Where is enterprise software development headed?


Today, predicting the future of enterprise software development is a complicated task. Especially, with technologies changing so rapidly. But still, there are some trends that show us in which direction everything is headed. One element that shapes enterprise software development at the moment is Artificial Intelligence. The value of the AI industry will be valued at around 30 billion dollars by the year 2025 (or even sooner) as some experts predict. In 2016, the industry was evaluated at 600 million dollars, so the increase is exponential. This fact should make software development companies think twice about their future investments.

Of course, the list doesn’t stop there. The software development industry will also be governed by cloud computing strategies, and the boom of IoT devices and automation. Besides these changes (that are more on the technical side), developers want to reach a higher level of personalization for the services and products they launch. The track of enterprise software development is dictated by the advancements in terms of tech. Here’s what to expect in one year from today:

Cybersecurity concerns and AI adoption in business

According to the second annual survey that Deloitte carried in 2018 on the state of Artificial Intelligence in the business industry, people still have a lot of concerns about the use of a new technology in business. Because AI is closely connected to where software development is headed, learning more about the risks of using this technology became a priority to most companies that are trying to make a change in their way of handling processes. The number one concern (also considered an obstacle) is represented by cybersecurity vulnerabilities. The survey showed that the industries that have decided to rely on AI or to at least adopt it in the upcoming years are:

Enterprise software development – 59%

Cloud technology – 49%

Open-source development tools - 49%

Machine Learning – 46%

Crowdsource development – 39%

The use of algorithms: RPA and BPM

Robotic Process Automation (RPA) differs from Business Process Management (BPM) and both seem to be developing at a fast pace. Even so, BPM may be more suitable for some companies (especially the ones that are more complex), due to their specifics. RPA relies on software technology, while BPM relies on holistic technology (the range of tech components is wider in this case, as it includes both business analytics and business process optimization). RPA is a smart choice for companies that involve monotonous, repetitive tasks that – when automation is not present – must be handled by human employees.

This leads to high production costs and time waste. RPA relies on algorithms with the sole purpose of minimizing manual, rule-based task that doesn’t require decision making. BPA is oriented towards re-engineering process flows entirely, as well as increasing productivity among employees at an enterprise level. One of the differences that make entrepreneurs choose RPA over BPM is represented by how disruptive each of them is. For instance, RPA is less disruptive because it works with the processes that already exist within a business, while BPM requires long-term efforts and dedication, thus disrupting the business industry considerably. Adopting RPA doesn’t require much knowledge in terms of technology, which means that all enterprises can use it without second thoughts.

Domain-specific tools

Any enterprise software development company tries to come up with products that solve the issues that entrepreneurs encounter when handling the workload of their firms. These products are expected to encompass multiple options, to give business owners the chance to control most of their business processes within one single platform. Even though such a product seems convenient, it’s not the best choice and it doesn’t define the path of future software development. Instead, they are trying their best to come up with products that are specific for one domain only.

Large-scale integration can’t be done conveniently at the moment, but software development companies work on finding lightweight solutions to integrate all software tools in an easier manner that won’t require as many resources. This should encourage more and more enterprises out there to adopt technology in one form or another. The value stream mapping of software development companies did suffer some changes in the past couple of years, but the best ones are just around the corner. The focus falls on better visibility, software programs that are easier to track, as well as offering entrepreneurs and their employees more control over how they deliver products and services.

What is happening to testing?

The past years were all about Agile and DevOps and the manner in which they shaped software development teams. 2019 will be all about what changes testing teams will have to undergo. Today, testing is mostly about performing tests manually and using tools (that oftentimes fail). Luckily, enterprise software development is going to shift from manual testing to automated testing. Even though developers witnessed some failures from Selenium or JUnit, searching for one defect and fixing it manually is much better than doing the whole process by hand. It takes less time and it comes with a series of benefits that can’t be ignored for sure. Traceability becomes an essential part of testing as well. Why? Tech integration will soon become mainstream and failure can no longer be admitted into the scheme. Thanks to organizational investments in improving their testing operations, the risk profile should be less scary in the following year.

Continuous Integration and Deployment**

Development teams adopting Continuous Integration practices can integrate and adapt codes inside an archive multiple times a day, and a predefined software component tracks all check-ins, allowing development teams to detect potential problems in the nick of time. Continuous Integration works with the source code that has been added to the version control system. In the past, most development teams relied on daily builds, which was not very effective. Now, these compilations take place several times a day and with every significant change. This helps developers get constant feedback on the software (which is a requirement today) and manage problems easier.