What do data-driven companies have in common?

What do data-driven companies have in common? Research reveals five key trends. Recent IDC research, sponsored by Tableau, found that 83% of CEOs want a data-driven organization, but only 33% of executives are comfortable questioning business KPIs and metrics, revealing disparities between what executives 'want' and 'have'. Nearly all executives say they want their organization to be more data-driven, but discount cultural investments that help bring that change to reality.

As more organizations see and understand their data, and some grow data use at enviable rates, Tableau and IDC felt it was useful to explore behaviors, characteristics, and key trends that set data-leading companies - ones with a strong Data Culture - apart. We conducted a survey of over 1,100 business leaders across 10 countries in technical and non-technical roles, investigating the presence and depth of five trends that drive a successful Data Culture and help shift the position of organizations to become data-leading.

In our research, we found that investing in data-driven behaviors often translates into measurable, positive impact and business performance with:

Five trends that define a strong enterprise Data Culture
The attributes of a leading Data Culture range from visible characteristics like training methods, tools available and used, and business processes to subtle, hard-to-quantify characteristics such as empathy, identity, and confidence in data skills. The five common trends among data-driven organizations are:
1. Talent: Setting expectations for a wide spectrum of data-related activities
2. Trust: Valuing trust and accountability in governance decisions
3. Mindset: Encouraging data exploration and curiosity for everyone
4. Sharing: Breaking down silos by emphasizing collaboration
5. Commitment: Realizing value from data, not just using it

Companies and Tableau customers such as Swiss Life, Bank Mandiri, Jones Lang LaSalle (JLL), and JPMorgan Chase & Co (JPMC) have evolved their behaviors and mindsets around data use to establish some of these defining characteristics, becoming data-leading. Let’s take a closer look at each trend and some of their transformational stories.

Trend #1: Talent
This trend relates to the ability of individuals to analyze, interpret, and communicate with data, and then use it to argue a point or make smarter decisions—a set of competencies also known as data literacy. The IDC research revealed that enterprises become more data-driven when they prioritize data literacy by hiring data-literate people and upskilling employees.
“Data-leading companies were 3x more likely than data-aware organizations to require new hires to know how to persuasively present data.”

Swiss Life, the 110-year-old insurance and asset management leader, experienced this firsthand. For years, the company struggled with expensive and complex data architecture—too many tools, data sources, and more. This caused extra work for IT and unreliable results. Something had to change. This led them to re-evaluate their approach to decision-making, starting with data skills. They developed cross-functional analytics training for hundreds of employees that built up their confidence and competence with using data. This investment in data skills led to a stronger, long-lasting Data Culture.

Trend #2: Trust
Critical to democratizing data literacy, governed access, trust, and accountability in analytics are foundational to a thriving Data Culture. Having both trust from leadership and transparent access to governed, accurate data, results in greater employee responsibility and accountability for the information used and needed.
With data-leading organizations in North America, 70% more respondents said that stakeholders made it easy to access the data they need to do their jobs than in data-aware organizations.

Bank Mandiri, the largest financial institution in Indonesia, embedded data-driven decision making at all levels with trusted self-serve analytics. Previously, analytics requests took weeks to complete, were shared in a difficult-to-consume format, and depended on the Enterprise Data Management (EDM) Group to handle. These challenges were at odds with the bank’s commitment to provide the best, most effective customer solutions. This prompted them to increase efficiency of processes and launch a new data governance unit. “Good governance is substantial to a data-driven organization,” says Billie Setiawan, senior vice president of the Enterprise Data Management (EDM) group. “It’s not about providing everyone with access to all data, but ensuring that people can access the data which is relevant to their responsibilities. We call it a ‘need-to-know basis.’”

Trend #3: Mindset
To create a strong Data Culture, our research found that it’s critical to transform behaviors and mindsets around data. A Data Culture encourages experimentation, innovation, exploration—and even failure—with data. Part of this is intentional prioritization and commitment from executives and individuals to bring data to meetings, use analytics platforms to ask questions, and to rely on data instead of assumptions or intuition when making decisions.
On average, 73.5% of respondents in data-leading companies across all geographies said their decision making was always data-driven.

Building management giant Jones Lang LaSalle (JLL) saw the strategic balancing act needed to create an effective training plan that evolved behaviors, mindsets, and skills around data. Make it too basic and you lose momentum; make it too difficult and risk alienating less data-literate employees and exacerbating the skills gap. They recognized data training is not just about technical skills; it’s how you think about data and develop a narrative around it. They designed trainings centered on how to ask questions and have conversations with data. From that flowed the analytics skills everyone felt comfortable using.

Trend #4: Sharing
Our research revealed that at the heart of strong Data Cultures is collaboration and community around data. Data-leading organizations eliminate silos by creating environments where people share and support one another to achieve common goals. This often shows up as internal communities, internal and external analytics events, office hours, and other community-building activities.
Organizations with strong Data Cultures made investments in 5+ community building activities—while organizations that hadn’t yet transformed their Data Cultures were supporting two or fewer.

JLL began its Data Culture journey with the support of executive leadership who prioritized data-driven decision-making in the entire workforce. They focused on developing a strong sense of community around data through analytics trainings, community-building programs, and continuously highlighting the “data champions” that work at all business levels. By celebrating analytics achievements and promoting “positive deviance,” JLL recognizes data use and asks that employees encourage peers to model similar behaviors, deepening the roots of their Data Culture, now and in the future.

Trend #5: Commitment
Most organizations want to be data-driven but the IDC research highlighted that the organizations who succeed have leaders that value and show commitment to data use. This shows up in investments across people, processes, and technology to deploy and adopt data and analytics at scale. It is also absolutely essential to have C-suite members and line-of-business who understand data’s importance and use it for themselves daily. In fact, “executives in data-leading companies are eight times more likely to actively use data in their work compared with data-aware companies.”
On average, across geographies, there was a 46.2% difference between data-leading and data-aware organizations with respect to treating data as an asset and recognizing the value it delivered.

JPMorgan Chase & Co. (JPMC), a leading global financial services firm, grew through mergers and acquisitions. Along that journey, data grew vital to business operations and strategy—helping enhance the customer experience, reducing risk, and informing strategy. But operating in a highly-regulated environment, IT had to establish data governance balanced with data access and compliance. Creating a Center of Excellence involving IT and other business leaders as enablers, JPMC transitioned from IT-owned to business-owned self-service data analytics. This helped remove any data barriers and enabled them to stay on pace with or ahead of industry changes optimizing success across marketing, branch operations, customer service, sales, risk, and compliance.

It’s a marathon, not a sprint, to become data-driven
Taking incremental steps can help organizations regardless of type, size, and industry grow their Data Culture, shifting from being data-aware to data-leading. Like marathon preparation, it requires planning, practice, reflection, and achieving small wins to work toward goals such as competitive advantage, customer satisfaction, and improved productivity to help your business thrive in the “new normal.”

Review our research with IDC and discover how Data Culture will fuel business value. To learn how to build one review the Tableau Data Culture Playbook. It includes valuable insights from customers such as Dubai Airports, Red Hat, and others who succeed at decision-making, data discovery, and other areas.

Consult this sample dashboard featuring IDC data to see where your organization ranks against others in being data-driven.

Ashley Howard Neville is Senior Evangelist at Tableau.