Announcing the retrain.ai Partnership Program

NYC / August 9, 2023 – retrain.ai, a leading AI-driven Talent Intelligence Platform, has announced the launch of an exclusive Partner Program available to consulting and recruiting firms. The company describes its new offering as a way for exclusive partnership with premier firms to bring their prospects and clients into the future of work with an AI-fueled, data-driven understanding of what they need to become a Skills-Based Organization.

The company uses a data driven, Responsible AI-driven operating model using billions of data points to help enterprises achieve a Skills-Based modality. 

“Becoming a Skills-Based Organization is the key to success for today’s enterprise HR leaders, but many don’t know where to start. When they ask a consultant for guidance on transforming to an SBO model they may get information, but not the tools they need to get started,” says retrain.ai Co-founder and COO Isabelle Bichler-Eliasaf. “We provide those tools, along with the expertise to optimize them for success.”

To accomplish this, retrain.ai centralizes data to create an adherent skills strategy to unify and standardize data sets to remove silos within HR functionalities.  This unified data set, paired with the company’s Responsible AI, equips HR’s to move faster and with more agility and efficiency. The platform continuously updates to eliminate future skills gaps within the organization where it is already implemented. 

Consultants in the retrain.ai Partner Program will have access to the talent intelligence platform’s Skills Architecture module to generate a skills-map of an enterprise client’s workforce, including unified skills language and agreed-upon job architecture. With better visibility into their employees’ strengths and skill gaps, HR leaders can spot hidden talent, reveal internal mobility opportunities and deploy talent efficiently during times of rapid change.

“Our platform provides HRs with a comprehensive understanding of their workforce and the right data to align with organizational goals,” says Bichler-Eliasaf. “Once our partner consultants provide their enterprise clients with a comprehensive skills catalog of the core competencies, technical proficiencies, and soft skills needed for each role in their organization, they can begin to strategize an SBO operating model.”

 

retrain.ai is a Talent Intelligence Platform designed to help enterprises hire, retain, and develop their workforce, intelligently. Leveraging Responsible AI and the industry’s largest skills taxonomy, enterprises unlock talent insights and optimize their workforce effectively to hire the right people, keep them longer and cultivate a successful skills-based organization. retrain.ai fuels Talent Acquisition, Talent Management and Skills Architecture all in one, data-driven solution.

What are the steps to become a Skills-Based Organization?

Our previous post discussed the key benefits of transformation into a skills-based organization, including agility, adaptability, talent optimization, employee engagement and DEI support. So how does an enterprise make the shift to an SBO model?

Here are five key steps:

  1. Skills Assessment. An enterprise’s first step is determining which skills are already in its workforce. A comprehensive skills inventory can be built using skills assessment tools, self-assessment questionnaires, and feedback mechanisms to capture the diverse skill sets present within the organization.
  2. Skills Mapping. Next, HR leaders need to identify the critical skills required for each role and project within the organization, mapping the existing employee skills against these requirements to identify skill gaps and potential opportunities for upskilling or reskilling.
  3. Skills Development. To engage employees in the process, enterprises need to create a culture of continuous learning and skill development, offering training programs, mentoring opportunities, and access to relevant resources. HR leaders can then encourage employees to take ownership of their skills development and provide avenues for them to showcase their skills within the organization.
  4. Skills-Based Hiring and Talent Mobility. Transitioning to an SBO model needs buy-in across the board, meaning hiring practices must focus on skills rather than traditional job titles, skills-based assessments and interviews are used to identify best-fit candidates, and employees are empowered to move across teams and projects based on their skill sets and interests.
  5. Technology Enablement. Leveraging Responsible AI-driven HR technologies can facilitate skills tracking, mapping, and matching at scale. Enterprises must invest in tools that allow employees to showcase their skills, create skill-based profiles, and connect with others via an internal talent marketplace.

retrain.ai is a Talent Intelligence Platform designed to help enterprises hire, retain, and develop their workforce, intelligently. Leveraging Responsible AI and the industry’s largest skills taxonomy, enterprises unlock talent insights and optimize their workforce effectively to lower attrition, win the war for talent and the great resignation. retrain.ai fuels Talent Acquisition, Talent Management and Skills Architecture, all in one, data-driven solution. To see it in action, request a demo.

