How to grow a data quality culture that takes action

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A data quality culture is one of those elusive outcomes that can so often make or break your long-term data quality vision.

Whilst many project leaders are capable of fostering collaboration and communication in their immediate team, some leaders find it hard to build on this to grow greater data quality awareness and action amongst the wider organisation.

In this article I wanted to share some tips that I’ve found useful for growing a data quality culture that promotes both awareness and action.

Tip #1: Start with a leader (hint: they come in different guises)

You probably know that if you want culture change then you need to get the right sponsors on board. However, one thing I’ve noticed is that within every organisation there are formal and informal hierarchies. You will find leaders who lack any formal title, but still command the respect of their peers.

These "informal leaders" are in many ways more critical than formal leaders because they can undermine any efforts you make at culture change if they're not onside. They have the total support of fellow workers.

Do some informal leadership discovery and find out who your workers respect and follow the most, Then try to get them onside.

As an evangelist they will become critical to your success.

Tip #2: Create a culture of experimentation and learning

One of the recurring themes I see in organisations that are embracing data quality is the ability to try new novel approaches to improving and managing data quality. But in many organisations, there is often a belief that if an idea fails, then someone should be punished.

Data quality is not a fixed science; there are no single root causes to any data quality error. It’s vital that you allow your staff free reign to try and innovate new ideas and solutions for improving data quality.

Make the data quality process a stimulating and learning environment and you will have no shortage of willing advocates who are keen to develop new skills whilst continuously taking action.

Tip # 3: Make the impact of data quality personal

Let’s face it, data quality is not the most exciting topic most workers will be asked to get involved with, so you need to make it personal to their working lives. Show how it impacts their performance, their customers or their department.

In the past I’ve demonstrated how poor data quality has resulted in reduced targets in call centres and field-force visits, which impacted worker bonus schemes, etc.

People will never change anything (let alone an entire culture) unless they reach a tipping point where they recognise it is personally damaging to continue on their previous path.

This extends not just to workers at the coalface of the organization, but senior management too. Get them to experience the realities of poor data quality. Show them the customer complaints that poor data quality has created. Get them to listen to the audio of frustrated customers. Make the problem real to all levels of the organisation.

Tip #4: Assemble data quality task forces that are multi-talented

I often see data quality projects that are almost entirely staffed by technical resources. When the project is completed, these staff move on to new initiatives so no real culture change is developed.

A smarter approach is to think of your team as a task force and draw on a range of different disciplines to make the outcome more relevant across the workforce, not just your immediate technical staff.

For example, in previous initiatives I have tried to invite software developers, data entry staff, "gold users," interns, senior managers and even customers! Try to create a kind of "Kelly's Heroes" team design; use whatever resources are available and make sure they can take the message back to their peers.

Tip #5: Reward those who take action

A recurring theme in successful data quality initiatives is the importance of sharing the success of your data quality improvement.

I’ve reported in the past on teams that are incentivised through bonus schemes and other performance measures, but you can adopt less expensive approaches such as annual awards or other recognitions.

You can also share your success by giving staff access to more training and skills development at industry events. When we interview successful project leaders on Data Quality Pro, one of the first things they want to do is share the story within their organisation so that everyone can feel part of the success.

For many professionals, being able to share the positive experience they’ve been on is simply reward enough. Try to see beyond the restrictions of your PR and communications department in preventing these opportunities. Embrace them, be open and encourage these opportunities as they can be a real motivator for staff.

Summary

Nurturing a data quality culture takes time, patience and planning, but is critical to long-term data quality management. What techniques have you found useful for growing a data quality culture?

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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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