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Digital Frontrunners in Helsinki: Lessons learned from marshmallows and safaris

We recently hosted our third Digital Frontrunners workshop in collaboration with Finland’s Prime Minister’s Office. The event in Helsinki brought together over 30 policymakers and experts from the Netherlands, Sweden, Estonia, Finland, Belgium and Denmark who have a mandate to deliver a future of work for all.

Following the double-diamond design process, the two-day workshop demanded that participants shifted from a ‘discover’ mentality to one of ‘definition’ across two days. We framed this journey by presenting participants with four policy challenges that need to be overcome in order to deliver an inclusive digital economy.

We defined these through our work on Delivering Digital Skills (a guide to preparing the workforce for an inclusive digital economy), new research, our two previous workshops, and extensive conversations with our participants:

  1. Continuous adaptation of training to changing skill demands
  2. Equal access to learning for people across demographics and contexts
  3. Self-driven motivation to upskill and adapt to digitalisation
  4. Systemic change across labour and education

These four challenges framed the activities and discussions held over the two days of discovery and definition.

Discovery: Holding the problem

When faced with challenges like these, it is tempting to jump straight into defining solutions. In our impatience to find them, we rarely spend sufficient time holding the problem up to the light and interrogating it. This can lead to missed insights, misunderstanding the needs of users, and wrong assumptions about root causes; a recipe for solutions that don’t work.

The first day of ‘discovery’ was held in the spirit of holding each of these four policy challenges before generating ideas for how to address them. As inspiration, Eliza Easton presented the latest research from Nesta defining the digital skills that will be most in-demand in a digital future. In this research, machine learning was used to study 41 million job adverts and make predictions about labour market demands. We also heard from Headai, a company that’s leading the way in applying similar techniques in Finland. Headai won the Ratkaisu 100, a challenge prize competition launched by SITRA designed to address Finland’s key future challenges.

Establishing the demands of the labour market in these ways is essential in really understanding the skills landscape, prior to designing policies for continuous adaptation of training. They’re also innovative ways of ‘holding the problem’.

Another way of doing this was inspired by the UK Government Policy Lab: we held an evidence safari. Around the room, we arranged over 80 easily digestible pieces of evidence relating to digital skills policy. Participants chose one of the four policy challenges to focus on and explored the evidence by moving around the room choosing the cards that were most relevant to their challenge.

In cross-country teams, an evidence base for each of the four themes was built. Looking at, connecting and discussing the evidence in this way is an effective way to better understand a problem. It allows quick interrogation of a wide range of sources, with a freedom missing in traditional desk research. It means you build an evidence base for a policy challenge as a team of experts, each bringing their unique perspectives to the conversation.

For example, an evidence card that provided an ‘aha’ moment for the team working on the self-motivation theme: research on the motivation profile of adult learners indicates that rewards can actually disincentivise people from participating in training, because the reward becomes the focus rather than the value of the activity itself.

Insights like this one proved key in the prototyping that would ensue on day two.

Building an evidence base first

Building an evidence base first

Defining a vision: an experimental spirit

Following a day of immersion in the policy challenges, we asked participants to engage their experimental spirit. We kicked this off with an old classic, the marshmallow challenge: teams must build the tallest free standing structure out of spaghetti, tape, and string capable of holding a marshmallow. The most successful teams prioritise iteration over deliberation, trying a number of approaches; experimentation over cautiousness, not waiting until the very end to see if the approach works.

Iterating through the marshmallow challenge

We learned from Finland’s Prime Minister’s Office that these are qualities they are seeking to foster in policy making too. The pioneering initiative Experimental Finland invites citizens, organisations and communities to test solutions to policy challenges in order to find out what might work at scale. A recent open call for experiments launched on the website in September 2018 specifically focused on building digital skills and lifelong learning capacities in the health and social services sector.

The initiative seeks to build a culture of experimentation inside government as well, for example by developing curricula around experimentation and training civil servants in behavioural science approaches.

Inspired by Experimental Finland, and building on the evidence safari from the day before, our group got creative and prototyped solutions to the four policy challenges (see below the blog for their ideas). In the spirit of the marshmallow challenge, we asked them to do this quickly and iteratively without the pressure of trying to find a perfect solution.

It’s difficult - especially when you’re an expert - to abandon the notion of finding the ’single right answer’ to a problem. We helped our group to do this by getting them to look at the question in hand through different lenses. How would an entrepreneur solve the problem? What if money wasn’t an issue? What if there was no money at all? And so on.

We took our participants on a two-day journey designed to challenge assumptions and put them in a creative space to generate fresh ideas. Most of all, we wanted participants to inspire each other and collaborate on addressing challenges affecting us all.

Collaborative toolkit for digital skills

Developing a prototype for one of the four challenges

Next steps for Digital Frontrunners

The four challenges were not solved in Helsinki - as much as we would love to claim otherwise. We have a great community of very committed and experienced experts, with a deep understanding of what the key challenges are, equipped with inspiring ideas for how to solve them. This is a brilliant starting point on which to build further research, discussion and activity.

We are excited for the next steps in this journey as we continue to build this international community. In the meantime we look forward to sharing the lessons we’ve learned along the way in an upcoming report due to be published later this year.

We will also be continuing to share inspiring examples of best-practice from across the Digital Frontrunner countries through our Spotlight series, the next one about Finland will be published later this month.

Idea prototypes

1. Policy challenge: Continuous adaptation of training to changing skills demand

Prototype Idea: An on-demand skills platform to identify skills gaps and mismatch

How it might work:

  • Harness AI to develop a system which provides live information on skills supply and demand in the labour market.
  • Partnership building plays a great part in the project: people from businesses, ministries, unions and educational institutions come together to evaluate the findings on skills and agree on courses of action, e.g. investing in training.
  • Based on the findings, an up-to-date live curriculum could be developed.

