What It Takes to Achieve a Data-Driven Culture

It’s Been Said that Culture Eats Strategy for Lunch

When it comes to big data, culture can also swallow up huge capital outlays, high-powered infrastructure and the smartest teams of data scientists.

But the upside is that a data-driven culture can mean the difference between the full payoff of your big data analytics business case and returns that are just so-so.

Why is that? Consider the intersection of these powerful forces. Culture is about how organizations evaluate performance, allocate resources and encourage people to act. And big data potentially transforms all of those areas. That’s why cultures built on big data and advanced analytics are increasingly synonymous with high-performance organizations.

After all, everyone has loads of data. But the winners are those who have the expertise, motivation and capacity to use it effectively and to drive bottom-line results across the whole enterprise. At such firms, data is not just an asset, but rather a way of life.

Achieving a Data Driven Culture is About Being Ready and Willing to Change

• Training people and incenting teams to uncover new insights – from changes in customer behaviors, to emerging supply chain threats, to subtle shifts in operational outputs.
• Being nimble and bold enough to act on those insights – often in real-time and outside the constraints of traditional business review cycles or strictly hierarchical authority structures.
• Moving away from risky, “gut-feel” management styles to data-driven and analytics-enabled models.

The Bottom Line:

Big data equates to big change for most organizations. Just how big depends on where your organization is today.

Hallmarks of Data-driven Cultures

Commitment

Data-driven cultures start with widespread commitment. Data-driven decision making must become the standard M.O. The expectation is that big data analytics is part of everyone’s job.

Top-down Leadership and Bottom-up Engagement

The strongest data-driven cultures are shaped and energized from both the top down and the bottom up. Senior management clearly and visibly signals the importance of big data to improving business performance through funding decisions and by defining and promoting new metrics for evaluating the business. Meanwhile, end-users – front-line managers, business analysts and others – use data to do their jobs everyday. And they have the tools, training and incentives they need to do so.

New Roles, New Titles

The rise of Chief Data Officers and/or Chief Analytics Officers is evidence that more companies view data as a crucial asset. But such titles do not by themselves change cultures. Organizational structures must be aligned under senior leadership to unleash full transformational potential of big data across the business.

Organized, Accessible and High-quality Data

A strong technology foundation entails multiple components, starting with an infrastructure capable of capturing, centralizing and storing a wide range of data. Then there are analytical applications that enable people to track key performance indicators, visualize trends and ask questions of the data.

Is Your Culture Data-Driven? Key Questions to Ask

• How often do senior executives review key operational or performance metrics? Do they use dashboards for on-demand reporting?
• Are legacy, “gut-feel” decision making models still in place?
• What is the turnaround time for ad-hoc reporting from the marketing organization? Supply chain? Finance?
• The most senior executive with responsibility for data and analytics is …?
• Which business unit or function has the best reporting capacity? How broadly are their reports shared or emulated?
• Are standard reports easy to read and understand?
• How many different data sources are used to make significant strategic decisions? Which data are most persuasive?

Data-driven Cultures in Action

Moneyball popularized the concept of data-driven cultures, and it remains a highly instructive example in terms of organizational resistance to change. As the book and movie show, conventional scouting methods were “disrupted” by new metrics for evaluating baseball prospects. The change was painful for those who clung to legacy analytical models. Similar scenes have played out in the C-suites of organizations large and small, and across many sectors – including other major professional sports.

Science Over Passion to Hit a Home Run

Build data sources to support the organizations's business problems. Then decisions can be made on more than just intuition and analytics can be refined and improved. Learn more about how to build a winning business in the story behind, "Moneyball."

Data-driven Companies

Brinker International, Inc.
“It all goes back to data and the insights derived from that data. Data must be the center of your business if you want to be successful.”

Medibank
“Vantage is helping us integrate our data and better understand how our customers are interacting with us.”