The Global Innovation Survey by McKinsey found that 84% of executives felt innovation is important to their growth strategy, but only 6% of them are satisfied with the performance on their innovation. One of the things that we work on at the prototyping team is accelerating and unblocking the technical innovation efforts of our customers. My name is Ryan Cross, and I'm a Prototyping Engagement Manager at AWS. Let me tell you a little bit more about what my team and I actually do. Often customers have an ambitious vision or an epic business challenge to tackle, and they need some support connecting where they are today, with where they want to be in the future.
More than just a demonstration of technology, prototyping bridges between business outcomes and technical capabilities. It's a proving ground for solutions without going all the way to production. By validating what is possible for customers, we can accelerate their innovation. Our work spans across every industry and into any technology, we are constantly pushing the boundary.
I am super lucky to be able to work with such a breadth of ideas. Being at the boundary every day is what gives us a really unique perspective on how different companies are applying the latest emerging technology to change their business and solve real world problems. Emerging tech is a big topic so I have a lot to cover today. I'm going to share three major themes and highlight trends and examples. I'll wrap up with some tips that you can apply to your own projects. With only 30 minutes, I'll be covering the starting points here, but there should be enough pointers for a good jumping off point. So let's get into it.
It's a bit of an old adage, but in 2020 almost everyone realised that the only constant is change itself. Many of us are still holding back making certain plans because it feels too uncertain to commit. In 2019, Ernst and Young published survey results showing that 79% of C-suite executives said their organisations were tolerant of failure, which is often a really key element to the success of innovation.
The disruption from the pandemic has shown that many businesses were not nearly as resilient as they thought. I'm not a business analyst by trade, but looking across the industry as a whole, the trends can seem like common sense. The rate of disruption and dynamic conditions has been increasing for a number of years, and the pandemic has only accelerated and exacerbated those trends. Handling disruption and being agile in a highly dynamic environment will continue to be required for many years to come. Workers have been pushing for more flexible working arrangements and now that workforce mobility trend will continue. Businesses will need to scale up and down in order to meet these elastic requirements as well.
From a technology perspective, Gartner released a report in December 2020 about emerging technology and plotted them on this radar chart showing the closest trends towards the centre and the ones several years away towards the edges. Grouped into three areas, interfaces and experiences include technologies like advanced computer vision that are fundamentally changing the way we interact with the world. Business enablers are technologies like Blockchain that impact enterprises by changing practices, processes, models and functions.
Productivity revolution is driven by the confluence of multiple intelligent technologies and smart application trends that has resulted in solutions that help organisations augment human efforts and potentially solve problems that humans cannot. When you look at the horizons of technology trends, there are two quotes that I find useful. First, "The best way to predict the future is to create it." As we've all seen, our situation today is a lot different than where we might have predicted it yesterday. Creating the future we want can take out a lot of the guesswork. Secondly, "The future is already here, it's just not evenly distributed."
As we can see from the previous chart, some people are already working with these technologies, they're just not mainstream yet. From a people perspective, we see some common behaviours and thought patterns at play when working at the edge. Perhaps unsurprisingly, people are both fearful and excited, a sense of trepidation and wonder which has kind of two sides of the same coin. They're really curious to know what they can do, but they're also really nervous about how these things are going to apply to them. Looking to the future, they're really trying to look forward and predict where their businesses are going to be and find the next big ideas that are going to change what their businesses look like.
Maybe that's why some of you are here today. There is also an increasing amount of focus on how those big ideas can create tangible results in the near term, rather than waiting for long-term investment returns. And what's great about this is that it matches quite well to some of the leadership principles that AWS follows. The first one is learn and be curious. We're constantly
looking to learn and understand things more. Secondly, we have a principle of think big, challenging ourselves to think about things with a bigger impact. The last one is deliver results. The best technology is useless if it doesn't solve a problem and if the solution isn't in someone's hands, then it equally comes up short. These are just a few of the principles that guide our work.
