“Garbage in, garbage out” applies heavily to artificial intelligence, or “AI”.

You need correct, complete and fresh data for accurate machine learning models. This means that in your Talent Acquisition tech stack, you need real time, regular, robust data flows between systems.

That is why we have started augmenting our Workday integration with AI. First, we create seamless integrations with our partners to enable effective workflows, then we leverage good data to inform, improve and scale those workflows.

The Beamery + Workday Certified Integration

Workday Recruiting is where recruiters manage requisitions. It is the source of truth for applicants. Beamery is where recruiters proactively source candidates, build pipelines, and nurture talent, including silver medalists—applicants who were a great fit for a role and made it to final rounds, but were second or third picks.

Because of the Beamery + Workday integration, all the applicants that weren’t successful from a Workday requisition aren’t lost. Each candidate’s data is deduplicated, enriched and converted into a unified talent profile in Beamery, and stored in the database along with any newly sourced candidates. Recruiters can then use both new candidates and silver medalists for the next requisition that opens on Workday.

Our Workday integration provides a bi-directional data flow of all candidate and vacancy information across the two systems. We share candidate names, email addresses, phone numbers, social profiles, locations, education, experiences, skills, languages and attachments. This gives us a good data foundation, which we can use for AI-assisted workflows.

Before we look deeper at how we improve our Workday integration with AI, we should align on the definition of AI.

What we mean by AI

AI is any technique that allows machines to mimic human behavior. This is largely associated with machine learning, where algorithms use statistical methods to learn how to perform a task from data, and do it better over time. AI can also include automation, a technique of running a process without human intervention by applying the same rule to every input. You can find an in-depth article on AI and automation in this guide.

With the definition in mind, we can look at the role of AI in our Workday integration.

How Beamery augments the Workday integration with AI

Beamery’s purpose in this integration is to help recruiters source qualified, engaged candidates, ready to be added to requisitions. So the role of AI here is to facilitate faster sourcing of high quality candidates. We do this in multiple ways, so let’s walk through a sourcing workflow to highlight these methods.

Using AI in candidate sourcing

You can start sourcing from within Beamery and build talent pools related to roles, skills and competencies. But rather than spend time searching and filtering for candidates in the database, you can use Beamery’s Suggested Contacts feature to instantly surface recommended candidates, including silver medalists, alumni, referrals and internal mobility candidates.

By allowing Beamery to pick up the slack and provide suggestions based on matches to existing ideal candidates in your pools, you spend less time trying to find the right people and more time engaging with quality candidates. The suggestions are shown in a ranked list, with a score for how well the suggestions match the talent pool and the reasons for the match, so you know why a candidate is a good fit.

Here, AI is used for prospect prioritization, and not for automated decision making such as adding candidates to vacancies directly. Ultimately, it’s up to you to decide which candidates to add to the requisition. AI is here to assist you, not replace your judgement.

A note on bias in our AI

To avoid bias in our suggestions, we take several steps. We exclude fields that could cause bias in the algorithms either explicitly—such as name, age and gender —or implicitly—such as address, education, salary. Our Quality Assurance team regularly retests our AI features, including Suggested Contacts, with representative samples of our database to ensure the algorithms and features are functioning as expected.

Additionally, users have no ability to influence the algorithm and include other information that might skew the results. Each field used to match candidates is also equally weighted in the algorithm, so there is no heavy dependence on one data point. Finally, Suggested Contacts does not use deep learning, and hence there is no opportunity for the algorithm to leverage other terms that may cause bias.

Once you’re happy with the candidates in your pool, you can bulk add them to the vacancy. At this point, these quality candidates are automatically synced into Workday.

Widening your search beyond Beamery

Now let’s say you want to widen your search, so you use Beamery’s Browser Extension on LinkedIn to source new candidates. Here, you can use the Extension to automate the repetitive tasks in your sourcing workflow at scale, like adding up to 1000 candidates who match your LinkedIn search into a Beamery pool, with a few clicks.

Automating your sourcing workflows

When a contact is added to the database, we automatically check for duplicate profiles, enrich the profile with publicly available online information using machine learning, and parse their resume into the right fields in Beamery. This information is then carried into Workday in real time when the contact is added to a requisition. If the contact is already in a requisition, their profiles are updated with any new information we find. So you can always see clean, up-to-date information reflected in both systems to inform your decision making and actions.

Throughout the sourcing and application process, you can also use Beamery’s rule-based automation engine to build relationships with candidates using personalized messaging, and collect their consent to maintain a compliant database. Finally, Beamery has suggested tasks to nudge you and help you stay on top of your priorities.

Takeaways

• Good data is fundamental to effective AI. Beamery’s Workday integration with AI functionalities, along with our deduplication, enrichment and parsing engines, ensure that up-to-date, relevant data is shared across the systems.
• With this good data as a base, we can help recruiters source high quality, relevant candidates faster from within the database, using Beamery’s ‘Suggested Contacts’ AI-assisted recommendation feature.
• Recruiters can rapidly source further candidates at scale from the web, using the Beamery Extension. From the Extension and from within Beamery, you can automate key processes in the sourcing workflow—such as talent pooling, candidate nurture, and consent management—so you can fill requisitions in Workday even faster, without compromising the quality of candidates or process best practices.