Author - arun

9 Techniques for Learning Agility in an Era of Disruption


Over the next few years, the work you’re doing now will change or disappear altogether. Use these 9 strategies to think, learn, and adapt your way to volatility and disruption. From mindset, learning less, using mental models, right through to developing the ability to unlearn.

See the full illustrated article outlining 9 strategies to achieve learning agility by clicking here and opening the elearning industry article. 


8 Future Skills for L&D Professionals


Make no mistake, our profession is needed now more than ever, but not in its current form. This illustrated guide explores 8 skills for Learning and Development professionals that will help transform L&D and future-proof your career.

These 8 skills for Learning and Development professionals won’t solve all our woes, but they will play an important part in enabling this change and, in the process, future-proofing your career:

>> Click here to read the rest of the article on the elearning industry website…

(Note – I wrote the illustrated guide that I’ve linked to above a while ago and it has received over 1.4k shares. Thank you for those who have shared it and I certainly hope its popularity reflects that it’s been of some use.)

Learning in a High Performance Ecosystem


The Learning & Development industry is slowly/ painfully/ finally realigning itself to focus on performance outcomes. This has many dimensions but essentially involves focusing on what people can create, solve and achieve which might involve learning.

Enter the concept of a ‘performance ecosystem’.

It’s a grandiose, bordering on a pretentious term, that explores the idea that we can achieve performance outcomes with the support of things, systems, and people. Like many, I’ve been exploring what such a performance ecosystem might look like.

My latest article on the elearning industry website entitled 8 Skills for L&D Professionals to Future Proof Your Career‘ looked at requirements to design experiences in such ecosystems, and included the following diagram.

It was only later that I noticed that this representation differed from my take on performance ecosystems in 2015 and the way I chunked it in 2016.

With the realisation that I was starting to argue with myself, I did what any self-respecting modern learning would do – I asked my collaborative network for help, in this case via this short post on LinkedIn.

At the time of writing this article that post, and the discussion it initiated, has hit around 9,000 views with thoughtful input from people all around the world. My question was largely pitched around the above diagram, asking for feedback and ideas on how others defined and represented learning and performance ecosystems.

The comments and time I’ve had to reflect on this issue led me to update my model to the following:

(keep reading after the diagram to see how people contributed to this model)

Firstly, HUGE THANKS to all who commented and helped me move to this next iteration. Secondly, let me (inadequately) summarise and respond to some of the comments and themes that came from the discussion. Of course, the Instructional Designer in me has made me theme the comments:


David James questioned the foundation of my initial diagram, rightly commenting that it could feel disconnected from the real world of performance. In this words:

“The thing that strikes me is that while the worker is at the centre, without acknowledgement of the work itself and the aspirations of that worker then the eco-system exists in a vacuum.”

Mark Britz agreed and went further, commenting:

“I personally struggle with the idea of a ‘learning and performance ecosystem’. It would appear as yet another way L&D distances itself from The organization.

This is a risk, and one that Helen Blunden pre-empted by suggesting that I seek broader input by asking people outside of L&D.

So far, in my experience of providing a high-level explanation of a performance ecosystem has resonated with my non L&D clients. The case study I discuss here was premised on our pitch to reduce learning requirements by focusing on performance support through, in that instance, people, resources, and a digital platform.

While I’m unlikely to show this diagram to non L&D clients or geek out about the details as I am here, I will definitely use the principles and model to help broaden the scope and reframe jobs which begin with the dreaded: “Can you build us a bunch of elearning/ workshops to …”

But I really do agree with the disconnection of the previous diagram. In my latest attempt above, I’ve placed workflow experience at the centre of the diagram. In simple terms, this is what people are doing in their job and, in a high-performance context, it involves the points I’ve listed in the diagram such as experimenting and stretch projects.


My original diagram had a person at the centre bounded by a circle marked ‘digital platforms and tools’. This rightly became the target of criticism, with Karen Einsteincommenting:

“I agree that ‘digital platforms and tools’ is probably too central to the learner here as there are a lot of great learning ecosystems which don’t necessarily include digital anything. Because the digital world is so complex and varied, you might want to divide it into different categories according to use instead of having digital be its own category.”

This point was reinforced by Nick Shackleton-Jones and Charles Jennings, who also suggested removing digital from the centre of the model.

While I agree, I found this challenging. I do see the evolution of digital to be a key enabler. Products like Slack and its more recent Facebook and Microsoft clones are some examples of how technology is deepening collaboration and supporting a culture of working out loud.

