Reskilling revolution: tech-enabled talent management for the future of work

Reskilling and talent management market map, by Emerge Education.

We’re building our annual list of the top emerging edtech companies in workforce development for 2024 with our Workforce Development board, chaired by Donald H Taylor. As we do, we’re diving into the trends and opportunities for innovation along each step of the workforce development journey, for individuals and for organisations → from job discovery, pre-hire assessment and interviews to onboarding, coaching and mentoring, skills development and skills assessment, and reskilling for the future of work.

This final article takes on talent management. We’ll explore the role of technology in enabling reskilling at scale, where individual organisational agendas and macro labour market conditions collide.

The learner journey in workforce development.

Read on for:

• Challenges, trends and opportunities, including our predictions for the transformative impact of genAI
• Views from sector experts, plus tips for founders
• A mini-market map of key players and top emerging startups in this space

Keywords: reskilling, future of work, skills gap, talent management, skills, training, learning, workforce development, L&D, skills development, skills assessment

💡 Why it matters

Dictionaries might be an unusual place to look for workplace trends, but the buzzwords they highlight each year can tell you a lot. In 2022, ‘quiet quitting’ defined a generation seeking to reimpose a work-life balance. And in 2023, Collins’ Word of the Year was artificial intelligence, capturing the hype around generative AI alongside the hopes and fears it represents — not least for workers.

Estimates suggest that 40% of the workforce will need to reskill due AI-driven automation over the next three years. That translates to 1.4 billion of the 3.4 billion people in the global workforce, according to World Bank statistics.

On the surface, organisations seem to be rising to this challenge: of Fortune 50 companies, 34% have made reskilling and upskilling top strategic priorities and have designated a hefty 1.5% of their annual budgets to support them. But investing in reskilling infrastructure, such as another LMS or LXP, doesn’t mean much.

Traditionally, higher education has been viewed as the primary route to secure a meaningful career. But more than 100 million low-wage workers globally may need to find new jobs by the end of the next decade. The WEF predicts that 44% of workers’ skills will be disrupted between 2023 and 2028 — up nine percentage points from its last five-year projection (when they predicted this would disrupt 85 million jobs globally between 2020–2025). McKinsey puts their number at 375 million workers in need of reskilling by 2030.

“Along with the promise of AI — to redefine how we work, rather than replace our work — organisations will still be pressed to have employees who know how to leverage the new tools and technologies rolling into their workflow. Add in the pursuit of market growth, declining birth rates, changing academic attainment standards and the need to draw upon non-traditional candidate pools, and you’ll find many companies compelled to keep talent management and reskilling at the forefront of their people efforts. This will likely be very challenging across at least the next decade.”

