What’s New and Exciting in the Field of People Analytics? 2023 Edition
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You may be wondering where I came up with the idea to write an article titled “What’s New and Exciting in the Field of People Analytics?” instead of my usual specified, solution-oriented post.
A peer at a very-big tech company emailed me with the following question this week: “What’s New and Exciting in the Field of People Analytics?” and my Medium blog originated as a way for me to answer HR questions in a public forum. And so without further ado:
The Theme of 2023: is People Analytics Invaluable or Not-valuable?
There is a clicky headline stat floating around about how People roles and specifically People Analytics were the fastest-growing roles across 2021–22. My concerning hypothesis is that this may be misleading due to the rollercoaster of Lockdown => Recession: these roles absolutely exploded in popularity across the boom times and then rapidly receded starting late 2022. The volume of roles that were posted just before a layoff or removed mid-flight due to a reduction in force might send the message that the function is a nice-to-have.
I would argue (naturally) that this is untrue. It is likely the case that some of the greatest hits of People Analytics — workforce planning, turnover /retention management, hiring speed — are not in season at the moment. But one door closes and another one opens onto….
New Problems to Solve, New Definitions of HR
In a global recession, the focus of People Analytics will naturally point toward managing the talent one already has — are they thriving? Are they able to do their best work?
Additionally, I am in Slack chats with 1000s of ex-FAANG workers who are un-consolidating and launching new startups. Their lack of brand recognition makes thrifty, effective recruiting and employer branding paramount. Below are some specific problems, solutions, and tools I see being particularly essential in 2023:
Accountability & Productivity, but not in a Creepy Way
Problem: There is a new trending term “Productivity Paranoia” regarding the inclination to worry about if employees are “being productive” while working virtually and out of sight.
How to solve it: Reframing the question to be more employee-centric by using check-in surveys (in the jargon, employee listening) to learn about employee “speed killers” — blockers or obstacles to accomplishing the work they seek to get done. Maybe tools will be lacking. Maybe managers will be causing systemic slowdowns. You won’t know until you ask and/or listen
Great tools & solutions:
- Worklytics & Perceptyx are two great suites for passively listening and gathering feedback on the metadata created by technology / tools
- Lattice & Peakon remain two of my favorite survey or pulse survey tools, but there are many great players out there (even humble Google Forms)
Too Many People Tools => The Great Bundling
Problem: https://hbr.org/2014/06/how-to-succeed-in-business-by-bundling-and-unbundling Tech landscapes move in waves of either bundling or unbundling. After a fever pitch of HR Tech point solutions being launched and procured over the growth years, you’re likely about to see every company try its hand at bundling. I predict you will see a number of companies beyond Deel and Rippling looking to add an HRIS component to their tool OR if they are an HRIS, they will acquire or quickly build more.
How to solve it: be very cautious about what you license and for how long — pilots will be your friend so you don’t have to procure and install something you haven’t yet tried. You can also build more yourself to justify the value of future tools. You don’t want to end up, for example, with a small scheduler solution that zaps up budget from an all-in-one.
Great tools & solutions:
- Ashby is a recruiting platform that is covering its basis with built-in analytics and dashboarding capabilities so you don’t have to add a whole stack of tools to make magic happen
Quick, Find a Way to Use AI in HR
Problem: Something something chatGPT, you’ve heard it all before. There is a race to incorporate AI into everything everywhere all at once.
How to solve it: I have enjoyed using ChatGPT to cover the basics of HR writing. For example, I can get some great free documentation to “what is Engagement and why does it matter? And spend more time on the engagement work, less time on the internal wikis.
Secondarily, I feel like very simple reporting challenges are still unmet, but well met by language models. All across the US I would bet analysts are opening up a large CSV and clicking filters and writing countifs to answer an easily summarized question like “how many people that work in engineering are women?” This is a job for AI, not for us. You can see my 2021 pre-AI attempt at this by Putting a Nintendo Oracle into Sheets.
Great tools & solutions:
- Orgnostic has risen to the occasion and added natural language prompts for People Analytics! I haven’t used it myself but if it works it is a profound step forward.
- Textio, Datapeople: two great tools for applying language models to job descriptions, typically a hive of discriminatory language. I don’t know how anyone will write a job description without these in the future.
No Code Required to Make Data Applications
Problem & Solution: a number of Analytics projects depend on process & tech. For example, workforce planning or reporting data will be part analytics, but also part UI for the ingestion and upkeep of data. You can now make more full-fledged applications, not just the sheets and slides of yesterday, to go above and beyond.
Great tools & solutions:
- builtwithaiclub.com: is not a solution itself, but a way to learn how to invent them. Made by an expert in quickly launching apps without code, anyone can learn how to stand up something that wows.
- AppSheet by Google is a sleeping giant. Behind the scenes of your workspace account is the power to turn almost any data process from a Sheet into a full app without much code.
- Fivetran: years ago, I sat in the BuzzFeed cafeteria at night with a lovely Python expert pal and learned how to code an ETL process by hand to get recruiting data into a warehouse. Today, you can click 3 buttons. Nuts.
How Do I Get Candidates to Accept my Offers?
Problem: In startup land, and with so many folks applying to and working at newer companies and experimental jobs, a new people analytics challenge is understanding the psychology of why candidates might decline job offers that are so expensive and time-consuming to arrive at.
How to solve it: there’s a whole load of work to be done in examining job offers and their acceptance/declines. For me, I know the solution has often been related to 1) poor employer branding (what does this company do?), 2) poor reputation (Glassdoor reviews are scarce or negative), 3) Comp and benefits not exciting or compelling, and mostly 4) Even though the role is exciting, the candidate experience felt negative and that’s a red flag.
Great tools & solutions:
Borrowing from another post, I shouted out Pave and two companies I love so much I started advising them, Pasito & Guide. This power trio would allow any team to have dynamic and colorful ways of explaining to any candidate the value of their offer, the power of benefits (once they join), and all other candidate questions in between:
