Phenom AI Day: Live Blog
It's officially Phenom AI Day! The special broadcast is streaming live from Phenom's world headquarters in Ambler, PA starting now. What we already know? Attendees will be given the unique opportunity to take an in-depth look at how global HR teams are benefitting from Phenom’s systems of intelligence within its Talent Experience Management (TXM) platform. In addition to showcasing the impact of artificial intelligence (AI) on hiring, employee development, and retention, four product announcements, and three industry-changing commitments will be revealed. 11:05am | Cue intro video explaining why HR needs AI 11:09am | JD, VP of Marketing at Phenom, introduces Phenom CEO and co-founder Mahe Bayireddi Mareau says experiences at every stage of the talent journey are important, especially since employees tend to look externally for new opportunities when they want to pursue a different kind of role. "We surveyed 5 organizations [within Phenom's Employee Experience platform] and found that only 31% from 2018-2020 were going through the entire onboarding process," according to Mareau. Even with career pathing and an internal mobility program, manual entry is a common roadblock. "There's a direct correlation between the steps we ask candidates to take and how far they get through the on-boarding experience [of an internal career site]," Mareau reveals. "It's become really clear that we can't rely on manual entry from employees in order to help them achieve the growth and potential they’re looking for to get them to stay. We need to rely on AI and data to help employees predict their future on their behalf," she states. 2:58pm | Bayireddi highlights Phenom’s 4 new product announcements This was a really informative, technical look at the sophisticated AI woven throughout the entire process of hiring, developing, and retaining talent lifecycle. Couldn’t catch the live event? Watch it here!
Live Updates
10:35am | Live music pre-show
This guy is great, BTW. If you’re wondering who he is, I found out his name is Andrew Lipke. Cool effect with the huge background screen of people tuning in remotely!
He equates AI to oxygen. “It’s the most essential thing… when you think about AI right now, it’s everywhere, it’s essential, and it’s invisible.” (I totally agree. Just think about the way we shop on Amazon or watch something on Netflix.)
Excellent AI can personalize, automate, and give insight — all in the background so you can supercharge the talent journey, he says. When you use the Phenom platform, it won’t feel like there’s an AI element there because it’s working the way it’s supposed to.
Bayireddi’s point of view (POV): “We live in an experience market. People will rarely remember what you say but always remember how you made them feel. To make that feeling relevant throughout the talent journey, enterprises have to use AI-first companies. But it’s not just about collecting data. It’s all about experience-driven AI that transforms data into knowledge.”
11:30am | Lindsey Mareau, Senior Director & Manager, Solutions Consulting, talks employee career pathing
11:35am | James Schlitt, Ph.D., Senior Data Scientist at Phenom, attends virtually to talk about career pathing and employee retention
Schlitt kicks off his segment by pointing out that, “It’s more valuable to find ways to retain existing talent than to find new.” He then brings up the Employee Tenure Prediction model, which helps talent management teams accomplish this. This model aims to answer questions like: Do we have a sense of potential career paths for our employees? Are they looking for new opportunities? How can we prevent major skill and capacity loss once they go?
According to Schlitt, “once we have a sense of their career path, we can prepare for the crucial inflection point: Do they stay, or do they go?” (Can't get that song out of my head now...)
All in all — the Employee Tenure Prediction model helps companies determine what holes they may need to fill and what internal talent they can develop to fill those roles.
11:41am | Suresh Babu Bevineni, Director of Engineering, Search & Personalization at Phenom, joins to showcase an employee career growth demo (If you’re not tuning in now and want to catch the demo, check out the replay at 1:04:08.)
11:45am | Deepak Banke, Product Development Engineer, Machine Learning at Phenom, talks about predicting skills for existing employees to power internal career pathing
He points out that Phenom’s ontology system includes 180K ontology skills and 500K job titles — all gathered over the course of a decade. (That’s A LOT of impressive data if you ask me.)
11:49am | Jesus Latorre-Socas, Lead Product Manager at Phenom, talks about suggested skill recommendations
To close the gap between relying on manual entry for vital information, Latorre-Socas recommends suggesting skills to applicants to improve application rate. But, he takes this concept a step further: “Not only should we be making those skill suggestions, but also using AI to determine if they’re a best-fit for the role [they’re] applying to or looking for in the future.”
According to Latorre-Socas, AI-powered skills are also beneficial for internal employees: “We’re understanding how well of a fit [employees] are to a job recommendation… so employees can know, what am I lacking? Where can I grow to get into my next role? That’s all leading to tremendous impact... a 40% increase in employee signups and almost double that in internal applies. From an organization perspective, that’s talent growth.”
11:52am | Jesus Latorre-Socas announces a new Phenom product: Enterprise Career Framework
Because there’s so much data that’s collected from candidates and employees, it’s not always easy to understand. Enter Phenom Enterprise Career Framework. This new product is intended to take all systems and data points and merge them into a single location where companies can manage all of it in a single view. (That sounds like a really user-friendly experience, in my opinion.)