What is a Skills-Based Organization?

One of the most significant shifts taking place within the realm of HR and talent management is the transition to a skills-based organization. Rather than focusing solely on job titles and traditional hierarchies, organizations are recognizing the importance of assessing and leveraging employees’ skills and capabilities to better drive success and foster innovation. But what exactly does it mean to transform into a skills-based organization? Why is it seemingly crucial for HR professionals to lead this paradigm shift?

Understanding the Skills-Based Organization

A skills-based organization places skill sets and capabilities at the core of its talent management strategy. Instead of relying on job titles and formal qualifications, enterprises instead shift their focus to identifying, developing, and utilizing the skills their employees possess so as to effectively match individuals to best-fit projects, initiatives, and roles.

What are the benefits of becoming an SBO?

  • Agility and Adaptability. In today’s rapidly changing business environment, enterprises need to be nimble and adaptable. By focusing on skills, companies can quickly respond to market shifts and reconfigure their teams as required. Skills-based organizations have the advantage of assembling cross-functional teams with complementary skill sets, empowering them to tackle new challenges and seize opportunities efficiently.
  • Talent Optimization. Traditional hiring practices often rely on predefined roles, limiting the potential of employees who may possess valuable skills outside their designated functions. A skills-based approach allows organizations to tap into the full potential of their workforce by unlocking hidden talents and engaging individuals to contribute in areas where they excel.
  • Employee Engagement and Growth. Engaged employees are more likely to be motivated, productive, and loyal to their organizations. In a skills-based organization, workers have opportunities to develop and showcase their skills, leading to increased job satisfaction and a sense of fulfillment. By promoting skill development and growth, organizations can foster a culture of continuous learning, which modern professionals highly value.
  • Diversity and Inclusion. Traditional job descriptions can use terminology that inadvertently creates barriers to entry. A skills-based approach promotes inclusivity by focusing on what an individual can do rather than where they come from or what their previous job title might have been. By removing biases associated with traditional hiring practices, enterprises can build diverse and dynamic teams.

In our next post, we’ll go over the key steps involved in transitioning to a Skills-Based Organization.

 

retrain.ai is a Talent Intelligence Platform designed to help enterprises hire, retain, and develop their workforce, intelligently. Leveraging Responsible AI and the industry’s largest skills taxonomy, enterprises unlock talent insights and optimize their workforce effectively to lower attrition, win the war for talent and the great resignation. retrain.ai fuels Talent Acquisition, Talent Management and Skills Architecture, all in one, data-driven solution. To see it in action, request a demo

HR Evolution in the Age of Talent Intelligence

This article originally appeared in Forbes.

In a year defined by the stark contrast of looming layoffs and a continued skilled worker shortage, it’s likely that 2023 will highlight the importance of HR’s role in leveraging data-driven insights.

At the end of last year, recruiting was a top priority for 46% of HR leaders, with enterprises revamping sourcing strategies to meet the demand. At the same time, 61% of business leaders were predicting layoffs at their companies. None of that slowed the nation’s quit rate, which landed at 4.1 million workers for the month of December 2022, the same time Robert Half’s “Job Optimism Survey” reported that 46% of professionals were looking, or planning to look for, a new job in 2023.

Such contradictory data can make an HR leader’s head spin. Figuring out how to manage it all on budgets tightened by economic instability is the icing on a very bitter cake. The answer?

In 2023, organizations need to be creative and efficient in their approach to achieving HR goals when using data-driven insights.

HR leaders need to synchronize talent acquisition, talent management and organizational skills mapping to create an agile and continuously growing workforce. By acting on AI-fueled, data-driven insights, enterprises can gain a better understanding of their organization’s job and skills architecture and plan for future skills demand—that is, if HR approaches talent intelligence properly.