Of course, technology is an enabler, not a magic solution or absolute requirement… but it can be a bloody impressive enabler. Examples like Amazon training its holiday hires in two days instead of six weeks demonstrates how technology can take performance support to a whole new level.

I’m a massive fan of the humble checklists and Quick Reference Guide, but come on… Amazon’s use of robot assistants and screens with just in time resources embedded in the workflow is surely a sign of things to come.

There I go again, getting seduced by the bling of rising technology. I think we’ll all agree that ongoing digital transformation is significant and will become more so, but I agree that it didn’t deserve the centre position in this model.

Even in the Amazon example, part of their approach involved incentivising the return of previous season hires, keeping up to 14% of them with competitive salaries and tuition incentives.

Digital is part of the picture and, in my updated diagram, I’ve relegated it to one of four elements under ‘Environment’. Having said that, let’s be sure to keep an eye on this one!


Nick Shackleton-Jones made a very useful observation about how I’d represented systems in my original diagram:

“I think you imply that people and systems are separate, where I feel that systems and people are merely means of delivering resource or experience. A person can provide guidance (resource) or tell a story (experience) for example. “

Helen Blundell eloquently followed this up:

“One of the the things I say to L&D people are that “people are the platform” and not to get hung up on the tools or platforms. If we can harness the potential of people to share their work, build their networks, know how to find stuff or be found in the “noise” then the performance we should be worrying about is improving and helping that person be a better person to deal with today’s current work environment (and even, their own life).”

Great points, which I found incredibly useful and yet, I still represent ‘systems’ separate to ‘people’ on my new diagram. While I absolutely agree with Nick and Helen, I had difficulty in doing justice to their insights visually, although I hope the systems-people connection is more obvious in this version.


Clark Quinn had some great suggestions about capturing the formal versus informal on a spectrum throughout the diagram. He even applied this to people talking about a spectrum from formal to the left and informal to the right, he said:

“In people you could have coaching to the left, mentor in the middle, and cooperation/collaboration to the right. Not necessary, just a possibility. 

I didn’t take his advice to the letter, but it did inspire the two axis for people and resources.

Clark also shared one of his diagrams around conceptualising an ecosystem here, which I found fascinating, particular for its consideration on tactics people engage with content or people.


Charles Jennings discussed my separation between learning and performance resources:

“That works fine when viewed through a functional lens, but there is a more profound separation of perspectives, with two different working models – the ‘learning-centric’ working model where learning is the focus and performance the outcome, and the ‘performance-centric’ working model where desired performance is the focus and learning may or may not be involved in achieving it.”

I wasn’t sure if Charles was raising this as a criticism or observation, but he succinctly captured my intention.

As stated in the opening to this article, I’m an advocate of the latter approach Charles described, of the ‘performance-centric’ model which may or may not involve learning. This is essentially the ‘performance hacking’  approach I described in this article.

I’ve found it useful to make the distinction between performance and learning resources, which are respectively described as ‘learning resources’ (such as micro learning) versus ‘job aids’ (such as a knowledge bank, checklist, or guide) in the diagram.

In fact, I changed the title of this diagram to ‘Learning in a High Performance Ecosystem’ to reflect the emphasis on performance.

On that note, I normally find myself rallying against ‘learner-centric’ L&D folk, but Nick Shackleton-Jones takes this further with his wonderful chunking of everything under either ‘resources’ or ‘experiences’ in this diagram.

I love Nick’s call to action of ‘resources not courses’, and that approach informs much of my work, but I would not go quite as far to dismiss microlearning and formal training altogether. In my opinion, while learning will often and ideally be replaced with excellent performance support, the need for it remains.

In my opinion, our brave new world requires more complex learning which is less about ‘retaining knowledge’ and more about developing the mindset and mental models to apply complex ‘know how‘, and be empowered by a broad ‘know who.’

Beyond performance support, there will be times when people need to think, solve or innovate their way out of, or into a situation. In such cases, accessing formal learning as both scaffolding or drip fed elements which integrates spaced recall, will play a role.

Ultimately learning occurs through the interplay between reflection and socially supported experiences but formal elements, particularly those pulled from a place of need and challenge, will provide important scaffolding to the overall learner journey.


Taking up the theme from above, Susan Leslie linked to her article describing what an effective learner looks like. This is a topic dear to my heart, and my take on it was captured by this infographic outlining 15 Powerful Learning Habits to Succeed in a Complex World.

