Data integration and data quality management have become important factors for many South African businesses, says Johann van der Walt, MDM practice manager at Knowledge integration Dynamics (KID). We have always maintained that solid data integration and data quality (DQ) management are essential building blocks for master data management (MDM) and we’re finally seeing that customers believe this too. One of the primary drivers behind this is the desire for services oriented architecture (SOA) solutions for which MDM is a prerequisite to be effective.
SOA relies on core data such as products, customers, suppliers, locations, and employees. Companies develop the capacity for lean manufacturing, supplier collaboration, e-commerce and business intelligence (BI) programmes. Master data also informs transactional systems and analytics systems so bad quality master data can significantly impact revenues and customer service as well as company strategies.
Taken in the context of a single piece of data MDM simply means ensuring one central record of a customer’s name, a product ID, or a street address, for example. But in the context of companies that employ in excess of 1 000 people, McKinsey found in 2013 that they have, on average, around 200Tb of data.
Getting even small percentages of that data wrong can have wide ranging ramifications for operational and analytical systems, particularly as companies attempt to roll out customer loyalty programmes or new products, let alone develop new business strategies. It can also negatively impact business performance management and compliance reporting.
In the operational context, transactional processing systems refer to the master data for order processing, for example.
MDM is not metadata, which refers to technical details about the data. Nor is it data quality. However, MDM must have good quality data in order to function correctly. These are not new concerns. Both MDM and good quality data have existed for as long as there have been multiple data systems operating in companies.
Today, though, they are exacerbated concerns because of the volume of data, the complexity of data, the most acute demand for compliance in the history of business, and the proliferation of business systems such as CRM, ERP and analytics.
Add to that the fact that many companies use multiple instances of these systems across their various operating companies, divisions and business units, and can even extend to multiple geographies, across time zones with language variations. It unites to create a melting pot of potential error with far reaching consequences unless MDM is correctly implemented based on good quality data.
None of these concerns yet raise the issue of big data or the cloud. Without first ensuring MDM is properly and accurately implemented around the core systems companies don’t have a snowball’s hope in Hell of succeeding at any big data or cloud data initiatives. Big data adds successive layers of complexity depending on the scope of the data and variety of sources.
Shuffling data into the cloud, too, introduces a complexity that the vast majority of businesses, especially those outside of the top 500, simply cannot cope with. With big data alone companies can expect to see an average growth of 60% of their stored data annually, according to IDC. That can be a frightening prospect for CIOs and their IT teams when they are still struggling to grapple with data feeding core systems.
While MDM is no longer a buzzword and data quality is an issue as old as data itself they are certainly crucial elements that South African companies are addressing today.