After looking at some of these wider trends, I reviewed internally what we've seen from customers applying these technologies and current projects. There were three main themes that the trends fit into. The first is Future of Work, the second is Smarter Applications, and lastly is Embracing Openness. I'll talk about each of these in more detail though.
When I look at these changing work conditions there's a couple of key pieces to them. Obviously those of us lucky enough to do so have gotten really familiar with remote working. That's going to be something that will at least persist for the near future. Even when people eventually get back into the office, it's going to be something that's far more common for everybody to deal with.
The velocity of change will also remain high and likely continue increasing. Everybody felt disrupted in the last year, but that's been something that has just exposed the changes that have already been happening and are going to continue to change. The jobs and skills of tomorrow aren't even known yet.
While people may be working remotely, local opportunities will become more important. People are looking to de-risk and diversify their supply chains with more local capacity. They're also looking at how they can personalise and improve their experiences with more local focus.
One of the best examples of this last year was Genie Solutions. They are one of the leading providers of practice management software for medical specialists across Australia and New Zealand. Early in the pandemic their customers had a new, urgent need to be able to deliver telehealth services to their patients because of the safety protocols that were being put in place. Genie's customers were even starting to turn to alternatives for solutions, so they needed to act quickly. By leveraging Amazon Chime SDK, a service that allows custom video conferencing solutions, they were able to get a working solution and integrate it into their existing product for a streamlined user experience.
A huge benefit for them was the fact that they're able to get something in the market in less than two weeks, which was over 400% faster than the normal release cycle, and increased adoption rates compared to other new product releases. If you want to get a better sense of this process, check out the Innovation Ambassadors podcast. Some of these changes to work will have long-term effects. Obviously people are getting more comfortable with video communications. You're seeing me over video today rather than in person as I'm sure all of us would prefer to be.
There's going to be an increased amount of remote collaboration as well. Even when people are in the office, there will be a need to involve those that aren't. And finally, everybody's becoming more familiar with new technology. There's always going to be an increased adoption of different technologies moving forward. Everyone will move to become digital natives.
An example of this is OneTwo, a new financial services company focusing on improving the overall experience for large financial transactions including mortgage lending. They have identified that the in-person experience of working with a broker was really important in establishing trust, but has limited ability to scale or be flexible to customer's needs. They had this concept of a TV show for one where you could create a really rich video experience for a single person that offered both the personal experience to build trust and confidence and technology to scale.
We helped build a solution that allowed them to orchestrate a lot of different video signals and incorporate intelligence services like transcription. This delivered a new experience for customers to work that many people have considered even better than the old way. There is also a podcast episode with more details on this as well. And this leads to one of the other things that we've identified, which is these innovation by-products. Disruption can create really unexpected results and innovation kind of begets more innovation. When you
break established norms, you can create the potential for new revenue streams. You can cultivate new capabilities that can be used in ways that were never originally designed. And perhaps most importantly, it can give you new perspectives, which allow you to look at old problems with fresh eyes.
One of the best examples of that was working with the National Basketball League this year. During the pandemic they were challenged by not being able to have live crowds at their games. The initial challenge was how to create a virtual crowd experience, both at home and on the court, so they can engage people in a lot of different locations. This ended up being quite successful and saw the ability for life-sized fans to be on LED panels at the games with different fan reactions. But the point that I found really interesting was the unexpected benefits. Now they have the ability to expand their reach beyond just what they used to do with live audiences.
They capture a lot of rich content and customer engagement, which they can then repurpose for other channels, such as social media highlight reels. There's also a podcast episode for this. The second major theme I saw was for smarter applications.
We're seeing a lot more intelligence being applied across the board. People want to be able to take the data that they have and enhance it. They want to be able to identify deeper insights and see patterns that they previously hadn't noticed. They're also looking at new ways to predict behaviour changes or detect anomalies for investigation. Black swan events like the pandemic will almost never be possible to predict, but there's always trends and information in data that is increasingly valuable. AWS has a
broad and deep range of machine learning services. The best way to categorise them is across three levels of depth. The top line services are ones that any developer can use just like any other API, without being a machine learning expert. The next level down is a toolbox for creating your own custom models, which requires a little experience. And below that is the ability to deeply customise the frameworks and hardware to optimise the results for the experts.