It’s also the driver behind my initiative to launch the Learn2Learn app later this year, which you can find out about here.


Chester Stevenson suggested:

“For the performance side have you considered looking at organizations necessary to look at the full ecosystem such as Operations and HR?”

Marcelo Borges seemed to be making similar points and I did add ‘Talent Management’ under the Environment section in part as a response to this. That said, I’d say this is the area I’d like to explore more both in terms of its potential and trends.


Finally, my attempt at creating this model resonated with Helen Blundell who said:

“What I like is that it feels like you are (just like I am) trying to encapsulate the richness of learning inside and outside the workplace and then putting some structure around it.”

Helen related some of her earlier explorations in doing something similar, including this diagram about networked learners.

Late in the discussion, after several models and diagrams had been shared, Damala Scales Ghosh referred to Einstein in summing up some of the issues raised by the discussion:

“As Albert Einstein wrote: ‘It seems as though we must use sometimes the one theory and sometimes the other, while at times we may use either. We are faced with a new kind of difficulty. We have two contradictory pictures of reality; separately neither of them fully explains the phenomena of light, but together they do.’”

Damala was generous to cite Einstein in relation to our humble rumblings at defining this elusive ecosystem, but it did remind me of one of my favourite quotes from George Box who said: “All models are wrong, some of them are useful.”

Models are inadequate representations of reality that we use to work with complexity. For my part, I’ll keep chipping away at this particular model in the hope it might help be more useful than not.


Thanks again to all those who answered my call and helped critique my last attempt. Now this diagram is fresh off the presses – have at it!

Please feel free to add your comments, criticisms and thoughts and who knows, I’ll probably quote you in my next attempt 😉


This article was first published on Linkedin in May 2017 here.

Reframing 70:20:10, The Anatomy of Workflow Learning


As a designer of 70:20:10 influenced solutions, I’ve found myself increasingly using the concept of ‘workflow learning’ to inspire, explain, and frame my approach.

It’s a framework I now implicitly refer to during the design thinking co-design process I use and has shaped the sorts of blends, campaigns, and ecosystems that are generated from that process. I’ve captured the essential elements of this model in the following diagram.

Workflow learning begins and is framed by the dynamic interplay between behaviour and mindset.

Or, as I’ve described it in the diagram, it places experience at the heart of the model and prioritises its interplay with a conscious process of reflection that bounds it. That’s worth emphasising because, in my opinion, the relationship between experience and reflection is the key driver of learning and change. Everything else, from training, performance support, to social learning, supports and scaffolds that key relationship.

Let’s dive in to see what this means for each element, starting with the two most important ones of experience and reflection.


Experience, based on behaviour and context, is the starting point and heart of workflow learning. It’s the primary anchor and the prism through which other elements are viewed by.

This starting point is an acknowledgement that work is learning. Further, it’s understanding that most learning happens when we are at the edge of our comfort zone, embarking on stretch projects where new challenges demand new mindsets and behaviours.

As long as the stretched comfort zone doesn’t snap, the result is an increase of capability and an expanded comfort zone moving forward.

I still find Mihaly Csikszentmihalyi’s Flow model to be a useful point of reference in striving for that zone of engagement, that lies between chasms of anxiety and boredom.

Structured action learning projects and stretch assignments can support engaging experiences, but it’s ultimately about the approach of the individual and organisation. Real gains require a personal growth mindset, where the individual is motivated and curious to experiment and improve, supported by an organisational culture which embraces failure as an intrinsic part of innovation and growth.


John Dewey famously pointed out that “we do not learn from experience… we learn from reflecting on experience.”

Without a reflective process, the experience that lies at the centre of this model would be relegated to being ‘stuff that happens’. I believe that reflective learning should focus on two elements:

  • Mindset, or the underlying attitude and perspective that lies behind and informs behaviour
  • Mental models, the conceptual frameworks and high-level linkages that are made between various experiences and elements

Stanford University’s Carol Dweck’s work on fixed and growth mindset has popularised the impact of mindset. Her research points to mindset developing through childhood experiences and environment and notes that it can be actively developed, even as adults.

The process of listening to ones ‘internal voice’, which is representative of mindset, and positively engaging with and redirecting that voice, requires a deliberate and sustained reflective process (not to mention buckets of patience and self-compassion).