Rob Lauber, strategic advisor — future of work Guild Education and Emerge VP

🏈 State of play

• Current generative AI and other technologies have the potential to automate work activities that absorb 60% to 70% of employees’ time today. The OECD has predicted that automation will eliminate 14% of the world’s jobs by 2040. A recent survey found that 4 in 5 executives say generative AI will change employee roles and skills, but only 28% have assessed the potential impact of generative AI on their current workforce.
• The average half-life of skills is now less than five years, and in some tech fields it’s as low as two and a half years. For millions of workers, upskilling alone won’t be enough.
• As a result, there are a lot of shrinking occupations. Twelve million occupational transitions are likely going to need to happen between now and 2030, with 80% of those in four occupational categories: customer service, food service, production or manufacturing, and office support. Those four occupations are going to need a lot of reskilling and support to encourage those workers to gain skills that will open up opportunities in other occupations that are growing in our economy. People in lower-wage jobs, below $38,000 a year, are 14 times more likely to lose their job or need to transition to another occupation than those with wages in the higher range, above $58,000, for example.
• Yet only 30% of employees at risk of job displacement from technological changes received training in recent years, and those most at risk are often the ones who are least likely to receive any retraining at all. A lack of career growth is one of the main drivers of turnover in organisations, regardless of industry — and on the flip side, more than half of employees aged 18–34 say career development and advancement potential are the main reasons that keep them in their jobs.
• One of the growth areas is the green economy. On the net-zero side, we see a net increase of around 700,000 jobs. However, this is actually displacing around 3.5 million jobs, so while that will be a huge growth driver in the future, there is a lot of disruption in the overall job economy for that net creation. How do we help workers transition from categories that are potentially declining to those greener jobs?
• In addition to hiring for skills rather than degrees, organisations could view these occupational shifts as a real opportunity to think about pipelines and pathways. In a Deloitte survey, 76% of C-suite respondents rated internal mobility as important, and 20% rated it one of their organisation’s three most urgent issues.
• We discussed in our previous piece the economics of promote vs hire.There’s a clear organisational benefit in building relationships with individuals by supporting them with their own development: 87% of Multiverse apprentices stay with their employers long-term, and 50% are promoted within six months. This makes intuitive sense: not only are these employees a proven fit for organisational culture, but their pre-existing institutional knowledge enables them, on average, to outperform new hires for the first two years in a role.
• The main drivers and motivations for reskilling and upskilling efforts worldwide in 2022 were increasing skills of existing staff to offset the need for outside hiring, followed by retention strategy. Reskilling programmes require sharp planning and a clearly-delivered outcome to succeed — when done so, 75% of completed reskilling programmes are economically positive, typically delivering productivity increases of up to 12% per worker.
• Forty-five percent of global businesses see funding for skills training as an effective intervention available to governments seeking to connect talent to employment. Funding for skills training ranks ahead of flexibility on hiring and firing practices (33%), tax and other incentives for companies to improve wages (33%), improvements to school systems (31%) and changes to immigration laws on foreign talent (28%).
• Another factor that is impacting on the labour market is an ageing workforce, which will affect everything as it relates to retirement and the fact that we’ve seen quit rates at an all-time high over the past two years. In the UK, the Centre for Ageing Better’s analysis of ONS data finds that only around one third of workers aged 50+ are typically re-employed after a redundancy.
• These changes are exacerbating skills shortages. The ManpowerGroup Talent Shortage survey revealed that 77% of organisations worldwide can’t find the skilled talent they need. Only 10 years ago, this figure sat at 35%, demonstrating how dramatically the problem has escalated. Skills shortages threaten to undermine growth strategies and commercial performance, and they represent an existential danger for many organisations. Of those polled for PwC’s 23rd Annual Global CEO Survey, 75% stated that finding the right skills threatened their business. The demand for AI skills, for instance, is very high, but the talent pool is limited; Deloitte reveals that 68% of early AI adopters report a moderate-to-extreme skills gap.
• The good news is that evidence indicates that workers are highly receptive to reskilling. BCG research suggests that two-thirds of workers are aware of the coming disruption in their fields and are willing to reskill to remain employed.

🚨 Challenges

“One of the biggest challenges/obstacles I see is that the People or HR function is too siloed. Rather than working in lockstep, for example, talent and learning are more like frenemies, with competing budgets and priorities, when there should be a joined-up strategy around when to hire and when to upskill to close critical skills gaps. That’s one of the reasons why I advocate for a Chief Skills Officer, which should ideally be part of the Strategy function rather than HR.”

