At a recent talk by Professor Graham Braithwaite of Cranfield University on the role and work of the UK Air Accidents Investigation Branch (AAIB) and the approaches taken to investigating an accident, it made me think about whether similar approaches may work for data.
Do you think there is a place for the Data Accident Investigation Board?
The process for the investigation of air accidents is specified in Annex 13 of the Convention on International Civil Aviation. The objective of this process is stated as:
The sole objective of the investigation of an accident or incident shall be the prevention of accidents and incidents. It is not the purpose of this activity to apportion blame or liability.
As a result of this objective, this means that people are less likely to lie or hide their part in any accident allowing investigators to better understand the root causes and contributory factors. This means that outcomes are system based and should identify why the safety system failed and are not individually based by stating who may have been to blame.
This has a two fold outcome:
- If system failures are identified, then this allows changes to be made to improve the overall safety of the system
- It avoids what may happen if an individual were to be blamed, namely that the accident could be considered as the failing of a single individual which may result in no changes to safety systems.
In Jim’s post about “The Poor Data Quality Jar” he, and the people who have commented, generally take a light hearted approach to the subject including suggesting public humiliation or electric shocks for staff who are discovered creating data errors. This may be fun for those not involved, and distinctly uncomfortable for those who are caught, but is likely improve data quality approaches only marginally. As people work within the context of an organisation and will be affected by its rules, procedures, standards, culture and behaviours, then it is unlikely that a single individual will be truly to blame.
A “No Blame” approach to the investigation of “Data Accidents” should focus on finding, and correcting, the root causes of data problems.
- Would this approach result in more Data Accidents being declared?
- Would this approach provide a more effective means for removing the root causes of data problems?
- Would this improve overall data quality?