Values and joint-leadership


Want to explore the connection between values and joint leadership, the Australian recently published this piece by Kablamo’s Angus Dorney.  You can read it below or at The Australian:

In business leadership, the conventional wisdom is that one person should be the driving force. The chief executive — that almost omnipotent person at the top of the organisational structure — holds the reins. Every success and failure, every brilliant corporate turnaround or dismal quarterly result, rests on their shoulders.

Any alternative leadership structure typically is met with eyebrows raised high.

That has been my experience since joining Kablamo, a digital product engineering firm, as co-chief executive last year, and it’s the reaction I was expecting.

At first I was apprehensive of sharing the chief executive role with founder Allan Waddell, but 12 months on this shared leadership model is paying dividends.

Stepping into a role where I would be making decisions 50:50 with another chief executive was a challenge I had never faced. Not many have.

Not only would I be sharing leadership responsibilities with the firm’s founder — a daunting proposition — but we were also such different personalities, with our own wildly different working styles and areas of expertise.

We even sat a Herrmann Brain Dominance Instrument test, a system designed to measure and describe thinking preferences in people. Our scores varied accordingly. Allan was the off-the-charts outlier in creativity and vision, while my results skewed towards analytical and logical thinking.

Human instinct being what it is, the initial reaction is to push away from this kind of personal dif­ference, particularly when you’ll be sharing leadership.

The differences in our styles are so pronounced that we’ve started referring to our leadership structure as the “odd couple model”. While one might think having such different personalities occupy the co-chief executive roles would be a recipe for disaster and discord, it’s one part of the arrangement that has made the model work so well for us.

Because of these differences, we each have clearly defined areas of responsibility. This clear delineation is critical for the shared leadership model to work. If we both had the same strengths and personalities, it would be difficult to divide responsibilities without some measure of resentment from one side or the other.

While the stark differences between us caused initial trepidation, there are key similarities we’ve found vital to making this leadership structure work.

Consider a Venn diagram. In the outer areas of both circles you have all the characteristics and idiosyncrasies that define our differences. But right at the centre, where the circles overlap, is where both leaders must be in alignment. These are fundamental. If the shared leadership model is to work, these are non-negotiable. These are each leader’s values.

For anyone considering the co-chief executive model, these shared values are absolutely critical. In our case, we have complete alignment on the type of business we want to build, how we want to treat people and how we want to be treated in return. We want to build a good business, not just a fin­ancially successful one. We’d rather walk away than build a company with a depressing, transactional culture filled with uninspired people who are there only for the money.

Knowing there’s absolutely no disconnect on these essential values convinced me to take the leap. Leaders who find themselves in a similar situation need to reflect on whether there’s alignment on these core values.

Five sayings that sound smart, but are actually dumb

Dumb photo.png

Nobody likes a smart ass, especially at work. Yet, there are common workplace sayings that people may think are smart, but they are actually dumb – I call them “dumb-smart” phrases.

When it comes to driving positive change in large organizations, language often gives a good indicator of how someone is thinking - or not thinking - when it comes to innovation. I’ve picked out my top five list of most irritating “dumb smart” things people say. I reckon there are more out there too!

 That’s above my pay grade”  This is usually said with a knowing look and a shrug. The problem is it sounds like the person saying it is humble, circumspect, and even responsible. But it’s really just another way to pass the buck and is incredibly self-limiting. After all, if you only see yourself at a low pay grade, it’s unlikely you are poised to climb higher. Moreover, it limits the discussion, so that any hope of actually solving the issue with is curtailed. Why is this dumb? Because if that’s your attitude, it always will be. You’re basically saying “I’m a cog in the machine so why bother? The machine wins every time.” 

“I told you that wouldn’t work” – I really hate this phrase. Just about all great business ideas come with risk and uncertainty. When developing and implementing innovative digital products, sometimes multiple iterations will be needed to get it right. While this process can look like its “not working”, high performing teams take the learnings from “failing safely” on board and make the next step even better. If you’re seeking to look smart by taking glory in someone else’s short-term failure —which this phrase implicitly does— then you’re going to inhabit long-term failure. People who sit back, avoid accountability and throw rocks at innovation are not as smart as they think.

“We should be using Blockchain/AI/IoT [insert latest tech buzzword]" – People might think they sound smart dropping the latest technology buzzword, but it’s not smart if you are trying to shoehorn it into your organisation. Using tech for tech’s sake is just dumb. The smart approach is to start with the customer problem and work backwards to solve it –  in fact, sometimes the best solution doesn’t even require a buzzword technical component at all! 

"We don’t care what our competitors are doing.” – While this might sound as though you’re embracing a virtue, taking the high road, living your bliss, what it actually signals is a willingness to bury your head in the sand. There’s nothing to gain and everything to lose by being ignorant of the competition. Take it from Sun Tzu, legendary Chinese general and philosopher: “If you know the enemy and know yourself, you need not fear the result of a hundred battles. If you know yourself but not the enemy, for every victory gained you will also suffer a defeat. If you know neither the enemy nor yourself, you will succumb in every battle.”

