When you look at sales, marketing, and other departments, you see AI and machine learning being used routinely. Chances are, your recruiting team is even using tools that take advantage of AI or ML such as Wade&Wendy, Olivia, Hiretual, or similar solutions.
Internally, your historical data can actually be more powerful than any of these tools when leveraged by AI or ML. Think about all of the candidate data that your recruiting team stores, or the data from internal employees, or even external/public data. The number of data sources at your fingertips is astounding.
However, most companies rarely, if ever, take advantage of these hundreds of millions of data points they have access to. And that’s why you’re different. Together, we’re going to provide you with three steps to prepare your business to leverage AI and machine learning to improve talent and HR outcomes.
Preparing your HR Department for AI and Machine Learning
Step 1: Maintain your data.
Keep your data complete, current, and consistent.
If you’re planning a major ATS migration from systems like Taleo or Kenexa to a newer system like Workday, then it’s necessary to evaluate the state of your data. Most likely, ATS vendors are going to tell you that not all data will be able to moved, and your team will need to make strategic decisions on what data is moved over. This is a non-starter if you have plans to add AI or machine learning to your HR processes and analysis. For AI/ML programs to take your talent processes to the next level, you need as much data as possible for the learning and intelligence to work at peak levels.
Keeping data as up-to-date as possible across systems can be a challenge when you have your job marketing team using tools like Beamery and Phenom, while other members of your recruiting team are leveraging assessment tools, and working within multiple spreadsheets. To ensure data quality, implement procedures or a master data record to determine your source of truth, or create a process for updating these records (you can also integrate systems).
Consistency is of the essence. With millions of talent profiles across multiple databases, you’ll find that job titles may not be consistent on their external profiles, and the language can differ from what you use internally. Create rules within your team and standards to ensure data is as uniform as possible, so it can be used effectively in advanced AI and ML applications.
Step 2: Eliminate silos and integrate your HR systems.
To best prepare your business for AI/ML, you’ll want to eliminate as many data silos as possible. When your recruiters create a silo by testing out the latest chat bot, they may think the tool is great, but it’s creating another track for data inconsistencies, and data that will not be communicated with the rest of your HR ecosystem.
Integrating your systems is a must if you want to make the most of AI/ML. Let’s say you wanted to leverage external compensation and competitor data versus your internal numbers. You’ll never be able to accomplish this without being able to integrate that data in some manner. Finding ways to integrate your data will better prepare your HR department and talent operations to implement AI/ML to streamline processes, or better analyze data.
Step 3: SwoopTalent
In each of these steps, we have some overlap. And that’s for a reason.
Every individual piece of your data sets and systems is related and overlaps as well. Your talent profiles and candidate records will overlap across different systems like Avature and Kenexa, and even your other tools like Beamery. Each record will overlap across different systems, which is why it’s necessary to have structured processes to keep data current and consistent, which results from eliminating silos and integrating your systems.
That’s a lot of work, but you can easily prepare your company for AI/ML with a tool like SwoopTalent because it connects your HR ecosystem like the central missing piece of a puzzle. SwoopTalent integrates all of your systems and enables lossless data migration, acting as the central data lake from which AI/ML driven insights can be drawn.
Through this interconnection, SwoopTalent allows all of your data to be accessed by any tool or system, constantly updates in real-time to ensure consistency across all systems, and creates a truly integrated solution for your team to use. This makes it easy for your recruiters to access current and consistent data, and allows your HR analysts to leverage all of this data for reporting, forecasting and more.
If your goal is to run a data-driven department, then SwoopTalent is your answer: helping you to arrange data to train algorithms, feed analytics, and power your AI/ML initiatives.
Final Thoughts: Preparing for AI and Machine Learning
At every stage of the talent lifecycle, your goal is to help your organization become more data-driven. Preparing your organization to leverage AI and machine learning is arduous, but the steps you take to get there helps your organization make more informed hiring decisions, create comprehensive talent analytics, and everything else in between.
Maintaining your data and eliminating silos on their own can take your company years and millions of dollars spent on third party consulting teams, internal developers/engineers, and system costs. However, using a platform like SwoopTalent, you achieve rapid integration of your HR systems to ensure a best-of-breed strategy, while also automating data refreshment and cleansing necessary to ensure curated data for powering your AI initiatives.
To learn more about how SwoopTalent helps you prepare for AI and “feed” it the highest quality data, click here to schedule a demo.
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