3Sixty Insights HRTechChat

Early this month, at an event for analysts, news media, customers and others, the artificial intelligence-powered global talent platform formerly known as Hiretual announced that it had renamed itself hireEZ. I enjoyed attending virtually and learning the rationale for the name change. We also heard details around the $26 million in venture capital that hireEZ noted it had just raised to help drive the objective of the rebrand: becoming the first vendor to define outbound recruiting as a market segment. Following the event, it seemed natural to invite hireEZ CEO Steven Jiang and Head of Marketing Shannon Pritchett to the #HRTechChat video podcast.

“We chose to rebrand to align with our company’s mission to create a new category,” Jiang said, during the podcast. “Our mission is to make outbound recruiting easy. We want to make it easy for recruiters to bring jobs to people. Our vision, three words, is ‘jobs find people.'”

Outbound recruiting itself is a collection of practices that have surfaced over the past several years. This market alert we published on the development delves into things. Suffice it to say, outbound recruiting is the yin to inbound recruiting’s yang….

Once a novel idea made possible by the then-novelty of the Internet, inbound recruiting is the idea that you can use the web as a fast way to attract large numbers of candidates to apply to your open jobs. This has its benefits. In contrast, think of outbound recruiting as a return to classic headhunting, but now aided by marked evolution in technologies such as AI and the cloud — and the Internet, of course. Within the external online environment, recruiters are better able to find and choose their targets. It is now possible for organizations to identify and approach right-fit candidates online for open requisitions and, thus, spare themselves the tedious task of sifting through a slew of information on candidates that found their way into the applicant tracking system. A thorough search may be impossible in the ATS. And it’s hit-or-miss on who, among these candidates in the database, may or may not be good matches anyway.

Outbound recruiting is far more efficient, and recruiters with the means to do so have increasingly been deploying it, in bits and pieces, as essential arrows for their quiver. “We’ve evolved into a more candidate-centric, candidate experience model,” Shannon said.

This is where the pinpointed, 1:1 nature of outbound recruiting comes into play, and that means to do so is where hireEZ enters the equation. The vendor’s technology already supports all five pillars of outbound recruiting: AI sourcing; robust, searchable data; email automation; diversity, equity and inclusion; and system integration. During the podcast, Steven, Shannon and I dove deeply into the details of these five pillars, which the aforementioned market alert also describes.

Against the backdrop of The Great Resignation and a job market that looks like it’s going to be topsy-turvy for the long term, what hireEZ is doing in the recruiting space is remarkable, really. What struck me most, possibly, is around something Steven said. He noted that, for recruiters to embrace outbound recruiting, they must internalize a fundamental shift in mentality. Inbound recruiting remains a piece of the puzzle, yes. But the passivity associated with waiting for candidates to pour in is incompatible with outbound recruiting, whose ethos is proactive, can-do, recruiting with intentionality. The talent acquisition departments that deploy outbound recruiting the most successfully will commence all their recruiting activities with an outbound mindset first, with inbound activities playing a supporting role in their pursuit of the objective.

Technology has advanced to the point where we don't really have to subject ourselves to the inflexibility of a number of traditional, conventional practices anymore, in human capital management. One of these is our approach to measuring employee engagement and collecting employee feedback. Technology has evolved. We can dive much deeper now and achieve several objectives at once. We have much more at our disposal now than just one-to-many surveys set to quarterly, twice-annual or yearly cadences.

"We're finding that a lot of the old ways, the conventional or traditional ways of doing things, just don't cut it," says Maurik Dippel, our guest for this episode of the #HRTechChat video podcast. Annual employee engagement surveys and the like just aren't "up to the to the task. The employee survey is an inflexible instrument."

Innovations in driving employee engagement and gathering employee feedback outside the confines and limitations of the conventional employee engagement survey -- these are areas of expertise squarely in the wheelhouse of Netherlands-based CircleLytics, where Maurik is CEO and co-founder. The CircleLytics solution comprises artificial intelligence; natural language processing; well-thought-out, tailored, guided open questioning; facilitated follow-up interaction between parties, who see and react to each other's responses; and additional activity to make the gathering of employee feedback highly interactive, dynamic, meaningful and... engaging. It's an approach that in fact promotes employee engagement as a part of the process. This is far more insightful and helpful than the administering of a survey to measure employee engagement, in my opinion.