“Are we just training our people so they can leave?” – Talk about defeatist. You should strive to have the best people in your business and to provide them with an inspiring journey. You want partners, not prisoners! If you’re worried about upskilling employees because they might take that education and leave, then you have a culture problem to go along with your untrained staff (by the way, your staff will leave anyway). Organisations that provide their humans with opportunities to grow and to learn are those that foster the highest levels of curiosity, creativity and innovation. Now that’s smart.

Look, I don't want to sound too harsh. All of us have probably used these words or others like them at some point, but like any culture shift - and innovation is all about culture - sometimes it starts (or ends) with a single phrase. “Smart dumb” phrases don’t help anyone, especially the person who delivers the misguided wisdom!

Have you got an “Innovation Killer” in your business? Here’s five dead giveaways

Killer image.jpg

Inertia has killed a lot of giants. The clients we work with know this. All of them are looking to overhaul their legacy processes, to implement new digital products and to use technology to better serve their clients. That said, an organisation's fate relies on its people, and one bad innovation apple can spoil the bunch – this bad apple is otherwise known as the dreaded “Innovation Killer.” 

The challenge is that Innovation Killers aren’t always obvious. They play it cool and practice passive resistance. They travel in stealth mode. They know that at the very least they must give lip service to the future, even while killing it in the crib.

The Innovation Killer is the opposite of an organisation’s "Change Agent” – that sunny innovation advocate who champions the push to implement new digital technologies. 

Luckily, years of delivering transformative projects have supplied our team with five phrases that we all agree are dead giveaways you’re dealing with an Innovation Killer.     

1. “We’ve tried that before, it didn’t work.” If a project didn’t work the first time, that doesn’t mean it won’t ever work. It might have been tried in the past, but never at this point in time, with this team, and this technology. If the previous attempt failed because of technical limitations, it’s possible those limitations have been addressed in subsequent releases or through entirely new offerings.     

2. “That’s not how we do it here.” Innovation by its very nature changes how things are done. Rather than think of how new digital products change current processes, they should be viewed through the prism of how they improve current processes.  

3. “We could do that ourselves.” If that were the case, it would already be done.

4. “That doesn’t fit with our policy.” Policies are written to help guide businesses; they’re not meant to be wielded as swords to cut down innovation. Good organisations update their policies as they grow and transform, because policies are written to fit the processes and capabilities of the time. Transformational digital products can only deliver their real value if they’re embraced by the whole business – this often means policies need to be updated to encompass the potential of the new technology.  

5. “People don’t like change.” This is perhaps the most common Innovation Killer phrase I hear, and it’s a red herring. It’s not change people fear, it’s loss. Truly innovative and transformational projects are a time of upheaval, but it’s an uplifting upheaval. Thankfully, while this is the most common objection, it’s also the easiest to address. Through good communication, taking the time to explain how much more efficient and productive they’ll be, and how the new technology simplifies their life and the lives of their customers, the Innovation Killer can be brought around.

When it comes to digital transformations, you can’t innovate without changing the status quo. In the face of this disruption, the organisation’s Innovation Killer will inevitably make themselves known and how you deal with them can make or break a project.

The good news is that the Innovation Killer isn’t a bad person (not most of the time anyway), they just have an attitude that isn’t particularly helpful. Whatever you do, don’t write them off or disregard them. By taking the time to understand the root of their reluctance, and addressing it, they can be converted. How to do that will be the subject of another post, but I'll say this, there’s no more powerful Change Agent than a reformed Innovation Killer.

Kablmo named ARN Awards Finalist


ARN Awards Finalist:

Excited to be named finalists in ARN's Innovation Awards for the Smart Technology Category:

Here’s an excerpt:

ARN is proud to announce the finalists for this year's ARN Innovation Awards featuring a stellar line-up of partners and start-ups.

More than 60 partners and start-ups make the final shortlist this year after receiving more than 400 award submissions, playing host to the most competitive and comprehensive selection of leading innovators across Australia.

Reflecting the depth of the local ecosystem, this spans value-added resellers, managed service providers and system integrators, alongside independent software vendors, start-ups and born-in-the-cloud players.

Read more on ARN here.

On Kablamo, Melbourne and Life Decisions.

Melbourne Street Scene.png

Here’s the latest on Kabllamo’s culture, courtesy Daniel Serrano, who has just joined the team down in Melbourne!

Over a month has passed in the blink of an eye.

I told myself I’d take the time to reflect on my first weeks at Kablamo once I had a better handle on what it all meant: once I had met the team in person, seen the projects, processes and pipeline. 

After a sabbatical filled with travel, and the valuable life-lessons that come with it, I vowed to never again work for a company whose only focus was to monetise the lives of its employees. 

I was eager to join a team that hasn’t forgotten what made us choose technology over other career paths in the first place; that sense of wonder and discovery that makes you want to keep doing what you’re doing. Not because it pays the bills, but because it’s interesting and engaging.

Don’t get me wrong. I’m not a naive idealist. I understand a business needs to be profitable, particularly if it cares about the wellbeing of its employees. What I mean is that there must be a beating heart behind every decision, paired with a vision that understands a good culture allows people to thrive and inspires them to grow to their full potential. 

That’s what I’ve found at Kablamo. It’s more than just a business. It’s a skills and talent amplifier where people are truly proud of their work and are always hungry to learn more.