HR’s Role In Talent Intelligence

Here are some tips for HR leaders on how to approach talent intelligence:

  1. Avoid the DRIP Problem

To compete within the volume, speed and disruption of today’s talent landscape, data is king—but actionable information and knowledge are the castle. Amassing data for data’s sake holds little value and can often lead to a DRIP problem: being data rich, information poor. Conversely, organizing, analyzing and interpreting data can provide rich knowledge and actionable insights needed to fuel better business decisions.

Given the continued talent shortage, expedited skills identification can be a great differentiator for high-performing recruiting teams. To source, screen, hire and retain the right employees with the in-demand skills needed for business success, enterprises should focus on harnessing the true value of data. By actively converting insights into strategies, HR leaders can proactively address skills gaps, plan for future skill needs and develop a more engaged workforce.

  1. Consider starting with job architecture and skills mapping.

To remain competitive and future-proofed, HR innovators should evaluate the skills their employees have, those they need and those that will likely become critical in the future.

More HR leaders are starting with job architecture, building a skills framework using unified skills language to better understand their people and spot hidden talent, diverse capabilities and skills gaps. They can then deploy talent efficiently during times of rapid change, scaling teams up or down as needed. Given the economic uncertainty, knowing where the risks lie can empower HR innovators to upskill, reskill and redeploy—rather than lose—good people.

  1. Don’t fall victim to talent scarcity.

Today’s talent shortage has negatively impacted businesses for well over a year, with more than 77% of CEOs reporting the ability to hire and retain skilled talent as an important factor in achieving growth. Traditional sourcing strategies aren’t enough; HR leaders must be more targeted and efficient than ever to navigate inevitable shifts in the market.

HR leaders can aim to expedite time and labor-intensive tasks—like scanning CVs for skills—so talent acquisition leaders can focus on more complex work. The goal is to find the right people quickly and accurately. In working alongside talent intelligence, HR leaders should focus on skills-based candidate profiling to revive past candidates as additional potential hires.

  1. Focus on internal mobility for talent retention.

Pursuit of the right talent doesn’t end once HR leaders hire people into open roles. Enterprises must proactively “recruit” their employees throughout their tenure via professional growth opportunities. Employees without a clear vision of their future within their organization are statistically more likely to leave.

Career development for today’s workers means learning and evolving within a multidirectional framework, with space to explore open roles, projects, gigs or mentorships, and with access to learning opportunities to reach them. As such, HR innovators can identify hidden talent within their workforce and visualize internal mobility pathways through skills development, increasing the likelihood that their best people will look for their next opportunity within the organization rather than leave to seek out other options.

Learning Curves And Challenges With Talent Intelligence

As HR leaders continue to define their role in the age of talent intelligence, it’s important to note the current limitations, challenges and learning curves associated with the technology.

Regulations And Responsible AI

As AI becomes more embedded in HR processes, so does the responsibility placed on enterprise leaders to manage the potential implications of AI adoption and to implement responsible AI principles. Responsible AI sources and screens applicants based on capabilities, masking demographics or other factors that can introduce unintended bias.

Regulations mandating bias audits, fairness algorithms and explainability to ensure responsible AI compliance are already on the rise. Regulations take shape from municipalities to states and globally, with compliance guidelines being defined in real time. Enterprises must continue tracking these developments to ensure their responsible AI parameters are in place.

HR Tech: What’s Working, What’s Not

Finally, the explosion of new technologies and AI-driven solutions in the HR space has put more data and automation in the hands of enterprises than ever before. HR leaders under pressure to make business decisions that fuel success, and to do so under tightening budget constraints, are taking a closer look at their HR tech stack to determine what’s adding value and what isn’t.

Overlap between HR tech solutions, or inefficiencies within them, represent an unnecessary expense that’s no longer considered the cost of business. Evaluate your tech stack to ensure there are no redundancies.

As 2023 continues to unfold, HR leaders can solidify their role in the age of talent intelligence.

 

retrain.ai is a talent intelligence platform designed to help enterprises hire, retain, and develop their workforce, intelligently. Leveraging Responsible AI and the industry’s largest skills taxonomy, enterprises unlock talent insights and optimize their workforce effectively to lower attrition, win the war for talent and the great resignation in one, data-driven solution.

