People Analytics

People Analytics uses business intelligence with a focus on people. It can be described as a methodology based on mathematics, statistics, and modeling, allowing us to gather evidence and predict patterns in behavior, productivity, and outcomes of the organization's people. This is crucial for decision-making.

In other words, it's a tool that enables the analysis of data and information about the people in your organization. This way, you can conduct a follow-up from Human Resources (HR) or Talent Management.

There are many benefits of using People Analytics in companies. For instance, it allows for the improvement of the predictive index, based on the analysis results. It reduces costs in terms of money and time as it enables decision-making based on statistics. It also eliminates the waste of time in manual data creation and analysis, and improves the well-being of co-workers by eliminating unnecessary tasks and processes. Additionally, it allows for reliable tracking of decisions made and seeing in real-time if they are effective or not for further confirmative or corrective decision-making.

The most important aspect when using People Analytics is choosing the right metrics. Some of these could include:

• Performance, activity, and productivity of teams and individual profiles.
• Efficiency in using human and process resources.
• The work environment: motivation, satisfaction, and commitment.
• Performance evaluation and discrepancies in expectations.
• Adherence to corporate culture.
• Efficiency in recruitment, selection, training, and development of HR.
• Ratios of absenteeism, turnover, and loss of talent, and the associated variables.
• Analysis of the return and costs associated with personnel in projects and business lines.

The challenge is to select data that is truly interesting for us. We need to ask ourselves the right questions to add value to organizational and business improvement.

What are the methods of People Analytics?

• Descriptive Models: This type of analysis is basic, like using dates and information summaries in tables.
• Predictive Models: This involves future analysis that predicts what will happen based on current data and trends.
• Prescriptive Models: Based on predictions, this type of model analyzes the effect and impact of intervention actions for prevention. It involves data collection, action recommendation, and prevention of potential impacts to facilitate decision-making by identifying the best solution among all possibilities.

In People Analytics techniques, we integrate statistics, experimental designs, model-oriented design, and the relevance of question formulation for organizations and businesses. All of this aims to obtain the appropriate data to answer these questions, applying scientific criteria and systematic records that lead us to evidence and facts to evaluate the results and propose action plans.

What are the first steps to apply People Analytics in your organization?

First, we need to understand that the operation of People Analytics must be contextualized and adapted to the particularities of each organization and the available data sources.

Generally, we can propose the following sequence of work:

• First Phase: Formulate the right questions and propose hypotheses related to the HR objectives you want to address.
• Second Phase: Define which data, indicators, and metrics are relevant to the formulated questions.
• Third Phase: Design a data analysis model suitable for the questions posed.
• Fourth Phase: Create a procedure for data collection and the application of techniques and measures.
• Fifth Phase: Collect, process, and analyze the data. In this step, you should use data analysis tools like R, Excel, Python, and SAS.
• Sixth Phase: Generate reports on the results using data stories, as a basis for decision-making and actions directed at improving specific aspects of people management or process organization.

In operational terms, some key considerations for the effective practice of People Analytics include:

• Designing People Analytics projects with a long-term vision, giving continuity to the measurements, analyses, and experiments over time.
• Framing and aligning the research design with the particularities of the organization, aligned with its activities and business.
• Starting with initial pilot exercises of selected metrics and indicators, considering data limitations, often lacking structure and perfect organization for analysis.
• Focusing on the realm of people management data, avoiding overextension into other areas, and working with professionals trained in data analysis and HR.

This serves as just an introduction to the applications of analytics in Talent Management. What are you waiting for to continue learning and start applying these insights in your organization?