Mr. Daragh O'Brien:

As somebody who advises on these types of projects for a living, it would be inappropriate for me to give a quote today. I do not fully understand the requirements at this point. However, what I can speak of in general terms is the root cause of cost overruns in data management projects. The average cost to an organisation from poor quality information is between 10% and 30% of turnover. This figure has been tested and communicated for the 20 years I have been doing this for a living. My good friend, Dr. Tom Redmond, one of the world's leading experts in the field, puts the figure at 30% of turnover. The root cause of the poor quality of information can be hidden information factories, people reworking data and people using data for different purposes etc. A key root cause is a lack of clear and common definition and understanding of where data is different or means different things in different areas and contexts. When people run a report or do an analysis, for example, it does not work and they must redo it.

I worked on a project in an EU institution in 2013 where the entire motivating force for the data governance programme was that the president of this organisation had been given three different figures for the same fact. It concerned him that his smart people could not give him a consistent figure. The root cause of systems like PPARS going horrendously over-budget was the assumption being made about the data and its meaning and structure. When the HSE project teams went to implement PPARS, there was an assumption that there was a contract for nurses but when they drilled into it, there were 300 or 400 contracts for nurses, depending on the structures that were put in place. That is why projects overrun. It is ultimately about assumptions being made about data because of a lack of clarity of governance and communication about what the data means. Data has wonderfully fluid powers as an asset in an organisation but one is it can mean different things to different people, depending on context. In order to tame these issues and avoid problems in any project, organisations must move away from thinking of these as a technology project where there is a business requirement stated before somebody does a bit of programming and it works. Professor Richard Mason of the University of Amsterdam developed a model in the 1990s looking at why between 70% and 80% of customer relationship management, CRM, programmes in private sector organisations failed.

CRM systems had a horrendous failure rate in the 1990s and early 2000s. The root cause was that it was being treated as a business strategy with a technology component. No one stopped to look at the definition, meaning and use of information. When organisations realised that and started doing that bit, failure rates dropped, success rates improved and end-user and customer satisfaction with the outputs improved. Going back to Mr. Kelleher's point about trust, the ability for people to trust what was happening with the data improved.