align more closely with actual market demand. Here are the main aspects:

1. Decoupling Points: DDR in SAP S/4HANA focuses on strategically placing decoupling points within the supply chain. These points act as buffers that help absorb variability and stabilize production flow. By strategically positioning these buffers, companies can better manage lead time and reduce the bullwhip effect.
2. Buffer Profiles and Levels: Buffer profiles and levels are fundamental components of DDR. These elements define the parameters for inventory levels, such as minimum, maximum, and target stock levels, and are dynamically adjusted based on actual demand patterns. This ensures that inventory is neither too high nor too low, optimizing carrying costs and service levels.
3. Demand-Driven Planning: Unlike traditional material requirements planning (MRP), which is forecast-driven, DDR emphasizes real-time demand signals to trigger replenishment actions. This demand-driven planning approach ensures that replenishment is based on actual consumption rather than forecasts, thus enhancing responsiveness to market needs.
4. Supply Order Generation: DDR automates the generation of supply orders based on buffer status and actual consumption data. This reduces manual intervention and helps maintain optimal inventory levels. The system can generate procurement proposals or production orders as needed to replenish stock efficiently.
5. Analytics and Performance Monitoring: SAP S/4HANA provides robust analytics and monitoring tools for DDR. These tools help businesses track the performance of their replenishment strategies by offering insights into key metrics such as stock levels, buffer status, and order fulfillment rates. Continuous monitoring and analysis enable ongoing optimization of supply chain processes.

In summary, Demand-Driven Replenishment in SAP S/4HANA uses decoupling points, dynamic buffer management, real-time planning, automated supply order generation, and comprehensive performance analytics to create a more responsive and efficient supply chain. Let's take a detailed look how it works.

DDR strategically decouples material flows, becoming less vulnerable to disruptions in the supply chain, and by protecting the flow through dynamically managed buffer (stock) levels for relevant products.

In the optimum way, your target is to ensure high customer service levels at the lowest possible inventory. With sufficient data to model customer demand, products, or components relevant to Demand-Driven Replenishment can be sufficiently well stocked to meet customer demand, but still stocked in low enough quantities to prevent excessive annual storage costs or losses due to expiry. Decoupling material flows at strategic locations can help avoid the Bullwhip Effect, which refers to increasing swings in inventory along the supply chain in response to changes in customer demand.

Looking at the example, you can easily understand the concept of decoupling as compared to the classic MRP concept.

The bullwhip effect describes the phenomenon that the variation of demand increases up the supply chain from customer to supplier. Considering a supply chain that consists of an original equipment manufacturer (OEM) and a first-tier, second-tier, and third-tier supplier, the OEM faces the lowest and the third-tier supplier the largest variation of demand as shown in the following figure.

It represents the uncertainty caused by a lack of communication between the various links in the supply chain. The distortion of information prevents companies from correctly predicting demand, resulting in significant costs for stakeholders.

These swings in inventory can expand exponentially up a supply chain and can cause excessive storage costs or losses due to expiry along all the levels of a supply chain.

The following two effects consequences of the Bullwhip Effect increase the cost for logistics and lowers its competitive ability:

• Too much stock resulting of the high level of safety stock necessary to ensure a sufficient service level.

• Variation in inventory level: The varying demand leads to variation in inventory levels at each tier of the supply chain. If a company delivers more than the next tier passes on, the inventory level increases. In reverse, the inventory is reduced in case a company delivers less than the next tier passes on. A high level of inventory causes costs for capital employed while a low level of inventory puts the delivery reliability at risk.

The five steps of the DDR process flow in SAP S/4HANA are as follows:

1. Determine where in supply network to place buffers.
2. Set up Buffer Profiles (master data) and determine sizing of each buffer according to lead times, demand, variability.
3. Adjust buffer sizes based on actual lead times and actual and projected demand.
4. Generate replenishment orders at decoupling points based on actual demand (consumption-based). Generate orders between decoupling points using classic MRP-dependent demand logic.
5. Prioritize orders in real time according to actual buffer penetration, and leverage order priorities in executing replenishment (distribution, production, procurement).

Decoupling points establish strategic stocks that are acting as a planned buffer between each side of the supply chain to protect the upstream parts from the fluctuating consumer demand. They reduce dependencies and complexity within in the end-to-end supply chain, and they also allow compression of the overall lead times, relevant in particular in industries where customers expect responsiveness.

Based on the various criteria, inventory decoupling points need to be chosen. Examples could be:

• Decoupling point buffer at the distribution center for fast customer service
• Decoupling point at a semi-finished good, because this semi-finished good goes into many finished good SKUs
• Decoupling point for a purchased item, because the supplier has capacity constraints and the lead time is highly variable

To identify products that can act as decoupling points, products are systematically evaluated and classified based on goods issue value, decoupled lead time, usage across BOMs and variation in actual demand.

Using the results of these classifications, you identify products that are relevant to Demand-Driven Replenishment (DD-relevant products).

The Demand-Driven-Replenishment Process (DDR) in SAP S/4HANA

There are two kinds of apps supporting the DDR process, configuration, and set up apps as well as operational apps.

The configuration and set up apps must be executed regularly.

