People Analytics: Where Do We Begin?Add bookmark
As an executive consultant in the employee engagement and motivation space I spend a lot of my time with HR professionals from organizations in just about every industry, and just about every part of the world. This access provides me with a window into their challenges, their successes, their needs and their concerns. Our conversations touch on recognition and performance management and coaching and leadership, among many issues. But the topic I hear the most about is HR or People Analytics.
HR organizations have long aspired to be strategic partners to the business. We want to be able to influence both the thinking and assumptions of leaders and the direction of the organization. Data and statistics is the language of senior executives, so to play in that space HR needs to come similarly armed. People Analytics provides our function the tools to truly be a strategic partner.
I have worked in the HR space for over 30 years. I spent many years on corporate HR staffs at Fortune 100 companies directing employee research and analytics teams, and I have led survey and analytics practices in consulting firms. I have seen firsthand the power of people analytics to shift the thinking of leaders, shine a light on critical organization issues, and drive actions that have significant impact on organization success. I know through my own experience that analytics is hands down the best way for HR to influence the direction of the organization and be that strategic partner and insights resource.
The reason why is easy to see. Numbers allow us to quantify impact. They identify linkages between actions and reactions. Analytics can help HR separate the nice to know from the need to know, and direct us to those policies and practices that will help the organization achieve its objectives.
Without the clarity that data provides, knowing what the right thing to do is hard. Those of us in HR can guess. We can speculate. Or we can know for sure. That’s what People Analytics brings to the table. We can propose actions and changes to senior leaders with the confidence that comes from knowing that the numbers back us up. And which of us in HR wouldn’t want that?
But easier said than done, right? The promise of People Analytics is clear, but the path to implementing analytics is much less so. Implementing analytics in an organization suggests the need for datasets and software and spreadsheets and statistical interpretation and data visualization. Creating an analytics function seems to bring even more complexity, potentially involving data scientists and programmers and on and on and on. Despite a high level of interest in implementing people analytics practices, the cost of entry seems very steep indeed. HR teams see the value of analytics, but are perhaps intimidated by the perceived complexity.
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Remember Occam’s Razor? It’s the maxim that says that of any given set of explanations or assumptions, the simplest is most likely the correct one. The reference to “razor” refers to the shaving away of unnecessary assumptions. Let’s shave away some of these assumptions about the difficulties in implementing people analytics in organizations.
Our organization doesn’t have access to the data needed for people analytics. Does your company conduct employee surveys, such as employee engagement, onboarding or exit surveys? Do you have access to HRIS data? Guess what? You’ve got the data you need to get started.
We don’t have the analytics software necessary to do analytics. If you are outsourcing your survey to a consulting partner, it’s likely that partner can provide the tools you need. Comparisons to benchmarks? Done. Demographic analysis? Check. Download data into spreadsheet software? Not difficult. Blend survey data with business performance metrics? Not every survey partner provides this feature, but the best survey firms can do this easily.
We don’t have staff with statistical analysis training or expertise. In my experience, the simplest statistical procedures are usually the best. A comparison of percent favorable/neutral/unfavorable scores across organization units or job types can speak volumes. Most survey reporting tools enable testing for statistical significance. Averages and between group differences can go a long way to helping us understand what is working and what isn’t, and what to do next.
I could go on, but I think I have made my point. We have a lot of assumptions about people analytics. It’s hard. It’s complex. It’s “sciencey”. We need to stop overcomplicating things. People analytics is within our grasp.
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To be completely fair, what I have described above is a very simple, entry-level approach to people analytics. There are lots of companies that have moved way beyond this. It can, and does, get way more complicated. But complicated is not where we need to start. We can make a significant impact in our organizations with even simple analytics. Let’s begin with simple and entry-level, and evolve from there. We don’t need to boil the ocean. We just need to wade in a bit.
This quarterly column is intended to be a guide to the world of people analytics. Not the theoretical, high concept and high complexity type of people analytics, but the kind that is doable in the average HR organization. The kind that can be done relatively simply, but shines a clear light on topics that are essential to organization success. We will walk through creating an analytics focus and strategy, working simply with data, and sharing the results of analytics processes with leaders. We’ll discuss real-word examples of how real-world analytics were used effectively in organizations, and the lessons learned from both effective and ineffective analytics.
At the end of the day, the objective of people analytics is to enable good, data-based decision making about people in the organization. It’s a strategic objective, but not a difficult one.
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