Onus Of Data Governance On Erp Systems
Master Data Management: Why does my organization require this
?
Master data management (MDM) has emerged as an important aspect of all ERP implementation or consolidation exercises. With ever evolving and increasing inventory, supplier, product and customer databases, it has become essential to cleanse and maintain the quality of the master data. More and more global enterprises across various industries have undertaken or plan to commence an MDM initiative in tandem with their ERP projects, though there are select incidents where standalone MDM projects are also taken up by some companies.
All MDM initiatives have two parts one, historical data cleansing and
data migration and two, on-going data management. Historical data cleansing essentially involves classification and enrichment of data. Classification involves creating a structure based on globally accepted coding standards such as UNSPSC, E-Class, etc. This helps in distinguishing and categorizing all the parts in the master data. On the other hand, enrichment ensures that all the relevant attributes critical and Non-critical are incorporated thereby facilitating the location of the particular data in the master data.
In order to keep the cleansed data clean, it is imperative to adopt an effective and efficient on-going data management (ODM) tool or what is more commonly known as Data Governance tool. The point of origin for Data Governance is the Master Data itself. An
MDM initiative is the first step in putting a Data Governance Model (DGM) in place but when organizations move from one ERP to another or move from their legacy based systems to an ERP, due to top management demand of timely rollout of ERP, planning for data migration and data management becomes the premier casualty, and with no data governance tool in place the entire implementation becomes sub-optimal from day one!
So, where do we get started?
It would have been great, if the organizations had just one set of master data, but this is usually not the case in most organizations. Many companies grow through mergers and acquisitions. For each company any enterprise acquires a typical ERP system at a minimum will have a Customer Master, an Item Master, and an Account Master. This master data is often one of the key assets of a company. Because it is used by multiple applications, an error in master data can cause errors in all the applications that use it. For example, an incorrect address in the customer master might mean orders, bills, and marketing literature is all sent to the wrong address.
During data migration, multiple masters need to be migrated to the new system. At the same time, this data which is migrated to the new system is cleaned, harmonized, classified and de-duplicated. Once the data migration is complete the only concern is keeping the harmonized data clean on an on-going basis, which is where data governance comes into the picture.
Data Governance is a point of convergence for people, technology and process in order to manage the crucial data (information) of an enterprise. This is a vital link in the overall ODM process for it maintains the quality and relevance of data, and makes it available to a wide range of decision making hierarchy across an organization. In other words, Data Governance is the complete management of the availability, utilization and security of the data in a company right from creation, through edits, to ultimate retirement.
Why is Data Governance so important?
Data Governance is a decisive factor in an MDM project because of two reasons:
1.It monitors complete compliance both internally and externally. From the internal perspective, DGM allows the requisitioners, local data managers and master data managers to view the entire data creation process and take suitable corrective action as and when necessary. This is besides overall monitoring of the material, product and vendor information in the master data.
2.An effective DGM can drastically reduce the threat to a consolidated master data repository. By bestowing data stewardship, it controls access to the critical master data. As result any change in existing data or creation of new data can be tracked and monitored at all times.
Aberdeens study of information collected from organizations, who had implemented an ERP system, shows that organizations who have integrated their ERP systems with master data management were able to realize the full potential of their ERP systems than those that had not. The study further goes on to indicate that organizations with higher levels of data governance and ERP integration with Master Data Management outperformed their peers with record improvements in metrics such as inventory accuracy (by 96%), improvement in complete and on-time deliveries(by 20%) which impacted improvement in reduction in operational and administrative costs and increase in profitability (by 13%). Not only this, organizations whose ERP system is integrated with data governance tools were able to report lesser schedule compliance problems and accelerate decision making. Data governance is strongly related to data quality which strongly impacts ERP performance.
Information Management for an enterprise though simplified in many ways since the advent of IT in the late 1990s, has become more complex with the emergence of a large number of IT solutions which upgrade themselves almost every year. This coupled with globalisation and the steep increase in mergers and acquisitions over the last decade necessitates the need for a Data Governance tool, with strict data stewardship roles in place so as to maintain the accuracy of data as much as possible for an enterprise to drive year-on-year productivity and profitability.
by: Zynapse
5 Process Fails In Mro Master Data Management Oracle Archive: Managing Databases For Reference Australian Firms Getting Ahead With A Data Centre Strategies Used For Data Security In A Cloud Data Center In Bangalore: Empowering The It Hub Data Center In Delhi: Catering To The Industrial Hub Data Mining-what Is Importance Of It?? Database Sharding Is A Popular Concept Used For Scaling Databases Dynamics Gp Recovering Failed Data Conversion Projects Save On Premiums With Data-tracking Technology Opt For An Ms Sql Server Data Recovery Tool Able To Eradicate Irretrievable Errors Choose A Trustworthy Ms Sql Table Recovery Tool For Crucial Sql Recovery Choose An Sql Server Backup Recovery Tool To Relieve From Corrupt Sql .bak Files