During my four rounds of remote interviews, what I discovered was enough to convince me there is something special going on at Kablamo. Special enough to come back to Australia. To move across the world and take on a new challenge.

I had the chance to work with some of Kablamo’s founding members during my time at Nine Entertainment. The first thing that became apparent was that after a couple of years at Kablamo, all these already talented individuals had reached new levels, both technically and personally. 

This was the first sign that whatever was happening was something I wanted to be a part of.

One of my favourite things about our people is the obvious passion with which everyone approaches not only their work, but also their lives. Kablamo encourages a healthy work-life balance, but it seems most people here don’t make that hard distinction when it comes to sharing whatever exciting discoveries they run into. The breadth and depth of combined knowledge within our team is fertile ground for constant discussion and reflection on almost every aspect of technology applied to human existence.

You would think that with brains this big, enormous egos would follow, but that’s the other reason why I love Kablamo. It has put such care in the people they bring on board that our undisclosed “no asshole policy" is at the top of every hire. So, what has unfolded naturally is an environment where merit leads the conversation and where being humble is part of everyone’s DNA. This almost completely horizontal structure means the focus is to discover the heart of the problem first, then find the real solution. No holds barred. No excuses. 

Looking at the applications Kablamo has built for existing clients, I haven’t experienced this level of engineering since my days in San Francisco; solutions that speak to the merit and potential of technology, rather than to the terms of a business agreement. This is not a sales pitch. It’s the reality of working for a company focused on getting things done, rather than extracting as much money from its clients’ pockets as possible. In fact, at the core of the Kablamo Way is bringing our clients along on the transformation journey, helping them stand on their own two feet by delivering a product they can maintain and own. We don’t want to lock them down; we want to set them free. 

Week after week, I continue to be amazed by the team, the drive, the vision, and the balance that has allowed such a company to exist. (For more on this balance, see a recent writeup by one of our co-CEOs here).

With so much talent here, every day is another chance to learn and push myself further. Innovation is so rapid at Kablamo, I don’t want to blink in case I miss something.

- D.

Explainer: What are deepfakes?


Check out Allan’s thoughts in this CMO piece on Deep Fakes (below or click here to read on CMO)

Have you seen the video with US speaker, Nancy Pelosi, appearing to be drunk and slurring her words? Or perhaps you’ve seen the one with Facebook CEO Mark Zuckerberg joking about knowing the public’s secrets? Or the videos of Rasputin singing Beyonce, Andy Warhol eating a Burger King burger or Salvadore Dali being brought back to life? 

In 2018, former US president, Barack Obama, warned in a video about enemies making it look like anyone is saying anything at any time.

While seeing long-dead artists animated in 2019 can seem like a bit of fun, it hides a darker problem about authenticity on the Web. And in an era of heightened concerns about the fake news label being thrown around to undermine news that doesn’t suit, deepfakes now look set to accelerate a crisis in trust in the Web.

Deepfakes are essentially videos, and in some cases audio, which purportedly show someone doing or saying something they haven’t in real life. They may show real people such as politicians, historical figures or just anonymous individuals. And they may be entirely manufactured, such as the ones showing long-dead people like Andy Warhol or Salvadore Dali speaking or interacting with things they never could have during their lifetime.

Machine learning brings photos to life

Simon Smith, cyber forensic investigator and cybercrime expert witness, told CMO the term 'deepfake' comes from the deep learning tech used to manufacture the fake videos.

“The very best technology is used to map out every muscle movement of a person’s face [if looking at the face only] and replicated into a learning algorithm and associated with a word, phrase, attitude or feeling,”  he explained.

“Once enough learning has been attained, it is possible to attain an almost life-like effect with the assistance of morphing graphical technology that takes into account the person’s age, muscles that move when other muscles move, stretching and expressions to give a realistic approach.”

The answer to why we are seeing and hearing about deepfakes now lies in a confluence of advances in technology and the work of the darker parts of the Web.

There's an exponential growth in computing power behind the surge of deepfakes, according to founder and co-CEO, Kablamo, a cloud-based enterprise software outfit, Allan Waddell. Adding fuel to the fire is the sophistication of artificial intelligence (AI) and pattern recognition on image datasets.

“It’s taking a set of images, and it’s been a large number of images, to create models to overlay on an existing people. Traditionally, the more images you have, the more accurate it becomes," he said. "There’s been breakthroughs in the number of images and datasets needed to create these [deepfakes].”

The rise of fake marketing?

Once upon a time, fake videos might have been created for a bit of humour, like politicians or celebrities with fake lipreading to have them say something which parodies themselves. Mostly they were harmless because they were easily identified as fake and exaggerated enough to defy believability. 

However, such advances in machine learning technology have enabled the creation of realistic-looking videos. Combine that with the pervasiveness of social media, where fake news and videos can spread without proper scrutiny or verification, and you bring the issue of deepfakes to the fore.

“The technology has been used for many years to help animatronics by mapping out joints and movements in cartoons. This is one step above that and [in the wrong hands] could cause identity theft, false impersonation, setup for crimes a person did not commit and much more serious repercussions,” Smith told CMO.

