2022 has already brought on a lot of things; one sure bet is it will continue to require more data. Zettabytes of it, thanks to 5G networks, cloud computing, and AI and machine learning software. As someone in a position of data and analytics leadership, what skills are most important in optimizing the role of data in your business ecosystem? We asked our Advisory Board members to share their thoughts. 

  1. Data Literacy. “Although our executives may have some data science background, this is not the reason they are in charge of the company,” notes Josh Tapley, Senior Director, Data Visualization at Comcast. “They’re also tight for time.” Tapley recommends stressing several elements of data literacy with your analyst or the team about to produce a report. This includes considering whether you are using the right charts to display your data, the ideal user experience, and the proper elevation of the message to people who are not data experts.

    Ben Jones, CEO of training company Data Literacy, agrees that creating greater data literacy in the organization is critical. “Executives will agree that they need to up their game talking about data and its importance and relevance,” he says. “Whether or not they’re embracing it themselves is another question. And I think that they know that they need to do that.”
     
  2. Business Change Management. New data tools and analytical approaches that evolve beyond spreadsheets are critical, but getting them to stick is just as hard. Those with roles in leadership in data analytics “need to come up with a roadmap to implement a series of changes, not just one change to technology, not just one change to data quality,” notes Jones of Data Literacy. “It has to really incorporate a variety of those different aspects of what it means for an organization to make effective use of data. It’s about training and also about looking at your processes and your tools and even your culture to find out how you can change to promote the use of data.”

    Suki Panesar, Deputy Director Strategy and Development (Data And Analytics) at the UK’s National Health Service (NHS), stresses that you are likely to run into three types of employees in a change management effort, all of whom need empathy along the way. “There are those who resist change, those on the fence who can be brought along, and futurists who can become champions of new technology going forward,” he says. “You need strategies at hand for working with each group of data analysts, including transitioning some to manager roles.”
  3. Democratizing Analytics. Companies where leaders know how to scale data science core capabilities to satisfy the ever-increasing demand and time-sensitive nature of decision-making are ahead of the game. If you’re not one of these data science leaders, it’s time to hone your skills, though the right technology also can play a role.

    “We’re seeing the emergence of low-code and no-code platforms that don’t require highly specialized teams to administer, and that integrate natively within existing workflows to reduce disjointed user experiences,” says Candra McRae, Lead Solution Engineer at Tableau. “With low-code and no-code solutions you don’t have to know how to create a dashboard or build a complex machine learning model to understand propensity or recommendations. This is a great step forward as it offloads simple, high-level insight generation to technology platforms.”
     
  4. Data Storytelling. “Successful data leaders have strong communication and storytelling skills,” says Heidi Lanford, Chief Data Officer at Fitch Group. “They’re able to articulate the impact they’re having to the business. They can find ways to show that they’re adding value. It's great that data quality is up over last year or more people can find it, but at the end of the day if the consumers of it aren't doing their day job differently, what's the point?” 
    Suki Panesar of NHS agrees, and sees data storytelling as a vital skill in coming years. “You must be able to work with internal and external customers to paint a story or vision of what they need and how they can be supported,” he says.
     
  5. Recruiting. Building a data team can be exhausting with so many new technology-driven companies on the hunt for talent. Nate Mayfield, Vice President of Applications Service Excellence, Strategy & Operations at Oracle, notes that you’ve got to be a great internal and external marketer about your culture to win at the recruiting game.


“Reputation does attract talent to a data and analytics team,” he says. “And it’s an interesting experience because word of mouth is such a strong force. Data science and analytics is still a relatively small community, and people talk. When people start to hear about what you're doing and how exciting that is, they want to join that kind of organization. And then tend to be more interested in the type of work that they're doing than other attributes of it, such as industry.”

Literacy, business change management, recruiting. It all may sound like a tall order. But as thought leaders like Randy Bean have noted, we have entered an age of data-driven leadership, and ensuring that your organization thrives will require continuous skill-building in 2022 and beyond.