Perhaps unsurprisingly, we're seeing an increased use of those high-level services. They provide off the shelf functionality without the need for a lot of configuration. They can be implemented and experimented with very quickly, and when you're ready for production they can accelerate and scale globally with you. An example of that was Qantas. As the national airline, Qantas was looking at how they could shift some parts of their business during the pandemic, and one of the opportunities that came up was their loyalty program. With lots of people suddenly unable to travel, they wanted to redirect their loyalty points for other things in the loyalty program. This also
created an increased opportunity for more abuse and fraud activity that Qantas needed to be able to mitigate. So they turned to the Amazon fraud detection service to implement an off the shelf solution. This allowed them to get the solution into market fast. We were able to help them customise it a bit and provide a framework for experimenting with other machine learning services.
Other businesses have already applied some intelligence to their applications, but they're constantly striving to deliver more results. So once they've gained some additional capabilities and seen the benefits, they often want to be able to take it to that next level. One of the ways to add more power is to leverage some of the powerful customisations. We're also seeing people that need something more and they create their own custom models using Deep Learning and SageMaker.
Ultimately, they want to be able to provide much richer opportunities for their customers that enables them to create personal experience that differentiates them from their competitors. An example of this is a popular e-commerce provider within Australia. They already took advantage of intelligent search engine capabilities and recommendation engine opportunities in their platform. They were recognising that because of the large number of products that were coming from third-party vendors, that they were struggling to provide the best user experience. That required them to work with a custom model that improved the metadata around their product catalogue. It provided an
automatic classification system to put products in the right categories based off of their metadata, which also improved their search results. The third and final theme is building in the open. We've seen an increased amount of open source technology being applied. Also new capabilities, such as 3D printing have really shown that people can do things on their own.
The decentralisation in both technology and information has also been a different model to build on. The first part of that is being able to collaborate globally from day one. There's an old adage that many hands make light work. We've seen that
when people or companies are collaborating together on a piece of technology, they're able to significantly reduce the amount of individual effort and still see the mutual benefits. When you have developed a community around an open source project, you have people that are contributing fixes and enhancements to the technology that you haven't had to directly build yourself, which lowers the effort to grow and maintain that software. It's allowing customers to move at a much faster pace. Sometimes the concern is that by having to deal with a large amount of collaboration overhead and the initial setup time, that it's slower. However, it's a principle we see play out regularly where we need to go slow at the beginning to allow us to move much faster down the line. Sometimes you take the lead with open source, and other times you're able to benefit from following. Both get you
further and faster. Open source projects have the benefit of a global scale. Not only does this magnify the impact, but a diverse number of perspectives helps create a better outcome for everyone. One of the most interesting examples of that was a project from Telstra. Telstra is a very well-known brand in Australia. As a telecommunications business, they're responsible for all sorts of different infrastructure and customer services. Most people would
probably have never thought of Telstra as an open source software provider. Telstra recognise the problem of digital accessibility for the 2.3 million Australians with low English literacy and non-English speaking. These
people have a barrier to interacting online with Telstra and many other organisations. They worked to develop a solution that allowed any web form to be automatically converted to somebody's native language and vice versa to allow interacting with someone's voice. After working through a pilot, we will be investigating open sourcing this project.
