The concept of measuring human capability isn’t a new one. One of the first, the DISC assessment, was first proposed almost a century ago in 1928 but is still employed today. These capability measurements set a framework for filling the wide ecosystem of the work world today. What is even more interesting, when you boil it down many of the methods we use in modern-day are evolutions from earlier efforts to measure intelligence alone. Yet in just the last few years, we’ve entered an exciting new step in the use of these instruments: The fourth generation of human capability measurement. In the past, we could have only dreamed of having contextual, scalable, and real-time measurements that could account for an evolving organization’s culture. But, before we get to this fascinating chapter, let’s look back on how we got here.
The First Generation
In the first generation of human measurement, early behavioral researchers saw that looking at raw intelligence alone was just the starting point.Understanding the disposition and capabilities of an individual required a form of objective measurement beyond just intelligence. In this genesis era of measuring human capabilities in the workplace, measurements like the DISC and MBTI were derived.
The Second Generation
In the second generation, we looked back on what we had learned and from this point of context, we dramatically advanced the science and practice of human measurement to be more reliable, valid, and scientifically rigorous. From this second deviation of measurement emerged the Big Five Personality types alongside measurements like the Hogan assessment. This is the time when we also began to explore what it would mean to build measurements tailored to the workplace such as the StrengthsFinder, which positively transformed many organizations. With these types of tests, employees were given the tools to define the strengths in their current role, albeit sometimes with a few modifications, or realize the role they were currently in didn’t let them truly utilize their strongest suits. This started to build the bridge that provided a more direct link between the test and the context it is hoping to predict in an organization.
The Third Generation
In the more recent third generation, measurements began to go digital. This was a huge step forward in science that largely improved on the original processes and started to glean information from large, comparable data sets. Being able to create true benchmarks across every user of a test was a crucial step in the evolution of this industry. In this era, game-based measurements emerged that focused on mini-games and open-source psychometric tests to try and measure behavior. Two of the more well-known examples of these are HireVue, which is a talent experience platform designed to automate workflows and make scaling the hiring process easier, and Pymetrics, a soft skills platform that uses data-driven behavioral insights and audited AI to create a more efficient, effective, and fair hiring process across the talent lifecycle.
The Fourth Generation
As we enter the fourth generation, the last century of advancement in the field of human capability measurement has started and advancement that wasn’t possible before is starting to materialize. The closer we can get to measuring what we seek to predict, the more effective our models can be. Now contextual measurements can be executed for the entire global workforce, as compared to what work samples in the past used to do for only a small, top percentage of the elite who has access to the means for an expensive executive assessment. Now, digital models can benchmark specific results by role, industry, geography, and even a specific department within a specific company—accounting for a company’s own organizational culture on a macro level. This era of instruments can also evolve their predictive validity in real-time as performance changes with the aid of machine learning. Almas, supported by the largest human development fund in the world, is excited to be the spearhead in this exciting new generation of human capability measurement.
As these more predictive, real-time, and contextual methods begin to empower businesses, there is great promise that they can overlook not only traditional biases such as race and gender, but socio-economic biases as well. Our goal at Almas is to make a dent in these kinds of biases that prevent people from finding opportunities and reaching their full potential. This in turn can only make the businesses we support more effective, efficient, and competitive.