Master Data Management of an ERP System

ERP packages contain several modules, such as finance, sales and distribution, materials management, manufacturing and production control, human resources, plant maintenance and quality management. Main characteristics of ERP system is that all its modules function in an integrated manner. Due to integrated nature of functioning, a few master tables are referenced frequently all across the system and databases, and shared by different applications, functional areas and sites. Data incorporated thereon need to be accurate, complete, timely and consistent. The quality of data as inputted in master tables, is a major reason for success or otherwise of an ERP system.

Collection and maintaining of master data

  1. Clear cut process and procedure for maintenance of master data.
  2. Ownership of data is properly defined.
  3. In built workflow and authorization for adding and modifying data.
  4. Documentation of the process.
  5. Audit trails of master tables are activated and modifications are logged in the system.
  6. Proper excel templates or data mapping with legacy system, for initial collection of data.

Classification of Master data

Collection of master data may be broadly classified under the following categories.

  1. Business Partner Master Data:

    1. Customer role-Delivery, shipment, invoicing, payment method, parent company of customer, country location (for tax and statistical purpose), status (active, inactive, potential), credit rating, financial groups, contact name and address, default currency, prices and discount, sales channel, sales office.
    2. Supplier Role-Receiving, transport, payment term, prices and discount, invoicing method, country location (for tax and statistical purpose), status (active, inactive, potential etc.), financial groups, contact name and address, default currency, purchase office.

  2. Item Base Data:

    1. Product category- whether purchase, manufacture, service or cost item with specialized management separately for each category.
    2. , Measurement unit and alternate unit for the item with conversation factor.
    3. item ordering system (manual, SIC or MRP), reordering factors (service level, safety stock, ordering interval, minimum ordering quantity, forecasting mode, seasonal pattern etc)
    4. Item costing data (cost component, surcharges, standard cost, transfer cost etc.), automatic process for generation of cost.
    5. Status of the item (running or obsolete), alternate and reversible item, list item (with user defined components).
    6. Rates- applicable price, price limit, rules for applying prices to purchasing and sales.
    7. Adding up segments to item code, such as project segment that assigns the item to a project, cluster segment used for planning and distribution.
    8. Vendors by item, freight categories and transportation services.

  3. Employee base data: Name, ID, personal details, service centre, service point, skill, hourly rate, overtime rate etc.

  4. Finance Master Data: In addition to master data requirement for specific financial modules such as general ledger, accounts payable, accounts receivable, cash management, budgeting etc, following finance master data are having impact across non financial modules:

    1. Basic finance parameters for the parent organization and individual company.
    2. Chart of accounts, periods, dimensions and transaction type.
    3. Integration parameter and mapping accounts for logistical transactions (originating from sales, procurement, manufacturing, service, subcontracting).
    4. Integration parameter and mapping accounts for warehouse orders such as inventory adjustment, inventory revaluation and warehouse transfers.

It may be reiterated that the above list is not exhaustive. The process and terminology used for maintaining master data in different packages, also differ.

Conclusion

Master data management is not a one time affair of data take on. Data quality for master tables is needed to be persistent on a long term basis. Discipline, ownership and process of master data governance are a critical success factor for sustainability of the system.



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