HR has always been data driven in part, but with HR tooling generating more data than ever before, it’s reached extreme levels. Every aspect of employee testing, development, and performance is recorded and stored. While that’s critical for recruitment, training, and employee termination decisions, it can also be overwhelming.
Additionally, many people lack the data literacy to interpret data properly despite 89% of learning and development leaders deeming it a high priority for their organizations. Sharing too much data is more often overwhelming than insightful, especially if people miss out on the specific information they need to make decisions.
Initiatives like removing silos between people analytics and HR and teaching how to process and interpret data through workshops and courses can significantly improve data literacy. By equipping your personnel with these skills, they’ll make better-informed decisions regarding potential and current employees.
What’s relevant for whom
Sending data (or access to it) from your people analytics software to everyone who uses it is a mistake. It’s an overwhelming mountain of information, and people often only need specific points of data to make decisions related to their work. Streamlining their access to data management platforms to include just the information they need will simplify their search for and implementation of that data and avoid overload.
C-suite
C-suite normally needs high-level data such as headcount, turnover rate, hiring rate, etc. Often, delivering a monthly report is more than enough. However, some will appreciate access to dashboards with real-time numbers, where they can drill into the specific reasons behind turnover and other influential metrics.
HR managers
Traditionally, people analytics has been kept separate from HR, but integrating that into the team and ensuring everyone adopts those skill sets is crucial. You need all metrics available to you as well as data literacy to understand what they mean, how they connect, and how to integrate them into decision-making for recruitment, performance management, etc.
Departmental managers
Department managers often need access to specific performance data for the department they’re running. Here, department leads use data for optimization, development, business strategy, and for reporting to their superiors. They need to see how the department is performing, what work looks like compared to this time X period ago, how the department is doing with KPIs, and the like.
Team leads
Team leads and Scrum masters need specific KPIs and performance data for their teams. Scrum masters may benefit from having access to the same data as Department Managers – especially if they’re using methodology like Monte Carlo simulations to predict future performance, time needed for tasks, etc. Team leads specifically only need the performance data and KPIs for their teams. However, they may incidentally want access to general performance data for the company, so they can see how their team is doing in the organization.
Defining relevant data sets
HR should have access to all organizational data. However, it’s also important to take steps to ensure your staff knows how to read and analyze it.
Normally, other teams should only see what’s relevant. For example, team leads would benefit from hyper-specific data, such as how often employees ask for help, how often they miss deadlines, etc. That gives them insight into how their team performs, how trusting their members are, and how much extra support they need in terms of training, communication, and facilitation. On the other hand, department leads should only have access to that data upon request or when it’s used to communicate specific information like gaps in competencies.
Alternatives to data analysis
Not everyone in your organization comes in having the data literacy skills to make sense of numbers and statistics. Additionally, it’s not always relevant to send raw data to people who simply need answers rather than uninterpreted information. To accommodate the varying levels of competency and prevent information overload, consider sharing data in other ways for greater productivity.
Data stories
Through data stories, your data analysts and experts transform information into clear “stories” that detail outcomes, results, and the meaning behind the numbers. Advancing technology increasingly enables automation of these stories (e.g., Google’s Maps Timeline, which showcases a data story to show how many miles you walked or traveled by train or car and collates data like how much carbon dioxide you saved by walking, how many calories you might have burned, etc.).
Data stories are more accessible to the average reader. Unless more than one team uses them, it may be counterproductive to create them manually. However, if you can automatically generate data stories around team productivity, output, and team happiness, it can significantly help individual teams.
Predictive analytics
Predictive analytics uses machine learning to pull meaning from existing and historical data and make predictions automatically. This removes the need for individuals to be familiar with prediction modeling or draw conclusions from data. However, you do need people to review it to ensure the predictive models are accurate and validated — meaning you need data analysts in HR.
Whether you’re using automation to create data stories and predictions or maintain in-house data analysts to share data across the organization, data should be human driven. You need human insight to connect trends, predictions, and outcomes to real-world events, possibilities, and problems, making it imperative to have people who understand data and metrics.
Conclusion
Data gives your business the means to understand what contributes to business success, why, and how to replicate it. However, not everyone in your organization needs all available data, and sharing it can be detrimental to its interpretation and implementation. Instead, your HR department should maintain control of your data and send it to relevant personnel. You could also break it down into dashboards and create data stories to remove the burden of data analytics from team leads, executives, and scrum masters. Doing so allows them to focus on managing people and the business instead. Assess your organization’s internal needs and processes to determine how you should best disseminate information across your organization and the level of access each department should receive. Once you refine your data procedures, you’ll streamline many business operations and improve productivity among your personnel.
About the Author: Jocelyn Pick