Rise of the Mammal: the existential threat facing traditional consultancies


Read Angus’s thoughts on traditional consultancies below (or read on TechDay here):

Business transformations are a challenging time for any organisation. During this time of relative vulnerability, many organisations turn to the major players for help – typically one of the big five consultancies.  

Very quickly, however, many businesses experience a disconnect between what they were promised and what is delivered. Common threads in these engagements are that the large firms over-promised, overcharged, underperformed, and often did so after agreed upon deadlines. 

Since starting Kablamo, a significant portion of our business has come from being called in to clean things up in the wake of these failed projects. In fact, these engagements happen so frequently we have our own internal name for them: “Rescue Missions”.

We recently partnered with UNSW Business School to investigate why this was happening so often. The initial qualitative research, in which we sought insights from some of Australia’s leading C-level executives, uncovered three key factors that contributed to failed transformation projects.

The first insight was that the traditionally dominant players, the big five consultancies, had struggled to adapt their business models for a changing technology landscape. In decades past, these consultancies had been engaged with primarily one outcome in mind – keeping costs down. In order to do so, they standardised their offerings around a limited number of services, essentially boiling down to variations of “lift and shift” outsourcing models. 

Today, however, businesses are looking for far more from their partners. They’re seeking innovative solutions that provide business differentiation, allow them to compete against industry disruptors, and future-proof their organisations. 

Critically, these solutions must be tailored to the specific needs and vision of the client. The big five consultancies struggle with the necessary customisation, the research found, because of their focus on standardised offerings. 

While this is a significant hurdle to overcome, and is a large contributor to failed transformation initiatives, the second factor the research identified was a lack of clear communication between partners and clients. Part of this breakdown in communication was attributed to the traditional view of IT as a cost centre. After engaging one of the large consultancies in an outsource project, rather than redeploy talent to more strategic initiatives, these staff members were often made redundant. The result of this, is a deficit in the technical and institutional knowledge required on the client side to effectively oversee and manage the partnership. This is particularly problematic during the initial stages of an engagement when contracts are being negotiated. 

By setting clear standards and expectations from the start, both parties have an interest in the relationship’s success because if the provider drops the ball, the client is empowered to move on to another partner. 

The final finding from the research was that a lack of clearly defined goals and metrics against which to measure the success of transformational projects hamstrung initiatives from the outset. 

With business today expecting more innovative solutions, measuring end-user experience or business performance is much more beneficial than the antiquated 99.XX% availability scores traditionally used to measure service provider relationships.

While proper measurement is important, clearly defined goals are perhaps most critical to the success of a project. Because the large consultancies have standardised their offerings, they struggle to investigate solutions outside of their standard services. 

This is where the new breed of smaller, more nimble consultancies thrive. Because they have the freedom and technical ability to consider all possible solutions, these newer players can take the time to intimately understand the client’s vision and find the best way to deliver exactly what they need. 

Part of the problem is that the large players are unwieldy and legacy-bound enterprises themselves. Generally speaking, enterprises are inefficient, so you end up in a position where an inefficient enterprise is trying to help another enterprise increase efficiency – it’s not going to end well.

As technology evolves, and business needs with them, the traditionally dominant consultancies face an existential crisis. Unless they learn to adapt, they risk sharing the fate of the dinosaurs. In their place, the smaller specialist players will thrive – their adaptable and nimble nature will see them mirror the rise of the mammals.   

The Ethics Centre: Injecting artificial intelligence with human empathy


Proud to see Allan’s latest piece on AI published by The Ethics Centre. Here is the full text or you can read it there:

The great promise of artificial intelligence is efficiency. The finely tuned mechanics of AI will free up societies to explore new, softer skills while industries thrive on automation.

However, if we’ve learned anything from the great promise of the Internet – which was supposed to bring equality by leveling the playing field – it’s clear new technologies can be rife with complications unwittingly introduced by the humans who created them.

The rise of artificial intelligence is exciting, but the drive toward efficiency must not happen without a corresponding push for strong ethics to guide the process. Otherwise, the advancements of AI will be undercut by human fallibility and biases. This is as true for AI’s application in the pursuit of social justice as it is in basic business practices like customer service.


The ethical questions surrounding AI have long been the subject of science fiction, but today they are quickly becoming real-world concerns. Human intelligence has a direct relationship to human empathy. If this sensitivity doesn’t translate into artificial intelligence the consequences could be dire. We must examine how humans learn in order to build an ethical education process for AI.

AI is not merely programmed – it is trained like a human. If AI doesn’t learn the right lessons, ethical problems will inevitably arise. We’ve already seen examples, such as the tendency of facial recognition software to misidentify people of colour as criminals.

Biased AI

In the United States, a piece of software called Correctional Offender Management Profiling for Alternative Sanctions (Compas) was used to assess the risk of defendants reoffending and had an impact on their sentencing. Compas was found to be twice as likely to misclassify non-white defendants as higher risk offenders, while white defendants were misclassified as lower risk much more often than non-white defendants. This is a training issue. If AI is predominantly trained in Caucasian faces, it will disadvantage minorities.

This example might seem far removed from us here in Australia but consider the consequences if it were in place here. What if a similar technology was being used at airports for customs checks, or part of a pre-screening process used by recruiters and employment agencies?

