How to Solve Data Quality Problems at the Source

Handelsbanken UK Head of Data Quality Mark Wilson offers his advice on getting to the root of data quality problems with frontline staff

Data quality has a profound impact on the daily work of frontline staff. And when frontline staff identify data quality problems they expect them to be dealt with promptly. Failure to do so can seriously drain morale.

In this week’s episode of the Business of Data Podcast, Mark Wilson, Head of Data Quality UK at Handelsbanken argues that fighting back against apathy is essential to drive business improvements using data and analytics.

For Wilson to create a grass-roots view of data governance at Handelsbanken he focused on working with frontline staff to improve data quality as well as data governance structures.

“We’re working with the front-end staff on how we collaborate with them more in their everyday work with customers,” Wilson says. “It’s really about being in that real-life world, away from that ‘ivory tower head office’ mentality.”

Ascending from the Ivory Tower

Understanding the realities of how businesses generate and use data and analytics on the ground is critical to fixing problems and improving results. And there are few better ways to learn than by getting your hands dirty.

For this reason, Wilson recommends that head office staff spend time working in the field to discover how frontline staff are using data and analytics, and what their challenges are.  

“They'll tell you the problems that really need solving and what’s causing the problems,” Wilson says. “Whereas if you sit too far back in the business, you just see the results.”

This distance can sometimes lead to head office staff misdiagnosing problems. Problems like blaming careless staff when, in fact, the problems may lie in processes and technology.

“A lot of our early wins, [came from] speaking to our branches,” Wilson recalls. “You're doing a disservice to not flush this out and talk about these things.”

He continues:” And as always, by enabling communication about them, you could find there is already something in place that a small, slight shift on a project path to factor something in might solve things that were never anticipated in the first place.”

Fighting Apathy in the Workforce

Data problems when reported should be resolved promptly. Failure to do so can seriously drain morale, and this effect can spread quickly throughout teams.

“I think this is something we consciously have to think about. What is the message we're sending when we don't respond?” Wilson remarks. “I think that [responding] is important for morale, for people's wellbeing or belief that they can make a change. And for the company to show that it’s listening.”

Creating structure and feedback loops for staff is therefore essential to providing agency to frontline staff – and showing that the company cares about their input.

“We should [have] data quality issue management processes in place where any employee can go into a place and record a data quality problem,” Wilson says. “You should be reviewing that, digging into the root cause, doing the evaluation, and perhaps then identifying who in the business has the responsibility to take the corrective action.”

He continues: “We should have a data governance committee in place who are keeping track of these open data quality issues. And that should be part of the management structure of an organization so you've got an escalation point.”

Ultimately, data and analytics teams are there to help companies meet their goals. Therefore, fostering trust amongst staff at all levels is essential.

“We're here to help the company grow and be better through better data management,” Wilson concludes. “So we need to word things in a way that says, ‘let us know if you've got a problem. This is who you contact. These are the processes in place to help you.’”

Key Findings

Leave the ‘ivory tower’. By working with the frontline staff you can gain a true understanding of how data is generated and what the problems are.

Create a structure for reporting issues. A formal structure not only helps to solve problems, it also shows staff that the business is listening.

Data and analytics should help businesses grow. Building trust among staff is essential – and it is an ongoing project.