Amanda Nolen, learning and skills strategist, and Emerge VP

• A skills taxonomy is only the first step. Building a dynamic, scalable job architecture — a real-time view of the skills needed for all the tasks in a business — is hard and time-consuming, especially as the nature of work is changing so quickly. But even with this important foundation when it comes to skills intelligence, you are still only seeing one part of the picture. Comprehensive, real-time labour market insights built-in are an important piece of the puzzle for talent acquisition, talent management and strategic workforce planning. Next comes the difficult job of deciding which skills get mapped to which jobs. Managers from different divisions may disagree about this; such disagreement is often symptomatic of a deeper misalignment, and companies will need to resolve that before they undertake any major reskilling initiative.
• Data alone is not enough. Untangling skills definitions and taxonomies alongside a greater availability of learning sources are not a guarantee of career progression. Digital content alone is not the silver bullet and neither are performance management frameworks. The wealth of skills data isn’t meaningfully connected yet. LinkedIn (hiring) and Oracle (CV screening) are leading HR behemoths that sit on a ton of skills data but have not done much yet to connect it. IBM Watson and Lightcase (formerly Burning Glass and EMSI) have done incredible work to demystify skills taxonomies and to understand macro skills trends to inform staffing plans, but gaps persist on a micro level in building employee-focused progression ladders.
• Improved skills still don’t equate to outcomes. Learning you are a 60% likely fit for a new job, with a few upskilling courses recommended to you, based on a data algorithm, isn’t going to get you far in life. Every human has their own circumstances and preferences, and automated career recommendation and guidance approaches in isolation fail to make a genuine impact. If you don’t have opportunities to show your skills, you could encounter problems with internal mobility and career progression, especially in large organisations. This means cleaning up organisational understanding of gateway and entry-level jobs that facilitate mobility. Performance reviews should take an organisational view, combining individual career aspirations with future jobs required by your company. Organisations such as Faethm and FutureFitAI use data analytics to assess, reskill and transition employees within an organisation.
• Job obsolescence. As automation shrinks the boundaries around jobs, many low-skill, low-paid jobs are effectively being designed to de-skill those working in them. Obsolescence is not inevitable — skills pathways can redesign entry-level and at-risk roles.
• The alternative credentials ecosystem is large and fragmented. In the UK alone there are currently more than 15,000 qualifications on Ofqual’s Register of Regulated Qualifications, offered by 242 different awarding organisations. Individuals aiming for a career in plumbing, for example, have to choose between 61 qualifications. Faced with such a bewildering array of options — and even more credentials and badges available online — plus limited transparency on outcomes, learners often make inefficient decisions when choosing training. Resolution Foundation data on training and job re-entry from previous recessions has found that longer-term training, full-time education or training associated with an employer was most likely to result in people returning to jobs; short bursts of modular and/or part-time training was less associated with either switching industries or getting back into the job market at a higher rate.
• Overall, adult participation in learning is falling, and it is not distributed evenly across society. The poorest adults with the lowest qualifications are the least likely to access training, despite being most in need. The result is that less than 60% of workers escape low-wage, low-skill clusters over the course of 10 years, and the odds decrease thereafter.

🔥 Trends

“The increasing pace of technology necessitates an increased frequency and speed of skill acquisition for people who want to stay relevant. This speed and frequency will also drive a shift to smaller units of knowledge: skills, competencies, micro-credentials. You can’t take four years to get a degree when half the job changes in two.

Companies will need help to rethink all their processes and systems that were built around qualitative interviews and performance reviews to find ways to determine what individuals really know and need to know. This will lead to increasingly blurred lines across traditional HR functions, as companies will need to think about the holistic employee lifecycle and pull multiple levers to get the talent they need. Do you build your talent or buy your talent? If you have a big talent acquisition team they may encourage you to buy; if you have a strong talent management team you might build. The answer should be that talent acquisition looks as much external, rather than thinking of this as being in competition with internal.”

Jonathan Lau, cofounder InStride and Emerge VP

• Interest in reskilling is noticeably increasing. It was the second hottest topic in the recent L&D Global Sentiment Survey 2024 . The interest is no fad. Google Trends data reveals that queries about reskilling have been rising robustly over the past five years. “A few years ago, few were talking about talent mobility,” Josh Bersin has noted. “Today, roles are shifting quickly, skills become obsolete faster than ever, and organisations must find people for new roles or projects rapidly. At the same time, employees expect to try new work, learn adjacent skills, work with new managers and teams, and take international assignments.”
• Although current skills shortages and skills gaps must inform skilling and training provision, they should not drive the way that skills are shaped. Training around specific skills risks training people into siloes. Previously, the ideal was to train employees with a ‘T-shaped’ profile, signalling deep expertise in one knowledge area combined with broad skills and the ability to collaborate across multiple disciplines. Workers tended to develop deep expertise early in their career and then supplement this knowledge over the years with on-the-job development of integrative competencies. Reskilling, with a goal towards sustained employment, requires a more flexible ‘M-shaped’ profile, where people reskill multiple times over the course of their career.

• Cognitive and self-efficacy skills topped the World Economic Forum’s list of the top 10 skills of 2023, with analytical and creative thinking leading the way. This is followed by resilience, flexibility and agility, motivation and self-awareness, curiosity and lifelong learning.
• The pace of workforce transformation is likely to accelerate, given increases in the potential for automation. In the latest McKinsey global survey on AI, 65% of respondents report that their organisations are regularly using gen AI, almost double the previous survey just ten months earlier. Respondents’ expectations for gen AI’s impact remain as high as they were last year, with three-quarters predicting that gen AI will lead to significant or disruptive change in their industries in the years ahead. The research also shows that many employees believe they lack the skills to use gen AI safely and effectively — and expect their organisations to provide those skills. Middle managers have a critical role to play in increasing employees’ comfort with both short-term gen-AI-enabled work and long-term collaborations with the technology.