To see it in action, request a demo.

 

Sources:

What Will HR Focus on in 2023? | Gartner | October 2022

When Does Your Salary Become a Threat to Your Job Security? | NASDAQ News | 2023

80% of workers who quit in the ‘great resignation’ have regrets, according to a new survey | CNBC make it | February 2023

Nearly Half of U.S. Workers Plan to Look for a New Position in the New Year | Robert Half | December 2022

 

The Responsible HR Forum Presented by retrain.ai

The conversation around responsible HR innovation and best practices has been growing steadily as enterprises look to ethically pursue equitable, diverse workforce growth. Its importance has further increased given the NYC AI Audit law taking effect in July 2023. 

Up to this point, much of the conversation has taken place disparately, with HR leaders, technologists and regulators operating in silos.

We are thrilled to announce that this May, we are hosting a first-of-its-kind event focused entirely on Responsible HR. We’re bringing together key stakeholders to form a community of HR leaders, technologists, educators, advocates and regulators to collaborate on our collective journey toward designing and adopting Responsible HR practices. 

The Responsible HR Forum

presented by retrain.ai

May 17, 2023

New York City

This full day of exploration and discussion will be kicked off by our esteemed keynote speaker, Commissioner Keith Sonderling of the Equal Employment Opportunity Commission (EEOC).

Keith Sonderling, Vice Chair and Commissioner, EEOC

Commissioner Sonderling will discuss increasing Responsible AI regulation as well as what’s on the legislative horizon for enterprises and HR leaders implementing AI-based tech solutions. 

You’re invited to join us as we bring together CHROs, regulators, legal experts, analysts, academics, nonprofits and more for a day of invigorating discussions, shared ideas and key strategies to prepare for this next wave in the future of work.

 

retrain.ai is a talent intelligence platform designed to help enterprises hire, retain, and develop their workforce, intelligently. Leveraging Responsible AI and the industry’s largest skills taxonomy, enterprises unlock talent insights and optimize their workforce effectively to lower attrition, win the war for talent and the great resignation in one, data-driven solution. To see it in action, request a demo

White Box vs. Black Box HR Solutions: What’s the Difference

As AI becomes increasingly embedded in HR systems, enterprise leaders face growing accountability from regulators, their C-suite, applicants, and more to ensure their solutions use ethical, responsible systems to mitigate unintended bias. As a result, Responsible AI is becoming a business mandate, with increasing momentum around laws requiring audits to ensure all benchmarks of Responsible AI are in place.  

One key component of Responsible AI is explainability. Users of an AI-based system should understand how their AI gathers, organizes and interprets data, as well as how the platform produces outcomes.

White box = Explainability

The level of transparency needed to fully explain an AI solution can only be found in what is referred to as a white box solution. With this approach, a full end-to-end view of an AI system’s functionality enables system users to see the what of the system–its data output–while also being able to ask the why–the methodology behind the results.

Such interpretability also allows data scientists and analysts to test the design and internal structure of an AI system in order to authenticate the input and outflow, gauge for errors or inconsistencies, and optimize functionalities accordingly.

What White box Means for HR Leaders

A white box AI solution empowers users to question processes and challenge results, which is especially critical when using such technology within HR functions. Armed with a thorough understanding of their AI solution, an HR leader can be sure their system is performing critical functions, such as mitigating bias risk within its machine learning models. Assured of such mitigation, the organization can stand behind hiring practices that fully support their diversity and inclusion goals.

Black box = Blind Trust

Conversely, there are AI systems for which explanations are too difficult to understand–or aren’t available at all. These are often referred to as black box solutions. In certain settings, black box AI can be useful. The algorithmic complexities necessary in fraud prevention systems, for example, are not explainable in simple terms. 

But within HR functions, a black box system doesn’t allow users to understand how the AI arrives at its conclusions around hiring decision support. As such, there is no visibility to detect errors within the processes, including the presence of possible bias permeating the algorithms.