Maurik agrees, of course, and notes that the model has a way of optimizing management-employee relations and helping these and related stakeholders reach consensus and accord internally on challenging issues. With its AI and NLP, CircleLytics' solution analyzes their answers and interactions to capture as broad of a spectrum of organizational sentiment as possible, to help employers reach consensus more readily and in ever better ways, over time. As a microcosm, it's not unlike the idea in the macro that we must inform algorithms right now with as broad of a spectrum of human sentiment as possible, to help ensure that AI evolves as humanly as we want over time -- the focus of another episode of #HRTechChat, from November 2021 with leaders from Cornerstone and AbilityMap.

But before you view that episode from last year, be sure to watch this one. Maurik does an excellent job of explaining how CircleLytics works. Plus, he and I covered lots of intriguing ground. Candidly, Maurik really made me think, and we think our chat will make you think deeply too on new possibilities in employee feedback and engagement.

"The annual performance review process is pretty broken," says Doug Dennerline, CEO of Betterworks and our latest guest on the 3Sixty Insights #HRTechChat video podcast. "It was created seventy years ago for hierarchical organizations," which means it's mismatched to manager-employee dynamics at most organizations today, according to Doug. His credentials and past experience leading well-known vendors in our space are formidable and lent gravitas to our discussion. And I happen to agree with him wholeheartedly.

Years ago, in a previous professional life, I wrote about "a coming mass extinction in human capital management." A result of advances in technology spurring an evolution in attitudes around how best to get the most out of employees, chief among the coming casualties would be the conventional, traditional annual performance review, in my opinion.

It was nothing particularly revelatory on my part. For a long time, plenty others had been saying similar things. The idea to say it was a "coming mass extinction" gave the idea some bite and sounded cool, I rationalized. Fast forward to today. The bite of the past two years accelerated the aforementioned evolution in those attitudes to the point where, here we are, fixated on how to create the conditions for an optimal employee experience at all times. Clunky, yearly performance reviews don't fit into this equation. We may still need them for compliance, sure. Factor machine learning and social media-grade functionality into continuous performance enablement, however, and a clear, auditable trail of information further supporting any action with an employee is possible and defensible from a regulatory standpoint.

Enablement is the new word, by the way. Doug doesn't like the word "management" in performance management, and neither do I -- not one bit. It's just as bad as the "management" in human capital management or talent management. The idea that we're enabling performance is a better, more accurate reflection of the purpose of evaluating employees, and we end up doing much more than merely evaluating them. This is a good thing.

Think of all the advantages modern technology for the employee experience affords us when compared to the old approaches. All you have to do is read Betterworks' tagline: "Betterworks closes the loop between people, strategy and results, enabling organizations to align even the most sprawling teams." There's no practical way to form a virtuous loop of people, strategy and results with only a conventional performance management system. Add work from home to the mix, and a renaissance, an expansion in our thinking in our approach to figuring out how employees are performing, is in order.

The frustrating and stilted thing about the way old-style performance management has developed, is that it occurs in a vacuum. It doesn't really drive strategy. It purports to help drive results, but barely does so. Mostly, staff loathe the tedious annual review process and anything to do with performance management. So do their managers. Underperforming or struggling employees fear the process. There's little room for positive engagement wherein they might feel good about the opportunity to get better at their jobs. It's all top-down evaluation, all the time, and, often, the process isn't even very efficient or effective in producing accurate, usable evaluations.

Leaders from a major multinational luxury fashion brand joined us for this episode of the 3Sixty Insights #HRTechChat video podcast: Chief People Officer Abigail Wilmore and Vice President of Global People Operations Jay Barrett, both members of our Global Executive Advisory Council.

This introduction is shorter than the usual. Our guests did a great job of describing their challenges and success in detail, and I encourage readers to view the episode. The fashion retailer has found immense value in Workday’s solutions as an indispensable tool to support and protect its employee experience over the course of the now nearly two-year-old pandemic. Abigail and Jay explained why this is so — and how it all came to be. Had they and their team kept the disparate, cobbled-together, unintegrated HR systems in place that predated Workday’s implementation, they honestly wonder whether they would have even been able to manage lockdowns’ impact on the employee experience. Such was the magnitude of the new software’s impact on their success.

