“In God we trust; all others must bring data.” – William Edwards Deming
Note: This blog post is a contribution to the #SHRM19Blogger website. If interested in discovering other amazing HR bloggers, please click the link to read other posts!
I took a stats class in grad school. I was initially excited about the class until I began swirling down the rabbit hole that was the complexity of SPSS, which was the computer program we used to plug in numbers and analyze data that I had no idea how to analyze!
How I passed? I have no idea, but I luckily did, or I may still be putting formulas into SPSS!!!
Whatever my struggles with sophisticated algorithms and formulas, I am a datahead! Data and numbers are POWERFUL tools that help all professionals make better business (and many times personal) decisions.
As has been written and talked about endlessly, it seems, HR has been slow to accept analytics as a tool to advance HR departments, businesses, or the profession. However, that tide has been changing quickly over the last decade or so.
Recently, I had the opportunity to discuss analytics with Giovanni Everduin, managing partner of The ETHNICITY Group, and a global expert on Organizational Strategy, Analytics, and HR.
Giovanni has two sessions at #SHRM19 titled: People Analytics for Beginners. One of his sessions will be Wednesday 06/26/2019 11:30 AM – 12:30 PM. My interview with Giovanni is below, and if you’re going to #SHRM19, make sure you check his session out.
PL: Thank you for taking time to discuss your session with me. I don’t wish to repeat questions from your previous interview, so I appreciate your willingness to let me think differently about this approach. Let’s begin with this: What metrics should every HR pro know about their business and/or organization off the top of their head?
GE: Well, before even getting to any HR related metrics, I believe a real HR pro needs to know core business metrics like revenue, expenses, EBITDA, profit margin, and cost-to-income. Then you probably want to know some measures around customer satisfaction, like net promoter scores, to understand the qualitative side of things. Depending on your industry, there may be more specific metrics that are relevant. From an HR perspective, again depending on industry, geography, and strategic business objectives, I would say metrics like Revenue per FTE, Profit per FTE, Time to Productivity, New Hire Failure Rate (I call this the burn rate – how many new hires resign or are terminated within the first year), and regrettable turnover in critical segments are very useful and at the strategic level that CEO’s and Boards are interested in.
PL: What other metrics do you believe are important for HR professionals to begin measuring and tracking?
GE: There are many, but for me personally I like looking at things like unplanned absence rate and cost and any solid measures around employee productivity. I would also look at granular engagement scores (beyond the headline number and only if it has been validated to directly relate to productivity or quality). Then there are numbers of more typical measures that are interesting like Time to Fill, Offer Acceptance Rate, Internal Growth Rate, HR Expenses per FTE, Layers and Spans of Control, Staff Cost as a percentage of Operating Expenses, and Diversity & Inclusion related metrics.
PL: For me, I am NOT a complicated math person! Addition, subtraction, division, and multiplication are my bread and butter. But I am so fascinated with metrics and analytics. I value them, but sometimes get intimidated by the formulas, or trying to measure something that may not be obviously measurable. Do you have any advice for people like me?
GE: I’m also not a math person myself. Whenever I speak at events people typically tell me that they are intimidated by all the talk of algorithms and advanced statistical analysis. Truth is, you don’t really need any of that to get started with HR analytics. Subtraction, division, and multiplication, a basic Excel spreadsheet, and some common sense actually go a long way! That’s why I do an exercise in my talks where we calculate the cost of absence with basic pieces of data that every HR professional has access to. Everything is measurable, even if not directly. You can always use correlations between different constructs as a proxy. Don’t get intimidated by what you could be doing; get excited by what you can be doing today!
PL: Many may believe that metrics are universally accepted by organizations. However, this is a fallacy! There are plenty of CEOs, Executive Directors, or managers who don’t value metrics, let alone HR metrics. What can HR professionals do to make a compelling business case for the use of metrics with a CEO or boss who doesn’t value or believe in the value of metrics?