“Human intelligence has a direct relationship to human empathy.”

If racism and other forms of discrimination are unintentionally programmed into AI, not only will it mirror many of the failings of analog society, but it could magnify them.

While heightened instances of injustice are obviously unacceptable outcomes for AI, there are additional possibilities that don’t serve our best interests and should be avoided. The foremost example of this is in customer service.

AI vs human customer service

Every business wants the most efficient and productive processes possible but sometimes better is actually worse. Eventually, an AI solution will do a better job at making appointments, answering questions, and handling phone calls. When that time comes, AI might not always be the right solution.

Particularly with more complex matters, humans want to talk to other humans. Not only do they want their problem resolved, but they want to feel like they’ve been heard. They want empathy. This is something AI cannot do.

AI is inevitable. In fact, you’re probably already using it without being aware of it. There is no doubt that the proper application of AI will make us more efficient as a society, but the temptation to rely blindly on AI is unadvisable.

We must be aware of our biases when creating new technologies and do everything in our power to ensure they aren’t baked into algorithms. As more functions are handed over to AI, we must also remember that sometimes there’s no substitute for human-to-human interaction.

After all, we’re only human.

Allan Waddell is founder and Co-CEO of Kablamo, an Australian cloud based tech software company.

The "Odd Couple" - my first year as co-CEO 

Alan and Angus Co-CEO.jpg

One year ago, I made the biggest move of my career and joined Kablamo as co-CEO.

Not only was shared leadership new to me, but from the outset it was clear Allan and I were very different people.

Allan brings the creativity and technical vision to our team. His insights into areas like artificial intelligence and running Agile at scale are mind blowing, and the right kind of crazy. He can take the esoteric and make it accessible, pushing all of us to think deeper, farther.

My strengths? Let’s just say I leave that kind of creativity to Al. I know how to build and scale businesses, plan and execute strategies, and keep organisations and people happy as they strive for greatness.

Human instinct being what it is, the initial reaction is to push away from this kind of personal difference in a co-CEO model. It can be a scary leap into darkness for both people. The “visionary” can worry that the “manager” mind might over-manage and constrain —becoming an idea killer, a clipper of wings. On the other hand, the manager may worry that the visionary will be impossible to channel in a way that can deliver consistent customer outcomes and meet payroll each week!

Long story short, between my unfamiliarity with this shared approach, and the fact we’re both such polar opposites, I was nervous about what lay ahead.             

While I’ve started with the differences, for the co-CEO model to work there must be some critical similarities – similarities which are values-based, not financial. 

For Allan and I, nurturing a strong values-led culture at Kablamo is a principle neither of us will compromise on. We have rock solid alignment around the type of business we want to build, how we want to treat people and how we want to be treated in return. We’d rather walk away than build a shitty, transactional company and culture filled with uninspired people who are just there for a paycheck.

And this brings me to another critical point: Ego. A healthy confidence and belief is one thing, but for the co-CEO model to work, you need to have right-sized egos that are willing to accept imperfection, share success and to learn from failure. In that sense, it’s not for everyone. Needless to say, trust —and a lot of it— needs to be a big shared value between both leaders.

So, what’s been the result for Allan, myself and the Kablamo team in our first year as co-CEOs? By embracing our differences, Kablamo has grown far beyond what I thought possible when I first agreed to share the CEO role. Our varied skill sets allow us to focus on the areas we excel, which has helped lead to strong organisational growth. 

In fact, 12 months on, it’s clear our differences are one of the biggest benefits of this co-CEO model (in a future post, I plan on digging down into this a bit more).

Not only has our customer base significantly expanded to include some of Australia’s largest media, financial and industrial organisations, we’ve more than tripled our staff numbers to accommodate the demand.

While growth is important, what matters most to Allan and me is Kablamo’s culture. We’ve developed a strong set of values and a vision for our future. We’ve also grown and evolved our leadership group on our mission to become a high performing team. We’ve started our employee benefits program, and launched our giving arm, Kablamo Impact. We want to build a good company, not just a financially successful company.

Underpinning this all is our focus on building a world-beating culture. Our secret sauce is our people. Day-in and day-out, this team is delivering truly transformational digital products and outcomes in some of Australia’s largest and most well-known organisations.

And their hard work is being recognised. Earlier this year, we were named as finalists at AWS’s Partner of the Year awards for Data, Analytics and Machine Learning.

Now with a solid foundation built, and much more confidence in our shared leadership model, this next financial year will be the most exciting in our history… stay tuned.

Even if you’re not ready or convinced by the co-CEO path, consider giving shared leadership a try, if only in a limited way —sometimes going against your human instinct can pay off. 

Read on LinkedIn and connect with Angus f.

Neobanks and the coming disruption?

neo bank.jpg

Check out the full text of Angus Dorney’s take on Neobanks (originally appeared in The Australian, if you want to read it there click here):

When the internet challenged the global media industry, companies were confronted with a stark choice — innovate or perish. Smart people saw the need to prepare for the digital era, and those that successfully digitised their offering stayed ahead of their disrupters.

Despite the media industry constantly managing financial pressures and shrinking budgets, media leaders were quick to innovate because they had to. They drew from a relatively limited war chest and embraced innovation throughout the organisation. In fact, those that failed to do so endured major business losses, including many that were fatal.

