Policy, Processes, Roles and Responsibilities
A vast majority of organisations are vying for better quality data, as they understand the benefits attached to ensuring it is clean and valid. However, many are still relying on short-term, tactical approaches to managing these initiatives rather than investing in governance – something that can infinitely increase the success and sustainability of data quality schemes. Data governance provides organisations looking for better quality with the solution they need, rather than offering a quick fix.
Although this has led to well-developed approaches to analysing data sets to pinpoint deficiencies and ways to enrich the asset, it needs to be repeated frequently in order to maintain a durable level of quality. Without governance, the data can not stay clean and valid in the long-term.
In order to maintain a high level of quality, data must be proactively managed to ensure it is captured correctly and deterioration is prevented – all of which can be provided by a structured data governance framework.
The phrase data governance is an umbrella term, describing a range of activities an organisation can undertake in order to improve the quality of its information. Businesses can become confused over how data quality relates to governance, but the concept is really simple.
A solid information governance policy supports any data quality initiatives carried out by a company. Without this kind of structure in place, any efforts to keep information clean are really just tactical fixes, rather than long-term solutions.
The framework ensures that responsibilities are established from the outset, which means everyone understands the role they need to play and the organisational processes needed to proactively manage data quality are put into place.
All three components of a data governance framework – policy, processes, and roles and responsibilities – is key to the success of quality initiatives.
For example, if an organisation has established a policy and roles, but has failed to determine processes, the results will be inconsistent. If a policy and processes have been put into place, but responsibilities haven’t, no one will be there to take ownership, meaning nothing will happen!
An organisation can only truly realise the sustainable benefits of data quality by using a governance framework.