Key evidence informing the approach:

Collaboration with all relevant stakeholders is necessary to identify skills needs

“Ensure all relevant stakeholders are involved in the production of information on skill needs”

OECD ‘Getting Skills Right: Good Practices in Adapting to Changing Skill Needs - a perspective on France, Italy, Spain, South Africa and the United Kingdom (2017)

It is important to evaluate what works when it comes to training programmes

"Engage in regular monitoring and evaluation. Rigorous evaluation of training programmes helps to improve their design by clarifying what works, what does not work, and under what conditions and for whom. Building monitoring and evaluation into the design and implementation of training programmes will help to ensure that scarce public resources are used efficiently and effectively".

OECD, 'Getting Skills Right: Good Practice in Adapting to Changing Skill Needs A Perspective on France, Italy, Spain, South Africa and the United Kingdom’ (2017)

Measuring only overall demand for digital skills can be misleading

“To find out which digital skills will be most needed in the future, we need to investigate employer demand and look into real-time information on the labour market, such as job adverts.”

Nesta, ‘Which digital skills do you really need? Exploring employer demand for digital skills and occupation growth prospects’ (2018)

2. Policy challenge: Equal access to learning for people across demographics and contexts

Prototype idea: Public ‘micro-learning platforms’ for lifelong learning aiming to reach vulnerable groups

How it might work:

  • Providing easy access for professional development, especially for those threatened by unemployment and in need of reskilling
  • Offering simple professional development tools for all sectors and professions
  • Visual learning materials supporting multiple ways of learning and consuming content
  • AI-powered and user-friendly system

Key evidence informing the approach:

Low-skilled unemployed workers are more likely to participate in ineffective labour market programmes

"High-skilled unemployed participate considerably more in training measures... low-educated and older unemployed participate more in lighter ALMP measures such as rehabilitative work experience that have note proved to be very effective"

OECD 'Back to work: Finland: Improving the re-employment prospects of displaced workers’ (2016)

In Finland, those over the age of 55 may struggle to find a new job if displaced

"Those who did not find a job within one year face a high risk of remaining jobless for a long time if not forever, especially if over the age of 55. This is also because new jobs are not always created in the regions where jobs are lost"

OECD 'Back to work: Finland: Improving the re-employment prospects of displaced workers’ (2016)

3. Policy Challenge: Self driven motivation to upskill and adapt to digitalisation

Prototype idea: ‘Digital Donors’ - a project that encourages people to donate and share skills

How it might work:

  • At its core would be a media platform (TV, social, online) presenting a ‘Digital Buddy’ of the month and bringing together people who want to donate their skills and learn from others
  • A focus on peer-mentoring
  • Use of gamification methods (storytelling, quick testing of ideas) used to trigger curiosity and participation

Key evidence informing the approach:

Emotional support, self-efficacy, time-management and learner autonomy are all important to drive persistent learning

“Holder (2007) examined predictors of persistence in online higher education programs. Based on responses from 259 participants, the study found that emotional support, self-efficacy, time management, and learner autonomy were influential factors”.

Sun Joo Yoo, Wenhao David Yang, 'Engaging Online Adult Learners in Higher Education: Motivational Factors Impacted by Gender, Age, and Prior Experiences’ (2013)

Rewards can disincentivise learning

"As stated by SDT [self-determination theory], when individuals are given (or expect) rewards for the performance of an activity, the reward becomes the main focus and they lose interest in the activity itself”.

Rothes, A., Lemos, M.S., Goncalves, T. 'Motivational Profiles of Adult Learners’ (2016)

4. Policy challenge: Systemic change across labour and education

Prototype Idea: ‘A one stop shop’ for lifelong learning connecting employees and employers.

How it might work:

  • For individuals - possibility to find all the relevant information in the same place including opportunities to develop personal competencies, further education and unemployment benefits
  • For employers - possibility to find out what kind of skills are currently needed
  • The network of actors in the platform consists of startups, civil servants, academics and citizens (the actual customers)
  • It would consist of various small platforms and applications that can ‘talk’ to each other
  • It would need to be a cross-ministry collaboration

Key evidence informing the approach:

In the UK, there has been a cultural shift towards lifelong learning

"Long-term employment within the same organisation has become increasingly uncommon and workers have recognised the need to develop new skills throughout their careers."

Jenkins, A, 'Who Upgrades to Higher Level Qualifications in Midlife?’ (2018)

Lack of time, cost, and difficulty finding appropriate courses are all barriers to participation in training

“Looking at situational barriers, lack of time and cost issues are given as the most prominent reasons for nonparticipation in previous research” (Desjardins, Milana, & Rubenson, 2006), whereas problems with scheduling or finding appropriate courses are reported as institutional barriers”.

Massing, N. and Gauly, B. (2017) 'Training Participation and Gender: Analyzing Individual Barriers Across Different Welfare State Regimes'

Author

Elsie Till

Elsie Till

Elsie Till

Assistant Programme Manager, Digital Frontrunners

Elsie managed the operations and internal running of the Digital Frontrunners programme.

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Karoliina Helkkula

Karoliina Helkkula

Karoliina Helkkula

Programme and Research Support, Digital Frontrunners

Karoliina supported Digital Frontrunners, Nesta's programme for future skills.

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Juan Casasbuenas

Juan Casasbuenas

Juan Casasbuenas

Curriculum and Content Manager

Juan was a Curriculum and Content Manager supporting the Digital Frontrunners and Global Innovation Policy Accelerator programmes.

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