Digital transformation experts shared their experiences of driving organizational change to create data-driven business cultures at the inaugural Business of Data Festival
The ways enterprises harness advanced digital technologies such as AI have matured rapidly in response to the COVID-19, according to many of the executives at this week’s inaugural Business of Data Festival.
As Tendü Yogurtçu PhD, CTO at data integrity specialist Precisely, said, enterprises have levelled up from talking about using digital transformation technologies such as AI to delivering the use cases that will ultimately transform their businesses.
“Data science teams are no longer just prototyping and trying to validate certain models,” Dr Yogurtçu said. “They are actually increasingly a critical part of the data strategy.”
However, speakers during the digital transformation focus day of this virtual summit also agreed that investing in digital technologies is actually the easier half of the phrase ‘digital transformation’.
Change Management is the Hard Part
For many executives, the hard part of digital transformation is changing how their companies operate to integrate new technologies with their processes.
“The technology’s not the problem part,” said Dan Power, Managing Director, Data Governance, Global Markets at financial services giant State Street. “What’s hard is changing behavior, attitude, prioritization of expenses and investment [and] getting management to think data-first.”
For Power, data-focused executives must ensure their strategies align with their companies’ broader business strategies. But to truly accelerate their organizations’ digital transformations, they must also push for data literacy at all levels of the organization.
Joe DosSantos, Chief Data Officer at BI platform Qlik, agreed that successful digital transformations start with getting key stakeholders excited about improving business processes in tangible ways.
“You really need to start thinking about, what is the thing that drives the imagination of the business to provide that digital outcome?”Joe DosSantos, Chief Data Officer, Qlik
He argued that this approach is more effective than trying to educate people about the importance of things like data governance in a vacuum.
“You really need to start thinking about, what is the thing that drives the imagination of the business to provide that digital outcome?” he said. “Once you get people excited about things, you can start to talk about the technology as a way to enable some output.”
Stephen Gatchell, Head of Data Enablement at a Massachusetts-based consumer electronics company, added that ensuring staff have the right data literacy levels is one of the key non-technical challenges executives must overcome to deliver successful digital transformations.
He asked: “How do you have the key components in the executives who are managing these digital assets, [so they can] understand from a data literacy perspective how data and digital come together to deliver the outcome that you’re looking for?”
Top-Down, Bottom-Up and Middle-Out Digital Transformation
Executives included Power advocated using top-down, bottom-up and middle-out change management initiatives in unison to achieve digital transformation success.
Executive sponsorship for data-driven initiatives is essential. But so is middle management leadership and support at the grassroots level. To succeed, executives targeting business transformation must communicate the benefits of their plans to stakeholders at all level of the organization.
“You can’t just jump in and say, ‘This is what the k-means clustering says’, if they have no idea what any of those words means”Hamdan Azhar, VP, Global Marketing Data Science, BlackRock
“Communicate,” Power recommended. “You’ve got to be able to tell the story. Why are we doing this? What overall strategic objectives does it support? What’s the impact on our customers? What’s the impact on our employees? How do we get people the training they need?”
“It’s fine to talk about data literacy, but you have to back that up with communications and training,” he added. “We need to train a ton of people in our firm that kind of grew up on Excel, to say, ‘Let’s get you to the next level of data literacy, which (by the way) means other tools.’”
Hamdan Azhar, VP, Global Marketing Data Science at investment management company BlackRock, agreed that equipping staff with the right data literacy levels is important. In many cases, he said BlackRock has found it’s necessary to start with the basics.
“As data scientists, we have to start from a position of deep empathy for the end-user,” he said. “We have to understand their mindset. We have to understand what they care about; what their priorities are.”
Taking a ‘Crawl, Walk, Run’ Approach
Azhar said BlackRock is taking a “crawl, walk, run” approach to delivering data-driven digital transformations.
“The idea is that organizations and individuals and teams exist at all levels of the spectrum,” he said. “We can’t just come in and say, ‘I’m a data scientist. How can I help you?’ because the vast majority of our audience might have no idea what that means.”
At the least mature end of the data spectrum, this means providing basic data literacy education to ensure company stakeholders understand what data is and how it can be used. But there will also be staff in any large enterprise who are passionate about data and keen to apply cutting-edge technologies such as AI in their roles.
There are so many functions, businesses and products within an organization, and they could all be at different levels of maturity”Tiffany Perkins-Munn, Managing Director, Head of Research, Analytics and Data, BlackRock
“I think it’s important for people who work in data organizations to understand that [driving change] is not necessarily a linear process,” noted Tiffany Perkins-Munn, BlackRock’s Managing Director, Head of Research, Analytics and Data. “There are so many functions, businesses and products within an organization, and they could all be at different levels of maturity.”
For this reason, it may not make sense to focus just on executive-level data literacy, or to begin with basic training for the end-users of data-driven tools and progress gradually to more advanced initiatives.
Instead, Perkins-Munn encouraged enterprises to develop a portfolio of data literacy and change management projects tailored to different job roles and skill levels. This will allow an enterprise’s ‘data champions’ to run, while other staff members are learning to crawl or walk.
Enterprises must undoubtedly work to ensure all staff have the right skills to understand and work with data. But the companies that are leading the digital transformation race are doing so in a way that frees up their most gifted staff members to run ahead of the pack.