For this, the latest episode of the 3Sixty Insights #HRTechChat video podcast, our guest was Michael Spataro, chief delivery officer for Legion, a provider of advanced technologies for workforce management (WFM). Michael and I enjoyed a wide-ranging, at once practical and philosophical discussion of organizations' relationship with their hourly workforce in the retail and service industries. Legion's software excels in helping employers in these industries support a strong, positive employee experience for their hourly staff.

In the summer of 2020, Legion published a report sharing the findings of a survey the vendor conducted. Respondents comprised about 500 wage and hourly employees and approximately the same number of managers, all in retail and the service industries. An top-line breakdown of the many findings is available in this press release.

According to the survey’s results, notably, two out of three top reasons for leaving an organization are essentially the same for employees and their managers. For wage employees, these top three reasons are a lack of scheduling empowerment, poor communication, and an inability to get paid early. For managers, the top three are the lack of tools that would make it easier for them to communicate with their employees, an inability to get paid early, and a desire to reduce the time they spend on administrative tasks such as scheduling.

Note that for the one that is not as similar, it pertains to the same issue nonetheless: scheduling. Notice also that all these concerns leading managers and their staff alike to leave their jobs in these industries all have to do, palpably, with the quality of their experience with the employer. If an employer were to address these, the payoff in their workforce’s relationship with the organization’s customers would probably improve significantly.

How do we know this? Michael and I delved into it a bit. For one, it’s a fundamental respect for the Service-Profit Chain, a well-documented idea detailed in Harvard Business Review. The central tenet of the Service-Profit Chain says floor associates satisfied in their work and its effects on their work-life balance are more apt to treat customers well, which, in turn, leads to better retention of both.

With this in mind, we discussed the past two years' impact on employee satisfaction in these types of roles. It hasn't always been the case everywhere, but the majority of hourly staff have long struggled to thrive in these industries. It can be thankless work. It isn't just the pay, which has tended to be low. The entire employee experience has historically left a lot to be desired in these types of roles.

For hourly jobs in retail and the service industries, as Michael puts it, the pandemic has precipitated a major power shift in the employer-employee relationship. All I will add is that the past two years have brought a festering inverse of a healthy Service-Profit Chain to the surface. Look at it either way, and the ramifications are clear.

"There’s no shortage of workers, but the availability of workers willing to do retail or hospitality jobs, where the employee experience is poor, has dwindled," Michael says. They're holding out for better pay and better conditions overall. It’s the reality of the Great Resignation in these sectors among these employee demographics. Call it the Great Resignation or something else, even. The terminology doesn't matter so much. What does matter, far more, is that the pandemic created a scenario wherein employees in these kinds of roles have been able to exert more influence over the conditions of their employment and its effects on their overall lives.

“It’s more than better pay," Michael says. "Employees want to interact with their employer" in much the same way they do as customers "with every other company in their life.”

Adriana DiNenno was our guest for this, the latest episode of the 3Sixty Insights video podcast. Adriana has an intriguing dual role at Infor. As product manager of Infor People Solutions, she plays a leading role in informing the development of Infor's solutions for talent in the workforce. She also helped found and co-chairs Infor People Wellbeing, an internal group focused on -- as the name implies -- supporting positive employee sentiment there. Note that the word is people, not employees. Increasingly, vendors and customers of software for human capital management are officially referring to their employees as their people, a more human term.

As co-chair, Adriana had a vision to help create a place where Infor's people can prioritize their mental health insomuch as it intersects with their work life. It's an area often overlooked in the world of work. She quickly came to the realization, however, that Infor People Wellbeing would and needed to encompass the full gamut of wellbeing -- not just the mental health aspect, but the physical, the financial, the environmental, and the social. "There are all these dimensions of employee well being," she says. "So there couldn't be a better name than Infor People Wellbeing," which happened to fit perfectly with the area of product she helps manage (again, Infor People Solutions).

