Category Archives: Media

Hero image for the Deloitte Australia Centre for the Edge report, The digital-ready workplace

The digital-ready workplace

We have a new essay published in Deloitte Insights, The digital-ready workplace: Supercharging digital teams in the future of work,[1]Evans-Greenwood, P, Stockdale, R, & Patston, T 2021, ‘The digital-ready workplace: Supercharging digital teams in the future of work’, Deloitte Insights, … Continue reading a collaboration with Rosemary Stockdale from Griffith Business School and Tim Patston from UniSA STEM at the University of South Australia.

Most (if not all) research groups have done a survey on the affect working from home has had—this is ours, though it’s ended up in a different place. We start by trying to understand the relative merits of a push or pull approach to support workers during the transition, where push is the usual “give them the tools and training we think they’ll need” while pull is empower and support workers in finding their own tools. Generally, a push approach works well when the challenge is understood beforehand, while a pull approach is better when the challenge is not well understood as it enables workers to adapt. We’d heard anecdotal stories that firms had taken different approaches, and we were wondering how the relative benefits and problems stacked up. What we discovered, once the data started coming in, was that we were asking the wrong question.

Continue reading The digital-ready workplace

References

References
1 Evans-Greenwood, P, Stockdale, R, & Patston, T 2021, ‘The digital-ready workplace: Supercharging digital teams in the future of work’, Deloitte Insights, <https://www2.deloitte.com/us/en/insights/focus/technology-and-the-future-of-work/supercharging-teams-in-the-digital-workplace.html>.
Hero image for the Deloitte Australia Centre for the Edge report, Unshackling the creative business

Unshackling the creative business

We have a new essay published in Deloitte Insights, Unshackling the creative business: Breaking the tradeoff between creativity and efficiency.[1]Evans-Greenwood, P et al. 2021, ‘Unshackling the creative business: Breaking the tradeoff between creativity and efficiency’, Deloitte Insights, … Continue reading Creativity is seen as an import capability for an organisation to be successful in today’s volatile, uncertain, complex and ambiguous (VUCA) world. Significant effort has been invested in fostering creativity in business, effort which sadly is often wasted. This essay looks at why this might be the case and what we can do about it.

Continue reading Unshackling the creative business

References

References
1 Evans-Greenwood, P et al. 2021, ‘Unshackling the creative business: Breaking the tradeoff between creativity and efficiency’, Deloitte Insights, <https://www2.deloitte.com/us/en/insights/topics/innovation/unshackling-creativity-in-business.html>.

Building the peloton

We have a new essay published in Deloitte Insights, Building the peloton: High performance team-building in the future of work. Jess Watson is the lead author of a report that looks into how we need to think a bit differently about teams, team work and leadership as the drive to create more agile organisations breaks down established organisation structures.

The report uses the analogy of a cycling peloton—the team-of-teams that competes and cooperates in a road cycling race—to integrate current research on team formation and operation in a world where firms function as a team-of-teams.

Continue reading Building the peloton

Innovating your way out of the crisis

We have a new blog post up on the Deloitte blog, Innovating our way out of the crisis.

In the past few weeks we’ve written about need for management to get out of the bunker mentality that uncertainty and a rapidly unfolding crisis had pushed us into, and how we have a perfect storm for innovation with demand collapsing for the old thing while new demand is popping up as we adapt, and the government is (effectively) subsidising innovation by providing unsecured loans and underwriting payroll (via JobKeeper). Put these together and you have the potential for (some) firms to emerge from the crisis stronger and more capable than they went in. New winners and losers will be created, and so on. That leaves one question unanswered: Where should a firm look for these new opportunities?

Now we’ve had a go at creating an innovation mud map to help find where a firm might innovate. Our hope is for this to be a conversation starter inside firms.

Published on the Deloitte Risk Advisory blog as Innovating our way out of the crisis.

The government is paying you to innovate

We have a new blog post up on the Deloitte blog, The government is paying you to innovate. The post points out that, due to a number of factors, now might be the perfect time to innovate.

There is a few reasons for this.

First is that we seem to have a perfect storm for innovation. The pandemic means that doing the old thing is not an option for many firms, with many of us stuck at home and the government restricting how businesses operate. At the same time, new demand is appearing and we all learn how to live in the new normal.

