© Crossrail LimitedI think all people who are involved in data in any way would like to be in a position where they were no data defects and data could be relied upon 100%. Is this achievable?

I regularly use a comparison between approaches to health and safety/ work practices and the approaches to data. A recent achievement on a major project I am involved with provides another example of how we should perhaps be approaching data.

For some time, one of the projects that I have been working on is Crossrail, currently Europe’s largest construction project. The project has a very strong focus on health and safety, with an initiative entitled “Target Zero: A state of mind” which aims to avoid all safety related incidents. This is achieved both through pro-active reminders of the importance of health and safety and a strong reactive approach where any reported occurrences are investigated and the learning points disseminated for all to be aware of. In short, there is a far higher focus on health and safety than may be the case for similar projects.

One of the constituent projects that makes up the overall Crossrail programme recently clocked up 1 million man hours worked without a single accident or dangerous occurrence. For anyone who has familiarity with construction projects, they will recognise that this is a significant achievement and represents real progress in improved approaches to health and safety.

Historically, for large construction projects it was expected that a certain number of fatalities and injuries was regrettable but ‘normal’. Staff tended to treat work as if it was a military campaign where heroic exploits are expected and rewarded. However, the impact on others of such approaches can be adverse and the risk to the objectives of an organisation high.

Examples of historic accident rates are:

  • Gotthard Tunnel, Switzerland (1871-1881) at least 200 fatalities
  • Forth rail bridge, Scotland (1890) 73 fatalities
  • Severn Bridge, UK (1966) 3 fatalities
  • Thames Barrier, UK (1980-82) 2 fatalities, 152 major injuries, 5,000 accidents
  • Seikan Tunnel, Japan (1988) 34 fatalities
  • Channel Tunnel, UK/France (1994) 10 fatalities

Whilst introducing such a high focus on improving safety clearly has a cost, these costs will be lower than the direct and indirect costs associated with any accident. Arguably, adopting improved approaches to health and safety also involves improved activity planning, improved risk management and greater staff training and awareness which can also help to improve the quality and timeliness of the project delivery as a whole.

In summary, leading organisations in Health and Safety believe that all accidents and dangerous occurrences are preventable and actively strive to reinforce this message by pro-active safety initiatives and by investigating any dangerous occurrence.

So where is the world of data?

Arguably, many organisations approaches to data management are comparable to the approaches to health and safety 50 or more years ago:

  • Data errors are seen as regrettable but ‘normal’
  • Effort is focused on productivity rather than quality (think of many call centres!)
  • Short cuts are seen as acceptable
  • Costs are higher than expected – both the direct costs of data management and the indirect impacts on business processes and analytical activities
  • Data quality is somebody else’s problem

So, can approaches to data quality improve in a similar way to those of health and safety? Of course they can, but it will require organisations to change their culture so all data errors are seen as unacceptable, so that everyone recognise they have a responsibility for providing good quality data. This change is likely to take time to achieve, but it is achievable!

What actions are you going to put in place to change attitudes to data?

Please note, this post represents the opinions of the author and not Crossrail policy

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