Algorithmic HR and its impact on Human Resource practices

In an age of Moore’s Law (the concept whereby the capability of technology doubles every five years), truly pioneering organizations are the ones who can not only keep up with technological trends but stay ahead of them. And one of the ways companies can do this is with algorithmic HR.

To some, algorithms are an unknowable entity; the runic wizardry that companies like Netflix and YouTube use to divine what movie or TV series you might want to watch next. But they’re so much more than that. And with the correct application, can provide a sizeable benefit to a variety of businesses.

When it comes to gauging staffing levels, hiring the right individual for the right role, and knowing exactly where your business needs to grow or improve, algorithmic machine learning and HR data analysis are already proving their worth.

This is because algorithmic management is rooted in artificial intelligence (AI). And as the workforce is transformed with technological advancements, so too should that company’s processes and practices.

What is algorithmic HR?

First off, let’s dispel some myths and humanize the language a bit. Algorithmic HR isn’t here to replace the ‘human’ part of Human Resources. It’s neither some autocratic unfeeling mechanism nor a reductionist system that breaks people down into ones and zeros. It’s simply another progression of digital HR and is ultimately designed to make your life easier.

In essence, there are three main features of algorithmic HR: the generation of digital HR data, the utilization of software to process that data, and the steps toward automating parts of HR management decision making.

Algorithms live and die by data. So without concise, reliable digitalized information, you won’t be able to extrapolate anything of significance. Examples of HR digitalization are things like transitioning from paper-based to digital records, on-demand training, and AI-driven recruitment, which are already in effect. Subsequently, a lot of the hard work has already been done.

But that’s not to say adopting AI-based learning and acting on algorithmically generated advice doesn’t come with it’s own set of risks and challenges. There is the potential to rely too heavily on programs which are fundamentally designed to simplify the complex.

Without taking into account extenuating circumstances, it would be all too easy to take the analyses produced and act blindly with complete confidence. Which can be dangerous. After all, the spellchecker could tell me a word I have written is correct but without the context of the entire sentence, it could in fact be wrong.

That’s why it’s necessary to understand how algorithmic HR can impact your workplace in both a positive and negative way. Doing so, you will be able to reap the benefits while being conscious of the complications that could arise.

How are algorithms changing the future of HR?

In the 21^st century, so much of what contemporary companies do and prioritize can be traced back to strides taken by Google. And, unsurprisingly, Google were one of the first to push forward algorithmic HR as a concept. Before the progenitors of this practice went on to form their own companies: such was the case for Google’s former senior vice president of people operations, Laszlo Bock.

Bock went on to form his own company, Humu, which specializes in creating and implementing algorithms which gather HR data from surveys, live working environments, and resumes, to put forward insights. Which can be studied and applied to enhance employee satisfaction, improve the hiring funnel, and retain the highest quality staff for longer. And thanks to the immediate tangible effects, this algorithmic approach could be worked into other front facing operations such as marketing, customer service, and performance.

So how does this link back to HR? Well, the fascinating (and enticing) thing about data-driven HR and people analytics is the breadth of flexibility. Algorithms are simply a coded language designed to interpret data, meaning they can be changed up and altered to suit almost any need – providing you have the requisite data. And HR presents three notable areas where algorithmic HR can be utilized best.

Hiring

Hiring and onboarding are an HR department’s bread and butter. And it takes considerable manhours and effort to ensure organizations are able to find the right candidates. But studies show that recruitment aided by algorithmic data leads to higher quality hires. In the same way a computer can search a weighty document for a specific word, clever algorithms can be programmed to sift through applications to pinpoint exactly what you need; or a close approximation for later human confirmation.

Workforce planning

Algorithmically generated predictive modelling and future trends are becoming increasingly important for companies to stay ahead of the curve. This can be harnessed in an HR capacity to ascertain the desired characteristics of dedicated workers, as well as identifying the cause for unwanted turnover.

Satisfaction

Understanding how to maintain employee satisfaction and bolster retention is another key way in which algorithmic HR can be employed. Through assessments of the working environment and internal surveys, employers are able to identify behavioral changes, allowing them to formulate a response to improve.

The benefits of algorithmic HR

Increased productivity

When considering the time invested alone, algorithmic HR presents a significant boost for organizational performance. The time it takes to trawl resumes, scan documents and conduct research can be slashed. Allowing HR departments to direct their focus elsewhere. Automating onboarding tasks and obligations also frees up time for staff, while offering each new hire a comprehensive joining experience.

Unbiased decision making

Part of the beauty of machine learning, AI scanning and HR data analysis is the overall diminishment of bias and discrimination. Over the years, steps have been taken to ensure employers aren’t filtering applicants due to factors of race or gender, and algorithmic HR takes this a step further, by pairing the highest quality candidates with managers without obstacle.

Insightful feedback

Algorithmic HR also goes two ways. Not only does it benefit managers looking to improve the workforce, it affords employees the platform and opportunity to be heard and receive actionable feedback. Progress, goals, aims, wellbeing, all of these aspects can be given the necessary attention and focus and opens up avenues to improve (such as development, training and support) faster.

And finally, the cons of Algorithmic HR

There are, of course, causes for concern with algorithmic HR. This is because these software analyses are tools and any tool, no matter how beneficial, can be misused.

Every actionable result hinges on the data that has been generated. Subsequently, if the quality of the data being analyzed is subpar or inaccurate, it will skew the results.

Much like reading a map incorrectly, following the wrong data could lead to disastrous results.

As AI is both programmable and learns based on what it is fed, there is the possibility of manipulation and alteration through misapplication. As stated in the benefits, algorithmic HR reduces bias but if you intentionally program your systems to search for specific keywords, it will dutifully obey.

And finally, there’s the impression an algorithmic HR dependent company gives off. To some new hires, the disconnect between being able to speak candidly to a human, rather than being processed by a machine, is daunting.

But the truth is, these challenges only arise when data driven HR is poorly incorporated or deliberately distorted. And when properly integrated, it can save time, money and effort in the long run.

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