Second, and as we pointed out in Getting out of the crisis, the business environment post shutdown is unlikely to be the same as pre shutdown. The best way to prepare is to experiment now, to learn how consumer behaviour is changing, and start building the assets and services that will you’ll use in the new normal.

Third, and finally, the government is providing unsecured loans and is even willing to underwrite payroll. The government is effectively paying you to innovate.

There’s already early evidence that firms who are experimenting and adapting will emerge from this shutdown more efficient and effective than they went in. Now would appear to be the perfect time to innovate.

Published on the Deloitte Innovation blog, 20th of May 2020, as The government is paying you to innovate.

Digital agency and the skills gap

The concluding report from Deloitte Centre for the Edge and Geelong Grammar Schools’ collaboration looking into digital skills in the workplace, Digital agency and the skills gap,[1]Evans-Greenwood, P & Patston, T 2019, Digital agency and the skills gap, Deloitte, Australia, … Continue reading has been published by Deloitte, Australia. This report pulls together the results from across the project to provide an overview of the journey and the findings.

There’s a huge amount of angst in the community that our education system cannot keep up with rapid technological change, however this project shows that this is likely not the case. What we’re seeing is, in many cases, not a lack of skills, but an inability to navigate an increasingly complex digital environment. While digital skills are important, knowing when and why to use these skills is more important, particularly in a world where new knowledge is no further away than a search engine accessed via a smart phone.

Workers are unable to make the connection between the skills they have and the problem infant of them, making this a problem of unknown knowns. It’s not that workers lack skills, what they lack is discernment, the ability to read the digital environment around them and make sharp judgements about when and why particular digital tools and skills should be used. A lack of discernment limits a worker’s digital agency, their ability to act freely in a digital environment.

Solving this problem is not simply a question of teaching students and workers more, and more relevant digital skills. We need to focus on fostering in them the discernment required for them to develop the work habits that will enable them to make the most of digital technology.

The project was a long and fascinating journey so this concluding report itself is quite long, around 12,000 words. A much shorter business-friendly summary, The digital ready worker,[2]Evans-Greenwood, P, Patston, T, & Flouch, A 2019, ‘The digital-ready worker: Digital agency and the pursuit of productivity’, Deloitte Insights, … Continue reading was published last week by Deloitte Insights. A lot of valuable insights were dropped on the cutting room floor to create that summary, hence this report.

This report provides a summary of project’s journey, from the initial provocation through the roundtables, the more recent workshops, to the development of the project’s conclusions, as well as providing a detailed exploration of the findings. If you’re an educator (K12 or post-secondary) you might find this longer report more valuable as it digs into the details of the models presented, and does a better job of exploring the implications of the findings. If you were involved in any of the projects, the this report will join a number of dots and provide that ah-ha moment.

Revisiting the concept of learned helplessness, the report shows how the solution to learned helplessness is not to teach students more digital skills, but to foster their digital agency, their capacity to act independently and make their own free choices in the digital workplace. The concept of digital natives is explored in light of what the project discovered, resulting in a new model of digital competence in the workplace the identifies four archetypes: the digital naïf, digital pragmatist, digital explorer, and digital evangelist.

Finally, the report develops a progression capturing how one’s digital agency changes over time, and explores how digital agency might be fostered in both students and workers, and the changes this implies.

References

References
1 Evans-Greenwood, P & Patston, T 2019, Digital agency and the skills gap, Deloitte, Australia, <https://www2.deloitte.com/au/en/pages/public-sector/articles/to-code-or-not-to-code-coding-competence.html>.
2 Evans-Greenwood, P, Patston, T, & Flouch, A 2019, ‘The digital-ready worker: Digital agency and the pursuit of productivity’, Deloitte Insights, <https://www2.deloitte.com/us/en/insights/focus/technology-and-the-future-of-work/learned-helplessness-workforce.html>.

