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Digital skills and the skills ecosystem

Fifteen years ago, many businesses were in crisis as they struggled to understand what the future held for them given the rise of the World Wide Web. Many believed their bricks-and-mortar business models were obsolete in the face of the confident and nimble dotcoms that were springing up everywhere. Jack Welch said that General Electric would have to cannibalize its own businesses to survive. And CIOs knew that their IT people, however skilful they were at C++, were not equipped to face the threat posed by newcomers confident in Apache, HTML, PHP or JavaScript – about which most IT people knew little or nothing.

Today there is a feeling of deja vu when faced with the next phase of the online revolution: ‘Digital’, 'Machine Learning' and more. Companies have realized once again that their technical people, marketing experts and others, while skilled, do not have all the capabilities needed for the new challenges. For many, the capability gap lies more deeply than skills: there are softer competencies lacking. Much of this resonates with the dotcom experience, so what can we learn from that experience as we face Digital?

What is Digital? In the absence of an accepted definition we define Digital as the use of new (often mobile, messy and unstructured) sources of data and data analysis methods for the purposes of generating new and better products and services, and better marketing and promotion. Digital = Big Data plus a few extras.

Understand the skills needed

During the dotcom boom many employers paid six-figure sums for HTML skills that were soon available for a small fraction of that. Or that could have been learned by existing employees within weeks. This time round, employers must take time to understand the skills involved, and not assume that they are all exotic and difficult to develop.

The starting point is a skills model. This can be created by identifying the many tasks needed to make Digital work. The top level of such a model is technology-independent, e.g. ‘Extract information from raw data’. The next level involves specific technologies: ‘Extract information from raw data’ would involve voice recognition, character recognition, image recognition tools and more. This goes a level beyond existing skills frameworks, which may never cover the non-IT, or even IT, skills involved.

The skills model will lead to a grid of skills ranging from Hadoop, Pig, NoSQL etc. through to non-IT skills such as statistical analysis and the tools like SPSS and R that support it. To build it, we need co-operation between IT functions and other business areas.

Understand the skills ecosystem

If we understand the skills needed, a number of exciting prospects open up. One is to identify where those skills ‘sit’ in the skills ecosystem. The skills ecosystem concept recognizes that the world of IT today is a complex one involving different habitats: the education system, the hobbyist sector, university research teams, techie entrepreneurs and start-ups, suppliers and (of course) corporate IT functions.

Some skills (e.g. SAP, certain kinds of databases) cannot be developed in all parts of that ecosystem because they are enterprise-scale tools needing vast investment. Others can spring up and grow everywhere: the latter spread much faster. This explains why Mobile developer skills were so much easier to source than (say) SAP skills when they first appeared: they arose naturally across most of the available ecosystem. So it’s not just the skills that matter: it’s how and where they arise.

This ecosystem is changing continually. For example, Cloud has put large infrastructures within the reach of more parts of the ecosystem. That has implications for those sourcing the relevant skills.

Using the skills model

Once the skills and the skills ecosystem are understood, they can be used to good effect. The build or buy decision becomes easier. Employers can compile a structured inventory of their skills, identify gaps, and use their understanding of the ecosystem to source the relevant skills.

A skills model may also be used to map skills onto specific parts of their organization and roles and thus inform structural and job design decisions.

Competencies and softer skills

We cannot overlook softer skills and competencies. In the dotcom era many observers said that the new ‘e-people’ were utterly different: they would think differently, behave differently. They were mostly wrong. Successful corporate IT leaders looked not so much for elusive new qualities but simply for people who were happy to be part of a team, who worked in a planned way, and who could co-operate and collaborate with a wide range of colleagues. It is important in the Digital age to maintain a realistic picture of what large corporates need and not to become too focused on the kinds of individualistic competencies that are needed in tiny start-ups.

What standard Digital jobs are emerging?

Do not expect Digital to be delivered by a few industry-standard jobs. That is not true of areas like software development and it may not be true of Digital. For software development, some companies have business analysis, systems design, coding and testing each being done by specialists. Elsewhere, multi-skilled generalists might do most or all of these activities.

It is premature to speculate on standard Digital roles, though in the longer term these could emerge, as they have in some areas of IT.

Key message

Employers should not take an ad hoc approach to Digital skills but start by understanding them using structured frameworks. These are best developed by collaboration between employers who are willing to share their knowledge and experience.

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