Software developers have been one of the most challenging jobs to fill in the US for nearly ten years, so it’s no wonder the developer shortage is on the rise, with new figures showing a 35% shortfall for 2025.
With analysts predicting that as much as 90% of organizations will digitize and implement robotic process automation (RPA) by the end of 2022, this talent gap can significantly impact operational efforts, hiring processes, and growth efforts across industries.
According to one study, it takes 50% longer to hire talent for tech positions than other positions and, on average, it takes 66 days to hire the right candidate.
IT leaders must figure out how to handle the challenges of developer talent to make sure their smart automation initiatives don’t stall or derail.
What are software developers and why is there a shortage?
Software developers are the brains behind computer programs and systems. In the field of intelligent automation, they integrate and manage capture solutions. The solution then gets business-critical data straight from customer communications. Automation then automatically classifies, extracts, validates, and directs business solutions.
Then another automation focuses on identifying, creating, and improving operational processes.
Most of his work is focused on writing code and monitoring and monitoring systems and applications.
Business leadership and knowledge workers depend on the work software engineers do to access the vast amounts of data within content and processes so they can discover patterns and insights that can improve customer experiences and better business outcomes.
Technology is constantly evolving, which generally leads to higher demand for software developers, but there is currently not enough talent.
the widely reported The software developer shortage has a considerable impact on businesses, ranging from overwhelming workloads and stopping innovation to not keeping up with the competition.
Additionally, building smart automation projects takes time, often from several months to more than a year. While it varies by workflow and business process complexity, the time it takes to build and monitor after deployment can consume resources.
A telecommunications company that we recently got engaged with had 80 bots running continuously, with 45 people managing them. It’s quite possible to narrow that down to just one person.
Automating the automated
Learning to code is similar to learning new languages, but what if you could add code within the company as quick and easy as adding a skill to Alexa to turn on the lights? What if your automation could create and enhance other automation?
RPA bots might be the best area to start with this concept, but automation automation can be applied to just about anything.
For example, automatically capturing, classifying, and distributing customer content during account onboarding or opening ensures there are no errors. Consider verifying data, making it available for business processes.
We’ve heard of building code that you can code, and the same concept could apply to automation that can monitor, understand, and create other automation within a business process.
Then imagine going one step further and implementing self healing automation. Once you create automation, you can continually monitor it to see how it works with process intelligence.
If it’s not working well, you can create alerts that take action and trigger another automation to fix the broken automation. Ultimately, I would make automation that can be repaired on its own.
The self-healing solution can create a cycle in which developers are no longer delegated to mundane tasks and have more time to use their creativity to identify new innovation opportunities within the company.
The future of developers demands a new strategy
Digital transformation has always focused on facilitating processes for the business side. IT professionals have been used to manage new and complex technologies and keep them running.
No, and low code
To address developer shortages and meet demands for innovation, leaders must turn to low-code and no-code (LCNC) platforms to make it easier for business users to become citizen developers and are empowered to rapidly design, train, and deploy skills. for intelligent automation platforms.
In fact, Gartner estimates that by 2024, 75% of large companies will have four or more low-code development tools for IT application development and citizen development initiatives.
A growing area within LCNC platforms is adding content intelligence skills to RPA.
Content intelligence skills are in addition to other automation platforms that allow you to understand, extract, and classify content without the need for a machine learning expert.
For example, an accounts payable analyst could add a previously trained invoice processing skill to allow the bot to read and understand fields within invoices. Furthermore, previously trained skills for different types of documents are now becoming easily accessible from digital marketplaces and can be trained and implemented in days or months.
Knowledge workers can be more hands-on with LCNC platforms and obtain information from documents to increase productivity and improve operational efficiency.
To illustrate this concept, imagine an office worker using copy and pasting from one document or system to another or clicking the same area on a screen dozens and perhaps even hundreds of times a day. Copying and pasting is a mundane, repetitive routine that is ready for mistakes.
Imagine that a message appears on the screen of a bot that recommends automating that task? Then an alert would tell the worker when a bottleneck occurs. When automation is on board, the bot will recommend a different workflow to avoid future delays or drift.
Automated automation and self-healing automation work in tandem to keep worker tasks and general business processes running efficiently.
Automation is generally implemented when the business user initiates the automation, not a developer.
As the developer shortage continues and organizations seek to maintain a competitive advantage in an ever-growing digital world, they must embrace more accessible and innovative ways to achieve intelligent automation.
Quickly adapt to digital transformation
Leveraging low-code / no-code platforms with the necessary cognitive skills will help you automate the automated and adapt quickly to meet the rapid and continuous changes in digital transformation.
Image Credit: Christina Wocintechchat; Unsplash; Thanks!