The digital-ready worker: Digital agency and the pursuit of productivity

We have a new essay published on Deloitte Insights, The digital-ready worker: Digital agency and the pursuit of productivity, which is the result of a collaboration between Centre for the Edge and Geelong Grammar School.[1]Evans-Greenwood, P, Patston, T, & Flouch, A 2019, ‘The digital-ready worker: Digital agency and the pursuit of productivity’, Deloitte Insights, … Continue reading As the blurb says, this essay looks into how:

To be effective in an increasingly technological workplace, workers must know, not just how to use digital tools, but when and why to use them. Critical to this ability is digital agency: the judgment and confidence required to navigate and be effective in unfamiliar digital environments.

There’s a lot of concern at the moment of a growing skills gap, the gap between the the skills held by graduates and those demanded by employers. Studies have been done to measure this growing gap, and significant resources have been devoted to updating curricula in an attempt to close the gap, all to no avail.

If we peal the lid of these studies we see they rely on aggregate skills data, typically from O*NET, which means that they’re limited to seeing a single negative view of how technology affects jobs, one where technology automates skills making workers redundant. The problem is that this isn’t the only pathway for technology to affect work. There’s also a positive pathway, where technology automates skills making the workers’ remaining skills more valuable, as well as a “no net change” pathway (or collection of pathways) which we have empirical evidence for but are yet to pull apart and understand.[2]Spenner, KI 1983, ‘Deciphering Prometheus: Temporal Change in the Skill Level of Work’, American Sociological Review, vol. 48, no. 6, p. 824, … Continue reading

One of the key insights, if not the key insight, from Centre for the Edge and Geelong Grammar Schools’ To code or not to code collaboration, was that many of the problems we’re seeing in the workplace are likely due to learned helplessness,[3]The term “learned helplessness” is borrowed from the psychology literature, drawing upon the work of Martin Seligman and many others. See, for instance, Martin E. P. Seligman, “Learned … Continue reading where a person suffers from a sense of powerlessness arising from a persistent failure to succeed. We’re teaching students how to use particular digital tools in particular ways, but we’re also teaching them that these tools are fragile and using them the wrong often results in problems and might even ‘brick’ the device. Rather than framing the problems we’re seeing in the workplace as the result of a growing skills gap due to the destruction of skills, it might be more appropriate to frame them as a problem of unknown knowns. It’s not that the worker doesn’t have the skills required, their problem is making the connection between the skill and the current problem they’re working on.

The solution to this problem isn’t to provide students with more, and more relevant, digital skills. Indeed, that approach is unlikely to help as the students are not lacking in skills. While it’s important to know how to use particular digital tools, it’s more important to know when and why these digital tools should be used. What students lack is discernment, the knowledge and experience required to make observations and sharp judgements about which digital tools might be useful and how they will affect the work. We need to foster in students the attitudes and behaviours—something we’ve taken to calling a predilection—that help them navigate the digital workplace and develop the habits that enable them to integrate digital tools into their work. Ultimately the solution is to foster digital agency in students, to help them develop the literacies, knowledge, skills and predilections the need to act independently and make their own free choices in the digital workplace.

The essay explores, in some detail, the concept of learned helplessness in the digital workplace, and how we might might foster digital agency in both students and workers. There’s also a few of useful models for thinking about this problem, helping us move beyond misleading dichotomies like Digitial Native vs Digital Immigrant which have proven to be wrong.

You can find the entire text over at Deloitte Insights. Feel free to leave a comment here with your thoughts.

References

References
1 Evans-Greenwood, P, Patston, T, & Flouch, A 2019, ‘The digital-ready worker: Digital agency and the pursuit of productivity’, Deloitte Insights, <https://www2.deloitte.com/us/en/insights/focus/technology-and-the-future-of-work/learned-helplessness-workforce.html>.
2 Spenner, KI 1983, ‘Deciphering Prometheus: Temporal Change in the Skill Level of Work’, American Sociological Review, vol. 48, no. 6, p. 824, <http://www.jstor.org/stable/2095328?origin=crossref>.
3 The term “learned helplessness” is borrowed from the psychology literature, drawing upon the work of Martin Seligman and many others. See, for instance, Martin E. P. Seligman, “Learned helplessness,” Annual Review of Medicine 23, no. 1 (1972): pp. 407–12.

