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Modern Enterprises Software Development Challenges

The constant evolution of technologies and industry standards makes it difficult to develop software.

The complexity of finding and paying for skilled development talent, the rapid pace of change, and the mounting pressure to accelerate digital transformation make organizations’ jobs challenging.

Let’s explore the biggest challenges facing software developers and how they can overcome them below.

1. Keeping up with the latest innovations

Digital transformation has been discussed for years, but many companies are still struggling to integrate 21st-century processes and systems.

The problem of outdated technology is immense:

  • Bad actors target legacy systems.
  • End-users cannot find information (and if they can, it’s often inaccurate).
  • Organizations lose money and time because of manual processes and poorly made decisions.
  • Organizations lose time and money due to manual processes and poor choices.

Remote working is at odds with on-premise hosting. In addition, poorly-managed datasets hide many missed opportunities.

According to McKinsey, 45% of digital transformation projects bring lower returns than expected. Digital transformation projects will likely deliver less profit than expected in 45% of cases.

A successful transformation initiative requires the following factors, according to the firm:

  • A clearly defined set of priorities linked to measurable business objectives
  • A mature approach to Agile development
  • Investing in the right talent – such as data science, analytics, cloud computing, and artificial intelligence or machine learning.

A Gartner analyst, Kristin Moyer raises a critical point in a recent interview.

It is important to distinguish between optimization and transformation when it comes to digital business. According to her, digital companies utilize technology to develop new products, business models, and operating models.

In optimization, you use technology to enhance customer engagement or sell more of your current product. “We use technology to do old things in new ways.”

There is no doubt that optimization is crucial, but it should be distinct from transformation.

According to Moyer, transformation is all about doing something new in a new way. This involves the use of technology to create and build new business models, revenue streams, and products that will change the way things are done.

True transformation can’t be achieved if you treat the two terms interchangeably.

You’ll also need to think long-term, beyond the initial transformation. For example, your strategy needs to consider how quantum computing might be incorporated into yours or how blockchain could be utilized.

2. Shift in culture

Despite the fact that technology is constantly changing, the biggest changes in software development have nothing to do with it.

More importantly, how teams function has changed.

As the world changes, today’s development teams must adjust quickly and focus on improving user experience and responding to customer demands instead of focusing solely on innovation.

It is a best practice that companies are now implementing to ensure their employees understand the software development world is changing rapidly. They must learn to adapt to the culture quickly and be more creative.

In essence, the dialogue becomes more about solving a high-stakes problem together.

One of the major challenges for software developers-and organizations, in general, is changing internal processes and eliminating silos. It is also one of the most important that new technology initiatives must be aligned with organizational culture.

Agile and DevOps practices cannot be applied effectively without alignment to develop data literacy and customer centricity throughout the organization.

In order to support cultural change, CIOs/CTOs need to work with HR to identify what technology investments and structural changes are required.

Afterward, develop a communication plan to persuade other stakeholders, such as department heads, to support new initiatives and overcome resistance.

It is also worth your time to recruit a small team to work on a pilot project demonstrating the benefits of cultural change with immediate wins affecting business processes and results.

3. Customer Experience

Eddy Vidal Nunez said it’s critical that companies “create a deep understanding of the market and the importance of CI/CD & its role in the customer experience.”

McKinsey says developing a data-driven strategy is key to the future of CX. The firm predicts that predictive analytics tools will make this process easier, but organizations must still determine what they need and build an extensive data ecosystem to store, secure, and surface insights to the right team at the right time, despite the rise of user-friendly predictive analytics tools.

In order to get started, you will need to address the following questions:

– What kind of information will you need to collect?
– Is that information yours, or will you have to invest in additional technology to gain access to it?
– If you own the required data, is it centralized?
– Could you verify the accuracy of this information?
– Which channels do you need to use for data collection?
– What is your plan to provide the development team with that information?
– What are the ways insights will be used to improve the experience?
– In what ways will you be able to measure the success of your efforts?

4. Privacy of data

As part of the development process, organizations should consider data privacy laws rather than leave them to the last minute.

This has always been important, but now it is more complex, and customers are becoming more conscious of how companies use their information.

Changing regulations with strict penalties for non-compliance presents one of the biggest challenges.

California just passed a law extending the protections outlined in the CCPA, and Europe’s GDPR has been in place for a few years. Several states have bills in the pipeline, including Virginia, which passed its legislation recently.

Organizations must ensure their applications can adapt as rules change, and new requirements are introduced, regardless of where their customers are located in Europe, CA, VA, etc.

According to Javier Trevino, at the beginning of any data privacy strategy should understand all the rules and regulations that apply to your particular industry. He said, “industry verticals will define how PII should be secured. There’s HIPAA in healthcare; for payments, there’s PCI DSS.”

Those needs should be addressed first. Otherwise, you might end up using workarounds that aren’t compliant.

Once you’ve selected a solution, you can focus on meeting the requirements. From there, you can create a plan which ensures complete transparency and tightly controlled data flows and includes data protections such as encryption and VPNs.

5. Cybersecurity

Cybercriminals are becoming increasingly sophisticated, gaining access to sensitive data such as HR records, IP, and consumer information as more and more organizations embrace IoT, data streaming, cloud-native apps, and remote work.

