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The data management processes and organisation of many South African businesses is immature and master data management (MDM) projects therefore tend to be IT driven – a classic mistake.
It’s one of the main reasons why MDM is getting a bad reputation for wasting money, wasting resources and delivering no tangible business benefits, says Johann van der Walt, MDM practice manager at Knowledge Integration Dynamics (KID).
That needn’t be the case, however, because MDM is a very capable set of processes, disciplines and technologies for achieving numerous goals applicable in today’s corporate environments and that range from supporting business decisions to paring down operational processes for greater efficiencies and cost savings.
It can also give conglomerates a unified view into their operations without incurring the steep costs and business disruptions normally associated with integration projects.
So why isn’t it performing as advertised? It comes back to the business maturity and the framework required for a successful implementation.
As is the case with some other projects MDM requires a combination of business processes, people with the right skills and abilities, and finally the technology. While the technology is undoubtedly an important spoke in the wheel it is a small one.
To put it into perspective: if an MDM project takes six months to implement the technology component should require only one month and it should only be considered some way along the implementation path, well beyond the processes and the people.
MDM isn’t typically implemented that way in South Africa. South African businesses see it as an IT project so they hand it over to the technical staff.
Forrester, the research company, puts it succinctly when it said in 2008: “Recognising and planning for enterprise MDM as a multiyear, multiphase business capability allows information and knowledge management pros to deliver trusted, quality customer, product and other critical data.”
There are 10 steps that KID follows when implementing MDM to ensure the highest probability of success:
* Identify the producers and consumers of the master data;
* Collect and analyse metadata about master data;
* Appoint data stewards;
* Implement a data-governance programme and data governance council;
* Develop the master data model;
* Choose a toolset;
* Design the infrastructure;
* Build and test the MDM solution;
* Modify the producing and consuming systems; and
* Implement the maintenance processes.
As is evident, technology only comes in at number six on the list, and everything before that is about process and people.