🌍 Key players

Reskilling and talent management market map, by Emerge Education.

This is a rapidly evolving space: just last month, for example, Cornerstone acquired SkyHive’s AI-powered skills intelligence platform and Randstad acquired torc, the AI-powered talent marketplace with more than 25,000 digital talent enrolled worldwide, with a specific current emphasis on LATAM, the US & India.

🔭 Who is getting ahead?

Businesses are typically less successful at reskilling than upskilling, because reskilling requires an organisation to work multi-functionally. Yet many companies are making significant investment in this area.

Microsoft announced earlier this year that it would equip 2 million people in India with AI reskilling opportunities by 2025. IBM has committed to training 2 million people in AI over the next three years, with a focus on underrepresented communities. Google Cloud has announced a new set of generative AI training content, available at no cost. Vodafone has pledged to fill 40% of its software developer needs with reskilled employees. Engineering and technology company Bosch has committed €1bn to reskill employees in high-growth roles such as AI.

Amazon’s Upskilling 2025 pledge includes a $1.2 billion commitment to upskill and reskill its employees. In another initiative, Amazon allows employees in its Career Choice program to pursue everything from bachelor’s degrees to certificates, and covers all costs in advance. That has proved to be a key factor in scaling up the program, which has already had more than 130,000 participants. Through its Machine Learning University, Amazon has enabled thousands of employees who initially had little experience in machine learning to become experts in the field. (It’s perhaps no coincidence that Amazon topped LinkedIn’s most recent report on the best US companies to grow your career.)

Uber covers tuition fees through the Open University, full time or part time, from flexible modular microcredentials up to undergraduate degrees. The learning-as-a-benefit scheme is available through the Uber app to Uber Diamond drivers, but drivers can also pass the benefit on to a family member (partner, child, sibling) who lives in or outside the UK. A two-year pilot was launched in early 2020, and later extended to UberEats.

During the Covid-19 pandemic, CVS used an intense, academy-like reskilling program to hire, train and onboard people (some of them laid-off hospitality workers) to create capacity for its critical vaccine and testing services. Now, the executive team has made training and reskilling an integral part of the company’s business strategies, so CVS has reskilling metrics built into performance assessments.. Each individual business leader is now responsible for designing and delivering workforce-reskilling plans to help the company reach its goals, and the ability to do so is factored in to performance assessments.

As part of its ongoing digital transformation, Ericsson developed a multiyear strategy devoted to upskilling and reskilling. This involved systematically defining critical skills connected to strategy, which correspond to a variety of accelerator programs, skill journeys and skill-shifting targets — most of them dedicated to transforming telecommunications experts into AI and data-science experts. The company considers this a high-priority, high-investment project and has made it part of the objectives and key results that executives review quarterly. In just three years Ericsson has upskilled more than 15,000 employees in AI and automation. Reskilling pathways are built into the company’s policies, tools and IT platforms.

🔮 Predictions

Today’s solutions define and untangle skills, while offering skill-informed content and learning pathways →

The pioneers in this space, including IBM, Lightcast (who recently started working with SAP, which used to maintain an in-house taxonomy of 7,000 skills, to keep a continually updated skill database) and the World Economic Forum (HSBC use a customised version) have helped employers and governments demystify and understand existing skills and future skill needs thanks to extensive skill databases and taxonomies. They give employers and employees the taxonomy and tools to understand more about themselves and their opportunities. Separately, content providers and curators have created skill-informed content and learning pathways that help take you from no to some knowledge of a topic, including Udacity’s nanodegrees and EdX pathways.

Tomorrow’s solutions will show relationships between skills and roles, while providing facilitated role-aligned career pathways and transitions →

Today it is still not crystal clear how roles relate to one another, how content X relates to content Y, nor how content and learning pathways facilitate role progression. To demonstrate greater impact and to experience greater uptake, skills taxonomies will have to show how role demands are changing and relate to one another, and training solutions of the future will have to actively use this information to move people from A to B. This means solving problems for employees who want to move from role A (such as database administrator) to role B (data analyst) and for employers who have employees in group A (such as product designers) that need to shift to group B (product managers).

How could that happen?