Reconstructing jobs: Creating good jobs in the age of artificial intelligence

Fear of AI-based automation forcing humans out of work or accelerating the creation of unstable jobs may be unfounded. AI thoughtfully deployed could instead help create meaningful work.

This is a 25 minute presentation providing an overview of the report Reconstructing jobs (published in 2018) from the Edge Session just after the report was published.

This third essay in the series, Reconstructing jobs, takes a step back and looks these jobs of the future might look like. The narrative is built around a series of concrete examples – from contact centres through wealth management to bus drivers – to show how we might create this next generation of jobs. These are jobs founded on an new division of labour: humans creating new knowledge, making sense of the world to identify and delineate problems; AI plans solutions to these problems; and good-old automation to delivers. To do this we must create good jobs, as it is good jobs that make the most of our human abilities as creative problem identifiers. These jobs are also good for firms as, when combined suitably with AI, they will provide superior productivity. They’re also good job for the community, as increased productivity can be used to provide more equitable services and to support learning by doing within the community, a rising tide that lives all boats.

Teaching creativity in the 21st century

In 2017 Deloitte Centre for the Edge hosted a public lecture by James C. Kaufman, PhD; a professor of educational psychology at the University of Connecticut as well as a creativity & education expert, where he discussed the challenges of teaching and assessing creativity. This is a 20 minute bite-sized version of the 90-minute lecture.

We noticed the similarity between creativity and our recent work on digital competency, which we published in “From coding to competence”. Both are depend more on attitudes and behaviours than knowledge and skills. Both are also tightly tied to context, and don’t transfer easily between domains.

The lecture is derived from Dr Kaufman’s cutting-edge psychological research and debunks common misconceptions about creativity, describe how learning environments can support creativity, while providing insights into teaching and assessing creativity within the established curriculum.

The lecture covers:

  • What is creativity?
  • Seeing creativity as a development trajectory and advancing along this trajectory.
  • Creativity across domains (not just ‘art’), and the ‘cost’ of creativity.
  • Measuring creativity
  • How can people become more creative?

The new division of labor: On our evolving relationship with technology

I, along with Alan Marshall and Robert Hillard, have a new essay published by Deloitte InsightsThe new division of labor: On our evolving relationship with technology[1]Evans-Greenwood, P, Hillard, R, & Marshall, A 2019, ‘The new division of labor: On our evolving relationship with technology’, Deloitte Insights, … Continue reading. This is the latest in an informal series that looks into how artificial intelligence (AI) is changing work. The other essays (should you be interested) are Cognitive collaboration,[2]Guszcza, J, Lewis, H, & Evans-Greenwood, P 2017, ‘Cognitive collaboration: Why humans and computers think better together’, Deloitte Review, no. 20, viewed 14 October 2017, … Continue reading Reconstructing work[3]Evans-Greenwood, P, Lewis, H, & Guszcza, J 2017, ‘Reconstructing work: Automation, artificial intelligence, and the essential role of humans’, Deloitte Review, no. 21, … Continue reading and Reconstructing jobs.[4]Evans-Greenwood, P, Marshall, A, & Ambrose, M 2018, ‘Reconstructing jobs: Creating good jobs in the age of artificial intelligence’, Deloitte Insights, … Continue reading

Over the last few essays we’ve argued that humans and AI might both think but they think differently, though in complimentary ways, and if we’re to make the most of these differences we need to approach work differently. This was founded on the realisation that there is no skill – when construed within a task – that is unique to humans. Reconstructing work proposed that rather than thinking about work in terms of products, processes and tasks, it might be more productive to approach human work as a process of discovering what problems need to be solved, with automation doing the problem solving. Reconstructing jobs took this a step further and explored how jobs might change if we’re to make the most of both human and AI-powered machine using this approach, rather than simply using the machine to replace humans.

This new essay, The new division of labour, looks at what is holding us back. It’s common to focus on what’s known as the “skills gap”, the gap between the knowledge and skills the worker has and those required by the new technology. What’s often forgotten is that there’s also an emotional angle. The introduction of the word processor, for example, streamlined the production of business correspondence, but only after managers became comfortable taking on the responsibility of preparing their own correspondence. (And there’s still a few senior managers around who have their emails printed out so that they can draft a reply on the back for their assistant to type.) Social norms and attitudes often need to change before a technology’s full potential can be realised.

