Many organizations seek to benefit from the data economy. However, our survey of 1,000 business leaders worldwide found that only a small minority are participating to their full potential.

These few—the “Data Economy Leaders”—are already making their mark on this new digital landscape, using data-driven insights to inform strategic business decisions. The results speak for themselves: in the last three years, 77% of Data Economy Leaders have seen their annual revenues rise, compared to just 36% of Data Economy Laggards, the term we use for organizations at the other end of the spectrum.

So, what can we learn from those that are not only participating in the data economy, but thriving?

Read on to get started on your journey to becoming a Data Economy Leader.

STRATEGY

IDENTIFY THE BUSINESS PROBLEM DATA INSIGHTS CAN SOLVE

A hallmark of Data Economy Leaders is a strong data strategy that opens opportunities for generating insights that deliver business value. These strategies should be led by your desired end goal, not by the data itself; otherwise businesses risk allowing outcomes to be dictated by data and not the other way around.

Successful strategies start with a business problem or objective. They then enable the use of data to address these business needs with actionable insights.

Let’s take an example: Companies want to increase their customer lifetime value and ensure customer retention. They need insights to improve customer engagement, with specifically targeted actions. Cloud-based U.S. software company Braze addresses this specific challenge for its customers, offering them the tools they need to derive these insights.

“We’ve brought funnel reports, retention reports, and advanced audience segmentation features into our product,” said Jon Hyman, Co-Founder and CTO of customer engagement platform Braze. “If our customers want to look at users who made more than $20 of purchases in the last year, they can target that segment with a reactivation or engagement campaign. We further use machine learning to train our models to help with predicting customer churn or purchases.”

The majority of organizations we surveyed planned to increase their data usage in the future, although priorities for data strategies varied across industries.

Data use case each industry is most likely to have committed to developing in the next 12 months

Healthcare and life sciences: Optimize internal processes and streamline operations

Retail and CPG: Optimize supply-chain efficiency

Financial services: Deliver more personalized customer service and/or a more personalized customer journey

Media and entertainment: Improve sustainability through better allocation of resources

Technology: Identify risk and prevent fraud

PEOPLE

BUILD A STRONG, TOP-DOWN, DATA-DRIVEN CULTURE

Technology infrastructure can only go so far without the people to support it, which is why Data Economy Leaders foster a strong, collaborative data culture. Here’s what that looks like.

Gain executive support

A successful data culture starts at the top. Senior leadership demonstrates how data-driven insights can help all levels of the organization. This means understanding and articulating the strategic importance of data, and using insights derived from analysis of that data to make critical business decisions.

Figure 1: Data Economy Leaders model data-driven thinking throughout the organization

Rethink the CDO role

It’s particularly important that Data Economy Leaders invest in talent. This starts with the role of CDO or equivalent; the right CDO will act as a bridge between business and technology and will view data through a strategic lens.

In some organizations, the role and responsibilities of the CDO are already evolving, as Tom Mazzaferro, CDO for Western Union, explained: “Rather than just looking after the data and the security of data, the CDO is becoming more about what can you do with data and how can you leverage it to transform the overall business,” he said. “And a lot of executives don’t see that role yet, because they don’t have the business knowledge to connect those dots.”

Appointing the right candidate to a senior-level role with overall responsibility for delivering your data strategy is fundamental to success in the data economy. Over two-thirds (68%) of Data Economy Leaders have created a CDO or equivalent role, compared to just 39% of Data Economy Laggards.

Implement enterprise-wide data literacy training

Leaders empower employees at all levels to access data insights and make data-driven decisions. Organizations should be aiming to develop a “common data language”—a universal set of terms and definitions that will allow different business units and functions to collaborate without friction.

Most organizations surveyed recognize the importance of data literacy, and the majority of leaders had established company-wide programs to ensure that all employees have at least a basic level of data awareness. The gap between Leaders and Laggards is smaller here, giving hope for the prospects of those who are currently behind.

“We have a data-literacy program that extends to all employees.”

Data Economy Leaders

Data Economy Laggards

PROCESSES

ENSURE YOUR APPROACH IS COLLABORATIVE, CLOSELY ALIGNED TO THE STRATEGY, AND TIGHTLY GOVERNED

Strategy is important, but creating the processes and skills to execute that strategy is essential. Our research identified the qualities consistently demonstrated in Leaders’ data processes, allowing them to leverage their data to its fullest potential.

Collaboration through data sharing—both internally and with external partners—is key. Organizations that can access and share data widely uncover previously unobtainable insights.

Applications of this can be seen at Anthem, Inc., where data collaboration is building models that offer physicians a complete view of the patient and allow them to provide a higher standard of care.

“By combining our claims data with the medical records data we get from the physicians, as well as genomic data sets, pharmacy data, and other external data, we can build a whole person view and, with the help of physician insights, predict how a disease will progress,” said Ashok Chennuru, Chief Data & Insights Officer at Anthem. “The physician caring for the patient can use this model to address the indicators and prevent disease progression.”

Second, data strategy and processes must be consistently aligned across teams. Something as seemingly simple as data definitions and labels requires coordination to prevent confusion and issues of data quality. Most Data Economy Leaders have a dedicated data or analytics center of excellence (COE) to drive this alignment—and those looking to become Leaders should strongly consider establishing one.

“We have a COE to help coordinate data policies across the organization.”

Data Economy Leaders

Data Economy Laggards

Good data governance ensures that processes are coordinated, and that siloed data is consistent, discoverable, secure, and accessible for varied types of analysis and by approved users.

Organizations that fail to meet this standard will find the value and credibility of their data is limited. “The ability for a company to leverage their data to create that competitive advantage is going to depend on the quality of that data. How it’s collected, how well it’s organized, how well it’s labeled, and is it fit for the use cases you want to apply it to?” confirmed Anita Lynch, Career Data Architect and CDO.

“It’s kind of a funny analogy, but it’d be like walking into someone else’s house, opening a kitchen cabinet and you see that they’re storing socks in there,” she said. “Would you really trust that?”

TECHNOLOGY

BUILD AN INFRASTRUCTURE THAT'S SCALABLE, INTEROPERABLE, AND COLLABORATIVE

Most organizations have already migrated their data to the cloud, but our research suggests many still don’t have the scalability and power they need.

It's clear that many more Leaders than Laggards have the right technology to access and participate in the data economy. At a minimum, firms looking to be Leaders need cloud data platforms that offer the following qualities:

Scalable and elastic

A cloud data platform should have capacity to manage a near-unlimited amount of data and provide almost instant and near-limitless scale, concurrency, and performance.

Interoperable

Data professionals should be able to connect to nearly any complementary solution, so they can enable data to move freely to and from the data platform and these solutions.

Collaborative

A platform should offer seamless and near-instant data sharing that enables any number and combination of individuals and organizations to provide and consume live data, insights, and data services across an organization; between organizations in the same business ecosystem; and globally.

Figure 2: Data Economy Leaders use platforms that are scalable, extensible, and ensure collaboration

Base: 240 respondents overall