Trends that enterprise companies should consider
I have spent the vast majority of the last six years immersed in the Talent Acquisition technology landscape. I have seen trends come and go, but the biggest takeaway from my time as an investor, researcher, and incubator of talent acquisition technology is that no trend just appears fully-formed overnight. New trends develop over time. Not every trend is ready for adoption at scale when it first reaches the marketplace. This can leave some companies facing either the intimidating prospect of jumping on board what can seem like a volatile new trend or feeling like they’ll be left behind.
Adopting technology simply because it’s the latest trend doesn’t make sense for most organizations, especially when new tech often comes to the table before the technology and marketplace is actually ready. Experimentation can help companies who have the bandwidth find those trends that are right for them, but it can also be expensive, time consuming, and ultimately hurt the quality of hiring. That’s why “Talent Tech Labs” monitors emerging trends in talent acquisition technology—as well as established trends to see how they are performing—in order to offer guides to the latest technologies, what they mean for the industry, and how companies can decide whether they are a good fit for their needs.
Here are a few of the trends that are poised to make a big splash in the near future
Advances in matching are accelerated by using algorithms and machine learning technology
New trends in matching tech go way beyond what job boards offer, Boolean search, or keyword matching. Today, ever-advancing algorithms and even machine learning technology provide faster and more efficient results. What might have taken a recruiter three days to do can now be accomplished in three minutes. While matching technology has been around for a long time, these new forms of matching are worlds apart from what has come before in terms of deeper insights into prospective unseen matches, speed and scalability.
Why now? New age matching systems works as much as 10 to 100 times faster, and can generate results at scale. Because of this, even in cases where the results produced by matching algorithms are just equivalent to what a human recruiter would have been able to generate, the time savings getting there are usually enormous.
Examples: Companies like Ideal, Restless Bandit, IBM Watson, and Hired Score are incorporating algorithms and machine learning into matching technology to bring greater efficiency and scale.
Adoption: Companies should determine what their matching needs are and adopt matching solutions based on data that they trust.
Programmatic advertising gives visibility on the effectiveness of job spend dollars
As opposed to being a new form of advertising, programmatic advertising is, instead, a way to measure job spend effectiveness so that advertising dollars can be put toward the most productive job sites and platforms.
Why now? Programmatic advertising has already proven itself in several industries, making it easy for companies to see its effectiveness firsthand without a lot of investment in implementation. What’s more, programmatic advertising is simple to use and offers analytics and clear performance metrics so companies know whether they’re getting enough bang for their advertising buck.
Examples: Recruitics, Appcast, and PandoLogic are just three of the companies offering programmatic advertising services tailored to talent acquisition right now. Because programmatic advertising has already been deployed in other sectors, a variety of other vendors offer similar services, but don’t necessarily focus specifically on recruiting.
Adoption: Simply having the data available is only one step to getting the most out of programmatic advertising. Companies also need to make changes to their job spend based on the results they’re seeing in order to achieve a return on their investment. Today’s systems can behave dynamically based on settings or rules set by individual companies. As a simple rule of thumb, the amount that a company saves by way of higher yields by using programmatic advertising should at least meet, if not exceed, the amount that is being spent on the service.
Social search tools expand sourcing at scale
Many companies say that they have already adopted social search technology, but what they’re actually doing is often a kind of “hunt and peck” approach, leveraging the networks of individuals for reach and exposure. Social search technology does the same thing at scale, accessing all publicly available information on prospects and passive candidates from across all social networks in order to find leads and get jobs in front of the people who are qualified for them.
Why now? Social search technology works much like any other job advertising approach, but instead of utilizing a source like Monster or Careerbuilder, it leverages social media across all available networks. This makes it uniquely suited to identifying passive candidates rather than only targeting active job seekers.
Examples: Entelo is a great example of a company that excels at social search. Other examples can be found in the Talent Technology Ecosystem.
Adoption: Social search is not intended to replace job boards and other tools, but rather to function holistically in conjunction with them. In order to determine what percentage of overall job spend should go toward social search versus job boards and other tools, companies should carefully examine their recruiting needs and be sure they have good analytics in place to measure what approaches are working best for them.
Experimentation with new technologies and trends can help keep companies fresh and on top of developments that are rapidly becoming industry standards
Recruitment Bots can deliver results when targeted, but may not be for everyone... yet.
By now, most companies have probably heard that recruitment bots are the wave of the future, but are they? The answer, at least right now, is both yes and no. Bots are already on the market, but the way that they are best employed remains very much a work in progress. While bots may not yet be able to provide an enhanced candidate experience at every step of the process, they are certainly able to add value for some companies when deployed at the right points in the hiring process. The key is in determining just where those points are and positioning bots discretely to do specific tasks rather than succumbing to promises of what bots may be able to deliver in the future.
Why now? For many, it still isn’t the right time to adopt bots into existing workflows and recruiting processes. However, while bots may not quite be the “magic bullet” that they are sometimes sold as, they also aren’t going away anytime soon, and now is definitely the right time for progressive companies to start paying closer attention to recruitment bots and asking pointed questions about how they work and what value they can deliver to organizations going forward.
Examples: Mya, TalkPush, and Olivia are among the companies bringing recruitment bots to the market, boasting a wide range of functionalities depending on the types of candidates a company is seeking. For organizations who are interested in adding recruitment bots to their processes, finding the one that’s the correct fit will mean identifying clear use cases and matching the bots that are best able to perform those functions.
Adoption: For some organizations, bots can raise completion rates and gather more (and more focused) data when incorporated into the pre-application and application phases of the recruitment process. For other companies, bots may be able to replace a mundane, time consuming activity like scheduling interviews. The best thing to do right now may be to keep an eye on bots and learn what they’re capable of (and what they aren’t) so that an informed decision can be made when the time is right to adopt them into an existing recruitment system.
Experimentation with new technologies and trends can help keep companies fresh and on top of developments that are rapidly becoming industry standards. However, uninformed and reactive experimentation costs companies a lot of time, energy, and resources, often for very little payoff. Companies should adopt new technologies when the cost of inaction is high and the risk of failure is low. Of course, most companies already know that. What they need help with is knowing when the cost of ignoring a new technology is higher than the cost of adopting it.
Fortunately, keeping up with the latest trends doesn’t always mean adopting technology just for technology’s sake. Instead, companies should keep their finger on the pulse of what’s happening in the industry so that they know what’s available and when the time is right for them to start adopting a new technology into their processes.
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