30 min listen
Kyle Winterbottom's 3 Data Leadership Trends to Watch in 2022
Kyle Winterbottom's 3 Data Leadership Trends to Watch in 2022
ratings:
Length:
30 minutes
Released:
Mar 17, 2022
Format:
Podcast episode
Description
Kyle Winterbottom, Founder and MD of specialist recruitment agency Orbition, shares three trends he believes will reshape enterprise data and analytics teams in the coming months
After 11 years in data and analytics recruitment, Kyle Winterbottom has an intimate knowledge of the trends shaping enterprise data and analytics teams. Since founding specialist recruitment agency Orbition two years ago, he’s noticed a number of significant changes in the industry.
In this week’s episode of the Business of Data podcast, Winterbottom shares how three recent developments are influencing the shape of enterprise data and analytics teams.
A Renewed Focus on the Data Foundations
The first theme Winterbottom says he’s observed is a renewed focus on ensuring enterprises have the right foundations in place, particularly where data quality management is concerned. This is translating into demand for data governance and engineering staff.
"The language historically used around governance has kind of turned people off,” Winterbottom says. “It’s often seen as a tick-box exercise, more about compliance. People realize now that, if we get this right, it makes our analytics endeavors better and more valuable.”
“Every organization is looking to start a data analytics journey or to do more with what they have,” he continues. “Data scientist was the sexiest job title of the 21st century until most organizations realized they didn't have the infrastructure to actually support the role. That’s why the last 2-3 years have seen the rise of the data engineer.”
Shifting the Focus to Soft Skills in Data Teams
The pandemic changed the role data and analytics plays in many organizations. Many teams are facing greater demand for data-driven insights and pressure to collaborate more closely with colleagues in other business units.
Winterbottom argues that this has affected the skills data leaders prioritize when building their teams and pursuing their own professional development. While technical skills remain critical, they are increasingly focused on ensuring soft skills, too.
“There’s a difference in the way organizations are considering hard skills versus soft skills,” he says. “We’ve nailed the tech side of things, for the most part. Now, there’s real emphasis on an individual's ability to communicate, tell stories, create buy-in and to influence people, especially at the senior level.”
“You could have the best transformation in mind, all the processes and all the technology,” he continues. “But if you have no people skills or can’t engage your team, nothing’s going to work. I’ve noticed, especially on LinkedIn over the last few years, more leaders are focusing on personal branding. More people understand that they’ve got to be personable.”
The Drive to Create Diverse Data Teams
It is often said that technology reflects the people who make it. Indeed, Gartner reports that diverse data analytics teams perform better and have a better understanding of customer needs.
So, it
After 11 years in data and analytics recruitment, Kyle Winterbottom has an intimate knowledge of the trends shaping enterprise data and analytics teams. Since founding specialist recruitment agency Orbition two years ago, he’s noticed a number of significant changes in the industry.
In this week’s episode of the Business of Data podcast, Winterbottom shares how three recent developments are influencing the shape of enterprise data and analytics teams.
A Renewed Focus on the Data Foundations
The first theme Winterbottom says he’s observed is a renewed focus on ensuring enterprises have the right foundations in place, particularly where data quality management is concerned. This is translating into demand for data governance and engineering staff.
"The language historically used around governance has kind of turned people off,” Winterbottom says. “It’s often seen as a tick-box exercise, more about compliance. People realize now that, if we get this right, it makes our analytics endeavors better and more valuable.”
“Every organization is looking to start a data analytics journey or to do more with what they have,” he continues. “Data scientist was the sexiest job title of the 21st century until most organizations realized they didn't have the infrastructure to actually support the role. That’s why the last 2-3 years have seen the rise of the data engineer.”
Shifting the Focus to Soft Skills in Data Teams
The pandemic changed the role data and analytics plays in many organizations. Many teams are facing greater demand for data-driven insights and pressure to collaborate more closely with colleagues in other business units.
Winterbottom argues that this has affected the skills data leaders prioritize when building their teams and pursuing their own professional development. While technical skills remain critical, they are increasingly focused on ensuring soft skills, too.
“There’s a difference in the way organizations are considering hard skills versus soft skills,” he says. “We’ve nailed the tech side of things, for the most part. Now, there’s real emphasis on an individual's ability to communicate, tell stories, create buy-in and to influence people, especially at the senior level.”
“You could have the best transformation in mind, all the processes and all the technology,” he continues. “But if you have no people skills or can’t engage your team, nothing’s going to work. I’ve noticed, especially on LinkedIn over the last few years, more leaders are focusing on personal branding. More people understand that they’ve got to be personable.”
The Drive to Create Diverse Data Teams
It is often said that technology reflects the people who make it. Indeed, Gartner reports that diverse data analytics teams perform better and have a better understanding of customer needs.
So, it
Released:
Mar 17, 2022
Format:
Podcast episode
Titles in the series (100)
Dee Samra: Data Governance Doesn’t Have to be a Dirty Word by The Business of Data Podcast