The Data Zoo (Part 4 of 5) – High compliance personalities

This is Part 4 of a 5 part blog post. If you have not read them yet, see:

• Part 1 – The Shape of the Zoo
• Part 2 – Low compliance personalities
• Part 3 – Medium compliance personalities

There are three species in the high compliance area of the Data Zoo: the Jobsworth, the Useful Person and the Data Evangelist.

The Jobsworth

The Jobsworth is a role we will all be familiar with from dealings in our everyday lives with officialdom – they are the people who say “Computer says no!”, “But the rules say…”, “That’s not in my role description” etc. Similarly, in the data world, the Jobsworth will typically be a low productivity individual who uses any ambiguity or lack of clarity in data, process or system standards as a reason not to do anything.

Positives

The Jobsworth will not enter any data unless it conforms to the rules/meets all process requirements/, so they will be less likely to introduce poor data than others. Their pedantic approach means that they can be a good way to test if there is any ambiguity in a new process or lack of clarity in data standards, you then have a challenge of correcting these issues in a way that they are happy with!

Negatives

The Jobsworth’s overly rigorous approach and inflexibility will mean that they can be frustrating and difficult people to work with. They typically have low productivity rates and will put more effort into moaning about perceived shortcomings rather than doing their jobs.

Impact on others

They can be very frustrating to work with for managers and colleagues. Managers will find their constant refusal to address any ambiguities and uncertainties in a positive way very frustrating. Colleagues and internal customers will also find the Jobsworth very frustrating to work with and may then choose to do the work themselves or go elsewhere for support.

The Useful Person

If you are in a high performing organisation, it is likely that you will have a number of Useful Persons in your team. These are the staff who work to the standards, are enthusiastic and typically will be very productive. They will be comfortable working with written or verbal instructions to address any identified process issues. They will tend to be happy with their role and may not see it as part of their role to encourage others to behave differently (see the Data Evangelist).

Positives

They are positive and useful team members who have a high work ethic and high productivity. They work to standards and are also happy to work to managers instructions where there is less documented clarity.

Negatives

Overall they are good to have around and exhibit good behaviours towards data and processes, but may not engage with others whose approach is less good.

Impact on others

As mentioned before, these are useful people to have in any team and can have a significant effect on the productivity and quality of the work of a team.

The Data Evangelist

The Data Evangelist is someone who has “got” the importance of data to an organisation. They may have had a light bulb moment/revelation where this suddenly became clear. They have boundless energy and will be actively involved in trying to convert others in the organisation to improve their approaches to using and providing data.

Positives

A positive force for change, they will tend to be outgoing people who love to preach about the value of good data practices. They will use their energy and enthusiasm to try to improve the behaviours and approaches of others.

Negatives

As the Data Evangelist can be so busy converting colleagues and stakeholders to better data approaches, their productivity may perhaps not be as high as others, for example the Useful Person.

Impact on others

The Data Evangelist can be a positive force for change and, when given the right backing, can improve people’s approaches to data and processes. Most organisations should have at least one or two Data Evangelists to actively improve data approaches, backed up by some of the other data personalities to ensure overall productivity is high.

The final post in the series will consider how these data personalities can tend to interact and what you can do to encourage the right data personalities.