We have probably been used to making decisions based on our “feeling” based on years of experience within the People areas making assumptions or conjectures that have not very correctly led us to achieve the expected result.
In our new reality, and in future realities, having the right information, at the right time and available in the right place, will allow us to improve our decision-making process in the management of the most important asset: people. And it may sound trite, but it is common to ignore the real causes argued through the data for which people make the decision to leave companies, or that it is affecting their performance or influencing their low level of engagement.
Building a management and work culture based on a thought data driven Within the People areas, it implies challenging the existing beliefs in the organization, breaking paradigms in the management and development of people, as well as forming new skills within the teams, which allow understanding and learning about the real performance as well as evaluating the experiences provided by the various processes of People towards collaborators.
For this reason, the adoption and development of a work model based on People Analytics will make it easier for us to build a sustainable work routine over time, aimed at designing solutions and services focused on improving the management and experiences of people, as well as achieving an impact positive in the result of the organization”.
Currently, thousands of organizations experience challenging environments and situations practically every day, which can generate some uncertainty when making decisions that will impact people’s performance. It is at this moment that the have data becomes a need rather than a desire to create the right initiatives or to this to the organizational challenge that seeks to face and make the best decisions in the People Management to give them a competitive advantage.
Steps to approach People Analytics
Possibly at this point in our head the next questions: Where do we start? Is it expensive? How long will it take us? Does it involve a great organizational effort? Well, here are some points that can help you visualize that first analytical project to be carried out in the coming months.
First step. Identify and establish what we seek to solve or improve in the organization from an analytical perspective and formulate it through a question that we will answer to the organization supported by the data. For example: What are the drivers that positively impact the rate of engagement in our commercial team?
Second step. Quantify the value that carrying out this project will have for the organization, that is, our “business case” that will facilitate communicating the economic value of the impact we seek to achieve.
Third step. Take into account the maturity and governance of our business processes in human resources, as well as the level of digitization that some of these have. This will make it easier for us to have information in a shorter period of time and consolidate the various sources of information for our analyses. However, this is not all, possibly here we discover that we do not have all the necessary information and we will have to work on it.
Fourth step. Form a work team, ideally, incorporating multidisciplinary knowledge with expertise in the areas of People, data science, HR tech and project management that will enrich the execution and result of the project.
Fifth step. Have the participation of the leadership team and functional managers of the business areas, who will play a double role: one, as sponsors of the initiative; two, as active participants in the elaboration of hypotheses that describe assumptions or premises that will serve as a guide in the analytical history of the data.
Finally, the adoption of a analytical thinking on the People Management It has begun to be developed and incorporated as an integral part of the strategic and operational model in human resources, enabling and orchestrating services and solutions of greater value, with better experiences and actively listening to people. Going from the “feeling” of things to speeding up decision-making based on data.
“What is not measured can not be improved”, Peter Drucker.