As we have learned on #HRTechChat over the past year, most roads in the employee experience lead to the intersection of concrete and abstract HCM -- the idea that easily and not-so-easily quantifiable activities in HCM are interconnected and holistically bear on organizational success. Over the course of our conversation, Adriana and I brainstormed several not-so-hypothetical examples, and it's worth noting: An organization's people's overall wellbeing may not be easy to quantify in a way that shows the potential impact on the business, and yet employee wellbeing undoubtedly affects productivity.

I very much enjoyed chatting with Adriana, a dynamic member of the team at Infor, and encourage everyone here to view the full episode.

i2w2izKNUjwFWrZAyee1

Your organization has completed a digital transformation. But the organizational transformation you hoped would naturally follow has not materialized. Why? What happened? Mimi Brooks, founder and CEO of Logical Design Solutions (LDS), joined us at 3Sixty Insights to answer this and discuss the tricky notion of the role digital transformation plays in organizational transformation -- and vice versa. This is a chicken-and-the-egg scenario wherein at times the chicken is first, and at other times the egg is. This and how organizational cultures and makeups of the future of work will affect digital strategies, as well as the near-future considerations at the intersection or organizational and digital transformation vis-à-vis the pandemic and a return to work, are among the many topics we covered with Mimi, our guest on #HRTechChat.

LDS is a management consultancy that works "with large global organizations on their digital strategies when they're trying to use digital to create organizational change," Mimi says. She speaks of a future workforce and sees a move toward employee experience plus productivity, as well as experiences in the context of work. In this way, digital transformation helps drive the gig economy. "I like to say worker experience, because it could be whomever and wherever work gets done." And this has implications for the semantics of the term employee experience, of course.

Getting back to the origins of digital transformation, Mimi says it "came first, because people bought the technology first. The human behavior was to buy the technology. And we thought that if we bought digital technologies that we would become digital, native companies as a way of working." And this didn't necessarily happen, even though they were good capital expenditures. The challenge since has been to transform cultures to be digitally native and receptive to using the tools and forming a virtuous circle.

The thing about COVID-19 and the major disruptions that came along with it is that it accelerated utilization of this preexisting digital infrastructure and has had a net-positive effect on the interplay between organizational and digital transformation -- again, that virtuous circle.

We touched on a lot more in the half-hour we spoke. I encourage anyone interested in this topic to view the full episode.

For this episode of the #HRTechChat video podcast, AbilityMap CEO and Co-Founder Mike Erlin and Mike Bollinger, vice president of strategic initiatives at Cornerstone OnDemand, joined me to discuss a crucially important area of focus: at this still-early stage of its development, helping to ensure that we inform artificial intelligence with the best human-centric data possible. After all, most of us would like to think that the behavior of AI, as it grows eventually to an exceptionally high level of sophistication and begins to take over higher-level decision-making, will continue to reflect what we hold dear as "humanness."

Both Bollinger and Merlin are vendor-side members of our Global Executive Advisory Council and repeat guests on the podcast. The episode you're reading about here has its origins in an an unrecorded conversation the three of us had several weeks ago. It all began when Bollinger alerted us to "Bias in AI: Are People the Problem or the Solution?" By John Sumser, principal analyst for HRExaminer, the article acknowledges two camps and their diverging viewpoints on the development of AI. "One group says people are the problem; the other sees them as the solution" in the development of AI, according to Sumser, who also says, "All tools contain embedded biases. Bias can be introduced long before the data is examined and at other parts of the process."

We commenced this episode by agreeing with Sumser. The way forward, in our opinion, is to flood AI with as much human perspective as possible. The alternative, for developers to work overtime attempting to ensure that AI remains devoid of human bias, may be the wrong way to go and, not to mention, possibly impossible. This is my own inference from Sumser's article. The approach is counterproductive if we wish to avoid the generally dystopian future that AI has the potential to produce should we fail at this point in time, right now, to shepherd AI in a direction that humans would recognize as desirable.

This does not mean a direction that humans necessarily would set on their lonesome, by the way. And, yes, there are implications for the future of work specifically. Erlin made great points here. In the world of work, when we test for cultural fit and soft skills, the best candidate for a role can often be nothing like we might have predicted. What manager anywhere would guess that a former daycare worker would be the best fit for a role in debt collection, for example? I might be getting it slightly wrong, but something like this is a finding that modern psychometrics have produced.

