Everywhere I go companies are focused on building a skills-based organization. Originally fueled by the need to hire and build digital skills, today companies are looking for skills in AI, new energy technologies, batteries, genomic sciences, and a vast array of new platforms, products, and industry processes.
Why is this happening? There are two enormous economic drivers.
First, our industries are collapsing. Retailers are becoming healthcare companies; energy companies are investing in solar and batteries; auto manufacturers are becoming software companies; and banks and financial services companies are now digital powerhouses (well, they’re certainly trying).
We study this industry convergence in our Global Workforce Intelligence program, and our new Pacesetter research (the top 10% most transformed companies in each industry) clearly shows that high performing companies simply have deeper skills in new technologies and practices than their peers. They can “see around the corner” in their business models because they understand where their industry, technologies, and customers are going.
But there’s a second reason: people are living longer. For the first time in my adult life the average employee life expectancy is almost four times the life expectancy of a company. According to historic research by JP Morgan Chase, 75% of companies disappear within 15 years. Yet we, as employees, now live into our 90s and we often have 60+ year careers. That means that we, as workers, have to “reskill ourselves” many times during our lifetime.
Our new research on banking finds, for example, that highly skilled software professionals are very aware of “salary-increasing skills” and they now refuse to work for companies that don’t use new technologies or promise to give them the skills they need for the future. So if we, as employers, are not constantly building new skills, our employees will simply leave. (At least the high performing ones will).
Supporting this change is a massive industry of new tools, platforms, and systems to assess skills, infer skills, find adjacent skills, and then help people build skills within your company. I won’t belabor you with all the solutions, but there are hundreds of vendors selling solutions in this area.
How, do you, as an organization, make sense of all this?
Well every company is arming up with tools. Learning vendors are selling skills-based content (our Josh Bersin Academy is built around 92 critical skills for HR professionals, for example). Recruiting vendors are building AI-powered skills engines to find candidates and source internal staff. Talent Marketplace vendors are building tools to help employees find mentors, coaches, projects, and internal positions. And big HCM vendors like Workday, SuccessFactors, Oracle, and ServiceNow are building end-to-end career and skills platforms to help bring this all together.
But there’s a huge missing link. How do you, as a company, possibly keep up with all the “skills” you need to know about? How does Chevron, for example, understand all the new skills they may need for energy engineering, power generation, or possible new businesses in mining, solar energy, or fuel cells? How does a pharma company like Moderna or Bayer keep track of all the new scientific discoveries in medicine and the skills they may not even know they need?
This is a massive, unsolved problem. As companies build these skills-based platforms they need data. Yes, the AI systems will “infer skills” and “create skills taxonomies” from information within your company. These systems can now mine your resume, your job experience, and your actual work (read your documents, your emails, your code, and your certifications) and find new skills, adjacent skills, and emerging skills. But how do you rationalize all these lists of skills against new jobs, industry trends, and the broad market for new roles and careers in business?
This is where Lightcast comes in. Lightcast, which is the merger of Emsi and BurningGlass, is the largest integrated data provider of jobs, skills, roles, and occupational data in the world. The company has been sourcing, consolidating, and integrating this data for more than two decades and they take the quality and validity of their data very seriously. Every day Lightcast scans all the jobs posted in over 40 countries to find new job titles, new skills, and new technologies and processes entering various domains of business.
If you want to get a sense of how dynamic this is, just look at Lightcast’s weekly skills updates. It’s astounding what they do. This company sources information from 18 billion government data points, over three billion historic job postings, more than 300 million employee profiles, and almost 10 million company profiles.
They clean this data up, aggregate it, and most importantly match it to a public skills taxonomy they maintain that shows the dynamic relationship between skills and jobs. Lightcast also maps these skills to government occupations to let you apply these skills to your jobs for sourcing, recruiting, and workforce planning. And since they have historic data, you can see trending hot skills, salaries, and even new job titles very easily.
I asked Lightcast, for example, to give me information on “people analytics” roles in HR. They showed me that the average pay in these jobs has increased by 38% in the last three years, and that skills in SQL are rapidly declining while skills in Python, R, and PowerBI are rapidly increasing. They also show me the cities and states where these jobs are located, and also inform me that 32% of these folks have Master’s degrees and 5% have PhDs.
So Lightcast data is not only validated and cleaned up, it’s also correlated with real jobs in real cities with real wages. So if you’re trying to build a skills-based architecture for your company, this kind of information can be vital.
The reason I write this is not to promote Lightcast per-se, but rather to highlight an important point. Whatever skills technology you select, the quality and usefulness of your data is vital. As companies build more and more talent intelligence teams and you start to access lots and lots of skills data you’re going to be constantly saying “well, are we ahead or behind in the market for this skill?” Or “what skills are we not even aware that we need?” This is the type of information Lightcast can provide.
And there’s more: there are many data providers in the market. Lightcast is also an advisory firm – they can teach you how to use this data and show you where it fits in your skills-tech architecture. I’ve talked with many Lightcast customers and they use this data for labor market analysis, sourcing, and important decisions like where to locate a new facility, where to place job ads, and what big new capability academies they should work on.
The Lightcast data is not exhaustive: there are always new skills being created. But this is a strong, hard-working team, and I’ve found them to be exceptionally helpful in just about any question you ask.
Lightcast has also joined us with Eightfold in our Global Workforce Intelligence Project, and they are helping us with a series of important industry Factbooks that I know you’ll find fascinating. The first one, which details skills gaps and trends in Banking, will be coming out soon.
I suggest you check them out: without a source of well organized, quality jobs and skills data, an enterprise skills initiative will struggle.