What Black box Means for HR Leaders

For these reasons, black box solutions represent a significant risk to HR innovators. In the larger sense, they demand a significant level of blind trust. More specifically, by masking information that can derail DEI hiring practices, they render an AI  solution non-compliant in the face of increasing Responsible AI regulation.

retrain.ai and Responsible AI

In providing end-to-end transparency for platform users, retrain.ai is a white box solution. In choosing this methodology, retrain.ai supports the rights of enterprises to know and understand how their HR platforms deliver critical information.

As part of our larger commitment to leading the forefront of Responsible AI innovation in the HR Tech space, retrain.ai works with the Responsible Artificial Intelligence Institute (RAII), a leading nonprofit organization building tangible governance tools for trustworthy, safe, and fair artificial intelligence. To see the retrain.ai difference book a demo

 

 

retrain.ai is a talent intelligence platform designed to help enterprises hire, retain, and develop their workforce, intelligently. Leveraging Responsible AI and the industry’s largest skills taxonomy, enterprises unlock talent insights and optimize their workforce effectively to lower attrition, win the war for talent and the great resignation in one, data-driven solution. To see it in action, request a demo

Disruption That’s Here to Stay: Skills Language & Talent Intelligence 

Across industries, the state of workforce management has been rocked by perpetual change over the last three years. If one truth has arisen from trends like the war for talent and the great resignation, it’s this: People are an organization’s greatest asset. 

Without the right people in best-fit roles, businesses risk obsolescence in a competitive landscape driven by new and evolving in-demand skills. So real is the challenge, a majority of CEOs have reported that the ability to hire and retain skilled talent is their most critical barrier to achieving growth.

Unified Language: The Importance of Skills

For HR leaders, the new world of work demands that talent have the specific capabilities needed in order to succeed in their role. Gone are the days of impressive titles or degrees; in-demand skills are what make or break recruiting efforts. Internal mobility is forever changed as well, with the upward professional ladder climb giving way to a more agile rock wall where skills-based opportunities can come from any direction in a myriad of forms. Roles, projects, gigs, mentorships, learning pathways–all are integral parts of today’s professional development spectrum.

AI: The Rise of Talent Intelligence

To break down every open role and job description into skills needed, or to scan every CV into skills language, would take a traditional HR team more hours than are even close to possible. Yet having a clear understanding of what skills they already have in their workforce, where the skill gaps are located, and which internal or external candidates can bring those skills to the table is critical to future-proofing their organization.

To both expedite the process, and to do so with granular precision, HR innovators are increasingly implementing talent intelligence solutions

What is Talent Intelligence?

Talent intelligence is AI-driven technology that unifies, organizes and interprets a company’s internal data, and combines it with external data on market trends,  emerging skills and labor statistics  in a way that informs and empowers HR leaders to make better workforce planning business decisions. Similar to the groundbreaking capabilities demonstrated by ChatGPT, talent intelligence uses generative AI with similar language processing technology, but expands on the model to provide a fully explainable enterprise-level solution. Built on ethical, Responsible AI means such solutions actively mitigate the risk of unintended bias seeping into machine learning cycles, which can derail DEI hiring practices. 

AI-driven Talent Intelligence and Skills Matching

Using talent intelligence to synthesize the combination of AI capabilities and skills-focused workforce development empowers HR leaders to make faster, better business decisions.

Skills Architecture

Making the best decisions around hiring and internal mobility means HR leaders need to have a clear, granular view of what capabilities their employees have, where the skills gaps lie, and how to future-proof their workforce through developing talent.

Using AI-driven talent intelligence to skills-map an enterprise workforce, HRs can establish unified skills language and an agreed-upon skills framework. Matching it with data insights, they can then align talent decisions with organizational goals.

Talent Acquisition

It’s estimated that in the U.S., it takes more than a month to fill an open position–and that on average, an HR leader must review more than 150 CVs for a single role. Multiply that across a large hiring initiative and there’s a very real cost to an enterprise, including recruiting expenses, time invested by departmental leaders and managers in supporting the hiring process, and the productivity disruption of a prolonged vacancy.

