By Jonathan Donner

As automation and digitization transform economies and usher in a new ‘future of work’, closing the skills gap is critical. In this note, we offer a way to think about a broad, dynamic set of institutions, channels, materials, and audiences that combine to create a multitude of approaches to workforce training.

With the support of the Mastercard Foundation, Caribou Digital is currently working on an initiative called “Skills for the Digital Age”, curating materials and conducting new research on the skills challenges presented by the future of work.

Our project is structured around the evidence that, in economies where mechanization, digitization, and automation are changing the future of work, almost everybody could benefit from a skills upgrade, and digital skills are not the only skills which need upgrading. This isn’t to say that ‘digital skills’ or ‘digital literacies’ are not critical. They are. But whether adopting new practices for agriculture, pursuing detailed craftsmanship, or providing attentive home care, livelihood skills of every kind are at a premium as digitization makes labor markets more efficient, more global, and more competitive.

Our first project under this banner focuses on Platform-Led Upskilling — how marketplace platforms can play a role in teaching livelihood skills. [See Whitepaper and Website.] But Platform-Led Upskilling is only one approach among several. This post sketches a broader picture of an ecosystem of approaches to skills in the digital age.

Listing the elements of a training ecosystem

If you wanted to inventory all the elements of a training ecosystem, what would you do?

You could map out all the sources for training: Schools, universities, training academies, NGOs, and employers are well known. Peers, too, are a great source for skills training. With digitization, platforms and EdTech companies join the mix.

You could list all the channels for training: Books, the mass media, face-to-face chats, and classroom settings have rich pedagogical traditions. Digitization has added online courses/distance learning, live streaming, short video, and real-time coaching ‘nudges’.

You could also cast a wide net for content types. As we mentioned above, it’s not just messages about digital literacy (though digitization means that is important). Others need core numeracy and literacy, vocational skills, financial literacy and business skills, and the ‘soft skills’ to interact and collaborate with teammates, suppliers, and customers.

And, you could think about all the different kinds of learners, the receivers of the content we just discussed. Schoolchildren and young adults. Employees. Job seekers, MSMEs and the self-employed each have different needs. And of course, digitization adds gig workers and platform workers to the mix — a new form of labor/livelihood not well accounted for in traditional employment typologies.

The skills ecosystem as an array of sources, channels, content & receivers

And putting them together

If you (or we) did that, a few things might become clear.

First, that there are many, many parts to this puzzle. String together almost any combination and you can imagine a part of the overall training landscape: From “NGOs writing books about soft skills for first time job seekers” to “technical schools streaming financial literacy videos to adult platform workers”. It’s a big field. The illustrative array in our table above has 1600 permutations (8x8x5x5).

Second, that no single permutation is a magic bullet. Skills for a digital age will be advanced by many institutions, by many means, about many topics, to many kinds of users.

Third, that digitization is a pull and a push, a need and an opportunity. Of course, digital literacy is a new requirement for many people, and those who can code and manipulate information digitally are in high demand. That’s the pull. But at the same time, digitization brings new methods, new affordances and opportunities to support livelihoods learning at scale. Digital makes a bunch of training gerunds more possible than ever before: Streaming, tailoring, adapting, targeting, translating, repurposing, and so on. That’s the push. This is a great time for innovations in training.

Finally, it’s clear that the old ways still work. Perhaps you’d notice that we have just echoed and invoked one of the oldest frameworks in communication research: The “SMCR” model. Emerging from Shannon and Weaver’s 1949 mathematical theory of communication and adapted specifically to human communication by David Berlo in 1960, the SMCR (Sender-Message-Channel-Receiver) model of communication is a multi-purpose framework. Admittedly, its one-way approach is not great for accounting for ‘feedback’ nor emergent systemic effects — but it still does the trick in surfacing a lot of the complexity in getting messages and content from point A to point B.

In all, this brief exercise illustrates how gathering the evidence around ‘what works’ (and how) in upskilling and training will require attention to many different combinations on the array. There are bodies of learning focused on the channels of instruction, others on the institutions, and so on. When the interdependencies and interactions start adding up (as they did here), it’s worth remembering that the most optimal configuration for one pathway might not be the most optimal configuration for the next. Our response should be to generate lots of research, and lots of conversation, while carefully considering the kinds of contexts to which our work applies. There’s lots to look at but, equally, lots of ways to help address the digital age’s skills challenges.