As data proliferation in the enterprise continues its exponential expansion and the size, complexity, and heterogeneous nature of IT systems environments scales to keep up, data quality and trust become increasingly important.

Investments in data profiling, data quality (DQ), and master data management (MDM) software can transform trusted data visions into reality. But many information and knowledge management professionals have learned the hard way that it’s foolish to expect this investment to be supported simply because senior executives happen to announce “data is our most critical asset” at a company meeting. No matter the rhetoric, a strong business case is required to open the purse strings.

It’s essential to determine the business value of investing limited time and valuable resources to the task of making corporate data more trustworthy. Here are five recommendations to ensure your DQ and MDM plans address key business drivers:

Audit pain points and inefficiencies across business stakeholders.
Information and knowledge management professionals often find it easier to measure the negative impact of existing processes using bad data, than to quantify the potential benefits of using good data. By identifying inefficiencies, you’ll be able to make improvements that provide the low-hanging fruit your trusted data initiative requires to prove its value.

Prioritise compliance initiatives in today’s period of economic uncertainty.
Given the current economic climate, projects with the highest likelihood of funding include support for regulatory requirements such as Sarbanes-Oxley, counter-party risk, and product recall/product safety support.

Rescue underperforming IT investments.
For the past 10 to 15 years, large enterprises have spent billions centralising and standardising their application infrastructures. Unfortunately, in many cases the results have been disappointing, with poor employee adoption due to an overall lack of trust in the information flowing through these systems. To protect these large investments, organisations must make improving data quality levels within these environments a significant priority. In fact, Forrester believes that most organisations begin their data quality journey here to rescue massively underperforming IT investments.

Partner with business stakeholders that “get it”.
Identifying the business stakeholders who can best articulate the impact that a DQ or MDM effort would have on his or her critical processes or decisions is your top priority. These stakeholders will not only provide you with clear and useful requirements that should go into the solution design, they also will provide the appropriate business perspective required to make your business case meaningful.

Hone your business case development skills.
Facilitation and interviewing skills are needed to construct business cases and engage with business stakeholders. In addition, financial analysis skills would also be of use – specifically when it comes to capturing your cost/benefit analysis and return on investment calculations. When performing that cost/benefit analysis, be sure to include all relevant costs including software, hardware, services, training, governance, change management, and ongoing support. Nothing can derail the momentum and support for an MDM programme more than starting out with unrealistic funding and resource expectations, then having to ask for more.

MDM remains an immature business capability and technology that offers compelling business drivers but also introduces a great deal of risk. Many aggressive organisations learned the hard way how an expensive MDM investment – if implemented improperly without effective governance – can in effect open a Pandora’s Box, propagating less-than-trustworthy data across the enterprise. But if scoped and managed appropriately, MDM can deliver significant benefits.