Depending on the frequency of the changes in your company, the following are suggestions for the frequency with which these apps need to be used:

• Schedule Product Classification (DD): yearly
• Schedule Lead Time Classification of products (DD): monthly
• Schedule Buffer Proposal Classification: daily

The first app that you use when you start with Demand-Driven Replenishment is the Schedule Product Classification (DD) app. With this app, you can classify your products by systematically evaluating them based on their goods issue value (ABC classification), use across BOMs (PQR classification) and variation in actual demand (XYZ classification) across a specified evaluation interval. Classifying your products helps identify whether they are relevant for Demand-Driven Replenishment, and helps define inputs for their buffer settings. Also, you can schedule runs to reclassify your products periodically to keep their classifications up-to-date, so that you get accurate results as you proceed with Demand-Driven Replenishment.

Buffer locations are determined manually according to the criteria defined in the DDI methodology. SAP S/4HANA offers various analytics to help the user make the determination.

Is the product a candidate for consumption-based planning?

• Based on value? → ABC analysis
• Based on variability? → XYZ analysis
• Based on BOM usage (/is the product used in many BOMs)? → PQR analysis

Product classifications can change seasonally or based on increase or decrease in demand over time. SAP recommends that you periodically reclassify your products to ensure that the right products are considered relevant for Demand-Driven Replenishment.

The second app that you use when you start with Demand-Driven Replenishment is the Mass Maintenance of Products (DD) app. With this app, you can display and change product details (master data records) relevant to Demand-Driven Replenishment. When you have classified or reclassified your products, you can view the results of the classifications in this app, and based on the results, select products that are relevant to Demand-Driven Replenishment. You can use the mass change feature to change the master data records for several products simultaneously.

The Schedule Lead Time Classification of Products (DD) is the third app that you use when you start with Demand-Driven Replenishment. With this app, you can classify your Demand-Driven Replenishment-relevant products by evaluating them based on their Decoupled Lead Time (EFG classification) across a specified evaluation interval. Classifying your products based on their Decoupled Lead Time (DLT) helps define inputs for their buffer settings. Also, you can schedule runs to reclassify your products periodically to keep their classifications up-to-date, so that you get accurate results as you proceed with Demand-Driven Replenishment.

Here, you see how products are classified based on their Decoupled Lead Time.

A product is typically classified into type E, F, or G based on its decoupled lead time, with products classified as type E having the shortest decoupled lead time and products classified as type G having the longest decoupled lead time. An EFG classification is typically used together with the procurement type for a product or component.

The sum of the longest lead times of nonbuffered products in a sequence headed by a buffered or DD-relevant product in a BOM, adds up to a cumulative lead time for the DD-relevant product that is known as the Decoupled Lead Time.

You can set separate, custom thresholds for Decoupled Lead Time (EFG) Classification based on procurement types such as Make, Buy, and Transfer. Note that all settings must be maintained.

For example, you might want to set different DLT thresholds for products produced in-house, products procured from external sources or products transferred in through STOs based on logistical, contractual, or cost considerations.

The fourth app is the Schedule Buffer Proposal Calculation app. With this app, you can generate buffer (stock) level proposals for your Demand-Driven Replenishment-relevant products based on their average daily usage, decoupled lead time, buffer profiles, and several other factors. Also, you can schedule runs to recalculate the buffer proposals periodically to keep them up-to-date, so that you maintain appropriate levels of inventory while using Demand-Driven Replenishment.

Buffer Proposals can change daily, based on several factors, including an increase or a decrease in demand over time. SAP recommends that you recalculate the buffer proposals for your products periodically to ensure that the right buffer levels are considered for Demand-Driven Replenishment.

Buffers are sized based on factors for ADU, Variability, and Lead Time. Default factors are populated in the Buffer Profiles. Factors can be adjusted manually. Buffer sizes are time-dependent (daily).

The lead time factor is determined by EFG lead time classification. The variability factor is determined by XYZ variability classification.

The buffer is typically divided into three layers: green, yellow, and red. This is based on increasing order, and depending on the stock situation. These layers are known as buffer zones.

Buffer zones are dynamically calculated using parameters such as Average Daily Usage and Decoupled Lead Time, and help determine the maximum stock level, the reorder point, and the safety stock for the stock buffer.

• The red zone denotes the highest severity in the buffer, indicating low stock levels, and an immediate need for replenishment. The buffer value at the top of the red zone gives the safety stock, which is the minimum recommended buffer level that can be maintained.

• The yellow zone denotes medium severity in the buffer, indicating lower than ideal stock levels and a need for replenishment. The cumulative sum of the quantities of the red and yellow zones gives the reorder point.

• The green zone denotes the lowest severity in the stock buffer, where if the available stock lies within this zone, there should be sufficient stock available to comfortably meet the current demand. The cumulative sum of the quantities of the red, yellow, and green zones gives the maximum stock, which is the maximum recommended buffer level, beyond which the stored inventory quantity can be considered as excessive.

The net flow position shows where the available stock lies within the buffer and accordingly indicates the stock situation based on the buffer zones.

After executing the buffer proposal calculation, the results can be reviewed using the SAP Fiori app Manage Buffer Levels. Therefore, you must assign the planner in the Area of Responsibility.

From the overview screen, you can analyze the results in detail.

You can navigate to the Average Daily Usage view to review the consumptions in the past. Based on this consumption in the past and the Buffer Zones, the system calculated the Decoupled Lead Time and the Classification.

All these figures can be reviewed using the SAP Fiori app Manage Buffer Levels.

An MRP run based on the new calculated settings is then run as a next step in this process.

The results of this MRP run can then be reviewed using the SAP Fiori app Monitor Material Coverage.