But it’s a tough task to stay on top of trends and developments – things in the digital world evolve fast, and for software developers this means they face a raft of challenges, ones that will continue to test them in the coming years.
Here are the major challenges software developers face…
1. Keeping Up with Innovation
Digital transformation is an ongoing challenge, with many companies still relying on outdated technology as part of their overall systems architecture. Legacy issues mean that developing new software either has to be done so with retrospective compatibility in mind (a challenge in itself) which doesn’t really solve the long-term problem, or old systems need to be discarded, which has additional cost implications.
But companies need to recognise the long-term value of making wholesale changes (if needed) at the start of new software projects, and build with future-proofing in mind wherever possible to take into account developments such as quantum computing and blockchain technologies.
2. Cultural Change
One of the toughest things to change is mindset, and for organisations to move forward in an agile way, they need to have processes and structures that allow them to adapt to constant change, and develop with the end user in mind at all times – the goal needs to be to enhance the user experience and respond to customer needs.
Changing internal processes and eliminating silos is one of the biggest challenges for software developers. But it’s also one of the most important – in order to maximize the value of new tech initiatives, business culture needs to align with this strategy.
3. Customer Experience and Data Collection
At the heart of all development is the need for engineers to have a deep understanding of the market and the importance of Agile and Continuous Integration and Deployment in the customer experience.
Some questions software developers and teams need to ask include:
• What information do you need to collect?
• Do you currently own that information or will you need to invest in additional tech to gain access to that info?
• If you do own the necessary data, is it integrated into a centralized location?
• Can you verify its accuracy?
• What channels will you need to gather data from?
• How will you route that information back to the development team?
• How will insights be used to improve the experience?
• How will you know if your efforts were a success?
4. Data Privacy and keeping up with Regulatory Changes
Businesses need to factor data privacy laws into the ground-up development process rather than treating it as an afterthought.
The regulatory landscape is ever-changing and updating, and becoming more complex as customers are starting to become more and more sensitive to and about how companies use their information, and profit from it.
Constant updates and increasingly strict non-compliance penalties mean your team needs to be totally up to speed at all times, and build in checks and safeguards to ensure updates aren’t missed. In other words, develop a plan that ensures complete transparency, tightly-controlled data flows, and includes data protections like encryption, VPNs, and more.
As more businesses embrace the Internet of Things, data streaming, cloud-native apps, and remote working, the number of cyberattacks has dramatically increased.
Add to the mix the looming threat of AI-powered hacking though tools that are already widely available through open-source AI projects, and hugely enhanced data transfer opportunities with the impending arrival of Wifi 6 – the future of internet and data security is a veritable minefield!
Software engineers face the serious challenge of building systems that simultaneously exploit the advantages of new technologies but prevent attacks, negate vulnerabilities and update to recognise the latest threats all the time.
6. AI and Automation
AI-embedded software has fast become the default across a multitude of sectors and applications, from sales and marketing tech to logistics and supply chain management and automated production lines.
Implementing AI and automation presents challenges for software developers on multiple fronts, including:
•Determining when to automate a process.
•How to effectively “power human augmentation.”
•Navigating the many challenges of test automation.
•Handling UI changes, multiple error handling, script execution, etc.
For engineers the challenge is to develop a sound understanding of where AI needs to be implemented and to what end – the focus should be on applying automation in areas that waste workers’ time or are particularly vulnerable to human error.
7. Data Literacy
Big data poses numerous challenges for today’s software engineers – from understanding the architecture that gathers the data to knowing how to output that data in meaningful and accessible ways means having an understanding of the entire process.
Where in the past, highly-trained data analysts would tackle much of the above tasks, today’s engineers need to have a similar grasp of the requirements in order to build integrated systems that deliver meaningful results to demanding end users.
Development teams and analysts need to work together to develop solutions that enable end-users to become more data-driven and self-sufficient.
8. Cross-Platform Functionality
The process was already underway before Covid-19, but the pandemic accelerated the pace at which systems now need to offer seamless, end-user focussed cross-platform experiences across all platforms, channels, and devices.
One of the biggest challenges facing software development teams is the increasing need to develop systems that offer this seamless experience but also maintain consistency in tone, user experience, messaging and design across all touchpoints.
In summary, being a software engineer has always been a challenging role – the future requires the same innovative, problem-solving approach that has always been required… it’s just going to be even more demanding!
Find out more about Realnet’s custom software design capabilities. Call us today on 01223 550800 or email firstname.lastname@example.org.