Here, Stuart Arthur shares his thoughts on what data and transformation digital mean to him.
The actual dictionary definition of digital is likely to refer to the storage and consumption of information involving electronic devices. However, in the world we live in today this has greatly evolved and now needs more explanation.
For me, digital means end-to-end customer centric solutions that are typically consumed online.
I instantly think about user research, user experience, web development, and also mobile consumption. When organisations talk about digital transformation, it generally means replacing heavily manual, physical processes with online solutions. That said, we're increasingly moving past these fields and into the realms of culture, redesigning processes, automation, and intelligence.
Is it IT, or is it digital?
For me, this conversation raises the question of how terms like IT, technology, and engineering compare to digital.
Unlike 'digital', which focuses on the customer, IT transformations, in the traditional sense, have been less about the external customer and more about the internal organisation - optimising internal systems, software, and data.
Yet although they might often be mistakenly treated as silos, digital and IT transformations actually depend on each other. It is technologies like Cloud, RPA, and AI/Ml which offer the capabilities to markets, organisations, and people that can enable digital transformations to succeed.
(For what it's worth, engineering — in my view — is more about problem solving and engaging skilled professionals to build software solutions, typically as part of an agile process.)
What really matters is transformation
I’m not really much of a fan of the term digital or digital transformation, which has been really overused and misused.
In my mind, true transformation is really about legacy organisations solving key technology challenges. For example, it’s about unpicking the fact that technology has enforced and constrained certain ways of working and is prohibiting change and progress; it’s about the fast pace of change and competing with the speed digital native competitors can move at without any baggage, and it’s about trying to adopt new technologies that open up possibilities. These are the challenges we should be focusing on.
Focus on the trends
Regardless of how we define IT, digital, and technology, some of the current trends I’m seeing and thinking about are the possibility of AI to eat software (just as software ate the world) as we’re seeing more and more aspects of the creation process becoming automated.
Then there’s no/low-code, and how long it will take before the only code being written by software engineers is for these new platforms. It’s a real possibility over the coming years as those technologies start to mature and evolve further.
The other thing that keeps me up at night is always software quality. There are lots of examples of poor software quality causing major issues for organisations and individuals, and if we don’t start to regulate ourselves as software engineers then we will eventually be regulated by the government, I have no doubt about that.
What we do is no less important than legal or other heavily governed professions and this makes things like code quality, good design principles, automated testing, and maintainability all the more important. Due to the importance of software, there’s also an argument that we should sign up to an ethical code of conduct in much the same way a barrister would have to.
The future of software
More immediate things on the agenda are advances in cloud technologies that mean greater focus can be placed on building software rather than worrying about infrastructure or security, which has been taken a step further with serverless capabilities. The major hyperscale cloud vendors have become so all-encompassing in terms of capabilities that you rarely have to look outside of the AWS, Google Cloud or Azure platforms to build anything. This in turn is creating a trend where companies no longer need to buy monolith platforms, middlewares, or use third-party RPA or AI/ML solutions. It's a win-win, since managing Microsoft, Google or Amazon is a lot easier for customers than managing a myriad of suppliers, and it also simplifies the complexity of a typical enterprise IT estate.
Design and architecture patterns are also maturing and attempting to build complex data lakes has long been a pain point for organisations, so it’s promising to see that domain-driven design principles are being applied in that space with the emergence of the data mesh pattern, dovetailing nicely with the small bounded services that are now increasingly popular — subject to context — in terms of backend services. This feels like a big opportunity to build more effective enterprise-wide data solutions in a more decentralised style.
A final word on digital...
There’s obviously a lot to cover here, and 'digital' also has its critics. But for me the negative connotations I associate with the digital moniker are amateurs knocking up WordPress websites or unreliable mobile apps as opposed to building well tested and coded deep technology solutions. This should be the focus of everything that comes under the IT, digital, technology and engineering umbrella so that we are equipped to meet the fast pace of change and respond to organisational challenges.
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