The media companies that survived were acutely aware of the need to innovate and actively sought to do so. From a corporate culture perspective, the entire organisation saw the need for technical and product innovation and it was seized enthusiastically throughout the business.

The wide-scale disruption visited upon the media industry should have served as a warning for other sectors. Yet, some industries failed to learn from the lessons of others.

Increasingly, smart people in financial services are passionately waving their hands as the industry finds itself similarly on the brink of a wave of disruption — in this instance at the rise of neobanks.

A neobank is a branchless financial services provider that operates exclusively with customers on digital interfaces, like mobile devices. Uninhibited by the practices of traditional banking, these upstarts are free to weaponise technology to their advantage, in what is essentially a form of guerilla warfare against the incumbents. Much like AirBnB and Uber shook the hospitality and transportation industries to their core, neobanks are set to challenge the banking sector.

In Australia, among the 2.1 million adults over 18 who are looking to change their main financial institution, about 16 per cent of them indicated in a recent Nielsen study that they’d prefer to use a digital bank. This is a five-percentage point year-over-year increase from a previous Nielsen study.

Since the big banks historically operate outside the start-up mentality, and in some instances have been known to dilute the essence of the start-ups they acquire, it’s important to consider what that might mean at scale.

As new entrants to the market, neobanks could be the catalyst that makes the financial services sector sit up and take innovation seriously. It’s critical that when this happens, executives and other leaders understand that innovation can’t happen in isolation. Like the media organisations who got ahead of their disrupters, innovation must be embraced throughout the entire organisation if it’s to have any chance of success.

The shift is already well underway. Neobanks are on the verge of exploding in the Australian market. A surge in applications for restricted banking licenses have been submitted to the prudential regulator APRA, with the first license going to a start-up called Volt. It was the first time in 28 years that a new bank was created in Australia. Start-ups like Xinja and 86 400 will also be important to monitor.

Despite their position as disrupters, neobanks have their own challenges to overcome. As a player in a heavily regulated industry, they can’t afford to forget the importance of network and data security, and governance. While chasing rapid innovation, some fintechs can concentrate too much on their own product features while deprioritising the development of APIs that will enable them to integrate with other products and service providers (including incumbent players). If not managed correctly, this inability to integrate with other platforms can become a major handbrake to future growth.

On the other hand, most incumbent companies in the financial services sector have been slower to innovate because they haven’t yet been forced to. When they do try and innovate, it is not always an organisational priority and is often an experiment made in isolation, separate from the rest of the business.

The finance industry, however, has an advantage that many media organisations don’t — access to massive war chests of capital, much of it within their own control. Whereas the media industry embraces innovation with comparatively limited resources, financial services have significant levels of capital available to invest. All the ingredients are there for the incumbents to lead the trend toward truly branchless digital banking before the newcomers beat them to it, but the big banks must first find the appetite to do so.

Financial services executives need to monitor the nascent neobanks closely and keep pace with their hunger for innovation. By learning from the media industry, they can get ahead of shaping the inevitable change before it’s too late.

Overcoming Customer Stockholm Syndrome


Kablamo has been breaking some new ground in Australia, engineering and delivering quality digital products as a service. That shouldn’t be notable in any way, but our customers aren’t used to getting exactly what they want, when they want it. 

Sometimes being a high performer in an industry with a bad reputation can be a burden due to what I call Customer Stockholm Syndrome.

Consultancies have been promising digital transformation for years and have largely failed to deliver – this makes our effectiveness a new experience for many. Kablamo is a digital product engineering company, building beautiful software on top of complex data sets. We consistently deliver exactly what our clients need, on time and on budget.

While this should be a perfect storm for kicking goals and landing clients, we have to be careful to avoid a corporate version of organ rejection.

Organ rejection occurs when transplanted tissue is rejected by the recipient's immune system, destroying the transplanted tissue. Despite incredible work from donors and doctors, the body pushes back against something that’s ultimately good for it, and the results can be tragic.

The stakes might be lower in the corporate world, but the risks are no less real. When your company dramatically outperforms what your customer is used to, they can feel like it’s all too good to be true.

As a reflex, clients may feel compelled to take some ill-advised course of action. In our industry, that might include reverting to old enterprise vendor management practices and policies, to their own detriment and ours.

This could mean inserting additional vendors for ‘competitive tension’, introducing reams of over-prescriptive legal doctrine, or building bespoke insurance and risk-prevention techniques – all of which are either unnecessary or only useful to manage the poor vendor relationships they’re used to.

This isn’t the client’s fault, of course. They’ve been held captive by underperforming service providers for years, a feeling we can all relate to. Just like victims of Stockholm Syndrome, they build coping mechanisms to get them through.

The solution lies in getting the customer to realise that by virtue of your product or service, they’re now free of the underperforming vendors. All this without coming off as pushy, which can itself be a trigger to Customer Stockholm Syndrome.

That said, there’s no simple resolution to this issue. It’s a people problem, and people are the best tool you have to solve it. For Kablamo, our leadership team have built careers in negotiating these scenarios, and we will continue to fight the good fight. Not only for ourselves, but for the future of our clients. 

