For the last few decades, consultants have insisted that companies need to transform into digital enterprises in order to keep pace with the rapidly changing business landscape. The pandemic brought that message home in a big way. Mark van Rijmenam, founder of Datafloq, explains, “If there is one thing that the Corona crisis has made clear, every organization needs to digitally transform their business as soon as possible. Digital is here to stay, and organizations are finally aware of it.”[1] So what’s holding them back? In many cases, the answer is people. Centuries ago, Niccolo Machiavelli, in his classic The Prince, wrote, “There is nothing more difficult to take in hand, more perilous to conduct, or more uncertain in its success, than to take the lead in the introduction of a new order of things, because the innovator has for enemies all those who have done well under the old conditions, and lukewarm defenders in those who may do well under the new.” Too many companies, in their transformation efforts, concentrate on technology and processes without giving enough thought to people.
Making People a Priority
Business journalist Stacy Collett notes, “Today’s digital business strategies come with a list of enticing expectations: improved process efficiency through automation, increased employee productivity, better management of business performance and new revenue streams, to name a few perks. But with all of the promises offered by digital strategy, there is one simple truth: ‘The people are the center of any digital transformation. We understand that it has to work for our users or we’re not actually solving their problems or making their lives better,’ says Mouneer Odeh, [former] vice president of enterprise analytics and chief data scientist at Thomas Jefferson University.”[2] Reinhard Messenböck, Michael Lutz, and Christoph Hilberath, analysts from Boston Consulting Group (BCG), agree that people often create bottlenecks to digital transformation. They explain, “Even as it becomes increasingly urgent for companies to create competitive advantage through transformation, more and more of them are finding this difficult to do. … Why do so many transformation efforts fall short of their goals? One factor we have observed is that as companies strive to increase the speed with which they generate and implement solutions, they tend to overlook a critical limit on their transformation efforts: the speed at which employees can absorb and internalize change.”[3]
According to the BCG analysts, “If companies want their transformation efforts to succeed, chief transformation officers (CTOs), working with a transformation office, must first develop a granular understanding of their workplace ecosystem — an area in which most managers are, at best, guided by intuition — and then ensure that transformation leaders in the organization can remove obstacles to change, mitigate risks, and help employees navigate the demands placed on them.” Ghislaine Entwisle and Kathie Topel, executives with Protiviti, add, “Enterprise transformation demands technology to work and people to adopt it. The ‘people’ component of enterprise transformation can make or break digital transformation.”[4] They believe that getting stakeholders involved from the beginning of transformation efforts can help overcome some bottlenecks. They explain, “To avoid failure by underestimating the people component, change enablement should start at the very beginning — at project identification. Stakeholders must be in initial conversations about technology transformation. They bring value as they offer viewpoints on impact to job functions, which opens a dialogue on guided support and remediation.”
Adopting the Right Culture
Even if stakeholders are involved from the beginning of transformation efforts, thought needs to be given and action taken to create the environment in which people will work (i.e., the corporate culture) as the transformation unfolds. Mai AlOwaish, Chief Data & Innovation Officer at Gulf Bank, and Thomas C. Redman, President of Data Quality Solutions, explain, “Building a data driven culture is hard.”[5] To enhance chances of success, they suggest organizations take the following steps. “First, it is important to start building the new culture from day one, even as doing so is not the primary mandate. Second, to change a culture, you need to get everyone involved. Third, give data quality strong consideration as the place to start. Finally, [recognize that] building this new culture takes courage and persistence.”
If a company can change its data-driven culture in the right way, McKinsey & Company analysts Alejandro Díaz, Kayvaun Rowshankish, and Tamim Saleh believe great results will follow. “Organizational culture,” they note, “can accelerate the application of analytics, amplify its power, and steer companies away from risky outcomes.”[6] From their study of leading data-driven organizations, they have drawn seven principles they believe underpin a healthy data culture.
Principle 1. Data culture is decision culture. The McKinsey analysts note, “Don’t approach data analysis as a cool ‘science experiment’ or an exercise in amassing data for data’s sake. The fundamental objective in collecting, analyzing, and deploying data is to make better decisions.” This is a principle we at Enterra Solutions® firmly believe, which is why we are focusing on improving Autonomous Decision Science™ (ADS®). In fact, companies have the best chance of succeeding if they are decision-driven, not just data-driven.