This is not the first open source project for Telstra though. Not only does that create a much bigger impact for accessibility across the web, but it also allows a global audience to be crowdsourced that is likely bigger than Telstra would be able to create easily on their own. Using Open Source has traditionally been a do it yourself situation, which requires technical skills, can be tough to get started, and scaling up your own solutions takes time and resources. Managed Open Source
seeks to reduce these barriers to entry. And an increase in offerings around managed open source has democratised the use of this software beyond developers. This allows people to experiment very quickly. You can implement at a much faster pace and, ultimately, if that is wildly successful, you can scale it up at a global scale with relative ease. A technology that
many people are watching and may feel like a solution looking for a problem is Blockchain. Different things can be built on Blockchain, but it can be confusing to get started if you don't want to get into the details. Amazon Managed Blockchain is a fully managed service that allows anybody to create an entire Blockchain network based on hyper ledger or Ethereum, instantly. There's also the Amazon Quantum Ledger Database or QLDB. This provides
a transparent, immutable and cryptographically verifiable transaction log. We've seen several Australian financial institutions with problems in the space, and they're currently building solutions with these services. Another example is the recent explosion in our community for non-fungible tokens or NFTs, that are rapidly changing the way digital art is being purchased. This distributed way of
handling lineage details is really game-changing. So if we take a step back a little bit and look at what is common to all of these projects, I want to call out a couple of things that were notably important. One of the first things was being able to challenge our assumptions, keep an open mind. Often the
businesses we were working with really had to disrupt their thinking and having an open mind really allowed their flexibility and creativity. Having great communications is also critical. One of the quotes, in particular from the National Basketball League, mentioned specifically how important it was to have open and frequent communications. We also saw that having a sense of urgency and being able to time box the efforts helps create a focus point for everybody to make progress in a very meaningful way in a short period of time. Things don't always go to plan and pivoting when something isn't working is really important. You want
people to invest your resources wisely and chasing a broken solution is wasteful. When we change the solution, that should be embraced and celebrated. It just allows us to focus on the best option for addressing a problem. One of the most important things that we have seen is having a supportive and engaged sponsor. Having a strong business mandate and top level buy-in to make these changes is really critical across the board.
When applying emerging technologies to your own projects, there are a few principles from prototyping that you might find useful. The first thing to point out for you is it's really important to start with a business problem and work backwards from your customer, rather than coming in with a particular presupposed solution. We want to avoid looking to change things for change sake. Use the business problem as your North Star and your customers as the best way to identify whether something is valuable to implement. The second principle is being able to determine the highest risk in the implementation and then experiment to de-risk. It can sometimes be hard to identify the risk at the beginning, but ask yourself the question: what's one thing, that if I knew now, I would be more confident to progress with this project and commit more resources? That'll lead you to identify what are some of the biggest risks in the project and how you can consider adapting them.
Usually, the best way to de-risk something is to build something and test that assumption, or test whether or not that risk is even a legitimate one. So do not over-index on building your complete vision. You want to find the thing that's the smallest thing to build and still allows you to validate the feasibility and to test the assumptions that you're trying to get. Number 4 is being able to rely on honest data to determine your next step. It's really easy sometimes to retroactively apply a story to data or to look only for results that confirms your initial hypothesis. By making sure that you stay focused on the business problem and identify metrics up front, you can minimise bias from creeping into the analysis of your data.
Just try to objectively follow the data when you're making decisions about how to move forward. One of the things that we do is use mechanisms to prevent narrow thinking. We have a mechanism that helps us to document and articulate both the problem and a specific measure of success that we're looking to improve at the beginning of any prototype. By focusing on the problem, we don't let our thinking can get overly distracted by a particular form of the solution or particular technology that we're trying to implement. And then lastly, look to leverage reusable patterns and frameworks that will increase your velocity. Whether
these are reusable deployment pipelines or front end templates, any of those kinds of things will allow your work to move faster without dropping the high standards of quality. If you want to learn more, there are many accessible ways to up-skill and get hands-on with the technology. If I can leave you with one final point.
Ultimately, change is our opportunity. Working in prototyping can be exciting to work on big problems with customers, but there is nothing secret or unique to us. Customers turn to us to unblock their incredible visions. Often what amazes me most though, is what other people are doing on their own. I hope what I've covered today gives you a few ideas and I'm very excited to see how you're going to apply emerging technology in your next big idea. Thank you so much for your time today. If you liked
the session, please take a second to complete the survey. I really appreciate any feedback you can give to help make these sessions more useful for you.
2022-01-09