If you’ve been following my blog series on how cognitive technology is transforming talent acquisition, you are likely seeing the potential it can have on your organization. So far during this blog series, I’ve covered how IBM cognitive capabilities can:
- help hiring managers find the right talent while staying focused on their primary job roles
- provide recruiters with access to the knowledge they need to quickly and efficiently find quality candidates
- connect new employees with the resources to get quickly onboarded and become a valued contributor to their organizations
Now it’s time to focus on our last persona, Sasha, a talent acquisition leader who is leveraging cognitive technology to become more effective in optimizing business outcomes.
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So how are we helping Talent Acquisition Leaders?
IBM cognitive technology addresses three of the most common challenges of talent acquisition leaders.
1. Leveraging internal and external data to better inform talent acquisition strategy
Many organizations have come to the realization that data held on internal proprietary databases represent only half of the picture. Take for example employee skills, employer brand, candidate experience and employee engagement. Completing the picture requires combining both internal and external data.
Cognitive technology leverages insight from unstructured data—resumes, free text surveys, blogs and social media profiles—and no longer requires following rigid processes or using specific forms or systems. Instead, it simply involves identifying the data sources.
So how is Sasha leveraging cognitive to better inform her talent acquisition strategy? She:
- Combines internal and external employee profile data to inform internal sourcing strategy and identify talent shortages.
- Measures candidate experience holistically by combining pulse surveys, social media commentary and employee review site data—enabling her to completely measure satisfaction and identify drivers of satisfaction and dissatisfaction to drive targeted process improvement.
- Leverages social media and targeted surveys to inform, measure and refine employer brand messaging, engagement and communication strategy by audience.
2. Determining which questions to ask and what data to leverage for answers
When pursuing meaningful insights from analytics, one of the common challenges is determining which questions to ask and what data to leverage for answers. Fortunately for Sasha, she can use the natural language interface within IBM cognitive capabilities to help her in this area. She can simply ask questions, such as “Which universities do we hire our top sales people from?” or “Which roles in our business are underrepresented by females?” and obtain a visual representation of the findings. Additionally, the tool will suggest other related questions and data points to review.
This tool is optimized for the needs of HR and talent acquisition, and leverages machine learning so that it becomes more intuitive with time to better support Sasha’s needs.
3. Making the transition to predictive analytics
The most critical consideration when making the shift to predictive analytics is to ensure that you are predicting success against a trusted measure. The second most critical is to ensure you capture predictors holistically, as they may exist at any point throughout the talent lifecycle.
For Sasha, cognitive technology has been a game changer because she can now leverage sourcing, assessment, performance, learning, engagement and exit data to identify predictors of success and/or failure. She is now able to mitigate risks and drive continuous improvement of talent acquisition strategies, targeted to specific role types:
- Reducing regretted turnover and talent drain
- Improving candidate and hiring manager satisfaction
- Expediting speed to productivity and business value
Whatever Sasha’s stakeholders need from talent acquisition she now has the means to measure and scale her ability to support it—responding to the needs of the business and transforming talent acquisition in real-time.
Although we’ve reached the last blog of this series on how each role is impacted by cognitive solutions, we’d love to continue the conversation with you on how it can make an impact on your role and organization.