Transforming from geek-only activity in the 1980s, to high-demand, high-salary jobs paving the way for a digital age, programming and coding have evolved over the years from a niche interest to a core business driver. Just as the technology caused a boom in elite IT skills with complex technologies, it’s also gone on to open up the field with simplified ones too.
Alan Jacobson is Chief Data and Analytic Officer at Alteryx.
In the last 100 years, technology has progressed beyond all recognition – from the mass production of the first car, to the ultra-efficient electric vehicles of today, and from the first plugboard or control panel coding to the Raspberry Pi and Bloxels initiatives to enable children to develop applications and games. The accessibility and availability of previously inaccessible technologies means that people of all ages and capabilities can achieve high impact success.
Despite many of the leading companies in the world recognizing that digital transformation is key to success in today’s economy, organizations are burdened by outdated tools and processes unable to improve business operations and outcomes. They are still entirely reliant on the code-heavy technologies of the past, and all the limitations said technologies bring. For these businesses, delivering insights at the speed of business has become increasingly difficult.
Driven by the competitive demand for automation and new applications vital for aspects of the transformation process, businesses using traditional software are simply unable to keep up. Hindered by a massive skill supply and demand skew, the demand for coding and programming skills currently far outstrips the requirement for these skills to compensate for outdated systems.
Code-friendly
Coding itself will remain irreplaceable. The ability to commune with technology in a chosen formal coding language to deliver outputs far beyond any consumer GUI will always be a highly in-demand skillset. As with the demand for cars over the last century, however, we now have the ability to ‘mass-produce’ similar outputs that programmers can deliver through upskilling employees with low-code systems - building an internal pool of talented employees with the skills, desire, knowledge, and analytical viewpoint to be successful and thrive in an increasingly ‘data-rich’ environment.
Gone are the days when coding was only for programmers. Development has become so accessible that anyone can design and create a game, application, or website without ever having to write a single line of code.
Advances in technologies are enabling businesses to exploit easy to use no-code and code-friendly platforms that help upskill workers so they can develop apps to answer questions and deliver insights at the speed required to thrive. Gartner recently predicted that by 2024, low-code application development will be responsible for more than 65% of application development activity. As the opportunity to develop applications outside the silo of the IT department continues, non-programmers who understand the business problem are increasingly empowered to be the ones who help solve it by developing business workflow applications.
Forrester analysts estimate 75% of all enterprise software will be built with low-code technology in 2021 alone. No-code and code-friendly platforms are also instrumental to organizations in delivering broader and a more sophisticated range of analytics capabilities, enabling data scientists to collaborate with non-coding stake holders in a code-friendly and code-free environment.
Coding is the digital crossbow
If we take a step back in time, analytics required skills like coding in R or other languages in order to build out predictive models - skills that the average individual didn’t and still doesn’t traditionally possess. With coding taking days or weeks, departments had to wait in the queue for a solution. With the advancement of code-free platforms, the analytical and development capabilities can be put in the hands of the business experts who have the context of the questions to solve, the data sources needed to deliver insights and, with the right analytic platform, the ability to develop apps that deliver speed to insight. Thereby, increasing overall productivity and efficiency.
Now effectively serving as the backbone for many corporate development projects, the no-code movement is the technological equivalent to the crossbow replacing the longbow in medieval armies. Whereas the longbow - a staple of the tech-stack in the 1300s - took years to learn to use... discounting the physical training, and mental acumen to needed to fully utilize it, the crossbow could be picked up by an untrained peasant and used within five minutes to great effect.
While the modern digital first workforce doesn’t need a crossbow to succeed, by providing technology solutions that help upskill workers, they can – individually and collectively – help drive organizational transformation. Businesses are effectively building their own internal pool of talented developers with the data literacy, skills, desire, knowledge, and analytical expertise to be successful and thrive in an increasingly ‘data-rich’ environment.
Data science and application development agility
The same platforms are also making technologies such as Machine Leaning (ML) and Artificial Intelligence (AI) more accessible and agile. No longer the exclusive domain of the data scientist, ML and AI can now be implemented quickly and typically cost much less than bespoke systems developed by coding specialists that can take and enormous amount of time to evolve. By using easy-to-use point-and-click or pull-down menu interfaces, users can start at a high level right away, without the need of years-long experience. Usually through libraries of building blocks to design and implement their individual or departmental systems, everyone can contribute and collaborate in the same platform, without coding experience, using simple drag-and-drop steps and deliver results in a few hours.
While developers and data scientists are always going to be in high demand, the overarching goal of these initiatives is to make data science and application development more accessible to the business analysts and domain experts who increasingly need to collaborate with larger teams who typically don’t have a lot of industry domain knowledge. These platforms allow the user to either develop technical proficiency through using code-friendly interfaces or opt for the drag-and-drop option which is entirely code-free and the way the majority of users approach computing.
The significance of these no-code, code-friendly self-service platforms is that they allow organizations to keep up with the innovation of the open-source world while expanding the reach of development to wider teams. As long as the technology infrastructure runs in this way there will always be a need for coders, programmers, and systems architects to code and monitor the thousands of applications and algorithms helping to make the digital decisions for the business. However, many organizations have previously been obsessed with hiring just for these specific and rare digital skills without considering what is truly needed to make it work for their business needs.
While the maintenance and broader system development is a job for the technical experts, application development doesn’t have to be the preserve of an elite few. With the right self-service platforms combined with a culture where people are encouraged to be creative and think critically, ask the right questions and solve all sorts of problems, the power of business application development is no longer restricted to a few gatekeepers, but rather it is available to all.
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