• Meaningfully connecting and unlocking the power of data. The next wave of big data solutions should help connect skills and create meaningful career progression pathway infrastructure. This means, for example, showing the exact progression of skills that project managers need to acquire to become product managers. This will have to consider levels of competency (such as, how does the progression change if I’m a level two vs four project manager?), as well as industry and geography. By looking at raw data about learning content, Filtered has built technology and a methodology to decipher the natural language of learning content into skills taxonomies. That work can now be joined up with job role data to make the connection from human being to learning content via skills, across companies, at scale. This just wasn’t possible five years ago. It is one example of what good data-oriented collaboration can bring.
• Guided career progression pathways. Where needs are more defined and outcomes are clearer, structured B2B corporate bootcamps could help elevate employees to promotions. Where direction is less certain and hands-on support is less needed, a guided mentoring and career advising touch could prove impactful alongside data-informed pathway scaffolding.
• Freelance gig marketplaces for for existing employees. Talent platforms are starting to pave the way for easier internal mobility by connecting employees with open positions. As they evolve, they could create modularised short tasks for existing employees, in the same way Upwork or Fiver help modularise tasks and work for remote and freelance talent, to help them prove skills, meet people on other teams and further expedite and democratise internal mobility. Novartis has implemented an AI-powered internal talent marketplace that predicts, matches, and offers roles and projects related to employees’ skills and goals.
• Assessment and accreditation mechanisms will also need to be flexible to the needs of diverse groups of learners. Qualifications for adults will increasingly follow a pattern of modularisation to be integrated within a system of credit accumulation, which can recognise and stack prior experience and prior learning, even where full courses (such as degrees or apprenticeships) are not completed. Portability will be vital, so that learners can own their own learning and transact on the basis of their qualifications.

🎯 Opportunities for startups

GenAI engines of opportunity for workforce development.

In this category, we see particular opportunities for AI-driven solutions that offer:

• Career navigation tools → Problem: When it comes to career choices, we are still in the dark ages. Solution: Use AI to create better predictions of good fit career paths.
• Learning networks and communities → Problem: Masterminds one of the most valuable ways to learn, yet not really scalable. Solution: Tech that enables masterminds/other communities to form and support each other.
• Flight simulator for interpersonal skills → Problem: Practising skills in a high-stakes environment is not the best way to learn because you cannot afford to fail, so in practice it doesn’t happen. Solution: generative AI unlocks flight simulator training for complex interpersonal situations — interactive learning experiences that create safe environments in which to train for high stakes situations or interpersonal skills. This is especially exciting as this moves from chat, to voice, to XR.
• Teaching employees how to use software to enable them to be more productive → Problem: Most SaaS tools are only used in limited way by majority of their users. Solution: Includes teaching AI, no-code skills and how to use sophisticated software.
• Learning materials co-pilots → Problem: Content creation is expensive and takes a lot of time, yet is critical. It’s basically in the job description of L&D professionals. Solution: Until now, machine learning techniques were used to recommend the right pieces of pre-fabricated content to learners. Today, we are starting to use generative AI to create the right piece of content for the learner from scratch based on their needs, radically reducing the cost and improving the effectiveness of learning materials creation.
• AI-powered second brain → Problem: We constantly come across new information and struggle to retain it. Solution: Better capturing and processing of things you read/come across and helping you apply it in your day-to-day. One big feature of this would be AI-powered automated tagging of the things you capture.
• Frontline worker management → Problem: Frontline workers are underserved. Systems to manage them are focused on ERP, not shopfloor. Solution: Shopfloor level management systems that are used by frontline workers 24/7 to track tasks, competencies, development, safety compliance and more, leading to greater productivity, transparency and development opportunities.
• Company-specific LLM for skill assessment → Problem: Tribal knowledge in companies is not systematically collected and organised to power hiring and development. Solution: Connecting all of a company’s performance, goal management and career development data to train a company-specific LLM that can power other applications/use cases like hiring, performance coaching/feedback and career progression.
• Entrepreneurial upskilling → Problem: There is a long tail of entrepreneurs and business owners (often outside tech) that have little to no support with how to run their business. Solution: Resources, programmes and guidance for this demographic.

