Hi, Friends,
Last week was a blast!
🚀 My Practical People Analytics Course and my company have been certified by SHRM to assign SHRM re-certification credits! This is really a testament to the quality of content and learning in this course. I am so honoured! By the way, I am offering a Black Friday deal for 40% off this week and following with a code: BF40BLAST 😱
🎓 One local university that cannot be named yet approved my People Analytics Certification Program for co-development with them to be taught in Spring 2024.
🎓 I taught a guest lecture at York University on Saturday last week, discussing my journey, two people analytics case studies, and the People Analytics Trends I wrote about last week. It was great to connect with students, and if you are looking for someone to come to your company and speak about people analytics, just let me know!
Please forward this newsletter and help me spread the word:
Okay, onto the newsletter now!
Today, I discuss the qualities you need in people analytics.
Why?
Because people are asking this question over and over again. We even briefly talked about it in the York University course with students!
We all want to be successful in this field, but it’s hard to cultivate excellence without a good framework.
Hence, in this short letter, I will speak of 3 dimensions that make you successful in people analytics:
Personality
Skills
Approach
Let’s dive in!
Personality
Personality combines the individual's stable, consistent, and persistent characteristics that make them who they are. There are many personality characteristics, including extraversion, and many frameworks that assess personality, like the Big Five Model (valid) or the infamous Myers-Briggs Model (invalid).
For people analytics, you need 3 characteristics:
Curiosity:
I still remember Janet Claudia Rodas speaking at the stage of the People Analytics Summit about curiosity leading the way in people analytics. And it is true. You need to be curious about human behaviour and dive into rabbit holes to be successful in the field. After all, when you work with the data, it’s all about what you will find.
Resilience:
Sometimes, things you find will not be what you want to see. Your hypotheses will be wrong. You will not have enough data to demonstrate you are right. And sometimes, even when data says otherwise, your team may choose a different decision. Remember, as a people analytics practitioner, you are in the service of the truth. Bounce back from setbacks.
Conscientiousness:
When working with data, you need to pay attention to detail. Focus on doing things ethically, on time, and budget. This is not limited to people analytics. It is instrumental in business.
Skills
The second is skill. People Analytics is a precision profession, and you must do things well to drive the proper outcomes for the company and your customers.
So, here are 4 skills you need:
Data Literacy:
Data Literacy will be the number one in-demand skill for HR in just a few years. AND, 85% of CHROs already ask HR teams to bring more data to conversations to help make better decisions. The revolution has started. Are you ready for it? Check out my free assessment here.
Project Management:
Pretty much any people analytics assignment is a project. Whether you are running a current state assessment, developing a new solution, or doing a quick calculation. You must ensure you know how to set up a project, run it, and deliver the outcomes constructively to drive action. You may not need a full PMP degree, but you must know the basics.
Analysis:
This one should not surprise anyone. You need to know how to use the data to extract insights to drive decisions and actions. This can be simple descriptive statistics, regressions, and network analysis. But you need to know analysis to work with people data. Check out my course for a quick and practical tutorial.
Communication:
Beta weights. P-values. Effect sizes. Network density and centrality. These are entirely useless to an average person if spoken in statistics language. You must translate your findings in plain English (or the language of your company). If you cannot communicate your findings, how are you expecting anyone to act on them? Learn good writing and storytelling.
Approach
The last element of people analytics success is approach—or how you will deliver outcomes from your people analytics projects.
Here are 3 to keep in mind:
Strategic:
Always start with strategy and the business outcomes. Sure, we think our accountability is to employees. Still, very often, our real accountability is to our shareholders, who are looking for profitability. Don’t get discouraged; it is hard to have profitability when people are leaving or are barely engaged at work. Just remember, you need to connect the dots.
Consulting:
The more questions you ask and the more you consult, the better your project will go. Why? You will understand the context well, the process well, and your data well. More importantly, you will engage the team in the project, generating momentum, excitement, and buy-in. Always overcommunicate.
Biased for Action:
Most projects die, including people analytics projects, because we are too slow to act. We need to work and act NOW to deliver the outcomes for the business. If we move with urgency, we build unstoppable momentum.
Here is the overall framework:
With that, I shall see you next week!
K
Whenever you’re ready, there are 2 ways I can help you:
#1 If you’re still looking to get started in People Analytics, I recommend starting with my affordable course:
Practical People Analytics: Build data-driven HR programs to 10x your professional effectiveness, business impact, and career. This comprehensive course will teach you everything from building an HR dashboard for business results to driving growth through more advanced analytics (i.e., regression). Join your peers today! Also, don’t forget your 40% off: BF40BLAST
#2 If you are looking for support in your Human Capital programs like Engagement, Retention, and Comp & Ben and want to take a more data-driven approach, contact me for some consulting services at Tskhay & Associates.
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