Software developers have been one of the hardest jobs to fill in the United States for nearly a decade, so it’s no surprise the shortage of developers is set to get worse, with new numbers showing a 35% deficit by 2025.
With analysts predicting that up to 90% of organizations will go digital and deploy robotic process automation (RPA) by the end of 2022, this talent gap can have a significant impact on operational efforts, workflows and processes. hiring and growth efforts across all sectors.
According to one study, it takes 50% longer to hire talent for technical positions than for other positions, and, on average, it takes 66 days to hire the right person.
IT managers need to figure out how to handle developer talent challenges to ensure their intelligent automation initiatives don’t get stuck or derailed.
What are software developers and why is there a shortage?
Software developers are the brains of computer programs and systems. In the field of intelligent automation, they integrate and manage capture solutions. The solution then obtains critical business data directly from customer communications. Automation classifies, extracts, validates and then automatically orients business solutions.
Further automation then focuses on identifying, creating, and improving business processes.
Most of their work focuses on writing code and monitoring and monitoring systems and applications.
Business executives and knowledge workers depend on the work of software engineers to gain access to the vast amounts of data contained in content and processes so that they can uncover patterns and insights that can improve the customer experience and better business results.
Technology is constantly changing, which usually leads to an increased demand for software developers, but currently there is not enough talent.
The widely reported shortage of software developers is having a huge impact on businesses, ranging from overwhelming workloads and halting innovation to not keeping pace with competitors.
Additionally, building smart automation projects takes time, often months to over a year. Although it varies depending on the workflow and the complexity of the business process, the time required for creation and post-implementation monitoring can consume a lot of resources.
A telecommunications company we recently engaged with had 80 bots running continuously, with 45 people managing them. It is entirely possible to reduce this to one person.
Learning to code is similar to learning new languages, but what if you could add code within the company as quickly and easily as adding a skill to Alexa to turn on the lights? What if your automation could create and enhance other automations?
RPA bots might be the best area to start with this concept, but automating automation can be applied to almost anything.
For example, the automatic capture, classification and distribution of customer content during onboarding or account opening ensures error-free. Think about verifying data, making it available to business processes.
We’ve heard of building code that can code, and the same concept could be applied to automation that can monitor, understand, and create other automation within a business process.
Then imagine going further and implementing self-healing automating. Once you’ve created the automation, you can continuously monitor it to see how it performs with process intelligence.
If it doesn’t work well, you can create alerts that take action and trigger another automation to fix the broken automation. Ultimately, you’d be making automation that can fix itself.
The self-healing solution can create a cycle where developers are no longer delegated to mundane tasks and have more time to use their creativity to identify new opportunities for innovation within the business.
The Future of Developers Demands a New Strategy
.Digital transformation has always focused on simplifying business processes. IT professionals have been used to manage complex new technologies and make them work.
No, and low code
To address the developer shortage while meeting the 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 empower themselves. be empowered to quickly design, train and deploy skills for intelligent automation platforms.
In fact, Gartner estimates that by 2024, 75% of large enterprises will have at least four 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 added to other automation platforms that allow it to understand, extract and classify content without the need for a machine learning expert.
For example, an accounts payable analyst can add a pre-trained invoice processing skill to enable the bot to read and understand invoice fields. Additionally, pre-trained skills for different document types are now becoming easily accessible from digital marketplaces and can be trained and deployed in days rather than months.
Knowledge workers can be more hands-on with LCNC platforms and gain insights from documents to increase productivity and improve operational efficiency.
To illustrate this concept, imagine an office worker who copy-and-pastes from one document or system to another or who clicks on the same area of a screen dozens or even hundreds of times a day. Copying and pasting is a repetitive and mundane routine prone to errors.
Imagine that a message appears on the screen from a bot that recommends automating this task? Then an alert would notify the worker when a bottleneck occurs. When automation is on board, the bot will recommend a different workflow to avoid future delays or deviations.
Automated automation and self-healing automation work in tandem to keep worker tasks and overall business processes running efficiently.
Automation is typically implemented when the business user initiates the automation, not a developer.
As the developer shortage continues and organizations seek to maintain a competitive edge in a growing digital world, they must embrace more accessible and innovative ways to achieve intelligent automation.
Adapt quickly to digital transformation
Leveraging low-code/no-code platforms with the necessary cognitive skills will help you automate automation and adapt quickly to meet the rapid and continuous changes of digital transformation.
Image Credit: Christina Wocintechchat; Unsplash; Thank you!