When I’m asked about my job title, sometimes I joke and say, “Eternal Student”. Practically, it is quite precise, considering the fact that most of my career consists of learning opportunities, which I happily grab. Aren’t we all? However, reflecting on the years, I’m pretty sure that the times I studied the most were when I was teaching.
Honored to be a statistical instructor at the local SPSS representative ten years ago, I guided corporate analysts to use SPSS software modules to deal with business questions. I recall my lectures, which included Statistics fundamentals, research methods, and data analysis practices needed to solve business challenges, as a rich learning experience for me. Being exposed to excellent learning materials, but mostly being open to students’ questions, which forced me to deal with different perspectives and illuminated dark areas of every subject I taught, all ensured that my teaching was a great way to learn.
Learn by teaching someone else
Obviously, my experience was validated by science: Teaching someone else, or even just pretending to do so, can help you learn. Studies revealed that when teachers prepare to teach, they tend to seek out key points and organize information into a coherent structure. Students also turn to these types of effective learning strategies when they expect to teach.
Encouraged by scientific proof, I’ve been sourcing the web for quite some time, searching for “People Analytics” colleagues who actually teach. I hoped to understand others’ experiences and figure out how teaching may enhance a career path in this field. Lately, I stumbled upon Sam Hill’s LinkedIn article, which summarizes what teaching “People Analytics” has taught him. Hill states the importance of generously sharing knowledge across the discipline. “Think and act open-source”, he says. In his writing, he kindly encourages practitioners to join conferences, events, and online communities, to advance their learning further, share their learning, and celebrate the success of others.
“Think and act open-source”… These words echo in my mind.
Share knowledge across the discipline
I was actually fortunate to experience the open-source culture when I started my journey with R programming. I was amazed to find answers to any of my peculiar yet common questions on Stack Overflow, a community of millions of programmers who really help each other on a daily basis. In addition, I found valuable help in R-bloggers, a blog aggregator of content contributed by bloggers who write about R. I would certainly not be able to practice R without this community. I can only imagine how super it would be to be able to ask and answer any question in the domain of “People Analytics”! How great it would be to practice coding on HR open data!
Indeed, there are excellent “People Analytics” groups on LinkedIn (e.g., People Analytics: Data-Driven HR), brilliant blogging platforms (e.g., Analytics in HR), and of course, I must mention, with respect and gratefulness, David Green, whose inspiring and comprehensive analysis are well known in this field. But all of this is not even close to the R community yet. Could open-source culture ever work in “People Analytics”?
Open-Source is where innovation happens
I believe the R community will outnumber the “People Analytics” community for a long time. But numbers are not the only condition for success. According to Matthew Mascord on OSS Watch, open-source communities may be extremely small. They start out either because someone wants something new to be built or someone intends to meet the future needs of others. In other words, open-source communities are where innovation happens.
It appears that this is exactly the case with the relatively new HR open-source initiative. Established by Ambrosia Vertesi and Lars Schmidt, this knowledge-sharing community brings open-source learning approaches to the global field of HR and recruiting. They seek to accelerate learning, close the gap between those who lead and those who lag, share best practices, learnings, and failures, and give permission to try, fail, and share.
However, it is reasonable to expect companies to object to such sharing. In today’s competitive environment, organizational data is strictly confidential. Nevertheless, there may be no real harm for business if someone shares with his professional community some “what, why, and how” with no data involved but rather pointing out general results, potential pitfalls, and key takeaways. Actually, Google does precisely that in re:Work, “a curated platform of tools and lessons, designed to help others use data and science to make things better”.
Focus on demand rather than supply
The open-source state of mind is much more complicated in “People Analytics” since practitioners must deal with a developing and immature field and internal clients within the HR department and business units. Although dozens of public case studies exist, our clients still need extra help defining the right questions and asking for the right solutions. Should open-source efforts be focused on educating the business community?
In the “People Analytics” field, focus on demand rather than supply was mentioned recently by Andrew Marritt, who develops empirically-driven HR leaders. Marritt suggests that instead of building a small team of highly capable analysts to provide a ‘supply’ of People Analytics, organizations can build ‘demand’ by making analytics-understanding a core skill in HR. Some of his activities are intended to show that techniques, such as predictive modeling or social network analysis, exist and what they can do. According to Marritt, “All analytic techniques require you to think about the workforce and HR in possibly different structured ways. Understanding them can even challenge your existing beliefs about how organizations work”.
Engage with local practitioners
Taking Marritt’s point of view into the potential open source arena of “People Analytics” led me to understand the importance of open discussion about the foundations of this field between analysts and their internal clients in HR. This can certainly be done at conferences and professional conventions. But for many, these events are too expensive or too far away. As an alternative, learning, and sharing within local meetups are more affordable and available opportunities. Meetups are quite common today for bringing people together to discuss things that matter to them, explore, teach, and learn.
Are there meetups for “People Analytics”? Absolutely! All over the world: New York, San Francisco, Boston, Detroit, Washington, Singapore, London, Zürich, Budapest, Antwerp… My next step was to find a meetup in my little corner of the world: Tel Aviv. Frankly, I really hoped to find one, but Alas! There was none!
So, would anybody in the Tel Aviv area like to pick up the gauntlet and join me in establishing such a meetup? Or, would anyone in the world who has already established a meetup for “People Analytics” like to share his experience?