The Power of Predictive Analysis
Organizations, regardless of their size, are now immersed in a vast sea of data and documents. The advent of the digital age has brought with it an enormous amount of information from a variety of sources. These data encompass a wide range of categories, including employee information, training data, performance metrics, and many others. These data represent a treasure trove of opportunities and knowledge, but at the same time, they can be a complex and challenging sea to navigate.
To effectively manage this wealth of data, a strategic approach and a deep understanding of the firm context are required. This involves the ability to identify and collect the most relevant and useful information and to translate such data into practical knowledge that can guide decisions and improve strategic operations.
In an era where data-driven management has become crucial, the competence to strategically select and leverage data is one of the key challenges and opportunities for modern organizations.
The vast amount of data available provides HR Analytics experts with the opportunity to extract crucial information for strategic HRM, aligning HR practices with the organization’s strategic objectives. It’s important, therefore, not to use the data merely to “snapshot” the present but to anticipate what will happen in the near future based on what we have learned from the past .
First, however, it is important to define what analysis processes are involved in Analytics (Power et al. 2018):
- Descriptive: This analysis aims to provide a comprehensive overview of the current situation, helping to understand HR data patterns and trends.
- Diagnostic: the causes of the problems or opportunities revealed in the descriptive analysis are analysed. An attempt is made to understand the ‘why’ of certain behaviours or trends.
- Predictive: Here, one enters the future perspective, using historical data to make predictions about future trends.
- Prescriptive: This is the step where data-based recommendations are made to guide decisions and actions. The objective is to provide suggestions on how to optimise HR operations or address specific problems.
As already pointed out, descriptive and diagnostic analyses are essential to gain a comprehensive understanding of reality and the past. However, it is important to emphasise that these analyses are also crucial for conducting predictive analyses as they provide the time series needed to identify future trends. The process of predictive analysis involves the ability to detect behavioural patterns, predict future employee needs and anticipate them.
In this way, HR Analytics proves to be a tool that is not just an analysis of past data, but a powerful way to guide HR towards a more strategic and proactive role in the organisation in the future. In the complexity of the modern marketplace, it is necessary for companies that want to perform to be one step ahead. This is why predictive analytics emerge as a key tool.
Specifically, we can list some benefits that arise from the multiple applications:
- Enhancing the Employee Experience: Through anticipating the needs and customising employee experiences, it contributes to a more satisfying work environment.
- Improved Time Management: Enables optimised work planning and time management, increasing operational efficiency.
- Targeted Strategic Planning: Enables companies to develop strategies based on accurate and precise forecasts, helping to optimise business planning and adapt to future changes.
- Cost Reduction: Helps identify inefficiencies and savings opportunities, enabling organisations to allocate resources more efficiently and reduce operating costs.
- Optimisation of Training: Determines employee training needs based on competence gaps and future forecasts, improving training effectiveness.
- Risk Reduction: Identifies and addresses potential risks, such as compliance issues or occupational safety issues.
To summarise, the data-driven approach to organisational management offers a number of significant benefits both individually and collectively. However, it is essential to recognise that the abundance and complexity of data requires appropriate skills and tools to fully exploit this potential.
Organisations must invest in the training and development of HR skills and the implementation of advanced technological tools. Only through this ongoing commitment will it be possible to reap the full benefits of data-driven management and drive the organisation towards success in an increasingly data-driven world.
References
Power, D. J., Heavin, C., McDermott, J., & Daly, M., Defining business analytics: An empirical approach. Journal of Business Analytics, 1(1), 40-53, 2018.
*This article is an original work of Rocco Giuliano