With Phenom Enterprise Career Framework, you’ll gain visibility into the entire skills inventory. This development allows organizations to “envision all the career paths within your organization to better understand the opportunities before you promote it to your employees,” he says.
11:55am | JD shares Phenom Employee Experience platform data
“When you have happy employees — and you engage them and give them the right technology — they become advocates. That’s where we want to go,” JD says. (In today’s hiring climate, happy employees are priceless.)
11:56am | Cliff Jurkiewicz, VP Global Strategy at Phenom, talks about anonymous site visitor behavior on career sites
“When we think about anonymous visitors on a career site — and candidates themselves — organizations struggle to identify these visitors and what their preferences are,” he says. “Only one in six anonymous visitors are clicking apply. And within that group, only 8% of all visitors are leaving information behind.”
The solution? Using AI to improve the candidate experience. “We want to understand who they are and bring value to the experience. So that they stay, and provide info… because they want to find a good job. With our candidate experience platform, we see almost a 3.5x increase in time spent on the site and double the number of completed applies.”
“AI is changing the equation: This isn’t just about the art of possible. It’s about the reality of science. Today, it’s a race to engage. Those that engage better, will win.”
12:00pm | Dr. Abram Van Der Geest, Ph.D., Principle Machine Learning Engineer at Phenom, joins
Abram dives into how a candidate might interact with a career site and how they typically get to a career site in the first place. He then touches on how a conversational chatbot can help provide job seekers with more relevant information that can help them on their search. (I personally love a bot that can answer my questions immediately and accurately...accurately being the key word here.)
12:11pm | John Deal, Director of Product Knowledge at Phenom, takes the stage
His main point: Phenom’s platform can make recommendations to guide candidates to available jobs that match their skills — but it’s also important to note that job seekers may want to choose their own adventure.
12:12pm | Sekhar Jami, Engineering Manager, Machine Learning at Phenom, shares more info about the impact of a chatbot on career sites
Lots of statistics give an inside look at the benefits and outcomes of using conversational bots on career sites. Who knew that by simply implementing a chatbot, “companies can experience a 95% increase in leads, 14% increase in applications started, and 40% increase in completed applications”?
(Sounds invaluable for capturing anonymous visitors that are in the early stages of their job search and driving conversion.)
His final thoughts: “Candidate behaviors are always evolving. To understand and evolve alongside changing candidate behaviors, our chatbot learns from the millions of conversations across the platform. By automating answers to common candidate questions, we free up recruiters to do more important work.”
12:15pm | Dr. Abram Van Der Geest, Ph.D. poses a question to the audience
Did you know that 45 - 75% of your anonymous visitors may already be in your Candidate Relationship Management (CRM) system? He then points out that profile-matching leads to site visitors is important and easy — if you have the right tools.
12:24pm | Sean O’Donnell, Lead Product Manager at Phenom, follows up Abram’s point
“You can measure all you want. But if you don’t have the right tool to do what you need to do, you’re not going to get anything done.” (I definitely resonate with this.)
To give engineers the tools they need to measure and interpret all the data they’re receiving effectively, Phenom developed search configuration tools that are now going to be available for customers. With these tweaked tools, customers can make further changes to their career site to personalize the experience for users.
12:39pm | Daniel Eggimann, Director of Product at Phenom, joins
“Content personalization allows our customers to provide a relevant experience to every candidate that comes to the site without the need for hundreds of different pages," he says.
To elevate this concept and turn it into a product feature, the Phenom team implemented an audience framework that allows customers to personalize what’s shown to each user based on where they are in the talent journey. This includes static and dynamic content, like videos, which are especially helpful on job description pages — the most important page on the site, according to Eggiman.
“It’s where candidates start the journey, and where most conversions happen.” (I don’t know about you, but I’ll watch a video over a boring job description any day!
This segment ended with a profound statement from Daniel that showcases how Phenom keeps what’s most important in mind — none of these features are valuable unless our customers are seeing results.
12:52pm | JD shares platform data on converting anonymous visitors to quality applications
1:05pm | Maggie Allen, Senior Director & Manager, Solutions Consulting at Phenom, talks about the challenges faced by recruiters and hiring managers
Hiring managers need a way to identify the best possible candidates for their open roles. Recruiters, on the other hand, are challenged by clarity and quality of fit to job description alongside an overwhelming number of resumes.
Her point: Both managers and recruiters are bogged down by time-consuming, manual tasks that make it difficult to keep up with existing needs.
How can AI & automation help?
1:10pm | Dr. Ilya Goldin, Ph.D., Principal Data Scientist at Phenom, discusses AI Discovery
"As AI designers, we think about what can we predict that’s useful? Then we determine, how can we predict a high-quality, good-fit lead?”
According to Dr. Goldin, the answer is Phenom AI Discovery — including fit score, job parsing, and other elements — that benefit from a “human-in-the-loop” model to provide real-time feedback that trains the AI to offer better recommendations over time.
To dive into these features in more detail, Dr. Goldin cued members of Phenom’s engineering team.
