Accurate, consistent, highly integrated data: business processes depend on that bedrock for operational efficiency, good spending controls and reliable decision-making.
But extracting the full business value from corporate data is no mean feat. Among other challenges, it involves the creation of well-thought-out data structures, great data quality management, the adherence to data regulations and the successful application of technologies that can eliminate data silos and streamline data access across the organisation.
Recent research by Information Age in association with data quality and integration software company DataFlux and business advisory firm Deloitte, exposes the wide set of challenges organisations face in their attempts to support spending control, financial forecasting, productivityand other critical business issues with effective data governance.
There is almost universal acceptance that organisations need solid data governance, which in the words of Philip Russom of The Data Warehouse Institute is “an organisational structure that oversees the broad use and usability of data as an enterprise asset”.
That structure – which spans people, processes and technology – manifests itself in efforts to “improve data quality, remediate its inconsistencies, aggregate it, share it broadly, and comply with internal and external regulations and standards for data usage,” says Russom.
And on all of those key aspects, organisations in the Information Age survey are at varying levels of maturity and embracing them with varying levels of commitment (see pages 4 and 5).
What is also widely evident is that, more than ever before, organisations are under intense pressure to improve their data governance. In the current economic climate, business leaders demand quality data: they need to know that they are making decisions based on sound data that is held consistently, whether it is stored centrally or collated from systems spread across different parts of the organisation.
Today, a great deal of that decision-making is centred on operational efficiency and efforts to understand every facet of business performance, with data being the key to identify areas where cost cutting is appropriate.
But there are external pressures for better data too. Authorities are demanding that organisations demonstrate that they comply with an increasingly wide set of regulations – from adherence to rules such as data protection and anti-money laundering laws, to compliance with rules that are specific to a given industry.
There is also pressure coming from the grass roots. As the survey shows, most users see data as a “valuable, trusted business asset” whose quality should be given a high strategic priority. The only problem is that it is not always well managed and not always trusted.
Whose data is it anyway?
One of the reasons for that is that there seems to be confusion about who should take responsibility for data quality and other aspects of governance. Although the consequences of weak data governance have been well understood in IT circles for decades, that is not necessarily reciprocated elsewhere in the business, and few volunteer to take ownership of the problem.
As our survey shows, business data stewards, data czars, compliance managers, corporate information officers, IT staff and individuals dealing with specific day-to-day operations are all identified as the owners.
In fact, other than funding, the survey shows “no one owns the overall problem” as the most common barrier to good data governance.
What no one argues about is whether data governance issues can be ignored. In the survey of 200-plus companies, there was a striking number who said they undertake no formal data quality efforts: zero.
IT professionals are acutely aware that their organisations are not maximising the value of their business data. And they also know what barriers stand in the way
The technologies and best-practice approaches to data quality are maturing, instilling a much greater sense of trust and value in corporate information