The Ultimate Inside Look at By-Product/Co-Product

By Eacliffe Stuart January 18, 2019 by Eacliffe Stuart

There are times when using By-Product/Co-Product functionality is mandatory, or else be ready to pay significant consequences in managing your manufacturing operations using related SAP ECC functionality.

What is By-Product/Co-Product?

By-Product/Co-Product is manufacturing functionality where a single PP-PI/PP (Incl.PP-REM) order reflects that fact, and when attempting to produce inventory for a single material, the manufacturing process unintentionally or intentionally produces an inventory of other materials. This option to use is strictly a finance decision since both options behave the same on the logistics side.

When to use By-Product/Co-Product?

The key of when to use this functionality is dependent on what is physically produced and inventoried, by the manufacturing process. To effectively use SAP to support related business processes, is imperative that the manufacturing master data and related functionality reflects this reality. There is nothing like hands-on experience to truly appreciate the negative implication of employing workaround solutions to avoid working with By & Co-Products. These negative implications quickly manifest in Capacity Evaluation, Material Requirement Planning for Short-Term, Medium-Term and Long-Term Time Horizon, as well as in Detailed Production Scheduling and Component  Staging. This all leads to a lot of guessing and/or the development of standalone tools to reduce the solution gap.

Why Use By-Products/Co-Products?

The following illustration is being used to explain the importance of using By/Co-Product functionality in SAP to reflect what is occurring in the manufacturing process

What can we observe between the Co-Product solution versus using separate planned orders for each product produced from a single manufacturing run?

1. Capacity Evaluation
   In the example provided, both solutions are calling for the same capacity hours. However, the only way this will occur is if planned orders are manually created to reflect tribal knowledge. This is an observation I made with a client. Unfortunately, MRP will generate exception messages to cancel these planned orders due to the lack of demand for the inventory. This is not an efficient use of employee’s time to be performing a task that MRP is responsible for and capable of doing correctly each day as demand changes.In reality, the capacity data for the two solutions will be significantly different since the planned order quantities for solution 2 (Without By/Co-Product Solution) is driven only by demand while for solution 1 also takes interdependency of each output material is taken into consideration. The interdependency for solution 1 is defined in the BOM. This means when there is a proposal to produce one material, it means that the generate Planned Order will also reflect output for the other produced material. It also means that the required capacity to produce all the calculated output is also reflected in the system.  This holds true for the entire time horizon. Solution 2 (without By/Co-Products) will not reflect any of this.
2. Material Requirement Planning
   With solution 1, when production starts, it applies to all produced materials. Looking at the illustration, this can be observed for Material 1_KG, Material 2_KG and Material 3_KG where the start time is shaded in green. When looking at solution 2 for the same material, it can be observed that the green shaded appears on different days. Similar observations can be made with component requirement timing for Component 1_KG and Component 2_KG.Like capacity evaluation, component requirement timing and quantity will be significantly messed up with solution 2 due to incorrect timing and duration of each of the generated planned order. There will also be understated requirements since planned orders will get generated only when there is demand. Remember, co-product means you must physically produce related materials even if there is no demand for it. There is a high probability that planners will introduce external tools to reduce the risk of shutting down production.
3. Detailed Scheduling
   Dispatching of planned orders (Finite Scheduling) is done to ensure there is no scheduling conflict for a shared work center. Looking at solution 2, technically, the planned orders illustrated could be scheduled without any conflict. The challenge is the tribal knowledge will not be aligned with how the planned orders are sequenced plus the timing of the GR (Goods Receipt) will not be close to when the total inventory is received.
4. Component Inventory Staging & Consumption
   Staging of component inventory is driven by Start – Finish Dates on PP-PI/PP (incl. PP-REM) Orders. The fact that the different orders all have dates adds complexity to this topic. Again, this leads to a high probability of external tools being employed to address this gap.By-Product vs Co-Product which solution to use, is decided by finance since the implication is strictly on the finance side. From a logistics perspective, the solution looks the same. From the finance side, there are implications on how products are costed, and variances are reflected against the produced materials. A production costing resource should be consulted for further details on configuration and process implementation.

The goal of any organization is to be best in class which is a key reason for implementing ERP systems like SAP. With such a significant investment, the information it provides should align with how things work at the manufacturing site. When to use By-Product \/Co-Product should not even be a debate. Looking at the illustration of solution 1 and solution 2 where the volumes are the same (Fat chance in reality), it can be clearly seen that why the totals for Required Capacity, Component Requirement, Planned Output, their daily timings are significantly different. The point is that solution 2 is not an option when the physical manufacturing process is truly producing By/Co-Products.

Tags: By-Product, Capacity, Co-Product, Demand, ERP, Inventory, Manufacturing Process, Planning, SAP, Supply chain