Similarly, reflecting on experiences with the view of challenging one’s mental models, is a crucial part of learning and unlearning. This process might start with basic questions about recent experiences such as ‘what did I do, what would I do differently, and what are my takeaways’ and can lead to fundamental questions to reconcile one’s world view with the constant reality check of experience.

Over time, such an open reflective process might call into question things we assumed to be true, as old and new mental models fight for their place in our minds. In such cases, the process of unlearning and letting go of redundant mental models, is just as important as developing new models moving forward.

My last word on this is that, in my experience, an effective reflective practice is inherently linked to a culture of investigation and research. There’s a place for regularly and mindfully asking reflective questions as one stares out the window but the process of diving into the web, pulling in resources, and creating mini-experiments to explore and validate ideas can also be crucial to support change.


Formal training is by no means the most important factor that lies between mindset and behaviour, but I’ve placed it at the top of the diagram because it’s the entry point for most L&D professionals.

As I keep emphasising, I believe that experience combined with a reflective process is the gold mine of learning and change. In that context, at its most extreme, training can be viewed as an inadequate but practical substitute for real experience. It also helps to define three high priority points of training focus:

  • Scenarios: to provide safe and supported (simulated) experiential learning
  • Case studies: to provide narratives and engagement points from other people’s experiential learning
  • Key concepts: to provide new mental models and frameworks to incorporate into the reflective process

When faced with a challenge where, for whatever reason, I’m limited in how I can draw on the 70 and 20, my internal voice runs something like this: ‘ideally they’d develop this skill through real life experience and reflection but, since that’s not on the cards, how can I best support them to do it in this training intervention?’

That leads to training that is focused on scenarios and role plays which place the learner in simulated, contextualised, and authentic challenges. This might take a multitude of forms including a written scenario that is debated via a discussion forum, a branched elearning module, role plays in a face to face workshop, right through to an immersive VR driven simulation.

The next level of engagement along that ‘experiential obsessed’ paradigm, is case studies. Using narrative to explore real life challenges helps engagement by establishing real world relevance. Such case studies will ideally include moments in the narrative to actively engage with learners, asking what would they do in that situation and how it relates to their own experience, supporting both reflection and context-based application.

On a slightly different tangent, training can help shed light on key concepts and mental models which inform the reflective process and supports a deliberate approach to learning and unlearning. This is particularly important for experienced practitioners and experts who have developed intrinsic understanding and abilities but might lack a ‘balcony view’ of what and how they are doing, and therefore how they might improve.

I’ve found that key concepts are often best introduced via infographics, short and punchy written pieces, or motion graphic explainer videos. Metaphors and narratives can help create context and make them easily digestible. Simple, visual, and quick tend to be my catch calls here.

It helps to design them with the view that they will be given context in an experience/ coaching interaction/ just in time moment, rather than viewing them as stand alone items which require mountains of context and background.

Finally, although I haven’t noted it in the diagram, another role of training is to support engagement in a change process. Campaign styled assets capturing key WIIFM (What’s in it for me) messaging around learning and performance objectives, helps support that ever crucial buy-in from the learner. After all, whether someone learns and changes is ultimately their decision.


With a focus on experiential, social learning can be posed as ‘how can people, teams, and communities support this person to reach the required outcome in the workflow?’ That means the most effective social learning is inherently performance focused and collaborative.

Coaches play a crucial role in the midst of experience, both in supporting a solution-seeking mindset to challenges and embedding a personal reflective culture. Mentors, like case studies in formal training, can provide inspiration and narratives that can be learnt from and applied to new contexts.

Beyond that, diverse teams, who bring a variety of mental models and mindsets to the table, contribute to developing self-awareness and that ‘deliberation’ I keep harking on about. In other words, collaboration with contrasting approaches and attitudes can help bring awareness to and refine one’s own mental models, mindset and behaviours.

Of course, it’s all encompassed by working out loud. Far from an optional extra, WOL helps to reveal workflows and provides greater opportunities for social and collaborative input. The internal process of consciously sharing and engaging with peers and communities also supports reflection and growth.


Last but definitely not least, comes performance support, perhaps the most powerful yet ignored tools in our arsenal.

I often half-jokingly explain that the role of L&D should be to kill knowledge. A bit provocative, because what I’m really striving for is to reduce cognitive load and stop weighing down people with facts and information, so their minds can be freed up for the important stuff of thinking, creating, and problem-solving.

