Five Keys To Building a Data Culture
- By Paul Mah
- September 23, 2020
Harnessing data can be the difference between staying ahead, or falling behind, notes Katerina Hanna, the APAC director for customer success at Tableau Software. Speaking in one of the sessions at the recently concluded Tableau Live, she noted that it is not the technology that helps companies succeed with data, but the culture.
Why culture matters
So why does culture matter? Hanna cited a recent IDC report that underscored how data alone is no guarantee for success. Based on a survey of 1,100 organizations and interviews conducted at all levels, it established that data-driven progress is inextricably tied to the culture of the organization.
“You can have a lot of data, you can have the best leading-edge technology, you can even have the best analysts in the world. But that is not enough to guarantee success. More and more organizations around the world are recognizing that turning data into information, knowledge, insights, and actions requires a data culture,” she said.
To be clear, changing culture is difficult. It requires a strong vision, determination, and resilience, observed Hanna. This entails embedding data into the very fabric of the organization, an aspiration is to get everybody to see the value in data, proper training so users have the confidence to use data, and continually inspiring everyone to leverage data for better decision making, she said.
Culture is defined by people
So how can organizations establish a data culture? Because a data culture is essentially the collective behaviors and beliefs of people who value, practice and encourage the use of data, a good strategy must involve every individual within the organization.
For a start, this means that organizations should recognize and value data skills as part of how they recruit, develop, and retain talent. Specifically, this boils down to a combination of hiring people with advanced data skills, developing them within the existing workforce, and engaging in data culture initiatives across all levels of the organization.
“People are at the core of any data culture. They need to practice using data every day, all of which then comes together in better decision making. Strong data culture depends on trust. Leaders in data culture believe that all their people are smart and capable. They empower people to ask questions, and they embrace critical thinking,” said Hanna.
Five keys for a data culture
In her presentation, Hanna outlined five keys to building a data culture embraced by Tableau.
- Trust: Leaders need to embrace critical thinking and trust their people to produce results.
- Talent: Support and enable data-capable employees through their entire lifecycle recruitment.
- Commitment: Incentivize and inspire existing employees to upskill and incorporate the use of data.
- Sharing: Share and spread success and use cases through the organization as part of the data-driven journey.
- Mindset: Nurture a new mindset across the organization that prioritizes insights and makes decisions based on facts, rather than intuition.
To illustrate some of the pointers in action, Hanna drew from anecdotes. For instance, an unnamed organization in China created a one-on-one training camp that accelerated data culture. By empowering and putting people at the front of their data-centric plans, the organization improved its analytics efficiency by 11% and simultaneously saved $1 million by not having to engage third-party designers and consultants.
On its part, Indonesia's largest financial institution, PT Bank Mandiri, teamed up with Tableau to develop more than 600 visualizations and dashboards to significantly improve their efficiency. One example given was manual data requests that took headquarters two weeks to process on average. This was cut down to just two days.
As transformation accelerates around the world, and macroeconomic and geopolitical factors force changes, the onus is on business leaders to bring about the necessary change to help their organizations thrive. There is no time like today for this change, summed up Hanna.
Photo credit: iStockphoto/imtmphoto
Paul Mah
Paul Mah is the editor of DSAITrends, where he report on the latest developments in data science and AI. A former system administrator, programmer, and IT lecturer, he enjoys writing both code and prose.