Talent Management is Broken and it’s Time for Data Analytics to Help.
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In one of my previous organizations, the leadership team assured me they had an excellent retention strategy for senior women because all the high-potential women were in a special leadership development program with free executive coaching, and they were also all highly-compensated.
I showed them a couple of data points that quickly got their attention.
1) Hi-Potential retention post these coaching programs is actually worse. Many almost immediately resigned upon “graduating” these programs over the past 5 years.
2) The current engagement and intent-to-stay scores for senior women is much lower than their male counterparts in the latest survey.
This LinkedIn post of mine generated real conversations and was featured on LinkedIn News last week. I realized I didn’t share my experience leveraging data analytics in Talent Management as much and it is time.
Many organizations had a challenging time attracting, developing, and retaining employees since the COVID-19 pandemic drastically changed how we worked. Ultimately, this is the core of an effective talent management strategy.
What is Talent Management? You all know how I feel about buzz words, so let me share a buzz word-free definition from McKinsey: “Talent management includes all the ways that organizations bring employees on board, keep them happy and productive, and help them continue to develop their skills over time.”
How can data analytics help? Here are a few ways I’ve leveraged data analytics in my previous roles as the Head of People Analytics.
1. Evaluate the High Potential and Leadership Development Programs
(1) Look backwards: One simple analysis is to compare the retention rate of the participants in the high potential and leadership development programs to those outside the programs. Another is to look at whether the performance and retention improve within a year of graduating from the programs. In my experience, the analysis is easy but finding good data historically is not. Some of the programs are not tracked in the HR system consistently so it may be challenging to identify the start and end time of certain programs, for instance.
(2) Look ahead: If Diversity, Equity, and Inclusion (DEI) is important to your organization, it’ll be helpful to use data to understand the demographic composition of individuals selected into the high potential and leadership development programs. Given these programs are the pipeline for future senior leaders, it’s critical to see whether the demographics mirror the current workforce. More importantly, if the data reveal that fewer women and BIPOC employees are represented in these programs, a deeper analysis of the selection process may be required.
2. Proactively Identify the Flight Risk and Retain Top Talent
Most mature people analytics teams now have a predictive employee attrition model, and several HR tech vendors also offer out-of-the-box attrition prediction capabilities.
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One area of application I’ve found that resonated with my stakeholders is with top talent. Imagine if you knew some of your top talent might be at risk of leaving due to workload, wouldn’t you use the opportunity to at least have a conversation and see what would make them feel engaged again? Once you have implemented a retention strategy based on flight risk, it'd also be important to monitor the effectiveness of the plan.
3. Identify Skill Gaps and Create a Strategic Workforce Plan
Do you know which specific skills your sales team needs to close the deal? Do you know what work experiences are best at developing those skills? Do you know where you have skill gaps in the current sales team? These are the questions I was able to answer with data. As many organizations shift their business model and operations after the COVID-19 disruptions, their sales team had to develop new ways to generate leads and close deals. These shifts meant developing new skills as well. Since you can’t improve what you don’t measure, the measurement of skills data for existing employees becomes the critical first step to understanding your current workforce.
If you want to learn about how to do this in practice, my latest people analytics course on LinkedIn Learning is now live! It took me several months to put my passion for “skills” into a condensed course. Please check out this practical course and let me know what else would be helpful in the future.
These 3 use cases from my experience are of course not the only areas of Talent Management, nor are they the only ways data analytics can help. I’d welcome your comments to keep this important conversation going on LinkedIn or offline.
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Dr. Serena Huang is an accomplished thought leader and professional keynote speaker who also regularly guest-lectures at top MBA programs including Kellogg, Wharton, and Haas. She coaches executives in financial services and tech on personal branding. She most recently served as the Global Head of People Analytics & HR Tech at PayPal and previously built the people analytics functions at Kraft Heinz, GE, and Koch Industries.
Dr. Huang is the author of a popular LinkedIn Learning course “The Data Science of Using People Analytics” with more than 10,000 learners, recognized as a Top 15 LinkedIn Expert in Chicago and a Leadership LinkedIn Top Voice in 2023.
Talent Management Strategist and Consultant | Speaker 📣 Marathoner 🏃🏼♀️
1yI love all of this, and what's really coming to light is the importance of Talent Management professionals to upskill in data literacy. There is a treasure trove of amazing data and insights to be utilized, yet often these functions don't have the access, awareness or competence. I've been saying for years that the future of HR requires people analytics skills 😁
Entrepreneur, GTM, Author
1yvery interesting with the way we are going..
Helping organizations improve and retain their most valuable asset: Employees!
1yExcellent read and good points to raise!
This is great! I took the new LinkedIn Learning course and I was hungry for more. Very insightful and engaging. Thank you!
Ping me to find out how to improve your #dataquality, #MDM and more with #dataobservability | CPO @Acceldata | Ex-Reltio CPO & CMO | Partner to CDOs & CIOs | Top LinkedIn Exec Voice | Who’s who in Data
1yExcellent article Serena H. Huang, Ph.D., I know I've been pushing this track, but #workforceanalytics will provide the missing link for #peopleanalytics because it can forecast disengagement, quiet quitting and burnout, in a digital form. Mindy H. whom I introduced you to a while back - not sure if you've connected, is an expert on this topic. I'm passionate about what you wrote, and also passionate about how employees and employers need actual quantifiable data to manage employee engagement, experience, reduce burnout, and therefore stem the tide of #attrition. The other angle is using digital usage data to assess training needs. Many employees are frustrated with lack of training, and inability to use the hundreds of SaaS tools that are thrust in front of them. #workforceanalytics can help with that as well. 😀