Talk To The Hand, Because The Business Isn't Listening

If there is one thing guaranteed to make employees glaze over, it is data. Every business strives for clean, accurate and trusted data, yet so many never achieve it. Why? Because of attitude. This whitepaper explores the soft side of data quality management: the cultural changes required inside an organisation before any tool or technology can deliver lasting results.

Attitude: The Biggest Barrier to Better Data

Most businesses carry a long history of engrained methods, such as the silo approach, where one department handles data entry and another manages the next stage. These processes are rarely questioned. The paper argues that success comes from challenging the process, asking why, and empowering change agents to alter the attitudes of those around them. By changing beliefs, behaviour changes too, bringing better results, less time wastage, greater efficiency and greater fulfilment in the job role.

Blame Culture and the Cost of Fixing Data Late

When data is poor, departments often pass the blame to someone else, leading to re-working and scrapping of defective data. The whitepaper retells the story of Everybody, Somebody, Anybody and Nobody, where an important job everyone could do was ignored until the last moment. It also cites the Quality Assurance Institute: an error detected during the project testing phase can cost up to one hundred times more to correct than the same error found during the design phase. Like a relay race, a dropped baton at any handover slows the entire process, so final inspection is sub-optimal and too late. Building information on bad data is like trying to build a house on sand.

Putting a S.P.I.N. on the Process

To attack data quality at its root cause, the paper recommends a S.P.I.N. approach:

• Situation: what is the real state of your data and data management process?
• Problems: what problems is poor data quality causing, and how often?
• Implications: what does this mean for you and your productivity?
• Needs/Payoff: what value would improved data quality deliver?

A practical planning list follows: secure higher-level management support, appoint accountable data stewards, fix the root causes of poor data capture, look at the downstream pain chain, define what good data looks like, measure performance with KPIs, and improve communication with a common lexicon of terms.

This whitepaper is for anyone frustrated that the business is not listening about data: data owners, managers and change agents who want to move their organisation from apathy and denial to active data management, reducing wasted time, financial resources and reputational risk.