GE: If a CEO doesn’t believe in any metrics, it will be hard for the HR person to convince them otherwise. Then again, if a CEO doesn’t believe in any metrics, he or she will not likely remain a CEO for long. I don’t see how you can manage a business – including its customers, markets, regulators, shareholders or even employees – without the use of metrics and data! If it’s the value of HR metrics that’s in question, the solution often is not around the metrics, but around the relevance of them to business results. As long as HR metrics drive or impact business results, I have yet to meet the CEO that isn’t interested. For metrics and data to be compelling, you need to be able to tell stories with the data. Storytelling is a critical and somewhat new skillset for HR, which I do believe still has a lot of room for improvement. The same data point can be used to tell multiple stories (even opposing ones if you are a good story teller!), so again it is critical to link your story to business outcomes and leverage business language to make it relevant to your C-Suite.
PL: Switching gears from the C-Suite to the frontline, how do you convince managers or supervisors to value and use people metrics in their daily tasks? Sometimes, they may not value metrics due to other priorities or focuses. Or, is it important to “sell” people metrics to frontline staff?
GE: Show them, don’t tell them or “sell” them. In my experience, people are always open to embrace things that add value to their lives or businesses. If you can show managers or frontline employees how people metrics and analytics can make their lives easier, better, or more successful, I doubt anyone would resist. If your metrics are not relevant or critical enough for the organization’s performance and success, they will be prioritized by default and frankly speaking – rightly so. If they are, but people are unaware of it, it’s the role of HR to showcase the value. In an age of ever increasing stimuli and subsequent distractions, people evaluate inputs based on usefulness for them, not usefulness to you.
PL: In our correspondence, you mentioned the term “sentiment analysis?” Can you please go into detail about what this means and how it fits into an HR context?
GE: Sentiment Analysis is part of Natural Language Processing, and relates to deriving emotion or “feeling” (categorizing it into positive, negative, or neutral) from a body of text using machine learning. I think this is a super exciting new tool for HR professionals as it allows us to get value out of a treasure trove of data that was earlier logistically impossible to utilize unstructured text. Think about it, the wealth of insight that every organization has within the free text data of their Engagement Surveys, Exit Interviews, Performance Appraisals, or Interview Feedback Forms. The problem is usually that, because its unstructured, qualitative data, it was nearly impossible to analyze it and extract structured meaning. Now, with natural language processing and more specifically sentiment analysis you can – in real time! During my talk at SHRM 2019, I will give a simple but cool example of how Qlearsite, one of the People Analytics startups that I advise, used this technology to drive real business value for a Fortune 500 firm.
PL: Would you recommend any resources, whether blogs, books, articles, that can be of use for a novice wishing to start up a people analytics program in their HR department?
GE: Where to start! The good news is that there are now a ton of resources available for people getting started or already maturing on their journey. Richard Rosenow, who works in People Analytics at Facebook, has put together an amazing starter kit on his LinkedIn page, which I highly recommend: https://www.linkedin.com/pulse/people-analytics-starter-kit-richard-rosenow/.
David Green is another person to follow within the People Analytics space. David is the number one curator of anything written, published, spoken or happening within the space, and he publishes these amazing monthly overviews of all the latest and greatest: https://www.myhrfuture.com/blog/2019/4/4/the-best-hr-and-people-analytics-articles-of-march-2019.
In terms of books, there are four books I would recommend to get started or keep moving. In no particular order, they are:
- Work Rules – Laszlo Bock
- People Analytics for Dummies – Mike West
- Storytelling with Data – Cole Nussbaumer-Knaffic
- The Power of People – Jonathan Ferrar and others
Lastly, I actually contributed a few stories and anecdotes to The Power of People myself. For those interested, I’m also including links to some of my own writings on People Analytics:
Giovanni Everduin, SHRM-SCP, managing partner of The ETHNICITY Group, is a global expert on Organizational Strategy, Analytics and HR. A Harvard Business School alum, he serves as Senior Advisor for HR & Organizational Development at Boston Global – a Harvard affiliated consultancy. He is also Senior Advisor for Qlearsite – a People Analytics company and sits on the advisory board of PeopleCart, a Social Rewards & Recognition company. Giovanni is a passionate writer and speaker on The Future of Work and People Analytics. He is featured in the analytics book “The Power of People”. In his spare time he and serves as Creative Director for a contemporary fashion label and recently produced an award winning documentary on Women Empowerment.