AI-driven talent intelligence helps HRs zero in on best-fit candidates more quickly by analyzing applicants at an atomic level, breaking down their talents into individual skills. Matching applicants with open opportunities, roles or projects based solely on skills means HR leaders can link candidates to best-fit roles with room to grow; and they support DEI goals by eliminating demographic or other information that can introduce unintended bias into the equation.

Talent Management 

As millions of workers quit their jobs during the Great Resignation, one reason continually showed up in the research: Lack of opportunity for advancement. Put simply, at a time when there are more open roles than there are candidates going after them, HR leaders must strategize how to provide employees with a vision for future opportunities that will utilize, challenge and develop a worker’s skills.

AI-driven talent intelligence gives HRs a watchtower view of their workforce, including a granular understanding of employees’ strengths, skills gaps, potential capabilities and hidden talents. Fueled by these insights, HR leaders can provide their talent with personalized career pathing, internal mobility opportunities including roles, projects, gigs and mentorships–providing the kind of positive, proactive employee engagement that’s more likely to retain valuable talent. 

 

retrain.ai is a talent intelligence platform designed to help enterprises hire, retain, and develop their workforce, intelligently. Leveraging Responsible AI and the industry’s largest skills taxonomy, enterprises unlock talent insights and optimize their workforce effectively to lower attrition, win the war for talent and the great resignation in one, data-driven solution. To see it in action, request a demo

VIDCAST: Keep Your Best People Longer with Opportunities to Thrive

Of the millions of workers who quit their jobs over the last two years during the Great Resignation, many cited lack of opportunity for advancement as a major factor. Employees saw investment in their professional development as validation that their contributions were valued and rewarded; its absence sent the opposite message.

Today’s HR leaders must strategize how to hang on to their best-fit hires so they become long-term employees. Much of this comes down to providing a vision for future opportunities in the form of roles, projects and gigs that will utilize, challenge and develop a worker’s skills.

In this session, retrain.ai Co-founder and CEO Dr. Shay David and Chief Research Officer Ben Eubanks of Lighthouse Research discuss how organizations can build a mutually beneficial path forward for valued talent. Their conversation covers:

  • How HR tech can counter today’s quit rates 
  • The connection between internal opportunities and worker retention
  • What we can learn from Great Resignation data
  • The DRIP Problem: Data Rich, Information Poor
  • Implications of the new employer-employee dynamic
  • How AI enhances the human experience at work
  • The importance of Responsible AI and explainability
  • Tips for HR leaders new to using AI-driven tech
  • Talent scarcity as a business problem, not just an HR problem
  • How HRs and hiring managers can align to optimize Responsible AI solutions

 

 

 

Upskilling and Reskilling in Uncertain Times: Wix.com, Second Nature and retrain.ai On Why It’s Time to Double Down (Part 2 of 2)

In a recent panel discussion, Dr. Eli Bendet-Taicher, Head of Learning and Talent Development at WIX.com, Ariel Hitron, CEO of Second Nature, and retrain.ai CEO Dr. Shay David shared insights into current upskilling and reskilling trends and challenges, the transformative nature of AI, and what it all means for the future of learning and development in HR. 

In part one of this blog series, we shared their thoughts on the importance of investing in talent development, mapping skills and unifying skills language across disparate HR tech systems within organizations. Here are more highlights:  

To see the full session on-demand, click HERE.

 

Ariel Hitron: How do you consolidate between the macro and micro, especially for a large enterprise that has thousands of employees? On one hand we’re thinking of skills in terms of capabilities, tasks, roles, etc. in the macro environment, then there’s the day-to-day. Where do you spend most of your energy, time and effort? What are the strategies and tactics? 

Shay David: That’s a great question because it’s kind of global versus local. In our system, we have a process we call calibration. We’ve trained our system to basically help automate the building of that job infrastructure, of that skills taxonomy, and we allow organizations that use that intelligence layer to begin to build their job architecture. 

