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 in which I studied the most were the times when I had been 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 myself. 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 get an impression of others’ experience and figure out how teaching may enhance a career path in this field. Lately, I stumbled into Sam Hill’s article on LinkedIn, which summarize 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’ve been 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 to 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
R community will outnumber the “People Analytics” community for a long time, I believe. 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 is 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 is a knowledge sharing community, bringing open source learning approaches to the global field of HR and recruiting. They seek to accelerate learning, close the gap between those who leads and those who lags, share best practices, learnings and failures, and give a permission to try, fail and share.
However, it is reasonable to expect companies’ to object such sharing. In today’s competitive environment, organizational data is strictly confidential. Nevertheless, there may be no real harm for business if someone share with his professional community some “what, why and how”, with no data involved, but rather pointing out general results, potential pitfalls and key takes away. 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 have to deal, not only with a developing and immature field, but also with internal clients within HR department and business units. Although few dozens of public case studies are out there, our clients still need the extra help in defining the right questions and asking for the right solutions. Should open source efforts be focused on educating the business community?
Focus on demand rather than supply, in the field of “People Analytics”, was mentioned recently by Andrew Marritt, who develops empirically-driven HR leaders. Marritt suggest 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 modelling or social network analysis do 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 in 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… For me, the next step, was simply 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 Tel Aviv area like to pick up the gauntlet, and join me in establishing such a meetup? Or, would anyone in the world who have already established a meetup for “People Analytics” like to share his experience?