Amazon Textract - An Early Look

Three scopes code.jpg

Last year at AWS re:Invent, Amazon Textract was announced as a next-generation OCR service which not only performs word-based translation, but can also provide form and table value extractions in a way that makes it easy for developers to link into their own services. Today marks its Generally Available release.

Optical character recognition (OCR) has always been a challenging problem to solve. The technology to do this has been around since 1914, yet some companies still employee a human workforce to perform laborious data entry from forms and documents into their corporate systems. Textract aims to automate this problem however it does not currently support handwriting within the documents.

Form and Table Support


In addition to word and line text extraction, form and table support is something that is rare to OCR technologies and even rarer to have it available as programmatically extractable information. Oddly, paragraph support is not present in the service.

Form information is available in API call responses as a key-value set and table information is available as cell blocks with row / column values and cell spanning information. All values regardless of type include bounding box coordinates (which is shown in the console demo screenshots) and confidence scores.


Testing The Limits

As with most services, the demo document is the best case scenario so I wanted to test with something unknown to see how well it did, using a document I had readily available. Here’s how it did:


From the screenshot you can see it did fairly well, though it did have some issues:

  • 90° Rotated Text Not Detected: One of the limitations of the service is that it only supports horizontally aligned text, so the text in this was not found correctly.

  • Multiple ‘X’ checks were not discovered: Though it correctly detected one checkmark (as the text ‘X’), it missed two in the same format immediately above it.

  • Did not detect single-row or single-column tables: In our testing with other documents, tables with a single row or single column were not detected as tables.

Pricing and Availability

Textract is marketed as costing $1.50 per 1000 pages, but it’s important to note that’s only for simple text recognition. If you want to detect table data, that price goes up 10x to $15 per 1000 pages and if you add form data the total becomes $65 per 1000 pages, a 43x increase!

As of today, the service has become generally available in the N. Virginia, Oregon, Ohio and Ireland regions. The service is expected to roll out to all commercial regions gradually as they improve the service.


Amazon Textract is a remarkable step up for OCR technologies. It exceeds competition such as the Google-sponsored Terreract project but costs can jump steeply when adding advanced features such as table and form information extraction.

If you’d like help designing an automated document scanning system, get in touch with us to find out how we can help you plan, design or build your solution.

Algorithms and Arrhythmia: How AI is revolutionising healthcare

Screen Shot 2019-05-13 at 5.28.54 pm.png

Kablamo’s Allan Waddell recently explored Health and AI for Health Care IT. Here’s the piece or you can read it on their site:

Artificial intelligence (AI), neural networks and machine learning can be ethereal concepts to the average punter, but when applied to the health sector their benefits come into sharp focus.

When technology can save a life, it suddenly becomes meaningful. Magnetic fields and radio waves took on a new meaning with the introduction of the MRI machine, and the same will happen with the application of today’s technologies in the health sector. 

We’re just starting to see the impact AI and image recognition can have on healthcare, but it is poised to be the technology’s biggest contribution to society yet.

Earlier this year, a group of Chinese and US researchers developed a program to automatically diagnose childhood illnesses including meningitis, asthma, gastro and the flu. This AI program works faster and, in some cases, more accurately than doctors.

However, as in the early stages of every new discovery, there are obstacles to navigate. Privacy concerns, investment requirements and regulatory issues are just some of the hurdles that need to be overcome. 

Despite the challenges, there are  potential benefits. Doctors are an invaluable part of society, but they are still human, and misdiagnoses happen. According to research, there are approximately 140,000 cases of diagnostic errors in Australia each year, with 21,000 resulting in serious harm and more than 2,000 resulting in death. 

Modern AI promises to solve this issue through the power of neural networks. Unlike traditional software that only does what it’s told, neural networks can teach themselves new skills with enough training data. By reviewing mammograms with and without cancerous cells, for example, a neural network can learn to identify malignant cells in new mammograms.

In 2016, a research team achieved just this. The Houston-based team built a program that analysed mammograms 30 times faster than a human, and with 99 per cent accuracy. More recently, Maryland researchers used AI to diagnose cervical cancer with 91 per cent accuracy, vastly improving the 69 per cent human success rate. 

These diagnoses were all made without an expensive medical professional, and without the cost of a clinic. 

The upshot is AI could offer better diagnosis, to more people, for less money, in less time, allowing doctors to focus on patients that truly need their care. Not only can technology improve current diagnostic methods, but it can also create new ones; neural networks will eventually identify links between symptoms and illnesses that human researchers would never have found.

Unfortunately, the AI healthcare revolution has a down side, and a price many Australians seem unwilling to pay.

To be effective, neural networks need the training data of many thousands of people in order to learn which symptoms correspond to which diagnoses. In the China/US study, 600,000 Chinese health records were used as training data, a feat possible thanks to the sheer size of the country, as well as China’s less stringent privacy culture.

In Australia, we’re far more protective of our data and cognizant of the implications of sharing too much. 

Privacy aside, there are challenges around getting consistent data, both to teach programs and to feed them for diagnosis. 

Inconsistent standards are used across the private and public sector, even between doctors in the same clinic. While getting clean data is technically possible, it could be a regulatory and administrative nightmare.