We can see something similar with AI. This time, though, the transition is complicated as the new tools and systems are not passive tools anymore. We’re baking decisions into software then connecting these automated decisions to the levers that control our businesses: granting loans, allocating work and so on. These digital systems are no longer passive tools, they have some autonomy and, consequently, some agency. They’re not human, but they’re not “tools” in the traditional sense.

This has the interesting consequence that we relate to them as sort-of humans as their autonomy and agency affects our own. They’re consequently taking on roles in the organogram as we find ourselves working for, with and on machines. This also works the other way around, and machines find themselves working for, with and on humans. Consider how a ride-sharing driver has their work assigned to them, and their competence is measured, by an algorithm that is effectively their manager. A district nurse negotiates their schedule with a booking and work scheduling system. Or it might be more of a peer relationship, such as when a judge consult a software tool when determining a sentence. We might even find humans and machines teaching each other new tricks.

As with the word processors, we can only make the most of this new technology if we address the social issues. With the word processor it was managers seeing typing as being below their station. The challenge with AI is much more difficult though, as making the most of this new generation of technology requires us to value humans to do something other than complete tasks.

The essay uses the example of superannuation. Nobody wants retirement financial products, they want a happy retirement, the problem is that ‘happy retirement’ is no more than a vague idea for most of us. We need to go on a journey through sorting out if what we think will make us happy will actually make us happy, setting reasonable expectations, and adjusting our attitudes and behaviours to balance our life today with the retirement we want to work toward. This is something like a Socratic dialogue, a conversation with others where we create the knowledge of what ‘happy retirement’ means for us. Only then can we engage the robots-advisor to crunch the numbers and create an investment plan.

The problem is the disconnect between how the client and firm derive value from this journey. The client values discovering what happy retirement means, and adjusting their attitudes and behaviours to suit. The firm values investments made. This disconnect means that firms focus their staff on clients later in life, once the kids have left home and the house is paid off. The client, on the other hand, would realise the most value by engaging early to establish the attitudes and behaviours that will enable the magic of compound interest to work.

As we say in the conclusion to the report:

However, successfully adopting the next generation of digital tools, autonomous tools to which we delegate decisions and that have a limited form of agency, requires us to acknowledge this new relationship. At the individual level, forming a productive relationship with these new digital tools requires us to adopt new habits, attitudes, and behaviors that enable us to make the most of these tools. At the enterprise level, the firm must also acknowledge this shift, and adopt new definitions of value that allow it to reward workers for contributing to the uniquely human ability to create new knowledge. Only if firms recognize this shift in how value is created, if they are willing to value employees for their ability to make sense of the world, will AI adoption deliver the value they promise.

You can find the entire essay over at Deloitte Insights.

References

References
1 Evans-Greenwood, P, Hillard, R, & Marshall, A 2019, ‘The new division of labor: On our evolving relationship with technology’, Deloitte Insights, <https://www2.deloitte.com/insights/us/en/focus/technology-and-the-future-of-work/the-new-division-of-labor.html>.
2 Guszcza, J, Lewis, H, & Evans-Greenwood, P 2017, ‘Cognitive collaboration: Why humans and computers think better together’, Deloitte Review, no. 20, viewed 14 October 2017, <https://dupress.deloitte.com/dup-us-en/deloitte-review/issue-20/augmented-intelligence-human-computer-collaboration.html>.
3 Evans-Greenwood, P, Lewis, H, & Guszcza, J 2017, ‘Reconstructing work: Automation, artificial intelligence, and the essential role of humans’, Deloitte Review, no. 21, <https://dupress.deloitte.com/dup-us-en/deloitte-review/issue-21/artificial-intelligence-and-the-future-of-work.html>.
4 Evans-Greenwood, P, Marshall, A, & Ambrose, M 2018, ‘Reconstructing jobs: Creating good jobs in the age of artificial intelligence’, Deloitte Insights, <https://www2.deloitte.com/insights/us/en/focus/technology-and-the-future-of-work/creating-good-jobs-age-of-artificial-intelligence.html>.