Data Quality is no longer Optional – Why?
The amount of data held by organisations is growing rapidly irrelevant of sector, size, or focus. Furthermore, the realisation that data is a massive asset is becoming more prevalent. No longer is the issue of data purely a function of IT.
With the increasing amount of data and the shift in focus from IT to Business comes many challenges, not least of which is Data Quality. So why has this become a key priority within so many organisations, in particular those industries and sectors that are customer centric? The simple answer is that business leaders and decision makers understand that in order to make the right decision and better serve their clients they need to have the right information to hand.
And herein lies the complexity. The “right” information is not easily attainable.
Delivering the “right” information to business users can only be done if the data that is interpreted to deliver reports, budgets, plans etc. is accurate, consistent, and complete. The age old adage of “rubbish in – rubbish out” remains a point in fact. Never has a statement been more accurate about information management.
So, how do you ensure your organisation’s decisions are based on accurate, consistent, and complete data? Perhaps even more pertinent is how do you sustain it? Be under no illusion, whilst it seems a simple and straightforward task and in essence it is, Data Quality needs to be underpinned by data standards defined by the business (Data Governance). This means getting business buy in, managing expectations, consultations, and a strategy that needs to align across all and applications.
However, the benefits can be extensive. Analysts report that through their research they estimate that any project of this type will typically deliver 500% return on investment. Benefits include
- Higher user adoption
- Greater confidence in reports, analytics etc
- Identification of cost savings
- Improved customer service
Delivering a Data Quality solution as part of an overall data management strategy is an essential tool and although not an easy one to identify. InforData recommend starting with a single key data element. Identify a specific element that is of key importance to your organisation, for example property. Thereafter, create data standards, identify, and document roles and responsibilities for data owners and stewards, which forms an integral part of your Data Governance framework. And, you will be halfway there.
Once these key pieces are in place, you can then build procedures that use the processes as defined within the Data Governance framework to begin a Data Quality initiative. This activity, linking Data Governance to Data Quality, ensures the automating of processes such as address, or customer, validation. In other words, cleansing your data and ensuring that the information being distributed to business users is reliable and accurate.
For more information about the work we have carried out with Notting Hill please visit our website at www.infordataconsulting.com or call us on +44(0)203 086 8276