Master Data Accuracy in the Realm of Supply Chain Planning
June 30, 2015

General Overview

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:

  • If in-house lead time, planned delivery lead time, lot size, or planning time fence happen to be inaccurate in the material master, it will impact the ability to meet customer demands on time. Incorrect procurement type (in-house, external, or both) will completely change the planning process.
  • Base quantity, machine time, or setup time in routing will adversely affect your production efficiency.
  • Components in the Bill of Material system will plan for the wrong product and end up not meeting the demand on time.
  • Routing or BOM assignment in the production version that is then reflected in the PDS or PPM in APO  again leads to planning inaccuracies.

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:

  1. Implementing a master data set-up workflow tool which can be triggered for creation and changes to the master data. This will ensure that the appropriate owners are engaged in the right sequence and with the right context. It will also incorporate the business rules to guarantee that only correct information is entered in to the system.
  2. Implementing a Data Governance tool such as SAP MDG to centralize master data creation and modifications. SAP MDG has the validation technique and duplicate check functionality which will help to improve the accuracy of master data.
  3. Using offline master data validation tools to apply business rules and to perform across-the-board validations,  and then loading them in to the system.

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