While businesses across the world are trying to make more effective use of data, analytics, and AI, a key impediment is holding many of them back: The lack of a culture that truly values data/analytics capability and the superior decision making that can flow from it. Yet as we’ll describe, it’s possible to create a data-driven culture and accrue the competitive benefits that result.
In companies with strong data cultures, important decisions are informed by data and analytics and executives act on analytically derived insights rather than intuition or experience. While digital-native companies like Amazon and Alibaba have strong digital cultures, many traditional companies are struggling to make progress. That’s mostly because few undertake initiatives directly aimed at achieving the desired culture change.
Thus, it shouldn’t be surprising that a 2019 Deloitte survey of U.S. executives found that most – 63% – do not believe their companies are analytics-driven and 67% say they are not comfortable accessing or using data from their tools and resources. Data from surveys taken over time suggest that the problem may be getting worse. A NewVantage Partners survey of large U.S. firms, for example, found that only 31% of companies say they are data-driven, a figure that has declined from 37% in 2017. In 2019, more than three quarters reported that business adoption of big data and AI initiatives remains a major challenge. But 95% of them said that cultural, organizational, and process challenges presented the biggest roadblocks to adoption. Only 5% cited technology as the problem.
The CEO’s role
Clearly, culture depends in large part on the orientation of senior leaders, and especially the CEO. There is little doubt that a CEO’s own reliance on data – or lack thereof – in decision making and improving the business sends a powerful message to the rest of the organization.
But a CEO’s initial resistance or lack of awareness does not mean that an organization can’t make progress. Just as CEOs are often counselled on their communications and leadership skills, they can also be moved in the data domain through coaching, either by an internal champion, such as the chief data officer, or by outside experts. Linking data and analytics to issues the CEO already holds dear, such as customer focus or employee empowerment, can prove persuasive, as can pointing to outside factors that depend on having a data-based decision making such as regulatory requirements (for example in hospital readmissions) or the threat of more data-driven competitors.
While the CEO should become a visible champion of the new culture, he or she needs an operational partner. A logical candidate is the chief data officer, a role that is growing in prevalence, visibility and scope. The CDO is well positioned to become the data and insight change agent, leading the initiatives we describe below.
Culture Change Programs
In addition to trying to convert a passive or reluctant CEO, three types of change programs can move an organization in the right direction.
Carefully planned educational programs should be pushed into every level of the organization. Experiential programs such as design thinking exercises, group problem-solving, and hands-on hackathons tend to be more effective than talking heads. Position-appropriate exercises for staff at different levels can illustrate the benefits of analytics and data-based decisions; for example, executives can focus on framing the problem, and front-line employees can interpret the implications of analytics for customer relationships. To see an example of one such initiative, look at this simulation program developed by one of us (Davenport) to teach analytical decision-making in a consumer products company.
Education should focus not only on attitudes and knowledge about data, analytics, and AI, but also on skills for finding and manipulating data at every level, including senior management levels. A survey sponsored by the data analytics vendor Splunk of 1,300 senior executives found that while 81% of the executives agree that data skills are required to become a senior leader in their companies, 67% say they are not comfortable accessing or using data themselves. Seventy three percent felt that data skills are harder to learn than other business skills, and 53% believe they are too old to learn data skills. Effective education initiatives can prove them wrong.
TD Bank Group, for example, has developed a day-long educational program called “Data and Analytics Academy for the Non-Analytics Executive.” The Academy employs an immersive approach using a customized case study, simulations, and a series of exercises. In the program, participants work on framing a business problem such as identifying customers whose portfolio of banking products is not maximizing the performance of their assets, identifying internal and external data sources to help address it, and then operationalizing analytical solutions. So far, more than 300 executives have taken the course. The D&A Academy is part of a broader set of programs designed to improve knowledge of and stimulate demand for data, analytics, and related technology. (See this article which details one such program.) These changes are working for TD; it recently made being “data-driven” one of its five strategic priorities.
Leading by example is also important. This requires showcasing leaders who visibly use analytics and AI in internal marketing programs to spread the value of the approach across an organization. Leaders’ exemplary behavior can also include modeling the desired attitude about data and analytics in meetings; leaders should frequently ask, “Do you have data to support that point?” and encourage others to do likewise.
While too few leaders recognize the importance of modeling and marketing their use of data and analytics, companies are increasingly designating champions of AI; 45% of U.S. executive respondents to the 2018 Deloitte “State of Enterprise AI” survey said their company was appointing such senior management champions. Forming communities of practice around analytics and AI are another way to publicize positive examples.
Promotions and rewards can also encourage change. If those who make effective use of data and analytics get faster promotions and salary increases, others will notice. Of course, this approach requires leadership endorsement and sign-off and execution by Human Resources.
Putting it all together
Eli Lilly and Company is applying many of these strategies to shift its culture. Chief data and analytics officer Vipin Gopal, the first Lilly CDO, is building on the company’s deep research- and statistics-oriented culture to engage its employees with advanced analytics and AI. Among other objectives, Gopal is working to communicate the value that these methods can bring to their work, ultimately reducing the time and cost required to bring new medicines to patients.
To that end, Gopal and his colleagues are pursuing a variety of strategies, including:
- Highlighting successes by early adopters and enlisting them help get others engaged;
- Forming cross-functional teams that combine people with backgrounds in data analytics, business, and technology and combining computer science, applied math, engineering, and behavioral economics perspectives to bring diversity and innovate thinking to projects; and
- Launching programs across the organization, including open houses, forums, communities of practice, educational initiatives, and a leadership council – in effect, building marketing capability for analytics and AI within the company that helps create advocates and ambassadors.
Technology is everyone’s job
Today, every job requires an orientation toward technology. Beth Galetti, Amazon’s senior vice president of worldwide HR, recently commented(when asked about the company’s $700 million reskilling investment for employees), “The most consistent thing we see that’s changing is the need for some level of technical skills in any job.” With basic tech-savvy, employees have not only the fundamental skill they need in a fast-evolving competitive environment, but the mindset required to support a flourishing data and analytics culture.
Cultural changes take a long time to mature, and culture is influenced over time by every leader who joins an organization. It’s important for someone to monitor changes in the data/analytics orientation of the leadership team (this might also be the CDO’s purview). Several years ago, the analytics group at one consumer products firm did an analysis of every senior manager to determine how oriented to data and analytics each was. Any manager deemed unsympathetic became the target of a customized persuasion initiative. If a manager left the company, all possible successors to the position were analyzed, and the most likely candidates were subject to persuasion interventions if they seemed to lack the desired data/analytics orientation. This program may seem manipulative, but it was in the service of the company’s success—and it’s the kind of thinking that advocates of data-driven cultures need to adopt.
In creating a data-driven culture, there’s no rest for the weary. We know of organizations that were hugely focused on data and analytics, but when the CEO champion left they drifted back to their old gut-based thinking and decision-making. From boards of directors to CEOs to analytics and AI leaders, everyone who believes in this focus should work to persuade others to adopt and maintain it. No one should assume that software and hardware alone will lead the organization to the cultural promised land.
Article originally published by Harvard Business Review
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