Re-aligning training strategies to respond to digitisation.

Automation and digitisation, suggest new principles for organising the emerging workplace. The landscape is shifting in areas such as career tracks within organisational hierarchies and notions about full-time jobs within companies. As the new workplace takes shape in the years to come, businesses will need to wrestle with the content of existing jobs, prepare for greater agility in the workplace, and learn to identify the early signals of change.

How work will evolve in the second machine age is a complex and unsettled question, but old practices are already starting to fall. Companies need to become more agile so they can embrace emerging new forms of labor flexibility. Workers need to have the skills and adaptability that would help make a more flexible job environment an opportunity to shape their careers in satisfying ways—perhaps with a better work–life balance—instead of a threat to their livelihoods and well-being. To acquire new skills that automation can’t readily replace, employees will need help from companies and policy makers. And understanding how workplace practices are changing is a first step for everyone.

When we talk about learning, the emphasis is often on “hard” skills, such as coding, analytics, and data science. While these skills will be critical, they are only part of the story. The dynamics in which information-rich tools become ubiquitous and people are a differentiator, paradoxically, increase the importance of such “soft” attributes as collaboration, empathy, and meaning making.


In most organisations, teamwork will be more important and valuable than ever. In both scientific discovery and commercial innovation, for example, the size of innovating teams has grown larger and the skills brought together are more diverse than ever. Teamwork doesn’t necessarily mean collaborating within teams in the classic sense of bounded groups of people working together on specific tasks. Instead, it’s often about teaming—communicating and collaborating with people across boundaries, such as expertise or distance, spontaneously and continuously. Organisations need to have, or develop, the skills for effective teamwork.


Global marketplaces can threaten the ability to spontaneously empathise, especially when we cannot see other people’s faces—for example, in geographically dispersed workforces or through remote service encounters. Genuine human connections can be made, and broken, quickly. Customers and employees alike feel deep loyalty to organisations that treat them with respect.

In an era of customisation, empathy matters more because it requires putting yourself in the minds of many different kinds of customers, not just the familiar ones for whom a product or service was designed.

Meaning Making

As information-rich tools help provide better solutions to complex situations, organisations will need to understand what matters for each person. Meaningfully connecting decisions, even those made by algorithms, to individual circumstances is likely to be the work of skilled people for a long time to come—if we prepare our organisations to think like this.

People who come to work believing that what they do matters—that in some small way it contributes to making the world a better place—are more committed to their organisations, more passionate about serving customers, and more resilient in the face of challenges. Good leaders have always played this role; when they don’t, people are more apt to act in ways that maximise self-interest and minimise effort. Articulating the purpose of the organisation and evolving that message as technology and customer needs change, is about to become an even more crucial.

Capability Determination

The costs and benefits of the decisions made by many high-volume, high-value, high-variability groups of employees, such as sales staff or project managers, are often unknown. It’s up to organisations to determine what measures matter, such as close rates or error costs; then you need to communicate these priorities. Once your organisation has decided what metrics to track, four steps should follow to determine the competencies that enable top performance:

  • First, find the best performers, and prepare to be amazed by how much more value they add with their decisions compared with the median performer. This sets a benchmark for the value that could be generated with the right training. (It can be large!)
  • Second, analyse what these top performers decide and do. That’s not easy, because much of it is unconscious. Still, it is important to learn as much as possible. On that basis, ensure that best practices are the focus of training and development programs. Novices could be easily taught to when the organisation has competency framework established.
  • Third, with these targets in mind, insist on well-designed training, based on insights from competency analysis, and support high-quality evidence gathering about results. Getting a return is, after all, the point of any investment. You will want to compare the work of those who have had new training to that of others who have not and to look for material differences in value.
  • Finally, commit to continuing this cycle of tracking expertise, improving training, and gathering evidence over time to improve performance

Sustaining Future Capabilities

  • Diagnose systematically. Companies are best able to build strong capabilities when they systematically identify the competencies, both institutional and individual, that can have the most positive impact on the business. Objective assessments are an important tool in this process—and few respondents say their companies use such assessments now. These diagnostics not only help companies assess their skill gaps relative to industry peers but also help them quantify the potential financial impact of addressing skills gaps. By diagnosing these gaps in a systematic, objective way, companies can better establish a foundation for the effective design of learning programs that link learning results to the business and include meaningful, quantitative targets.
  • Design and deliver learning to address individual needs. The core principles of adult learning require that companies tailor their learning programs to employees’ specific strengths and needs, rather than developing a one-size-fits-all program for everyone. In our experience, the most effective approach to adult learning is blended—that is, complementing in-class learning with real work situations and other interventions, such as coaching. The results suggest that all companies could take advantage of more novel approaches, such as digital learning (which can reach large groups of employees anywhere, at once) and experiential learning (which links skill development to day-to-day work experience in a risk-free setting).
  • Align with and link to business performance. To be effective and sustainable, competency building cannot happen in a vacuum. Learning objectives must align with strategic business interests, and, ideally, competency building should be a strategic priority in and of itself. Making human-resources functions and individual business units co-owners of skill-building responsibilities and then integrating learning results into performance management are effective steps toward achieving this alignment. These actions will also ensure broad buy-in for learning success, at both the organisational and individual levels. To ensure that their learning programs have real business impact, organisations must focus on metrics, as our most effective capability builders often do. They must establish rigorous performance-management systems with robust metrics and then measure progress against clear targets, to know where and how skill gaps are (and are not) being closed.

Organizations that are most effective at competency development, say sustaining capabilities over time and linking learning to company performance are integral parts of their competency-building programs. They typically use more methods than others to develop employee skills, more often say their human-resources functions and businesses co-own learning, more often use metrics to assess the impact of their programs on the business, and in turn report more success at meeting their programs’ targets