A Guide On How To Build A Data-Driven Organization

Most organizations, especially large enterprises, are investing resources in collecting, storing, securing, and analyzing their data. In fact, a recent Bain survey reports that more than two-thirds of the 300-plus executives they questioned say their company invests heavily in data analytics, but more than half also expect transformational returns on their investments.

Why such serious focus on data? McKinsey Global Institute says that data-driven organizations are 23 times more likely to acquire customers, 6 times as likely to retain customers, and 19 times as likely to be profitable. With these success benchmarks and the promise of discovering business-altering insights in reach, companies like Charles Schwab, Jaguar Land Rover, Lenovo, and more are using data to find game-changing insights. These insights are generating positive outcomes like improved decision-making, enhanced business operations, and stronger customer engagement.

Becoming a “data-driven” business doesn’t always come easily and there will likely be some hurdles along the way. That’s because data and technology alone won’t make an organization more successful. It requires a shift in mindset and efforts from leadership and employees. Orchestrating change, and doing it efficiently, requires executive advocacy, agility, data proficiency, and a broad, active community to ensure the mission, goals, and needs of the entire organization are met—in process and technology.

Once you’ve reviewed these critical questions, you’ll be itching to embark on a path forward towards creating a Data Culture. By doing so, you’ll tackle some vexing business problems—like customer acquisition and retention, focused and effective marketing, product innovation and development, quality control and assurance, and more. You'll also gain a competitive edge for near and long-term success.

Jaguar Land Rover shifted to data-driven business conversations with its C-level executives by adopting one analytics solution and insisting it power all of their board reporting. In less than a year, three-fourths of their business groups power and maintain their reports in one place and Jaguar Land Rover has more than doubled use of its data visualization tool as it democratizes analytics across all departments.

For anyone to skillfully analyze data in their job, they must be data-proficient. It’s not just having the right skills, but also the inclination towards making data-driven decisions instead of going by instinct or gut feeling alone. Organizations with a successful Data Culture both hire people with the right skills and aptitude to make data-driven decisions, and help employees develop their analytics skills through trainings, show-and-tell sessions, and other activities.

A company that regularly encourages and supports people who challenge the status quo will see less complacency. Encouraging curiosity and discovery with data becomes the daily norm. Self-service analytics also play an important part in empowerment. A company that allows for self-service analytics will eventually see data working its way into all conversations as they start with and evolve based on questions, investigation, and “aha moments”.

Charles Schwab’s analytics usage skyrocketed when they shifted the way that they supported employees’ experience with data, from data access to data analysis. They went from 6,000 users to 16,000 (nearly 90% of the company) in 18 months because they invested in training and supporting their people to be successful. "We developed an approach that supports both the experienced analysts as well as the novice business users, advancing our data-driven culture,” said Andrew Salesky, Global Data Officer.

Data silos are prevalent across most organizations. With a clear, agile data-management framework anchoring your deployment, however, you’ll have clean, trusted, ready-to-use data that the right people can access.

What are the ingredients to success? Appropriately balancing control and freedom with users through a baseline framework that generates a stable, secure, trusted analytics environment. Making sure your organization develops iterative and repeatable processes will also maximize success before, during, and after deployment. This isn’t a one-and-done process, though. Ongoing monitoring, evaluation, and maintenance, led by IT, is equally important to verify that analytics performance supports business needs through change and maturation; and the environment remains secure for everyone. The impact is usually time and cost-savings, improved business processes, and stronger customer or partner relationships—all of which enhance a brand’s reputation and bottom-line.

JPMC moved from IT-owned to business-owned self-service analytics to keep up with rapid industry changes and better optimize for business success. In a highly-regulated environment, IT needed to first establish enterprise governance that balanced data access and compliance. Championed by its community of data enthusiasts (also known as the Center of Excellence (CoE)) and with IT as enablers, JPMC adopted Tableau as its enterprise data analytics solution. This has driven stronger data accuracy with nearly 30,000 users in branches and 500-plus business teams who make better, more strategic decisions that improve the bank’s health.

Community creates a network of people within your company who use data to share and collaborate. A strong community will eventually thrive if leaders help carve out the time, space, and resources for everyone to advance their data skills. In turn, this will grow analytics adoption and learnings as more people realize the power of insights discovered individually or collectively. Plus, your company will reduce data silos, streamline efforts, and better align business metrics.

Having a community leader (or a group of leaders) is essential; someone who documents enablement resources, connects users together, and evangelizes analytics across the organization, putting data at the center of their conversations. Your internal data communities, as encouraged by the community leader(s), can also flourish by connecting with external communities who share similar passions for data.

Cargill operated in a traditional BI model, but shifted to self-service, making everyone a “community enabler”—curious and hands-on with data who invite others to join them. Looking to existing data communities for inspiration, they developed their own internal community supported by IT, which organized Data Viz challenges and other activities to boost skills. Ultimately, Cargill’s analytics community quadrupled in size and thousands of employees have uncovered millions of dollars in opportunity.

Do you still question if now is the time to become data-driven or if you’re in a suitable place to cultivate a Data Culture? Just remember you’re not alone undertaking the challenge. Other businesses share your struggles or aspirations and succeeded with appropriate leadership support and attention, by staying flexible to changing needs, investing in the right technology solutions paired with defined processes, and developing a strong focus on the people that define the organization’s culture.

“Leading organizations in every industry are wielding data and analytics as competitive weapons, operational accelerants and innovation catalysts,” explains Douglas Laney, VP analyst at Gartner. They’ve thought about their business goals, objectives, and challenges and how data management can help address them. Their capabilities and results are also a testament to what’s possible when data and analytics become the focal point of an organization’s strategy, processes, and investments.

Read more about the elements of strong Data Cultures and learn how to build your own with the step-by-step guide, Tableau Blueprint.