When I was a child, anyone over 1.80m was considered to be tall. Genetic evolution, dietary habits and health status in childhood have gradually pushed up the threshold, so that our reference points today are different. Just stand outside a school when the children are leaving, and you’ll feel smaller by the day.
We are tall or short (a simple, biased opinion) based on whatever we use as a reference. Despite the fact that height is an objective and measurable dimension, it’s a figure that nevertheless gains greater significance if we understand the factors that influence it and how it evolves, and compare it with other points of reference (which are also evolving).
How do companies measure people?
Companies likewise need to measure people, as they do other strategic assets, in order to achieve results and grow. They carry out interviews, assess, gauge the level of engagement, carry out surveys on the value of training imparted, and even analyse the reasons why an employee may decide to leave the company, so that they may improve their loyalty mechanisms.
All of these issues are usually resolved through interviews or surveys, in the hope that response rates (and honesty rates) will be acceptable.
But, given the technological resources we now have available, you have to admit that these approximate systems are no longer enough. We have the data, the tools and the capacity to be more precise, but are we prepared to apply this new analytical mentality to talent management?
The analysis of talent management: People Analytics
The value of what we now call People Analytics is based on the premise that decisions regarding people management are the most important decisions that a company will ever have to take, and the ones that will have greatest impact. Achieving extraordinary results is possible only if people decisions are taken fairly, accurately and promptly, and if companies start to take an interest and make progress in the field of analytics so that they are better able to learn from their past and look to the future.
In a volatile and changing environment, experience and intuition are no longer enough for good, timely decision-making. We have to make better use of the wealth of data now available thanks to digital growth; we have to really milk such data to glean information from it which will help and inspire us to be a step ahead of the game, shedding light (and new questions) on issues such as:
- What candidate profile will have greater potential in our company?
- What competences will have the greatest impact on certain groups?
- What differential skills will be required in our business, and by when?
- Where can we find such skills in our organisation today?
- What is the expected turnover in key groups, and when will it happen?
At Ferrovial, we are convinced that digital transformation is also an opportunity to improve our methods, and we are convinced too that in the future it will be necessary to measure more, and better. We’re only just starting out in the field of talent analytics, but we want to help our businesses to go down this route adding value and linking in with real needs in each context.
People management takes place in a world of relationships, emotions, perceptions and biases, and therefore data must be an increasing source of evidence and a solid reference point for decision-making. It’s no longer a question of “human resources”, we all manage persons and, increasingly, data, bots, and internal as well as external processes.
Another reference point we should be familiar with is Google, a business based on the value of data and which has already, for some time now, been investing in and committed to this technology as a means of gaining competitive advantages in talent management. Every company should apply these concepts in their own particular context and to the best of their ability, in order to ensure that they are investing in a proportionate manner and adding value to their business.
And, lastly, if in your own organisational context you also believe that knowing is not enough, that you need to understand, anticipate and take more objective and timely decisions within your area of responsibility, get some training in analytical skills, collect data, look for evidence, and learn how to interpret and express both data and evidence in order to exert influence. There’s no time to lose (some of these algorithms are already overtaking us [on the left]…)
Data and data measurements are sometimes worth more than gold… so it’s time to take some measurements!