Data management has gone from being a niche concept to a fully-fledged way of life for many organisations. It has slowly but surely risen up the business agenda and is now a boardroom level priority. The asset is now accepted as being a tool that fuels innovation and fosters excellence.
However, despite this upturn, effective data management is still an issue for many. For example, Dynamic Markets has found that 94 per cent of organisations still suffer from common data errors, in spite of the fact that these very businesses see data as being integral to their objectives.
One of the main reasons is down to ineffective data management. This is not to suggest that no form of governance exists, just that it tends to be fragmented. It is all too easily to slip into a localised mentality and address issues that are only relevant to specific department.
What is required then is a holistic approach, one that is fully integrated and comprehensive. Organisations looking to boost their data management strategy should consider orientating it across three themes.
These are: detection, analysis and resolution. With detection, you are looking to identify things that are 'not on radar'; with analysis you are looking to restore integrity to data (clean, consolidate and standardise); and with resolution you are looking to set rules, establish a benchmark and then measure against key performance indicators.
The business benefits that come out of this are a better understanding of the value of your organisation's data assets; cutting down on unnecessary expenditure; enhancing regulatory compliance; and the centralisation of your data.
It goes without saying that businesses looking to invest in data need to implement a data management programme that works within the parameters of your organisation. The programme governing it needs to be long-term, adaptable and aligned to your chief objectives. From this point onwards, the future is a lot clearer and a lot brighter.
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