Establishing data governance programs, data quality initiatives or other projects aimed at looking after or enhancing the well being of a company’s data can be difficult to get underway and sometimes even more challenging to keep alive. Such initiatives (especially if your company’s funding approach forces you to tackle them as a series of individual projects) cannot always deliver the concrete and tangible “things” that you might get from a more traditional IT project. More often than not there is no new asset created, no new system to implement and enable across a go-live weekend, nor are benefits always obtained and measurable in the short term. Unless your business is facing real pain (and honestly attributes that pain to not just problems with the data itself, but also with how the data came to be in the state it is) then you may well struggle building support for, and keeping data initiatives running.
- Knowing what you have – an inventory of your data;
- Knowing where this data is – which systems house which data and (ideally) how it moves around between them;
- Knowing which stakeholders care about which data (you don’t need to get to business data ownership just yet, but at least you should know which data helps achieve, or threaten, which stakeholder’s bonus package);
- Knowing what preventive maintenance is required to keep your assets running at the required level and optimize the investment in them- some idea (and documentation) of where the problem areas lie. The big data quality issues (and importantly their real impact on the business);
- An understanding of how you can protect your asset – which may include classifications for data along with associated handling rules and other security aspects; and
- A vision for continuous improvement and a better future state of asset management – thought out and documented ideas for better use of your asset (which might include identifying and reducing redundancy, identifying inventory gaps or working better at the extreme ends of the asset life cycle).