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When Confucius said ‘a journey of a thousand miles begins with the first step’, he may have been talking about People Analytics. All organizations , including the ones at the cutting edge such as IBM and Google, started their People Analytics journey with the same basic tenants. This article outlines the art and science behind starting a People Analytics practice, and laying a strong foundation for future scale.
The fact that you’re reading this article means you’re convinced at some level that technology in HR has some value. Let’s stretch that belief a bit further and say People Analytics also matters. In fact, it matters a lot. The insights derived from HR Information Systems (HRIS), from engagement surveys, and from various other sources help inform the broader HR community and equip business leaders to make better decisions - that ultimately result in superior performance for the organization.
For example, we can identify talent in critical roles across the organization by geography, function or product. Pair that data with overall employee engagement in these pockets, and finally triangulate with some predictive analytics based on turnover data to identify key employees that might be a retention risk based on tenure, time in role, market demand, etc. Taking appropriate steps to retain a large percentage of these employees can mean business continuity and smooth delivery of strategic goals.
There are different levels of effort and capabilities required to create value from People Insights. Let’s look at these levels from a People, Process and Technology perspective for a better understanding.
Beginner: Respond to data and analysis requests from HR partners or directly from business leaders. Pull reports from HRIS, manually check and clean errors in data, and join reports and create pivot charts if needed to show aggregates. For example, list of all retirees from a manufacturing facility in Texas for the last 5 years, or number of new hires year-to-date in Sales by product.
"All organizations , including the ones at the cutting edge such as IBM and Google, started their People Analytics journey with the same basic tenants"
Intermediate: Build an HR Database that connects all the disparate data sources and applies business rules to automatically check and clean incoming data. Create daily/weekly/monthly snapshots to track changes over time. Use the database to query data in real-time for ongoing requests. For example, year-over-year comparison of revenue per employee by product or turnover trend by season in a specific market.
Advanced: Create a self-service HR portal supported by the HR database. Integrate single sign-on(SSO) to administer data access based on user country, region, function, role, etc. Build filters for org hierarchy, geography, function, product, and employee demographics such as gender or generation. Publish dashboards by subject area and train HR partners on how to access and use the portal to consult with business leaders. For example, help leaders understand in real-time where is their workforce located globally? Which functions are growing, and which ones are shrinking? What percent of females are in leadership positions? Are we growing the minority workforce at an acceptable rate? Etc.
Building and growing a People Analytics function requires planning, investment and focus. But the return on investment is also very high in terms of operational efficiency, scalability, agility, accuracy and most importantly–ease of data availability that informs high quality decision making across the business.