💎 Tips for founders

• Focus on ecosystem integrations. Make sure your product clearly fits within the broader HR and workforce development data and tool ecosystem and has an extended value chain vision. Odds are your early stage product won’t (and shouldn’t) be solving the full value chain of your customers’ problems. As such, don’t expect your clients to replace their longstanding SaaS infrastructure and download new software. Integrate with existing systems and data through APIs, and minimise friction and time-to-value while maintaining an ambitious product vision that can deliver more value over time in the workforce development journey
• Leverage external brand credibility. In a sea of self recognised ‘award-winning’ startups, find ways to leverage external credibility to jumpstart your brand. The main sources of external credibility include: practitioners, influencers, academia and big name clients, with various levels of potential impact depending on your business. We would like to see more companies that leverage practitioners and influencers, which we believe is a highly relevant untapped source. For example, while it’s enjoyable listening to a professor’s HBS social entrepreneurship Grameen bank case study, learning guerrilla tactics on setting up a challenger bank directly from Muhammed Yunus could be much more powerful. While there are a lot of great marketing content creators, many people would be better off learning growth hacking from growth hacking thought leaders like Andrew Chen.
• Differentiate through process excellence. Content will not be a difference maker in this crowded marketplace. All bootcamps build key features such as careers services, robust curriculum, strong employer networks and so on. How will you deliver better student experience and outcomes? For example, Springboard uses virtual internships and one-to-one mentoring, matching every learner with an expert practitioner in their target industry to provide weekly tailored support including goal setting, progress tracking and technical feedback. These are operationally difficult to scale — Springboard has 1,000+ mentors — but students say they are leading reasons for choosing them. Learners need to trust this is the right choice for them, which could mean evidence around employment outcomes, salary increases, and/or alumni endorsements.
• Signpost pathways. Be clear about your learners’ starting point and the learning pathway you are building. For example, Kenzie Academy offers different related job pathways, so if a learner is struggling with one pathway they can consider pivoting, rather than dropping out. Scaffold towards learning opportunities after the course finishes; the initial focus may be employment outcomes, but learners will also need a pathway to future skills building in association with that career. This is especially true of short courses and bootcamps.

🔗 Read on

• How to build a unicorn in workforce development
• Simon Nelson, former founding CEO of FutureLearn, shares his experience of building and scaling Europe’s largest MOOC platform — Product-Market Fit Academy
• Jonathan Lau, co-founder and COO of InStride, shares different ways to monetise edtech products and five go-to-market strategies — Product-Market Fit Academy
• Developing skills and establishing new pathways into jobs (2021), our deep dive report in collaboration with Coursera, Ufi and Filtered
• Our focus on frontline workers — read overview and market analysis here, and full report here
• Part 1 in this series → How startups can drive innovation in recruitment, career navigation and pre-hire skills assessment
• Part 2 in this series → Edtech for employee engagement: how startups can support onboarding, retention and a strong learning culture
• Part 3 in this series → Can technology and AI support coaching and mentoring at scale?
• Part 4 in this series → (S)killing it: how workforce development and learning will power our AI future

Read more news, views and research from the only fund backed by the world’s leading education entrepreneurs, in Emerge Edtech Insights.

📣 Call to action

We are now building our list of the top emerging edtech companies in WD in 2024.

👇 If you have seen an exciting company in this space, please tell us in the comments 👇

Our list analyses 100s of companies operating worldwide, using public and private data — it is crowdsourced, and voted on by our Workforce Development edtech action group, led by Donald H. Taylor.

Please share companies you think we should consider in comments 👇and join us on 3 July to discover who has made the final list!

🙏 Thanks

At Emerge, we are on the look-out for companies (existing and new) that will shape the future of workforce development over the coming decade.

If you are a founder building a business addressing any of these challenges in L&D, we want to hear from you. Our mission is to invest in and support these entrepreneurs right from the early stage.

If you are looking for your first cheque funding do apply to us here: https://lnkd.in/eWi_9J5U . We look at everything as we believe in democratising access to funding (just as much as we believe in democratising access to education and skills).

Emerge is a community-powered seed fund home to practical guidance for founders building the future of learning and work. Since 2014, we have invested in more than 80 companies in the space, including Colossyan, FutureFit AI and SkillsTrust.

Emerge Education welcomes inquiries from new investors and founders. For more information, visit emerge.education or email hello@emerge.education, and sign up for our newsletter here.

Thank you for reading… I would hugely appreciate some claps 👏 and shares 🙌 so that others can find it!

Nic