EdCast Expands The LXP Market With Focus On Global Upskilling
As I’ve described in several articles over the last few weeks, the Learning Experience Platform (LXP) market is growing rapidly. This market is now over $200M in size, growing at over 100% per year, and vendors like Degreed, EdCast, Fuse, CornerstoneOnDemand, SkillSoft, Valamis, and others are jumping in.
In this article I’d like to highlight EdCast, one of the early players in the space, and explain how the company is focused on upskilling by building a series of “skills marketplaces.”
About EdCast
EdCast was founded in 2014 by software entrepreneur Karl Mehta. Karl founded the company when he was working as a venture capitalist doing research on many of the technology trends in his portfolio. He saw the need for an aggregator of information to help people learn and stay current on trends in technology.
While Karl did not come from the HR market, he brings a technology perspective to the LXP space. He is a successful entrepreneur (he was Founder & CEO of PlaySpan Inc., acquired by Visa Inc.), he served as a White House Presidential Innovation Fellow during the Obama Administration, he was on the advisory board of Intel Capital, and he founded the Silicon Valley based tech-driven non-profit, CodeforIndia.org. So he sees the world of skills and education on a global scale.
He positions EdCast as “the knowledge cloud for digital economy” and I believe first coined the term “Netflix of Learning.” He sees the LXP technology as a vertical federated search and content platform, extensible to skills development in any domain.
EdCast wants to be the platform for learning and information discovery, focused on many different audiences. To advance this strategy EdCast acquired two companies (Sociative, a machine-learning company started by two senior machine learning experts; and Sales University, a company that built an AI-based sales enablement solution.) EdCast also introduced GuideMe, a digital enablement tool competing in the growing market for online performance support systems (WalkMe, SAP EnableNow, and others compete in this space).
Why the acquisitions? EdCast believes the real problem is digital knowledge management, so the company is building a complete knowledge platform filled with content, expertise, and deep levels of machine learning.
EdCast’s Upskilling and Content Strategy
A series of recent announcements clarify where the company wants to go. Consider the two markets for skills development in business:
Internal Corporate Upskilling: Inside a company (the green circle on the left), the LXP has the potential to collect, publish, tag, and recommend training, articles, documents, and videos to employees in a personalized and relevant way. Using machine learning, the software can align content to your role, your desired skills, and connections to other experts. Each company has its own specific roles, internal content, and desired career paths, so the LXP becomes an internal “reskilling” platform and career development tool, unique to the way your company works.
Most companies have enormous problems in this area. One of EdCast’s clients, for example, has more than 80 different paid subscriptions, all on independent portals. The LXP can index this information and make it relevant to people who never knew it was available.
Public and Professional Upskilling: In the broader economy (the blue circle on the right), the LXP can perform a similar function for professional networks, communities, and global reskilling programs that cross company boundaries. This is where EdCast has been focused, driving broad usage and deeper domain expertise in certain professions.
While corporate buyers look at solving the problem on the left, which is company-specific, they also need the solution on the right, to help each individual advance their personal skills. So the two markets are very complimentary.
LMS vendors have dabbled in this market for years, selling their LMS to for-profit content companies, educational institutions, non-profits, and other organizations selling training. But it has been difficult for LMS vendors to bring these two worlds together, because the SCORM API keeps content separated from user data.
In the LXP market, where content publishing and sharing is integrated and machine-facilitated, we can think about this problem as a set of vertical “skills marketplaces” (common courses, credentials, skills models, etc. in a given profession). This is what EdCast hopes to achieve.
A Little Background on Machine Learning (ML) for Learning
To understand how these blue and green circles come together, it’s important to briefly discuss machine learning.
As a software platform acquires data (Google, Netflix, Amazon, Facebook, and others), engineers can start to write algorithms that predict behavior, improve recommendations, and refine search results. Netflix does this for movies; Amazon does this for shopping; Google does this for general search. Data is the engine that fuels these companies, because it teaches their systems how users behave and what they want.
The AI and ML algorithms, while also important, are more of a commodity. Engineers can find machine learning algorithms in open source, or they can use Google, IBM Watson, or Amazon APIs as their tools. As the data set becomes bigger and deeper (more voluminous in a given domain), the system gets smarter and smarter.
In the case of employee development, the problem of providing job-relevant learning is complex. (I consider it a “vertical search” problem like Google for Jobs, Google Image Search, etc.). We have to consider the job, its requisite skills, an individual’s existing level of expertise, the desired skills and credentials people want to achieve, and finally the credibility, authority, and mentorship of the authors or coach. There is a lot of data to analyze.
As I’ve thought this through, there are at least four types of data to bring together.
Given this rich set of data, there is a lot of opportunity for machine learning to add value. A well-performing can ingest data, categorize it, and learn over time – and the more users and context it can obtain the better.
Companies like Netflix, who have worked on this for years, have created “personas” of different consumers, so they know what types of movies and content appeal to each group, reducing the size of the problem. Facebook has done this, and I’d imagine Amazon does as well (I’d guess Amazon has many buyer profiles in its algorithms). Over time we would like the LXP to do the same: get smarter about IT training, security training and sales training, etc.