Imagine a future of work where AI lacks this perspective, drawing instead solely on conventional decision-making metrics such as credentials and past work experience. That's where we're headed, a future where the AI for talent acquisition, for example, will have been developed with data that precludes the AI entirely from the very ability to unearth delightfully unintended, unexpected relevance. In an additional twist, it's a particularly human outcome that mere humans would never reach on their own.

Erlin further expounds on the idea. Incorporating quantitative evidence of human bias -- think inherent human preferences -- into the referenceable data sets available to AI generates higher-quality, human-centric current and future choices for humanity, he suggests. I agree. And it's a continual, never-ending process to feed this type of information to AI, which should then provide us suggested courses of actions. Furthermore, we must think deeply about the questions we ask AI to answer. For example, rather than ask, "How can reduce crime?," we should consider asking, "How do we create an enriching community?" -- lest AI return answers that only exacerbate human suffering or frustrations.

For this episode of #HRTechChat, our guest was Caitlin MacGregor, chief executive officer and co-founder of Plum.io. As readers of the 3Sixty Insights blog know, we are convinced that there is a critical link in human capital management between artificial intelligence and psychometrics, and this critical link needs a cacophony of advocacy. The idea is that fast-developing AI for the world of work runs a risk -- a huge one, actually -- of failing to account for the most important, necessary aspects of humanness. That is, unless we intercede immediately and in a big way. If we don't, the prospects for humans in the future of work might not be too good.

To be clear, I am hopeful. Caitlin and I went into some depth on the rationale behind this urgency and why this kind of key information may nonetheless be less than a priority among forces currently steering the evolution of workplace AI. Plum's expertise and value proposition are in the psychometrics side of this equation. Drawing on the latest science, the vendor deals in modern psychometrics. In other words, and to pilfer an old marketing slogan for Oldsmobile, a now-defunct automobile brand, this is not your father's MBTI. Advancements in the science behind industrial psychology have produced instruments capable of much depth and accuracy in testing for the potential of people.

And the question has now become, what's stopping us from doing all we can to take all this new high-caliber insight into humans' potential and inform the development of AI for the world of work? We're talking about soft skills, by the way. These are the gold standard in predicting humans ability to survive and thrive in a given role. It isn't hard skills or past experience or past performance. Too many factors are at play.

A bright future of work is possible. Its likelihood hinges on a number of things, and one of those is how good of a job we do right now in feeding still-young AI nutritious data on people potential. It's the dimension and perspective that conventional data on people's job eligibility (e.g., credentials) and past performance, while necessary, can't provide. Among the upsides, meanwhile, will be increases in retention from improvements to the employee experience and employer culture and brand.

Readers can complete a Plum Profile, by the way, and get access to their own full Professional Talent Guide to learn "exactly what drives and drains them," as Caitlin puts it.

For this episode of the #HRTechChat, our guest was Melissa Swisher, chief revenue officer of Socrates.ai. To say Socrates.ai is an artificially intelligent chatbot to tie together various domains of the enterprise software ecosystem is probably the most straightforward description.  The description implies only a small sliver of Socrates.ai's potential application. Some of these domains themselves may have chatbots specific to various proprietary software, and Socrates.ai an draw information from it all.

As Melissa elaborated during our chat, Socrates.ai "is an employee experience platform. Think of it as an experience layer" that hews to employees' preferences. My take is this: Think of it as a prosthetic to facilitate a unified experience in employee self-service as this pertains not just to staff's employment, but to anything they wish or need to know over the course of a given workday. In my experience, ESS for human capital management specifically offers a rich potential vein of return on investment, and I can only imagine that this ROI grows exponentially when applied to more of the employee experience. Melissa and I delved into some interesting numbers around newfound efficiencies deployments of Socrates.ai have produced.

Naturally, because of the solution's relations to AI, our conversation expanded beyond Socrates.ai itself. And, as mentioned during the chat, I really wish something like Socrates.ai had been available to me much earlier in my career, when I worked with a team at civil engineering firm to figure out what the company had done, in its past, that was relevant to the many responses to request for proposals we drafted. A prosthetic to identify and pull that information from within the depths of the company's enterprise would have been nice.

Then again, it was 2003, not 2021 -- the age of AI. We've come a long way, and I encourage everyone to listen this episode.