Once you have established solid processes for data collection, storage, and management, the next
step is to analyze and interpret your HR data to generate actionable insights. This chapter will discuss
various techniques for data analysis, as well as the role of data visualization in communicating results
and driving data-driven decision-making.
Descriptive analytics is the most basic form of data analysis, focused on summarizing and visualizing
historical data to identify patterns and trends. Descriptive analytics techniques include:
Data Aggregation: Combining data from multiple sources to create summaries or reports, such as headcount by department, average time to fill open positions, or employee turnover rates.
Data Visualization: Presenting data in visual formats, such as charts, graphs, or dashboards, to make it more understandable and accessible to decision-makers.
Diagnostic analytics goes beyond descriptive analytics by digging deeper into the data to uncover the
root causes of observed trends or issues. Diagnostic analytics techniques include:
Correlation Analysis: Examining the relationships between variables to identify patterns or associations, such as the correlation between employee engagement scores and retention rates.
Regression Analysis: Modeling the relationships between variables to determine the impact of one factor on another, such as the effect of training programs on employee performance.
Predictive analytics uses historical data to forecast future trends and outcomes, helping
organizations make proactive decisions and identify potential risks or opportunities. Predictive
analytics techniques include:
Time Series Analysis: Analyzing data over time to identify trends and predict future values, such as forecasting employee turnover rates or hiring needs.
Machine Learning Algorithms: Using advanced algorithms to build predictive models based on patterns in historical data, such as predicting employee attrition or identifying high potential candidates
Attrition Predictive Dashboard – Agile HR Analytics’ Solution
Prescriptive analytics goes a step further by recommending specific actions to optimize outcomes based on the insights generated from predictive analytics. Prescriptive analytics techniques include:
Optimization Models: Using mathematical models to identify the best course of action under various constraints, such as allocating resources to maximize employee engagement or minimize turnover costs.
Simulation Analysis: Testing different scenarios to evaluate the potential impact of various decisions, such as the effect of different compensation packages on employee retention rates.
Data Visualization and Communication
Effectively communicating the results of your data analysis is critical for driving data-driven decisionmaking and fostering a data-driven culture within your organization. Key principles for successful data visualization and communication include:
Simplicity: Choose clear and concise visualizations that convey your insights in an easily understandable format.
Relevance: Tailor your visualizations and reports to the specific needs and interests of your target audience, focusing on the most relevant and impactful insights.
Interactivity: Use interactive visualizations and dashboards that allow users to explore the data, filter results, and drill down into specific details.
Storytelling: Present your insights in the context of a compelling narrative that highlights the key findings, implications, and recommended actions.
Tip: Tailor your data visualizations and communication style to your audience’s needs and preferences. Keep your visualizations simple, intuitive, and focused on the key insights that drive decision-making.
By mastering these data analysis techniques and embracing effective data visualization and
communication practices, you can transform your HR data into actionable insights that drive strategic
decision-making and improve organizational performance. In the next chapter, we will discuss best
practices for scaling people analytics, measuring its impact, and exploring future trends in the field.
There is a lot of “free” info out there about HR functionality, team building and improvement, but none of them compare to our data-driven, practical and real world guidance, summarised in this digestible and uncomplicated handbook.