Our system has learned through natural language processing and has analyzed tens of millions of job descriptions and hundreds of millions of CVs to learn, for example, what are those jobs in practice? From that layer, our system can be calibrated for a specific company–different equipment, different locations, different values, etc. We allow customers to start with a labor market data-fed template and then go through a process of validation. Further input to the system then provides more for it to learn and the process can replicate at every level. We want to get tools to the people that are actually in the field–that need to hire people and train people–so that they can use sophisticated AI not to replace themselves, but rather as decision support.

AH: What do you see when you think about the skills gap in broad strokes like corporate level, and then the people who are actually being hired or reskilled into new roles? How do you connect the two?

Eli Bendet-Taicher: Companies really need to first understand what kind of roles make the most impact and what kind of roles they see changing the most. They need to focus on the problematic roles, the revenue-generating roles—all the roles that make a big impact. We started there because it pains more to lose people there than in other departments. The end goal is to cover everything, but when you have a huge monster like Wix or other big companies, it’s a bit difficult to do all the mapping of roles very, very quickly.

You have to understand what the heat map is–where you really need to focus–and start there. Once you do that, and it’s an exercise that works well, then you can implement it for other roles using a similar methodology. Tools really help you do that. AI is a great tool, but you need to do the fine-tuning through continuous calibration. Once you do that, you’re on a roll.

AH: So after you’ve done the mapping, and know where those skill gaps are, how do you actually deliver in a way that drives change? Making a change in behavior within how people do their day-to-day job is really really hard because people generally don’t love change.

SD: The overall digital transformation and disruptive landscape mean that the environment is changing. And when the environment is changing, the question is, how do we respond to that? The customer-facing teams are probably the first to change, so sales and customer service, which use a lot of soft and hard skills. Second is that there are big gaps, generally speaking, in the market around digital skills, particularly for the older generations. If you were a shift manager at a manufacturing facility and your line of business is changing–maybe because it’s now automated or because some manufacturing was shifted abroad or something like that–what do you do next? We think about skills as a ladder and for a lot of people displaced by automation, digital transformation, or now recessionary pressures, without help they’re at risk of falling too many steps down the ladder.

But what if you could learn some of those new digital skills? It doesn’t mean you become a Python programmer and start building robots yourself, but it could mean you learn how to operate drones, which is an emerging job of the future. There are jobs in moving from old energy to new energy, or from old banking to new banking. Those are all a combination of soft and hard skills but mostly focused on digital. And the good news for learners is that many of those skills can actually be learned online using free content from public sources like Coursera, Udemy, or corporate learning programs, all of which could be made to fit those specific roles and those specific skills.

AH: The acceleration of Covid does put a lot of pressure on salespeople, for example, who have these amazing soft skills they’ve honed over many years like empathy and relationship building. You have very tenured employees having to reskill into this new environment. What do you see in your organization? 

EBT: We always listen to our people in action. So if we see issues with active listening or asking powerful questions, for example, we say okay, we need to create training that is specific for that. We also need to understand whether these behaviors are changing post-training. Then we need to really measure that behavior change to understand, will we be able to move the needle there? How does that translate to more revenue? 

We’re trying to correlate our learning data to performance data to revenue data to show ROI. It’s challenging for every L&D professional to correlate their work to business success, but if they’re able to do it, and they have the tools to offer enough insights and data to show it, they’ll get the budget, they’ll get the headcount. We’re not usually viewed as a revenue-generating department but if my KPIs are derivatives of the business KPIs, I can connect myself to the success and show ROI.

 

 

retrain.ai is a Talent Intelligence Platform designed to help enterprises hire, retain, and develop their workforce, intelligently. Leveraging Responsible AI and real-time labor market data, enterprises unlock talent insights and optimize their workforce effectively to lower attrition, win the war for talent and the great resignation in one, data-driven solution. To learn more book a demo

Upskilling and Reskilling in Uncertain Times: Wix.com, Second Nature and retrain.ai on Why It’s Time to Double Down

Economic shifts are causing some companies to slow down, lay off or cut back on employee services. Does that mean it’s time to hit the brakes on talent development? 

Absolutely not.

In fact, it’s the perfect time for enterprises to invest more in the reskilling and upskilling of their people. Doing so only helps to better address the new challenges of today’s financial crisis and prepare to fuel productivity when the economy recovers. 

