During the past 12 months, IT professionals and information managers throughout the UK have had to confront an uncomfortable truth: that the data over which they have stewardship is often not ‘fit for purpose’. When Information Age readers got together for a roundtable lunch this time last year, delegates swapped war stories (off-the-record) on the apparently appalling state of their organisations’ data.

 One year on at September’s roundtable debate, sponsored by data quality and integration software company DataFlux, there has been a subtle change in perception: as the awareness of the ‘dirty data’ problem has grown, so has the acceptance that it is not going away. “The data may be rubbish”, as one head of information at a local police force put it, but now the issue is how information managers are going to solve – or at least contain – the problem.

There was no consensus among participants on the best way to address that – not least because the question of ‘data ownership’ is often a bone of contention. “The people at the top don’t realise that dirty data will take a long time to clean up,” bemoaned one data warehouse manager of his organisation. “So we’ve been looking for ways of putting forward the case that data cleansing is an important thing for us to do – with clear business paybacks. But, frankly, the users don’t want to know”.

And this lack of user buy-in is proving a critical sticking point. In several organisations, participants revealed, attempts to engage users in data quality drives have proved futile and has led in some instances, to overall project failures. As one head of information systems for a government department recalled, a major project in his organisation nearly ended in disaster because data capture fields had been systematically, if unwittingly, misused by the end users.

One effective way to tackle this problem, suggested the head of information at a heritage organisation, is to identify “visible” painpoints within the organisation that can be dealt with discretely and quickly, and to leverage that success elsewhere in the company.

“It’s best to look for areas where people are crying out to do something productive with the data, for example those dealing in CRM (customer relationship management), and secure quick wins there.” But importantly, she added, the project should be followed by a “lessons learnt” exercise, in order to ensure the users “understand what the business wants to do with its information and the value of that information”.

For some participants, however, blaming users only masks a wider organisational problem, of which poor data governance is a subset: namely, that the majority of companies have inadequate information management strategies, reflected in poorly designed data captures systems, non-existent data retention and records management policies, and a lack of established information processes.

This problem was aptly expressed by the records manager of a large professional association, who revealed that, instead of addressing these issues strategically, “the IT department just keeps saying that we should buy more storage, because it is cheap. But the overhead of managing all that information is just proving too much,” she complained.

Implementing a successful data governance strategy, it seems clear, will require organisations to face up to the systemic, and in many instances cultural, problems commonly associated with organisation-wide information management. And that needs to be taken seriously by everybody concerned: users, technologists and management alike.