By Robert Audet
Data is at the front and center of everything an organization does. It helps business executives make better-informed decisions, predict what customers are likely to buy, produce smarter products and services, and optimize business processes. Data also powers transformative technologies (e.g., AI, predictive analytics, machine learning), which organizations are leveraging to create a competitive advantage or achieve strategic objectives.
But whether data can help an organization realize its full potential is not determined just by the technological investments a company makes. It also requires companies to have a strong focus on embedding data into every aspect of their culture and processes, which can involve a big change of perspective for many firms.
Recognizing the increasingly important role data plays, Chief Data Officers (CDOs) and other business leaders often talk about the need for a data-centric culture. However, many struggle to articulate exactly what that means—and what it looks like for their organization. This lack of clarity is only one of the obstacles that CDOs and other data leaders face when trying to establish a framework for data to transform and power an organization.
In summary, a data-centric culture represents the degree all people in an organization value trusted, understandable, accessible, visible, and connected data that improves insights, supports behaviors, and fuels better operations and strategic decisions. A data-centric culture also represents shared beliefs and values related to data established by leaders and then communicated and reinforced through policies and behaviors.
A data-centric culture expresses itself through the approach organizations take to combine technical capabilities, workforce skills, and information sources to draw in the best possible data, effectively analyze it, and use insights to guide management actions. Organizations with a data-centric culture make decisions based more on evidence and less on intuition, personal bias, and false narratives. They use data to inform strategic decisions, and day-to-day operations. In addition, they make data available across the organization to empower employees and reinforce strategic direction. For example, a CDO at a large Federal government agency, rolled out staff-level dashboards with the metrics leadership used to track performance, so people in the field could see the broader picture they were impacting with their work.
“Ad hoc data management can lead to ad hoc analytic results,” says Anne Levine, Deputy CDO at the Federal Communications Commission, adding, “A data-driven culture ensures that each of our different mission areas are in sync with one another when conducting their analyses. It means making sure people are on the same page, and know what the assumptions in the analysis are,” adding, “Better quality data leads to better outcomes and better decisions.”
Like the overall corporate culture within an organization, which influences day-to-day behaviors and how companies operate, the aim of a data-centric culture is to embed good data management practices into all aspects of corporate culture and processes, and have references to data be part of the organization’s communication fabric.
Organizations with a data-centric culture make operational or strategic decisions based on the best available information and challenge assumptions. There is a common understanding that better quality information, combined with analysis, results in better outcomes, decisions, and a shared interest in using data in innovative ways to solve problems more easily.
When everyone speaks the same language, there can be more efficient and effective communications when working with data. Data centricity can help “connect the dots” and create understanding across organizational divides. It can also reveal issues with the data (bias, poor quality), which is a good thing, as everyone is seeking the best answer.
Data-centric cultures, along with associated data literacy and analysis capabilities, do not emerge spontaneously. They begin with getting leaders to understand what data can do for an organization and how it can increase their ability to achieve strategic goals and exceed stakeholder expectations. This is one of the biggest challenges CDOs face—and it often starts with having to define their own role and the value they bring. “It’s a new role. There is a constant need to communicate the responsibilities of the CDO, demonstrate the value the role can bring to an organization, and gain political capital in order to drive lasting change,” notes Matthew Graviss, CDO at the US Department of State.
Even in supportive environments, CDOs must overcome ingrained obstacles, such as a fear of change within their organizations, ongoing attachments to legacy technologies and application development approaches, and a focus on the tools used to manage data, rather than the data itself. CDOs need to become the champions of change and using data differently.
In addition, a CDO often must make the case for new data systems, staff training in data literacy, and onboarding new skills. While CDOs are highly placed with growing accountability and authority, their priority is usually on getting the hundreds of little things right to ensure that data is being properly collected and analyzed. However, the technology behind a large-scale data-centric organization is sophisticated. CDOs need to work with colleagues to articulate the required investments in both technology and human capital to build capabilities. This challenge can often be exacerbated by a lack of data literacy among senior management.
Sometimes, CDOs need to reevaluate the way their organizations are structured to make data more widely available, standardized, and more effective. “Data is often fractured into silos, and people are not using the same language when they talk about data,” says Katherine Tom, CDO of the Board of Governors of the Federal Reserve System. “Data professionals are using too much jargon and business people have little understanding of it. It is preferable to use more plain English to reveal the business insights as if the data are telling us stories.”
In fact, communication is a bigger part of a data leader’s job than most people think. That can mean deputizing data ambassadors to work with different groups in the organization to find out what their data needs are, and to find ways to effectively ingrain data-driven practices in their day-to-day operations. It also means keeping in close contact with other organizational leaders to find out what their priorities are and what problems need to be solved, so you can make existing data practices more effective.
It is not easy. The CDOs we interviewed stressed the need to focus on the “nuts and bolts” of their role, such as curating data sets and managing the data infrastructure, while being a data evangelist to bridge the gap between the organization’s current understanding of the power of data and what is required to build a data-centric culture. “You won't make front-page news by establishing a data quality program,” Levine says, “but you will if poor data quality results in bad decisions.” In the end, building a data-centric culture takes patience, persistence, and pragmatism.
With so many challenges, we have identified a few key elements to help CDOs and other data leaders create a more data-centric culture.
A data-centric culture can reshape and improve almost every aspect of an organization, from increasing operational performance, to enhancing the customer experience, and delivering new projects and services. In addition, a having a data-centric culture is becoming essential to enable leaders to effectively manage the organization and successfully navigate challenges. From conversations with data leaders across the globe, it is important to remember that the journey is long, “so pace yourself, win a few battles first, before trying to win the war,” says Tom Dunlap, CDO, with the London Stock Exchange. Having heard how data leaders are embedding a data-centric culture within their organizations, what can you do to start building data centricity within your own organization?
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