In the realm of supply chain planning, the accuracy of master data matters significantly. Most companies operating on a large scale tend to have highly complex supply chains. Companies that run on SAP for their core system infrastructure, go with SAP ECC (Enterprise Central Component) as their foundational ERP system for transactions. These companies also begin using SCM/APO as their planning systems. The ERP system consists of various modules such as Material Management (MM), Production Planning (PP), Sales and Distribution (SD), Quality Management (QM), and Finance and Costing (FICO) etc. Each of these different modules have their own master data i.e. Materials, BOMs, Customer etc. The planning relevant parameters are just as dynamic as product definitions. Technologies that manufacture efficiently and provide fulfillment methods are constantly evolving. Reflecting accurate master data at the precise level of granularity is critical. Furthermore, it directly reflects on the quality, feasibility, and efficiency of the outputs that the planning system generates. Hence, master data accuracy is the key for optimal supply chain planning.
In SAP architecture, SAP ECC is the system of record for all the master data which is sent through SCM by an integration layer called Core Interface (CIF). Master data is sent to the SCM system under three different conditions: Initial Data Transfer, Delta Transfer, and Change Transfer. Transfer of transactional data is typically done in real-time or near real-time.
Key Transactional Data, which is used in supply chain planning, consists of plant, material master, work center, production data structure/production process model (BOM, Routing, and Production Version), and transportation lanes The key transactional data that are used in supply chain planning are stock, purchase requisition, purchase order, planned order, production and sales orders While most of the master data is created and maintained in the ECC system, certain planning specific criteria are created directly within SCM, such as transportation lanes, quota arrangement, product interchangeability etc.
Garbage In / Garbage Out
Incorrect master data in the source system will result in the same being transferred to the planning system, which the planning engines will consume and thereby impact the output of the planning results. This is a huge problem affecting many companies.
Here are some examples of this in action:
All these examples of master data listed above must be accurate in order for the planning system to run efficiently, and for the output of the planning result to be meaningful. Only then, the planners can proceed with the execution process so they may convert the planned order to production order. The purchase requisition is converted to a purchase order, and an availability check is performed either in ECC or SCM, using GATP to confirm the demand.
How do we improve the accuracy of master data?
Master data accuracy can be improved in several ways. Companies achieve this either through centralized or decentralized master data management. Master data accuracy depends on the company and how different master data is handled from division to division.
We can adopt different methods to improve the master data accuracy such as:
All the above methods can be adopted to improve the accuracy of master data and to standardize the overall process.
In short, improving master data accuracy is not simple or trivial. It requires discipline and focus. At Intrigo, we understand the challenges that companies face every day in order to ensure that their data is accurate and fresh. Our products such as Optek enable planners to easily analyze and maintain the components of master data. Optek helps ensure that data is always relevant, thereby improving quality and success in the implementation of planning systems.
To learn more about Optek, click here.
–Shunmugam Ramasamy, Solutions Consultant, Intrigo Systems