Industry 4.0, cloud, edge computing quantum computing, blockchain, the IoT, AR/VR are all buzzwords that were used repeatedly in 2019 when referring to digital transformation.
But what does it all really mean, and what does the future hold for digital transformation in 2020 and beyond?
To help you navigate this ever-evolving industry, we’ve gathered what we feel are the most essential trends that organisations will face in the coming year. All the trends we’re suggesting have a bearing on people, as we believe that people will be of utmost importance in the coming year.
Today’s evolving consumer landscape puts organisations under constant pressure to innovate, making digital transformation a top priority for businesses. True digital transformation though, requires a lot more than implementing a new website or mobile strategy. It’s the execution of a broad programme of initiatives from adopting a flexible, secure IT infrastructure, to mastering the use of data, implementing intelligent, automated workflows as well as training programmes that focus on digital competencies. It also involves the use of flexible talent models to rapidly access in-demand skills, enabling businesses to deliver a seamless customer experience.
But the people element of digital transformation is probably just as, if not more important than the technology perspective. Finding the right people who can automate your IT environment in such a way that allows for efficient and safe application deployment is crucial.
We foresee people at the front of all initiatives while more and more companies realise that technology comes after people. Without their acceptance, the technology goes nowhere, no matter how good it is.
We expect to see a continued focus on security, personal information and wellbeing. There will be a greater awareness and realisation of the impact of what we are doing and how we are doing it, along with the effect we are having on our environment.
Pushback on Novelty Innovation
Businesses of all sizes have begun to confuse novelty for innovation. Innovation inspires change, whether that’s changing your offering, expectations or the entire game. The only benefit novelty offers is newness, for example, the ability to unlock your car and turn it on with the push of a button on your mobile phone.
Whether it’s incremental or disruptive, innovation has to be relevant, and rooted in the core competencies of an organisation. This is how businesses can ultimately maintain a competitive advantage. After the hype of bitcoin, the general public have become callous to the technological hype and are more sceptical of the potential. This will continue in 2020.
More “Smart” things
The trend is already on the up and will continue to do so. Smart shelves, speakers, lights, toasters. Some will be a novelty and die out, some may turn into valuable additions to our day to day lives.
As with everything, people will decide what they find useful and what’s just fuelled by marketing or hype. If something doesn’t make your life easier or offer added value, then it won’t get used. If it doesn’t get used, it will get forgotten about and essentially deteriorate the credibility of that product and brand.
Voice is the new interface that surrounds us in many places, and in many ways. 2019 saw the uptake of voice interfaces from Google’s Assistant to Amazon’s Alexa. Siri failed to be truly any good and people lost faith in it, the second movers in the market have since seized the opportunity of where it went wrong for Siri, and have capitalised on the advances in technology.
Voice interfaces and their uses are driven by consumer need, but research is of significant importance. You need to understand and research how consumers interact with brands, what they need to know from these brands, and whether / if voice is a suitable way to deliver. But some of the most effective voice applications today are news, information-retrieval Q&As or games.
The minority report is here. With the new radar features in some phones, we can now wave at them to interact. They have become spatially aware. This has the potential to become a bit of a fad, however, we think that it is a space to watch as there could be some really interesting uses of these new sensors that had not been thought of previously.
Take the challenge of using mobile devices in construction and manufacturing. This can be a barrier to use with protective clothing, for example, gloves getting in the way or the inability to pick up the device. Being able to gesture at the device opens up new possibilities. The concept could be extended to take into account head movements or even combined with computer vision to enable deeper and more complex interactions. New sensors or features in mobile devices, always spark off completely new ways of looking at things and this is definitely a space to watch.
For tech companies that rely on sophisticated engineering, staying ahead of the game appears to get harder every day. We anticipate the realisation that commoditization is happening faster. It took a while for content management systems to commoditise the website management market, the same could be said for customer relationship management systems. Custom versions are still viable in some instances but for the majority, the commoditised implementations are just fine. More advanced technologies will become commoditized and we are already seeing this with Machine Learning and we feel this will not be slowing down anytime soon.
A native Mobile app, maybe you don’t need one of those?
Maybe, maybe not. Moreso maybe not. On the face of it, this seems very controversial for a tech company, doesn’t it? Native apps aren’t cheap to build and maintain, and unless there is a really good reason to build one, you may be going down the wrong path. Of course, there are native apps that work very well, but it’s also the case that many apps out there simply disappoint.
In a wave of excitement and enthusiasm, an app is created, but what results is that users don’t come, or those that do, don’t stick around for long. We have come full circle and back to web technologies, just how Apple envisaged it in the first generation of the iPhone. The dawn of the PWA is upon us. We need to realise that often doing the simple things well, greatly increases our chances of success.
A move to profitability over hyper growth at all costs
This is aimed squarely at the tech startup scene. Investors have already begun to shift their mindset away from hyper-growth with insane valuations that are hard, if not impossible, to truly quantify.
The old adage of what goes up must come down and what goes up faster comes down faster. This hype will have a wider impact on the tech community. Looking beyond 2020, this could be the start of the long term trend. When the hype subsides, the large investments and excess money causes there to be less direct investment in the people needed to grow the companies. This then has a knock-on effect on the wider industry, releasing experienced people into the market to do great things away from the hyper start up market and impacting the “skills shortage” as a result.
The realisation that 100 people don’t always go faster than 10 in tech. We have often wondered what so many developers do in some startups.
The “AI” Boom
2020 will be the year of machine learning (ML) or what the marketeers call AI. AI has been one of the fastest moving, but least predictable industries in recent years, but we are specifically calling out ML, as this is an area that can be realised by many in most areas over true AI. Machine Learning has seen rapid growth in adoption in the last few years, and is now visibly deployed in industries ranging from finance to healthcare and even retail for uses including customer service and security.
We said last year that we would see more assisted tools in traditional tools. Even tools that are really just “CRUD” apps (such as CRM’s), have seen machine learning being injected into them and we anticipate that this will continue.
The world has begun to see that ML is not just about replacing manual tasks, but enhancing and adding value to the work we do and reducing human inadequacies, such as not spotting the gorilla in the room or even that missed comma. ML can help us live more productive lives - but only if we know how to harness its power. Rather than trying to encode machines with everything they need to know to start with, we want to enable them to learn, and then to learn how to learn.
Rather than big swooping ML innovations, we expect to see a higher number of smaller additions contributing marginal gains that extrapolate out over the days, weeks and years.
We expect to see more and more unobtrusive extensions such as GMails suggestions, where it will preempt what you are about to type and mobile devices learning which apps you will want at the time you want them.