As 2020 winds to a chaotic close, Abakar Saidov envisions a much brighter landscape — at least across the talent acquisition and management space.
The CEO of Beamery believes the coming year will be marked by using data to predict and recommend talent moves, ensuring that artificial intelligence no longer goes unchecked. Such data also will be used to evaluate talent based on more than resume-listed skills, combatting “garbage” talent data and moving behind lip service paid to diversity, equity and inclusion efforts.
Saidov, whose firm recently launched an AI-driven digital data hub that uses graph technology and deep learning by tapping into more than 1 billion data points, explained his predictions in a recent interview.
What’s your sense about how HR and TA professionals will use data to predict and recommend talent moves in 2021?
What some of the modern technologies are doing is creating ways to understand intent behind what people are, what they do and what they want to be, and connecting that with where they come from through a lot of concepts that exist on the consumer side. So, for example, news feeds on social media are constantly learning about your preferences. In an ideal state, the company is actually learning about their employees’ preferences, intents, direction around things like skills and where they want to be, and then marrying that up with where the business is going — organizational demand and supply.
What sort of pushback will we see from employers around the use of AI to secure a more diverse workforce?
The historical pushback has been bias when you’re trying to make a specific, point-to-point hiring decision. AI is much better at seeing patterns than people. It’s up to us to make decisions based on those patterns. What’s much more prevalent in AI for HR is actually giving your consent to say use my data to give me a better job or a better career rather than what’s happening in consumer markets. You know that old adage is, if you’re not paying for something, you are the product, whereas on the HR side, you’re doing so voluntarily.
How will a shift from skills databases to skills clouds based on talent graphs drive the ability to mine meaningful data and focus more on the dynamic nature of people and employment opportunities?
A simple skill database is static. Take a software engineer that knows C++ with 10 years of experience. That may have been five years ago. They’re no longer interested in that programming language and not working in it. The idea of a skills cloud is creating cross-referential data about the direction of where somebody is going. So you’re creating inference and intent concepts rather than match to three skills. Because then you’re always struggling with the problem of verification and understanding quality, whereas the concept behind a skills and capability cloud is that you’re creating a multidimensional viewpoint.
How can organizations ensure that they’re working with the most accurate, consistent and current data to avoid what you’ve termed “garbage” talent data?
It’s very easy to be tempted by laziness and make decisions based on insights because you have to get through a million candidate records and want to get that down to 10,000. The challenge is, are those actually good? The outcome should be productivity and a meaningful impact on jobs. Being able to actually tease out whether it’s skill-backed data or intent vectors creates a much more useful way of looking at talent. Companies have typically looked at either an employee, contractor or applicant rather than a horizontal layer of people who can contribute something to my business, and they are evolving all the time and then moving. And so, the manner of employment shouldn’t really matter.
How will appointing a diversity, equity and inclusion officer hold organizations accountable on this issue and move beyond lip service?
The lip service that I’m describing is a lot of organizations have “diversity targets.” They’ll say, we need to achieve X. But the other two words are equity and inclusion. It doesn’t matter if you have diversity of opinion if nobody’s there to hear it and voice it. And so, a lot of companies are hiding behind, oh, we’ve hit X% target of diversity as measured by Y without actually showing or moving the needle on whether those people are included and their opinions are being heard. That’s why appointing a DEI officer is not just a gesture towards that; you’re actually giving somebody the job of doing that.
