Recently, the concepts of Analytics and Smart Data are everywhere, even in the Human Resources’ world. This is one of the major trends being developed in technology, data, and information. But in which ways can we translate this data analysis into People’s Management, and which opportunities should not be missed in this context?
I am aware that this new trend has been given very different names, on the internet, and in the different media that we consume day by day. Because of this, I think it is important to contextualize first. People Analytics uses the data and information available to build predictive models, enabling us to respond to business needs more proactively and design more customized policies and processes. This approach allows us to explore concepts and ideas that empower us to be more efficient in making decisions and responding to business challenges; for example, reducing the voluntary turnover of the sales force by impacting directly the most important business KPIs.
Years ago, in Human Resources, we began to collect and record data that allowed us to detect trends, to know the impact of our actions and to make more justified decisions. This approach has helped us to be a more competitive company by implementing measures that reduce absenteeism, increasing diversity in all areas or making the talent attraction process more efficient.
Currently, we are gathering information that helps us understand and solve specific problems through the employee’s experience in the processes of attraction, development, loyalty, compensation… The data mining and monitorization of information enable us to assess the effectiveness of our initiatives and take a step further by adjusting the design to the real needs of people. For example, efficiency in the ways of working, the impact of the training, the adjustment to the selection process or the satisfaction of our employees are some of the variables that we consider to be more agile in our processes.
Modern technologies allow us to be more ambitious by applying Big Data tools to analyse the behaviour of our employees and to be more precise in the decision-making and solutions’ design. Solving the challenges we face means having a specific goal that meets a business need. For this, we need to debug data, select relevant information, examine what gives value to our hypotheses and test it. At this level is where the challenge arises: Big Data or Smart Data?
The branch of Smart Data is becoming more common, but getting it right on how to apply all the information we have within our field is very difficult. And this is what is going to add real value. Analysts work on developing predictive models of loyalty, the best ways of leadership, personalization of incentives, etc. These models are incredibly valuable, but one of the most challenging obstacles of People Analytics is not only modelling itself but also the implementation of the changes.
What does People Analytics need to be an efficient tool itself? Firstly, we must standardize in an automated manner the collection of information in all areas of Human Resources to ensure that the data has the same format and is regularly updated. Once a standardization has been reached, it is necessary to define the challenge to which we want to respond and to involve all the areas that will benefit from the predictive model. For example, if the model seeks to detect which is a better profile for the sales force, the commercial area management team should be involved in the selection of variables that will be part of the hypothesis we will test, but we will also include the compensation team, talent, training and all those who have information that is relevant to achieve our goal.
Another opportunity will arise when applying Artificial Intelligence and Machine Learning to measure and analyse the fit of a candidate for a position. The use of this technology will allow the analysis of the candidate’s profile through the voice, non-verbal communication, and facial expression among others, in an accurate and highly reliable manner.
In this area, a bright future awaits us. A flow of valuable information does not cease and we need to know how to implement it effectively. But ahead, we have major challenges ranging from collecting data to modelling. What is certain is that the path of Smart Data has no backward. Any company that expects to compete with solvency needs to see the advantage of its benefits. If not, it will be doomed to disappear.