In a world where a kid with a smart phone can out fact a Mensa convention, why wouldn’t we use the tools around us to minimise redundant learning and support people to use shortcuts, tech, and systems to reach their performance outcomes.

The comic I created a year ago still captures this better than I can put in words alone:

Performance support might come in the form of simple yet powerful checklists (if you doubt the powerful aspect, check out the Checklist Manifesto), micro learning styled videos to support just in time and just enough learning, or an intuitive Knowledge Management System (KMS) that presents knowledge totally integrated into the workflow.


In a perfect world we wouldn’t need to categorise and compartmentalise learning elements because it’s ultimately all bound together and entwined in a complex mesh.

That said, from an industry perspective, learning professionals have commoditised and deliver formal training to the near exclusion of all else. In that context, I do believe 70:20:10 is more relevant now than ever.

Workflow learning, as I’ve described it, is not a break from 70:20:10, rather it’s another way to support much-needed realignment within L&D that was best captured byCharles Jennings when he challenged us to: “Start with 70 and plan for the 100.”

The model I’ve outlined simply helps me to focus on experience first and approach everything else (formal, social, support) through that prism. I share it here, in the hope that others find it useful and that, through the discussion that might follow, it can be improved.

Design Thinking for Learning Innovation – A Practical Guide


About a year ago, one of the big four Australian banks approached DeakinPrime with a challenge. We were asked to pitch for a compliance training job targeting the bank’s thousands of independent insurance brokers. The initial request was very specific, calling for quotes to build 9 elearning compliance modules.

We’d been exploring design thinking for some time and Simon Hann, DeakinPrime’s CEO, was inspired coming fresh off the plane from Stanford’s dschool, so we decided to go in a different direction.

Our pitch tentatively suggested a few elearning modules combined with some on the job tools however, we proposed to develop a more considered solution via a deeper design process which would examine learner needs and workflows, with the call out that we might end up redefining the problem altogether.

To our delight, our key stakeholders at the bank loved this idea and gave us the go-ahead to embark on a design thinking journey. The resulting co-design approach led us to ditch all 9 elearning modules. Instead, we developed a sales portal that provided just-in-time resources, guided customer interviews, and quick search options to access tools and support.

This solution is now live to over 5,000 people and the best part is that, rather than being trained in compliance, brokers who use the platform to increase their sales are inherently compliant. (Watch this space for a more in-depth case study).

In this instance, design thinking supported us to kill training and build an innovative performance tool directly linked to learner needs. In other jobs, it’s helped co-design learning and change campaigns that span tens of thousands of people.

Using design thinking hasn’t always led to paradigm-shifting solutions though. I’ve previously written about the potential fail points of creating 70:20:10 solutions and, in that context, a design thinking process can be crucial in establishing what not to build, instead revealing simple and realistic elements that can be embedded in the workflow of our audience.


For me, design thinking is about starting with empathy, designing collaboratively, and failing faster, to create innovative end to end experiences.

I explored the above summary in more detail during a recent presentation to the LearnX Conference. Click on the presentation below for more and for a sneak peak of the three workshop process that we’ve developed at DeakinPrime.

While we use a design thinking mindset & tools in all our jobs, we use this three workshop process for significant learning & performance projects that lend themselves to complex blends, campaigns, or ecosystems.

If the embedded link below doesn’t work try viewing the presentation here.

Please note, it might not make that much sense without my explanation to support it but hopefully, it gives you an idea.


Beyond the model I’ve previewed in the presentation above, there are a number of tips to keep in mind:

1. Involve your audience early and often

Don’t work off assumptions or second-hand information. Instead, go to your target audience to observe, interview, and empathise with them. The best technique I’ve found for this is to include them in a co-design workshop and charge that group to interview their peers for further qualitative data.

2. Dig deeper with ‘whys’

The interview process, of asking why multiple times, has been a simple yet powerful change to gaining understanding. For both peer interviews and ones that our team conducts, it’s allowed us to go beyond the obvious pain point and uncover underlying needs

3. Collaborate by being visual

The cliche design thinking workshops involve countless sticky notes and cards up on walls. This is more than a gimmick; it’s an efficient way to sort, theme, and share information collectively. Done correctly, using tools such as card sorts or analysis grids, involves and empowers a group to quickly cut through data and make decisions.

