How to nurture a data steward culture


In my last post I discussed one of the important traits that I feel truly great data stewards possess – the ability to effect change. Today I want to talk about how you actually identify, train and nurture everyday workers into the role of data stewards.

Most organisations don’t have a career structure for data stewards and compared to other data roles it’s often rare to see data steward job titles being posted by recruiters. To procure a team of data stewards it’s so important to develop a system in your organisation that enables in-house workers to transition into the role of steward.

There are some reasons why this home-grown technique is vitally important:

  • Management will be investing in their own staff, demonstrating that they care about the culture of data and the quality of information that workers have to live with every day.

  • In-house workers know their "patch of data" intimately and can therefore make smart decisions when it comes to identifying areas of improvement not just in the data but in partner processes, customer support, in-house systems and so on.

  • You can’t throw a ton of bodies at a data quality problem and expect it to go away. I personally prefer the home-grown, transitional-type improvements because it gives the organisation time to accept the changes required. Nurturing home-grown stewards aligns perfectly with this approach.

To make this post practical, I wanted to list the following steps I took in one organisation to help build a team of data stewards who then went on to great things, supporting the entire organisation and eventually other organisations in their career.

Step 1: Identify data workers who want to improve their own careers

In my situation, we had no outside funding so I had to nurture stewards internally. I first looked at the more senior technical staff, but instead opted for low-skilled data entry workers who worked part-time shifts. My thinking was that these folks were keener to learn and develop because a lot of their time was spent on quite mundane data-related tasks.

Step 2: Assign a point of ownership for data

The data entry staff largely worked on their own patch of data, so we told each person they would become the expert on census data, the expert on retail data, the expert on road network data, etc.

This lifted their morale because now they were doing more than just entering data and fixing mistakes - they had a real title and focus to their work.

Step 3: Provide simple stewardship training and processes

I taught the fledgling stewards how to document an information chain, perform validations at different points across the chain and assess the quality of data using techniques they could easily grasp. The focus was really around providing basic techniques and then getting the staff to develop new and improved processes. I emphasised that my method wasn’t necessarily the best way, and quickly the team started to develop often simpler and more effective means of validation and monitoring.

Step 4: Reward and recognise the keenest members

Because we had a large group of data entry staff, we started to pick out those who were most keen to learn. Many people started training in their lunch breaks and learning how to code so they could become better stewards – so these were given supervisory and trainer type positions.

Step 5: Extend the reach of the team

Now armed with solid stewardship skills, key members of the team started to branch out of our unit and provide services to the rest of the organisation. A real culture of data awareness and quality management began to develop as they formed a network of influence.

Step 6: Add fuel to the flame

Inevitably, some of the stewards moved on to bigger organisations. This was always a rewarding event because it meant that the process was working. It’s perfectly natural for some stewards to want greater challenges often in larger organisations or more complex data landscapes. You should always nurture junior stewards so that the cycle continues.

Perhaps you have an alternative approach or have been through the process yourself. Why not share your experiences below?


About Author

Dylan Jones

Founder, Data Quality Pro and Data Migration Pro

Dylan Jones is the founder of Data Quality Pro and Data Migration Pro, popular online communities that provide a range of practical resources and support to their respective professions. Dylan has an extensive information management background and is a prolific publisher of expert articles and tutorials on all manner of data related initiatives.

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