Despite the obstacles, AI’s potential benefits to healthcare are not just worth pursuing, they should be a priority. Just as governments are now (rightly) planning for the arrival of self-driving cars, we need to plan for an AI powered healthcare system today.

Standards on access to data need to be agreed upon, along with a transparent and open opt-out process. A standardisation of medical data is also long overdue. More than just setting us up for the benefits of AI, patients would see immediate benefit from more consistent data recording.

It’s a long road between here and a world of automated and accurate AI powered healthcare, but it’s one we should start preparing for today. 

Without this preparation we’ll see more noble but half-baked ideas launched before they’re ready, eroding public trust. It’s a world we can see, but one we can only reach with a clear-eyed vision of the journey ahead.  

Amazon AWS Summit Intel


Great to be able to share this from the AWS Summit and Paul Migliorini, Amazon Web Services’s ANZ lead (as reported by CRN, read the whole story here).

When asked whether AWS's largest partners like Accenture, Deloitte and DXC were getting in on the machine learning action as well, Migliorini said global systems integrators are investing heavily in those areas, but are working with consultancies of all sizes.

"You're looking at these organisations with really deep specific capabilities… Kablamo, DiUS, and Intellify, these sorts of companies… they're working with these larger integrators as well in that really cohesive way for customers. And I think that's one really nice thing about the evolution of the way the partner ecosystems are working today."

Miglironi wrapped up with his three key messages for the channel, which included his call for partners to challenge AWS harder.

"The first is that success will come from thinking long term about customer success, which means that putting a focus on outcomes, no matter how small project or revenue is, everyone will be rewarded by customers for the long term. So we want our partners together with us to think long term and to put customer outcomes ahead of any other short term game.

Amazon Summit News: Kablamo Named Finalist Partner in ML

AWS Partner Network.jpg

Kablamo is proud to have been named a finalist in Data, Analytics and Machine Learning today. CRN covered the story (read here):

Amazon Web Services has named its top partners for 2018, with Melbourne-based Versent being named best consulting partner for the third year in a row.

The awards were handed out during AWS Partner Summit in Sydney this week, selected by a panel of AWS experts.

Video: Why "Build it and they will come" doesn't always work

Watch Victoria dismiss the Field of Dreams’ “build it and they will come” fallacy when it comes to building great UX, or read her comments below.

I find that the way products are traditionally made is "build it and they will come" approach. So, a few people in IT sit in a corner by themselves, make a product. Then they get a manual 200 pages long, give it to the user and say, "Use it for the next 10 years." And that takes an effect. So, if, if somebody feels like something is forced upon them, they are less likely to use it. They're not sure how it integrates with the process, and it might be flat-out wrong. It might actually incl ... increase the burden on their wellbeing.

Using the process where the user is in the beginning, and getting that journey, and seeing how this product can improve them. And doing that from the beginning, so the user feels like they're involved in the process. They feel like they're contributing to it. So that when it comes out on the other side, they're not only love using the product, they're an advocate for it.

Video: Lessons learned from design done wrong

Watch Victoria and Allan talk about why design can go wrong and how to avoid the pitfalls. Read the transcript below.

One thing I see very frequently is UX happens in the beginning, development happens second. And so you do the interview, you do the research, you do the user stories, you have the design, give it to the developer, you walk away and you work on something else.

Now in real life, things change when they get developed so, you would have the journey and you would have all of the principles imbedded in that however, you would start working on one of features making sure that's up to scratch, having the screens, the-the designs and then passing on data onto development and you don't walk away because what I find, more often than not, the developer goes we can do ninety percent but this ten percent it's not really feasible so we would go oh, right let's rethink this so you can tackle this right there and then so you can come up with a better solution. Sometimes the solution is actually better than what you originally came up with. And so you tackle that there, everything becomes unblocked and you can start working on-, on other things. So you have design check-ins. 

Victoria's right. That's exactly like, what happens is-is-is sometimes, you know, th--I think any business where there is silos, you're going to have challenges. Um, if you're not thinking about cross functional and the way make cross functional work. Um, it's very easy to go, 'well, let's just stay in solitude, feel safe and secure and we'll have designers a thing over here and we'll make the best design possible and then we'll have this development over here and the best development possible'. Because cross functional is too hard. If you think cross functional is too hard, you--like you really have not been working in the industry long enough because the idea is if you--you have to make that process work if you want to get the agility and the, and the flexibility that Victoria's described. 

I think any business that is still holding onto um, either ivory towers or the way in each of those disciplines without factoring in the results of the other--of any other discipline, that's when it really falls apart. 

Video: How to improve the user experience

Introducing Freddy, Kablamo’s Dev dog, and watch Allan Waddell and Victoria Adams weigh in on what’s needed to make UX work. Here’s a snippet:

It takes experience to know how to engage customers in the right way. It's not as simple as just putting a wire frame in front of a bunch of people and getting a result. You have to know what your tests are for. You have to know what hypotheses you're validating, specifically, and you have to get those answers and be able to measure that in the right way and then understand those results. It's like saying the difference between data and information. You get a whole bunch of data back, but it doesn't really mean what you think it means unless you thought about that preemptively.