Achieving Success with Data Analytics - Addressing the Talent Gap

Achieving Success with Data Analytics - Addressing the Talent Gap

Hosted by CDO Magazine and ComSpark, the CDO Midwest Summit 2022 registers its name as the most insightful in-person event in the data and technology space. One of the 30 breakout sessions indexed at the one-day summit was “Achieving Success With Data Analytics.” The session — moderated by Ken Steinhardt, Infinidat’s Field CTO — featured the following distinguished data executives as speakers:

  • Jeff Brown, VP- Consulting Services, Data And Analytics, Avaap
  • Ajaz Mohammad, Director, Data Strategy and Enterprise Architecture, Great American Insurance
  • Sandy Steiger, Senior Director Advanced Analytics and Automation, Total Quality Logistics
  • Scott Dennull, VP- Infrastructure Services & Operations, NetJets

The panel’s discussion focuses on the need for the right talent in data and analytics. Regarding the impact of talent diversity, Dennull states that it is critical to understand that different people bring different capabilities to the table. He believes some people elevate a data conversation with their in-depth data knowledge, and Denull urges organizations to consider such talent.

“We look for individuals who have broader knowledge. But, the most important thing I think these days is being flexible,” Mohammad adds. He further mentions challenging the status quo and bringing talent to the entry level because their curiosity can lead to discoveries.

Brown emphasizes the need for people who have diverse knowledge. “Getting your people to branch out a little bit from their core area — not completely depart from it — is important.”

Steiger, however, approaches the issue by stating the need for not only diversity and skill sets, but diversity and thinking in general. She addresses the low percentage of women in data and analytics, noting, “If you're bringing in people who think differently, who act differently, who have a different world and life experiences, you're approaching all of your problems differently.”

She suggests considering the following factors when choosing the right approach, tools, and people for data analytics:

  • Understand the problems to be solved with data.
  • Know the skills or tools required to solve the problem.
  • Find the right person for the project.

Concurring with Steiger, Brown says, “Mindset is the most important thing.” Next, it’s important to place people in an area where they can succeed. “I think there is a lot of opportunity to grow the team the way you want it when you put some structure in there and understand where people fit within that.”

Dunnell adds another perspective, pointing out, "The key was looking for people who had the drive, the attitude to succeed regardless of what fundamental skill or talent you were looking for.”

Steiger maintains that resumes make hiring difficult because typed skills do not always match the applicant’s pragmatic aspects.

According to Mohammad, the problem-solving approach is crucial in data and analytics. The organization must address the business from the perspective of its purpose, requirements, and successful problem solving.

The speakers agree that having the right data is all about the quality of information, the governance around it, and who should be able to access it.

Steiger notes that figuring out the right metrics to analyze the ROI associated with data and analytics determines its success. She bases her success metric on providing optimum problem-solving information so that people come back with more relevant questions.

Echoing Steiger, Brown says being successful in data analytics boils down to more people engaging with data and getting value from it to return for more. Mohammad adds that the other criteria include people being confident with data and creating a database that contains all the information to cater to business needs.

According to Steiger, relationship-building and behavioral skills are must-haves in honing a team’s development skills.

Responding to audience questions, Mohammad explains that Great American Insurance incorporates multiple aspects of AI, ML, low-code and no-code while maintaining the right expectations with the leadership.

He shares that the organization has started its digital journey and is in sync with the development team, focusing on data needs. He says that the organization aims to capture meaningful data for agents to have information at their fingertips in the long term.

“I believe that data and analytics will massively improve the human condition, particularly in health care,” Steinhardt adds in closing.

Watch other CDO Midwest Summit 2022 sessions HERE

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