4. Use personas

Even if I only have 2 hours instead of three workshops to design a solution, I still tend to use personas. These simple characters support deeper empathy by getting personal and specific. Each job varies but some key elements tend to include how the person thinks, feels, and does around a particular issue. Their key needs, pain points, elements of their workflow and day, and how they access learning, communication and information. For some reason, I’ve found 3 to be the magic number of personas.

5. Incorporate Action Mapping.

While I use many traditional design thinking techniques, I do incorporate a version of Cathy Moore’s action mapping to further understand personas and the gaps between them and the required actions they must take to reach success. Identifying performance gaps in terms of Knowledge, Skills, Motivation/Mindset or Environment can help inform the latter stages of ideation.

6. ‘Orphan your ideas’

I coined this phrase in one of my first workshops and it’s one that continually resonates with participants. It stems from when I was an elearning designer and had a sign over my desk reminding me that ‘I am not my module‘. Similarly, people need to separate themselves from their ideas. Some ideas will get shot down in an instant, others will evolve and end up being stars, but they are not us, and the quicker we orphan them, and allow  them to go their own way, the faster we can create better ones.

7. Everyone can prototype

Low fidelity prototyping can be extremely simple. At DeakinPrime we often include illustrators into the workshop process to bring ideas to life but, for often it’s enough to have participants drawing a concept model of key content, or a stick figure storyboard of a coaching experience, or a wireframe sketch of a portal including moveable sticky notes. It’s inherently rough and quick, but can provide a preview of an experience to allow us to fail faster.

8. Field testing should focus on empathy, not validation

This was a tweak I’ve only learnt recently. Initially we would engage participants to test low fidelity prototypes with their peers, charging them ’to test ideas we’re working on’. Recently, I experimented with charging them to ‘find out more about our audience group,’ using the prototypes as a conversation starter. This shifted people from defending a solution to asking more probing questions, empathising, and revealing needs.

9. The final journey map should include fail points and dependables

The culmination for the more complex jobs we work on has been a wall to wall journey map. A key swim lane in such a journey map is to consider other touch points and people. While we begin the process unashamedly empathising with our target learners, at this point we really want to empathise with the managers, delivery team, IT or others who will be called upon to play a role in the solution.

10. Draw on resources & tools

It’s great you’ve gotten this far as you’re obviously willing to learn from my mistakes and experiences, and there are countless others out there doing great work for you to continue that process. Sites like Stanford’s dschool and Ideo, while not learning specific, are incredibly generous, with fantastic tools and resources you can download right now.

11. Start small, iterate, and learn

It can be intimidating to get started, so be sure to take things a step at a time. You can begin by making sure you talk directly to learners, involve them in the process, and have the means to quickly test half-baked ideas before investing much into them. Be compassionate with yourself as you make mistakes, learn, and improve.


Feel free to check out some of my other work on design thinking and related topics:

Video: Learning Innovation: A Design Thinking Primer for L&D , a presentation I delivered earlier this year. Less nuts & bolts compared to the slides above, but a good starter with some background on the why & how of design thinking in learning.

Infographic: Design Thinking in Learning, now a year old this infographic still captures some key points & my key references.

Article: eLearning Modules will Die and 70:20:10 will hold the Smoking Gun, the premise behind that first case study I cited in the article of shifting from elearning modules to performance solutions.

Infographic: Workflow Learning


Charles Jennings recently challenged L&D to ‘start with the 70 and plan for the 100‘. This infographic explores that approach by focusing on workflow learning, starting with what’s happening in the workplace and drawing on pull resources and collaboration to support deep and continuous learning.

If you’re interested in how to design such learning ecosystems, I highly recommend my previous post about design thinking for human centered learning as a way to explore and support workflows.




Cartoon: The Training Project


Not an argument against all training, but a reminder to design with performance in mind because, sometimes, there are easier ways to overcome that challenge :)

Quick addition to my original post: I’ve had several requests from people wanting to reprint this cartoon in newsletters/ publications. Im happy for you to do so but please take the following three steps:

  1. . just drop me a quick PM/email to let me know where it’s being used
  2.  where possible please include a live link to my blog
  3. if we ever meet in person, drinks are on you 😉





INFOGRAPHIC: Heroic Journeys to High Performance


Yes, they’re fictional characters but their journeys of struggle, set backs, and ultimate victory resonate deeply. Consider this snapshot of how some of our heroes achieved high performance and mastery in the hope that it might inspire some real heroic journeys for us all.



If you like this be sure to connect up with me via social media to stay in touch with future posts. Also be sure to have a look around at my other infographics and content.