As per statistics released by the Manpower group in 2021, over 20 million jobs were eliminated during a two-month period in 2020. If that was the trough, the current labor market scenario is at its peak. In sharp contrast to 2020, 2022 is the best market that job seekers have experienced over their career. Employers across industries are reporting strong hiring as they ramp up to align their business with the post-pandemic new normal and get back to business with full force. The challenges that employers now grapple with are: How to recruit the right talent for open opportunities in a job seeker’s market; how to attract talent in what’s supposedly the most competitive job market in a generation; and how to be smart about talent management. 

Employers can no longer rely on legacy data points like educational qualifications and work experience, combined with a conventional interview process to validate skills and determine “cultural fit”. Overall, this approach is legacy, subjective, has multiple drawbacks, and can introduce potential bias opportunities. The good news, however, is that with advances in data science, companies can now leverage technology solutions that can help them build a data-driven foundation that fosters a strategic and optimal talent management capability. To discuss the critical role of advanced analytics and AI in talent management, SAPinsider recently invited Kumar Ananthanarayana, Head of Product for Phenom, a leading AI-powered talent experience solution provider. You can watch the full video of the discussion here.

Leveraging AI-Powered Talent Management to Build World-Class Talent Management Capabilities

As mentioned previously, recruiting in the current market and in the digital age – whether for external or internal candidates — needs to go beyond the conventional data points. As Kumar highlights: “In the pre-COVID days, it was really a fight for talent. And that has just accelerated now. Along with that, we are seeing this whole new trend of the Great Resignation, where employees are leaving for different domains. So employee engagement, employee retention, and growth become super important for HR as well.” 

It is becoming increasingly imperative for organizations to put data at the center of their talent strategies. This data-driven approach that harnesses advances in data science, AI, and machine learning (ML) can not only help organizations hire talent that aligns with the unique objectives of the roles they are trying to fill; it can also help them enhance other key talent management aspects like onboarding, performance management, and optimal talent deployment. 

The good news is that organizations are already leveraging analytics-based talent management solutions. Recent advances in AI have allowed many solution providers to introduce AI-powered talent management solutions. In a recent survey by Manpower group, 47 of the Fortune 100 companies indicated they use some form of analytics-powered talent management solution. These solutions enable companies to continuously improve hiring results through more personalized, data-driven experiences for candidates, recruiters, and hiring managers. As Kumar highlighted: “Almost all of our customers say they've been able to identify people who visit their career site — but haven't applied — more often with our technology. Using AI, personalization, or the chabot engages candidates, so even if they don't apply, our customers are able to identify these leads and create an organic pipeline they can campaign to for new job opportunities in the future. That's an example of how AI can really open up new avenues for efficiency. 

What is Phenom TXM?

Phenom is a global HR technology company with the purpose of helping a billion people find the right job and discover their true potential. The core offering from Phenom is Talent Experience Management (TXM). TXM is an AI-based SaaS platform that connects every interaction across the four key talent experience areas: candidate, recruiter, employer, and management. Phenom TXM allows every experience in the talent lifecycle to be unified in a single platform. The benefits are experienced by all stakeholders in the process. Candidates are finding the perfect fit faster. Recruiters are creating meaningful moments. Employees are engaged and evolving, and managers have more actionable insights than ever before. At the core of Phenom TXM is the power of Artificial Intelligence. But that is not the only aspect that makes technologies like this powerful. As Kumar highlighted, TXM unifies technology and experience design to enhance the entire talent journey is made possible by the following aspects:

• Artificial Intelligence
• 1:1 True Personalization
• Intelligent Search
• Enterprise Talent Graph
• Holistic Integrations
• Digital Accessibility

A core differentiating aspect of TXM that Kumar highlighted was:” One of the core differentiators from a platform perspective is we offer a very connected experience. So that means the candidate experience is super connected to the recruiter experience and the manager experience where data across all these experiences and even employee experience per se, but data across these experiences are centralized in one spot.”. You can learn more about Phenom TXM here: https://www.phenom.com/txm_platform

Avoiding an Important Pitfall of AI Induced Bias

Like any other advanced technology, solutions there are aspects that need to be kept in perspective when implementing solutions like Phenom TXM. One critical point is the AI bias. As an example, diversity and inclusion (D&I) have emerged as a critical issue in recent years. When organizations incorporate these AI-enabled talent management tools, it is critical to ensure that their DE&I goals are being met as well. Kumar emphasized this as well when he indicated: “I think the one important thing to understand from a biased perspective is the data source itself for your training more, right. Obviously, from past hiring decisions, there could be potential bias in some of the decisions that have been made. So for us, we look at what are the key aspects we need to look at from, delivering an AI experience. So we look at completely anonymized and no PII kind of data, we look at the titles, skills, the correlations between skills, the correlations between the title and top skills, the location of the job, the Preferences from the location, perspective, experience perspective.”.

What Does This Mean for SAPinsiders?

There is no doubt that AI-powered talent management solutions have the capability to transform the way companies manage talent in today’s era. However, there are certain aspects that SAPinsiders need to be kept in perspective when they embark on building this capability. Make talent management a part of centralized enterprise intelligence. There has been a major focus on centralized enterprise intelligence recently. All key solutions, like SAP BTP, are focused on helping organizations build a centralized view of their enterprise. Talent management solutions should not be an exception. As highlighted above, a robust solution will connect various critical aspects of talent management. As Kumar highlights: “We have solutions that cater to various personas. On the candidates, we build a career site that is driven by personalization, recommendation, and insights. We have a chatbot for candidates that visit our career site. Similarly, we have an employee experience for employees to log in and look for the next job within the enterprise, or even grow their skills and competencies and potentially set a career path within the organization that feeds back into the AI. We have recruiter products that provide key insights, looking at potential fringe scores of candidates, rediscovering best-fit pass applications to jobs to help them close the job faster. And hiring managers, of course, need that intelligence to understand the Fit levels of candidates, even source candidates on their own to their own jobs using technologies like AI.” Plan your roadmap before you embark on the journey.  As we consistently highlight to SAPinsiders, building a roadmap is critical to a successful journey in key technology initiatives, and it looks like the industry experts agree as well on this. Kumar brought this up as well: “It's always important to understand how you can build a roadmap or journey to centralize your enterprise talent intelligence; you can go for point solutions; they may be able to work in specific areas. But from a long-term scalability perspective, it's important to understand how to tie some of those outcomes to other aspects of your TF function or TM function.” Pace your journey for success. Plan your journey in a phased way, building foundations for subsequent stages. What is critical in such implementations is the adoption, not just the implementation. As Kumar suggested: “From an AI adoption perspective, one of the recommendations we have is to take a crawl, walk and run approach, right. So especially when it comes to talent acquisition, it might be difficult to really onboard a new AI platform and just deploy it to everybody to start using that. So typically, we recommend our customers to implement the out-of-the-box functionality, deploy a career site, measure candidate behavior so that we can start learning about your enterprise context, and then start to scale that across the organization for recruiters and managers.”