Principle 2. Data culture starts at the top. According to the McKinsey analysts, “Commitment from the CEO and the board is essential. But that commitment must be manifested by more than occasional high-level pronouncements; there must be an ongoing, informed conversation with top.”
Principle 3. Data must be democratized. Bain analysts, Michael C. Mankins and Lori Sherer, insist, “The best way to understand any company’s operations is to view them as a series of decisions.”[7] And decisions are made throughout an organization, not just at the top. That means data must be democratized. The McKinsey analysts write, “Get data in front of people and they get excited. But building cool experiments or imposing tools top-down doesn’t cut it. To create a competitive advantage, stimulate demand for data from the grass roots.”
Principle 4. Data culture accepts risk. According to the McKinsey analysts, “An effective data culture puts risk at its core — a ‘yin and yang’ of your value proposition. Although companies must identify their ‘red lines’ and honor them, risk management should operate as a smart accelerator, by introducing analytics into key processes and interactions in a responsible manner.”
Principle 5. Culture change requires transformation champions. McKinsey analysts explain, “The board and the CEO raise the data clarion, and the people on the front lines take up the call. But to really ensure buy-in, someone’s got to lead the charge. That requires people who can bridge both worlds — data science and on-the-ground operations. And usually, the most effective change agents are not digital natives.”
Principle 6. Collaboration is good, but beware data sharing. The McKinsey analysts ask whether it is wise to share data beyond company walls. Their answer, “Not so fast. … There’s increasing buzz about a coming shift to ecosystems, with the assumption that far greater value will be delivered to customers by assembling a breadth of the best data and analytics assets available in the market rather than by creating everything in-house. Yet data leaders are building cultures that see data as the ‘crown jewel’ asset, and data analytics is treated as both proprietary and a source of competitive advantage in a more interconnected world.” There is a fine line between the need for security and the need to collaborate in connected world. Finding the right balance is essential for success.
7. A data-driven culture requires marrying talent and culture. According to the McKinsey analysts, “The competition for data talent is unrelenting. But there’s another element at play: integrating the right talent for your data culture. That calls for striking the appropriate balance for your institution between injecting new employees and transforming existing ones. Take a broader view in sourcing and a sharper look at the skills your data team requires.”
Concluding Thoughts
Jeff Wordham, Geoff Tuff, and Bill Briggs, principals at Deloitte, conclude, “Technology is relatively easy, as any veteran CIO will tell you. It’s people that are hard. For all the technical challenges that accompany the introduction of new systems or products, human factors are most likely to determine their ultimate success or failure.”[8] They add, “With a deeper understanding of what makes people tick, technology and business leaders can make better technology decisions and create more meaningful digital transformations, engaging experiences, and valuable disruptions.” Although I have focused on people and culture, no transformation will be successful if they don’t work in harmony with technology modernization and process improvement.
Footnotes
[1] Mark van Rijmenam, “The Data Organisation is Here to Stay, and Organisations are Finally Aware of It,” Datafloq, 18 May 2020.
[2] Stacy Collett, “Humanizing the digital experience,” CIO, 24 June 2019.
[3] Reinhard Messenböck, Michael Lutz, and Christoph Hilberath, “Putting People at the Center of Change,” Boston Consulting Group, 9 July 2019.
[4] Ghislaine Entwisle and Kathie Topel, “People: A Forgotten Element of Technology Transformation,” CIO, 9 May 2022.
[5] Mai AlOwaish and Thomas C. Redman, “What Does It Actually Take to Build a Data-Driven Culture?” Harvard Business Review, 23 May 2023.
[6] Alejandro Díaz, Kayvaun Rowshankish, and Tamim Saleh, “Why data culture matters,” McKinsey & Company, 1 September 2018.
[7] Michael C. Mankins and Lori Sherer, “Creating value through advanced analytics,” Bain Brief, 11 February 2015.
[8] Jeff Wordham, Geoff Tuff, and Bill Briggs, “The Human Side of Tech: Driving Behavioral Change,” The Wall Street Journal, 5 April 2018.
