Let’s face it, if an organization is spending millions of dollars to purchase and integrate an ERP system, then the project requirements and schedule will be driven by the IT department. Unfortunately, in the definition of the scope of the project most will only focus on moving the “dirty” data from the legacy system to the bright new and shiny ERP system. The IT implementation then moves to the next integration and the users of the data will have the same data issues that plagued them in the legacy now also in the new ERP system.
A flawed philosophy is to migrate the legacy data, meet the deadline, call the project green and successful while the users must figure out to how to correct and update the data. These ERP systems are not designed to handle the volume of change to data, provide a simple method to track change, obsolete a record with history view and archive functionality is non-existent. Another reason this is a flawed philosophy is that purchasing contracts are set up based on the “bad” data, a unit of measure, part number or manufacturer change will void a contract resulting in wasted time of valuable resources and at the end of the day an inability to source the item, this could set in motion a critical manufacturing line shut down. Let face it, an ERP system is designed store a product or service record providing the business a method to transact, not to cleanse a record to a single master version of an accurate classified, verified and technically described Master Record. Therefore the activity of migrating data to a new system is not Master Data Management.
Master Data Management needs to be independently structured and separately managed in the organization not through IT. It is critical that within the Master Data Management organization to properly represent the business assets of the data (engineering, purchasing, customer, etc). The data is the core information used as the foundation to run the operations, sometimes referred to as the BI for the analytics of sound decision making processes. If the data is incorrect in the new systems, how is the BI improved? How is the business case ever calculated and successfully achieved? I can’t even imagine trying to tally up the potential “cost savings” when bad data is migrated to a new system.
Establishing a MDM program will need to have clear and well defined ownership, stake in the end user organizations and representation in the design and schedule of the software roll outs with full participation in all the projects with data involved. They should also participate in the project design strategy for systematically cleansing, classifying and migration of the data to the new system. Strategy should include an audit of data in the legacy system, let’s face it there maybe 20 year old records with no transactional history or balance on hand in inventory. Should this data be moved to the new system? The answer is NO.
An MDM data strategy to support the IT team can encompass a number of options. A simple option is the publishing of a long term schedule establishing adequate time for the data group to meet the data cleansing and classification requirements. This is not always possible, so what about a phased strategy? Some of the possible steps should include
- Evaluation of data to review transactional use
- Evaluation of the stock on the shelf and confirm that none of the inventory should be obsolete and disposed of.
- Review of data related to the equipment but is not inventoried
- Identify data that should not be moved to the new system
- Establish data priorities for cleansing starting with high transaction use and stock items classified and cleansed first.
An ongoing maintenance and new set up process is imperative to be established with an easy method to request an urgent record during the data migration to support the day to day operations of the business.
We need to get out of the mindset that MDM is simply a data migration to a new system. MDM is a business process to establish the single version of accurate information which is then propagated throughout the organization, part of which is the proper migration of data from legacy systems.
