People Analytics: Your very first step in a long journey
People Analytics: Your very first step in a long journey
People analytics is gaining special interest in the Israeli HR community these days. HR leaders in all kinds of organizations start to prepare their plan for 2018, and many of them finally set the major goal: Use people data to support business decisions. However, they share a common barrier, which is embedded in the simplest question: How should I start?
Plenty of “first step” advice. Which to follow?
If you are an HR leader who looks for advice, don’t start with Google search for “People Analytics first step”. Or do start with these search terms, and deal with more than 10 million search results. Any HR consultant that you can think of, and even any HR tech supplier, have already dedicated at least one blog post to this subject. The consequence is a flood of advice, tons of paragraphs about data integration and platform selection, and so many buzzwords about data science and machine learning, which will probably make you feel aversion in regards of the whole journey.
Instead, I recommend starting your journey by following only one step: Listen to prospective project sponsors. You can read about it in detail, in the new book: The Power of People: How Successful Organizations Use Workforce Analytics to Improve Business Performance, by N. Guenole, J. Ferrar and S. Feinzig. In a nutshell, these authors suggest that in your first few days of the People Analytics journey, you should explore prospective project sponsors. “A project sponsor is a person or group who provides support (through financial means or personal endorsements) for a workforce analytics project or activity”, they explain.
Start interviewing the influential leaders in your organization, and identify the source of support and possible projects for your new People Analytics function. “The more conversations you have with prospective project sponsors early on, the more likely you will be able to separate good projects from really exceptional projects”, the authors conclude. These interviews will help you to prioritize the projects, based on real business questions that impact your organization.
Prepare for a conversation with influential leaders
Are you comfortable to start a discussion about People Analytics in your organization? Most HR leaders that I’ve met so far would respond negatively since they are not familiar enough with the complexity of the People Analytics domain. It may be clear that People Analytics goes beyond the HR department scope, as opposed to old-school organizational researches. HR leaders might have heard that it is all about business performance. They also might have a clue about different kinds of data, which can be used not just for inference but rather for prediction. However, without a deep understanding of this new field of practice, they may not feel comfortable to start conversations with influential leaders in their company. They surely need a short, yet thorough, preparation. A parsimonious definition of the People Analytics domain, that close the gap between c-level business questions and the everyday tasks of the people analyst, is probably most useful at this stage.
For that purpose, I’ve suggested, in a previous blog post, a definition for People Analytics, which contain five perspectives. It has a top-down structure, describing People analytics through different organizational perspectives, which emphasize not only the complexity of this field but also its vast influence in different aspects of activity in the organization. Explicitly, I suggest to describe this domain, starting from C-level and business perspective, go through HR processes that derived from it, and through IT and HRIS that enable to manage it, and end up with a data science perspective and the role of the People Analytics leader:
Understanding this scheme, and specifically, the way each level in this structure is influencing and being influenced by the nature of the level on its top can help HR leaders to get prepared and feel more comfortable in their first communication with business leaders in the organization.
Make your own interview guideline
A conversation with business leaders should not be spontaneously handled, but rather planned in advance. Particularly, it should be clear what topics to bring up and how to develop each topic during the conversation. An interview guideline is a useful tool for that purpose.
When I approach a new organization, with the aspiration to start a People Analytics project, I base my interview guideline on the aforementioned five perspective definition. But before I start designing my guideline, I write down a short list of objectives. Having a clear list of objectives ensure that the right kind of information actually raised during the interview. In other words, it keeps the interviewer from getting lost during the interview.
For example, here are two possible objectives for an interview:
“Explore metrics of desired business outcomes that may lead to a funded analytic project.”
“Discover sources of data, people with access to data, people who assist in data preparation.”
The structure of an interview guideline is straightforward: Start with a short introduction to present yourself and the purpose of the conversation, and follow with some warm-up questions that establish rapport. Proceed with open-ended questions about each of your topics and probe to get specific examples whenever needed. End with some wrap-up questions that conclude the subject, and give the interviewees an opportunity to ask you anything in response to their experience, before you thank them and complete the interview.
For example, here is a question from a guideline based on the five perspectives (C-level and business): “What are the most important outcomes in your line of business? How does it measure? Probe for metrics: sales, customer services, safety, etc.”
Qualitative research is beneficial
Communication skills are considered crucial for a People Analyst, mainly due to the need to communicate research findings and “tell stories with data”. However, the ability to conduct a conversation with business leaders is important as well. When everyone in the field of People Analytics is obsessed with data and predictive models, it is worthwhile to remember the benefits of the traditional qualitative research methods. After all, the key to success in People Analytics is asking the right business questions. It must come first, long before analyzing data sets, using sophisticated machine learning models or creating an amazing visualization. These “right questions” are actually the outcomes of good conversations with business leaders.
I encourage any HR leader to find those right questions using the principles of in-depth interviews and scan the organization with a methodological tool. Sometime it may be even a good idea to consider a professional interviewer for this task. Such interviewer may expand the guideline questions, in order to achieve a deeper understanding of certain subjects, lead the discussion to various directions, and probe for detailed responses to each question.
The whole point in an in-depth interview is to create the right atmosphere for rich content responses: open-ended questions enable participants to express themselves and tell “their own story” with unique terms and words. This, in return, may reveal unexpected and unusual themes and subjects. Moreover, during a professional interview, participants are encouraged to express themselves freely, share opinions that may be deviant from consensus, and get a sense of importance, which may lead to commitment and involvement.
Have any thought or question about your first steps in the journey of People Analytics? Please share in a comment.
About the author:
Littal Shemer Haim brings Data Science into HR activities, to guide organizations to base decision-making about people on data. Her vast experience in applied research, keen usage of statistical modeling, constant exposure to new technologies, and genuine interest in people’s lives, all led her to focus nowadays on HR Data Strategy, People Analytics, and Organizational Research.