While all the LXP companies are working on this (Cornerstone, Degreed, EdCast, Filtered, Fuse, Skillsoft, Valamis, others) engineers have told me that ultimately the best solutions will be the ones with the best data. And the must be domain specific and deep, so we can apply repeatable models to each learning strategy. (This is often called narrow AI, because it is focused on a specific problem.)
Let’s suppose you’re an engineer and you want to learn how to code in Blockchain. If you buy a book on the topic it will start at the beginning, take you through concepts, show you code, and ultimately give you examples. In an LXP you may have hundreds of books, courses, certifications, and expert material available, and the ML engine can potentially display this in a personally relevant fashion.
What EdCast Is Doing Now
Let me now briefly discuss three of EdCast’s publicly announced global initiatives.
NASSCOM’s Global Skilling Program
The first I want to mention is the NASSCOM global reskilling program. NASSCOM is one of the largest professional development communities for IT, outsourcing, and technical skills. The organization, headquartered in India, supports more than 4 million technical and outsourcing professionals and provides training, skills maps, career guides, and professional programs for some of the world’s largest companies. Because India is one of the world’s fastest growing economies and has become the global hub for technical outsourcing, NASSCOM has an enormous database of information about skills needed in the future.
Right now, working with EdCast, NASSCOM has created its Future Skilling Initiative, which has identified nine critical emerging technologies for IT and technical professionals around the world. These are Artificial Intelligence, Virtual Reality, Big Data & Analytics, Internet of Things, Robotic Process Automation, 3D Printing, Social and Mobile, Cloud Computing, and Cyber Security. They are covering quite a wide gamut.
In each of these 9 areas (AI, Big Data, and RPA are launched), NASSCOM is developing a set of 55 job roles and key skills, creating introductory and advanced learning paths, and aggregating hundreds of hours of training, content, and professional development resources. Since NASSCOM’s clients are the Fortune 100 biggest companies in the world, their users have the potential to aggregate, curate, and build pathways for the technical needs of large companies globally.
NASSCOM plans to use EdCast to catalog content and encourage subject matter experts to publish a wide variety of content for IT professionals. They are working with other education agencies in India and expect to deliver this “skills marketplace” to its member organizations later this year.
NASSCOM also plans to build certification and assessments that help technical professionals make sure they really learn what is needed in these critical areas. The initial partners are impressive: Wipro, Infosys, Genpact, Tech Mahindra, Google, Amazon, Microsoft, and others have signed up.
World Economic Forum’s Global Skilling Program
The second global skilling program EdCast has been supporting is the World Economic Forum’s global upskilling program, www.theskillset.org. While its goals are similar to NASSCOM’s, the approach is different. WEF is building a globally available platform that aggregates technical and professional development content from some of the world’s biggest companies. These companies are donating internally developed training programs so individuals around the world can take training, complete certifications, and discover new skills.
The companies involved are impressive: Cisco, PEGA, Salesforce, SAP, HP Enterprise, CA, Cognizant, Tata Consultancy, PWC, Accenture, have announced membership. Each of these companies has also provided a senior executive sponsor to work with WEF and they are working together to build a global catalog and skills taxonomy.
Of course this kind of massive aggregation effort is difficult because there is so much overlapping content, different formats, and various different definitions of competencies. Using the LXP, however, the content can be organized by skill, job, and vendor, and machine learning will again make it more and more relevant over time.
Country of Norway’s Global Skilling Program
In a third global upskilling program, EdCast is fueling the Nordic Futures project, an initiative to build digital and social skills to workers in Norway. While this program is brand new, it has the same goals as NASSCOM and WEF’s program, focused on empowering individuals to share their knowledge, curate information, and build new skills at the lowest possible cost.
How This Impacts the LXP Market and EdCast
So what does all this mean to the LXP market in general and EdCast in particular? It’s really pretty simple. Remember that the original purpose of the Learning Experience Platform was to make learning relevant for individuals, not just to manage training programs. By working with these kinds of organizations, EdCast hopes to gain access to more content and data and become smarter about what careers, content, and skills people need. I would expect there to be a bit of a race among LXP providers to go after these kinds of programs.
Selecting an LXP:
As you decide to buy an LXP for your company, I recommend you think about the things I discussed in this article.
Is the platform smart enough to recommend the right content for the types of users and skills you need? Can the platform ingest, tag, categorize, and learn fast enough to quickly adapt to new content and not produce rubbish when you browse around? Does the vendor have the staff with skills and tools to clean data, normalize all the duplication you’ll create, and build learning algorithms to get smarter? Does the system have the security to protect internal proprietary data yet still gain access to machine learning and content from the rest of the network? And is the system flexible enough to enable all the “tribes” in your company to optimize its use for their own learning needs?
As the market grows and machine learning becomes more mature, I promise to tell you more about what I learn – and as always welcome your stories and experience.