1:16pm | Arjun Guru, Product Development Engineer - Machine Learning at Phenom talks about AI parsing
How does AI help job and resume parsing? “We first try to identify requirements from the job description. Then we extract necessary and relevant skills, which are ranked in order of importance for the job. We also developed a new approach that enhances the list of skills based on related job families," Guru reveals.
The same technology can be leveraged for parsing candidate resumes. This AI-powered data extraction and matching is paired with human feedback to create a dynamic fit score. (If you’re anything like me, you’re probably wondering what a dynamic fit score does. Keep reading to find out!)
1:20pm | Vaibhav Bhalla, Product Development Engineer, Fit Score at Phenom, shares additional information on Phenom fit scores
“Fit score depends on four major criteria; skills, title, location, and experience," Bhalla states. Recruiters have the ability to adjust criteria parameters and designate an ideal candidate to help the AI learn and provide more precise scores and matches. AI utilizes this information to assign a fit score — A-fit, B-fit, C-fit, etc. — to help recruiters quickly see which candidates are a better fit for each open position.
1:25pm | Kumar Ananth, Executive Director, Product Management at Phenom, introduces another new product feature: Recruiter Personalization
“We shouldn’t tell recruiters what to do — they know what they want to do in the product. But what is challenging for a recruiter today, is they have a lot of candidates and a lot of activity happening. We want to provide key insights to help recruiters stay on top of their work.”
Through Recruiter Personalization, it’s easy to identify who the recruiter is, what jobs they’re assigned to, the pipelines they’re working in, and the skills they're interested in. According to Kumar, we have quick tips to help recruiters onboard candidates, a personalized dashboard, and a streamlined way to request candidate feedback. (Cue recruiter applause.)
Demo Recruiter Personalization here.
1:32pm | O’Donnell shares data to showcase the impact of recruiter-focused features
“The Phenom platform, as a whole, decreased average time to fill a role from 42 to 21 days and when using fit scores, the time-to-hire dropped to a 20 day average,” he reveals. (If you’re counting, that’s 22 days saved per role saved!)
1:40pm | Dr. Jeff Weekley, Ph.D., Clinical Professor, Naveen Jindal School of Management, University of Texas at Dallas, talks AI and hiring bias on stage with Dr. Goldin, Ph.D.
AI and its role in supporting DE&I and hiring practices is one of the hottest (and most controversial topics) in the industry. Tune in to the whole convo here.
“Are we building tech for equitable treatment?,” asks Dr. Goldin.
According to Dr. Weekly, companies run into issues if there’s an adverse impact that appears within their hiring process. “An adverse impact exists when the hiring rate for one group is substantially less than the hiring rate for another group. But there’s no single definition of ‘substantial’.”
Dr. Goldin summarizes Phenom’s three-pronged approach to develop socially responsible AI:
Key takeaway? If your hiring process has an adverse impact, you need to break down the process and find the source of the issue.
1:55pm | Dr. James Schlitt, Ph.D. walks us through Phenom’s Adverse Impact Dashboard tool, designed to help recruiters craft the best queries that will attract candidates without creating bias
2:02pm | JD shares Phenom data on Recruiter Productivity with AI
Top stats:
Biggest takeaway? These are tangible results that are making a profound impact on recruiters across the globe.
2:15pm | Bayireddi rejoins to offer a unique POV on today’s hiring environment
“If you look at what’s happening in the market right now, high-volume hiring has drastically changed, especially for frontline workers. We have to move away from the old way of recruiting to a new way — if you want to flourish, you have to think differently. That’s where AI comes into the picture,” he says.
"We have to think about humans, intelligent automation, and contextual process optimization together because that’s where the game is going for the next 10 years.”
To help kickstart the next phase in AI for HR, Phenom gathered data, analyzed patterns, and developed a new layer of intelligence within its TXM platform, called Intelligent Automation, which will start by supporting high-volume hiring for frontline workers and early talent.
2:28pm | Ananth shows a demo of Intelligent Automation for Frontline workers
2:45pm | Adam Thompson, Director of Project Management at Phenom, introduces the Talent Acquisition (TA) Automation Maturity model
“We created this model to help companies better understand how AI can be applied to the talent industry,” Thompson says. (Love the Iron Man reference, btw.)
To see what level your organization is on in the TA Automation Maturity model, companies can take a quick assessment to uncover areas where AI and automation can accelerate hiring and improve their talent experience.
3:00pm | JD announces that 3 industry-changing commitments will soon be revealed
3:05pm | Commitment to the industry is announced
To support this commitment, a new AI Certification program will launch in early 2022. You can get on the list here to be among the first to gain access.
3:12pm | Commitment to Phenom customers is announced
3:19pm | Commitment to Phenom prospects is announced
3:25pm | Closing remarksTo see Phenom’s AI and automation in action, request a demo today.
Kasey is a content marketing writer, focused on highlighting the importance of positive experiences. She's passionate about SEO strategy, collaboration, and data analytics. In her free time, she enjoys camping, cooking, exercising, and spending time with her loved ones — including her dog, Rocky.
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