In a recent panel discussion, Dr. Eli Bendet-Taicher, Head of Learning and Talent Development at WIX.com, Ariel Hitron, CEO of Second Nature, and retrain.ai CEO Dr. Shay David offered insights into current trends and challenges, and what it all means for the future of learning and development in HR. 

To see the full session on-demand, click HERE.

 

Here are some highlights:

 

Ariel Hitron: To quote the World Economic Forum, “One in three global organizations is accelerating upskilling or reskilling programs in response to COVID-19. In doing so, they recognize the value of their people — the vast potential of each individual to leverage his or her existing skills to add value beyond their current role and learn new skills in response to changing needs.” 

Backing up a bit, why do you think some enterprises are accelerating upskilling efforts at a time when others are cutting back? 

Shay David: When we talk about acceleration, it’s acceleration of several secular trends that already started years ago–namely the capability to be flexible and work remotely, the capability of doing more knowledge work, the capability of having flexible teams. If we look at the larger trends in the market, a lot of it has been about the move into digital services, digital economy, digital transformation in general.  

COVID didn’t invent any of these trends, it was just the accelerator that forced a lot of people to rethink: What are we doing? What skills does our team need? Are we giving our teams those skills? All of the sudden, businesses found themselves needing to reinvent. And when you reinvent a business, you have to add new skills. At retrain.ai, we focus on understanding what that skills landscape looks like, and with a lot of our customers, we’re definitely seeing that trend. 

AH: Now we’re heading into a slowdown in the market. Hiring is definitely changing. Do you think this will also have an impact on the upskilling, reskilling and learning programs? What are your thoughts on that?

Eli Bendet-Taicher: A lot of companies have been downsizing in the past few weeks and months–but they don’t want to downsize their business. So they’re finding ways to be more effective and productive with fewer people. They may need employees to take on more responsibilities or change roles, which in turn means they need to be reskilled or upskilled through programs that are ready to go.

So I actually think this recession will make companies and organizations actually invest more in L&D, more in reskilling and upskilling programs, because they just have to. They still need to thrive, they still need to bring money to the table, and there may be other changes coming. They may even need to pivot the business at some point, and they’ll need to train their people with everything they have in order to do that.

AH: Okay, so as a business leader you have to do more with less, or more with what you have in terms of human resources. Picking up on that, what do you think learning and development leaders need to do to support that?

EBT: At Wix, we needed to really map the skill set and competencies for each role at the company. You have to be able to see what kinds of roles you have, what kinds of roles you need, and what it will take to deliver the expertise in each skill set for every role. It’s a full understanding of: This is what I want, this is what I have, and what is the gap. From there you can create programs specific to bridging that gap. 

We found we also needed to have a great interoperability policy. If I’m moving a person from one role to another, our organization needs to support that person with upskilling and reskilling so they’re able to do the job the best way they can. At the end of the day, you need to invest in people’s learning and development so they know they have that support. 

AH: Wow, a lot, a lot unpack there. So why don’t we start with the mapping of the skills for each role? Shay, you’ve spent quite a bit of time thinking about this challenge. Maybe you can share some of your insights? 

SD: In our view, skills are the atoms that can help define what tasks are; tasks join into roles and roles join into occupations. You can also talk about an interesting hierarchy like capabilities and competencies–there are many different ways to skin the skills cat, if you will–but the bottom line is that you need to have a unified language that consolidates different systems within an organization that are otherwise siloed. 

Think about most of the organizations you’ve met to date. They probably have some sort of human resource information system or some human capital management system, most have learning management systems, probably some sort of onboarding system, employee performance systems, comp and benefit, and so on. Organizations, particularly global enterprises, have six or seven different systems to view their employees. The challenge that we have is that most of those systems don’t speak the same language. So the first order of business is to get the proper language in order to create a cohesive job architecture and skills taxonomy.

In our second post of this series, hear from our panelists about calibrating the macro and micro elements of skills mapping, the demand for hard and soft skills, and how AI can both transform data into actionable insights and enhance–not replace–the human experience of work. 

 

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