You need to figure out a better way to manage your company's massive amount of critical "master" data. Do not worry, you are not alone. In a 2007 Accenture survey of 162 global CIOs, 75% said they want to develop an overall information management strategy in the next three years. Doing so would "reinforce the need to fully manage their organisations' data and leverage that data for strategic advantage," said the report.
To succeed, you need a master data management (MDM) strategy that spells out how you are actually going to pull this off. It must address how you are going to get organisation wide buy-in, what the end state of your systems and data management practices will look like, and the technologies you will use. Selecting an MDM vendor is a critical initial step for software development team.
Since you get only the services you ask for, writing a precise and informed request for proposal (RFP) document can only help your overall MDM effort. Siperian, a provider of MDM platforms, has seen a sizeable increase in the number of RFP’s it has received during the last two years. Company executives noticed that many proposals lack the unified, comprehensive view that is necessary to ensure long-term success. As a result of looking at more flawed RFPs than you have seen programmer résumés, Siperian identified 10 common mistakes that CIOs make when companies put together an RFP for their master data management efforts.
Ravi Shankar, director of product marketing at Siperian, urges CIOs to avoid these critical mistakes in their RFPs. Doing so can lay the foundation for a complete and flexible MDM solution that addresses both current requirements and unforeseen future data integration requirements. If not, he notes, CIOs "will end up with broad master data management silos." Which is the exact opposite of what an MDM solution should do.
Mistake 1: Failing to ensure that multiple business data entities be managed within a single MDM platform
This is a biggie. "When you select and deploy an MDM platform, make sure it is capable of managing multiple business data entities such as customers, products and organisations all within the same software platform," Shankar advises. "By doing so, system maintenance is simplified and more cost effective, which results in lower total cost of ownership."
A large Siperian pharmaceutical customer recognised that it would need to add more business groups and functionality to its enterprise MDM system and can do that today because the flexibility was built into the strategy from the outset. Shankar notes that an alternative is to deploy and manage separate master data solutions, wherein each manages a different business data entity. However, he says, this approach would result in additional system maintenance and integration efforts and a higher total cost of ownership.
Mistake 2: Ignoring data governance needs at the project or enterprise level
"The important thing to realise is that when doing MDM, you are really doing data governance," Shankar says. Data governance is unique to each company since it is based on the company's business processes, culture and IT environment. However, most companies select an MDM platform without much thought to their enterprise data governance needs.
"It is critical that the underlying MDM platform is able to support the data governance policies and processes defined by your organisation," Shankar notes. "In contrast, your data governance design could be compromised and forced to adapt to the limitations of some MDM software platforms with fixed or rigid data models and functionality."
Controls and auditing capabilities are also important data governance components, according to Shankar. To properly support this function, the RFP should "require the MDM platform to integrate with a company's security and reporting tools to provide fine-grained access to data and reliable data quality metrics."