The situation could worsen soon.

A recent Forrester report predicted AI-powered hacking would become widely available shortly, though open-source AI projects have already made these tools widely available.

Cloud adoption and IoT have led to many unsecured endpoints and vulnerabilities that can only be detected by AI-enabled monitoring tools. With the arrival of 5G/WiFi 6, the challenge may become even more remarkable—since data streaming is expected to increase dramatically. When big data hits, organizations need to be prepared to deal with the big wave of data. Organizations already face tremendous challenges managing & securing their data.

Javier Trevino said, “static analysis tools should be executed against code bases to recognize any security vulnerabilities using standards outlined by The Open Web Application Security Project (OWASP).”

Identifying vulnerable areas and mapping out your threat surface will give you a starting point for tackling challenges one at a time.

6. AI and Automation

Across almost all industries, AI-enhanced software is the norm-from sales and marketing tools to logistics systems and supply chain management.

Several challenges arise when software developers try to implement AI and automation, including:

– Automating a process when it is appropriate.
– Effective methods for “power human augmentation.”
– Handling the many challenges associated with test automation.
– Changing the UI, handling multiple errors, and executing scripts.

Developing a strategy to overcome these issues will be the first step for organizations.

Furthermore, successful automation requires skilled resources, so you should not replace workers with robots. Instead, automation should be applied where workers lose time or where human error is more prevalent.

In addition, you should identify the right tool for the job. This means taking automation one step at a time by placing the tools that best address your hyper-specific needs rather than focusing on it as a broad, multi-process effort.

7. Data Literacy

The ability to extract and normalize data, analyze big data, and act on insights gained from big data was previously the domain of data scientists with advanced skills in SQL, R, Python, and big data analysis.

AI, ML, Natural Language Processing, and other technologies have made their way to the masses in recent years, becoming more affordable, accessible, and relatively user-friendly – being integrated into the apps we use daily.

Even though data scientists don’t have to run reports anymore, many organizations are still unsure of how to implement these tools and use AI-driven insights effectively. A Harvard Business Review study found that participants struggled not because they lacked technical expertise but because they lacked problem-solving skills.

Participants found it difficult to:

– Make the proper inquiries
– Recognize relevant information
– Validating data integrity
– Validate hypotheses

In order to improve end-user self-sufficiency and data-driven behavior, development teams and stakeholders should work together.

The ability to self-serve business intelligence tools, access AI-driven insights, and generate intuitive reports will help end-users quickly answer specific questions about their roles.

You’ll also want to ensure that problem-solving tactics and tools are keys to an organization-wide continuous training initiative that visualizes and helps you connect the dots. However, you’ll want to ensure that problem-solving tactics and tools are part of an organization-wide ongoing training initiative.

8. Cross-Platform Functionality

Nowadays, companies must provide customers with a seamless, unified experience across all platforms, channels, and devices.

Keeping consistency across all touchpoints and providing on-demand support wherever customers contact you is one of the biggest challenges facing software development teams.

An example shared by Abel Gonzalez Garcia from a past project he worked on. He said, “in one recent case, the application we tested was designed to work on different OTT platforms like Apple TV, Roku, Android TV, and Xbox Fire TV. This is a significant challenge, as we must have similar functionalities on all the platforms; however, the platform’s architecture often didn’t allow us to implement a few things, and we needed to figure out a workaround.”

9. Budgeting

In the wake of COVID shutdowns and a loss of business, many companies are working with smaller budgets than expected. Now, they’re pushed to figure out how to do “more” using a much lower budget.

Spending should be aligned with current priorities, even for organizations that have done relatively well.

After COVID, top-performing organizations are more likely to focus on new business priorities, according to Gartner. A CIO’s response should be to evaluate business cases to maximize investment returns and reallocate internal resources to prioritize digital innovation, according to analysts.

When you’re no longer renting office space, you can use the money you’ve saved to hire strategic employees, launch a product, or partner with an outsourcing company.

10. Talent

The issue of staffing is also a major one for organizations.

Due to the infamous IT skills shortage, many small and mid-size businesses compete for highly specialized, in-demand skills with multibillion-dollar companies like Amazon, Google, and Facebook. As a result, smaller firms will have to match the salaries and perks of giants to attract top US talent.

Regardless of whether they hire in-house or outsource talent, companies need to understand what they’re looking for.

IBM reports that most companies still focus solely on filling skills gaps related to hard skills like data science, AI/ML, cybersecurity, etc., instead of developing new ones.

The company needs people who can:

– Identify metrics to track performance and identify vulnerabilities in data ecosystems, including communication between applications, devices, and infrastructure.
– Ensuring data integrity, security, and knowledge sharing are maintained through policies and governance.

The soft skills you should possess are the ability to empathize, actively listen, communicate, solve problems, think creatively, and be adaptable.

In addition to training existing engineers and developers, organizations must also ensure a future-proof workforce. In order to make sure your team is up-to-date on the latest tools and tactics, you’ll need to rethink the entire training process and onboarding process.

While “hard skills” are also crucial, you can use outsourcing to fill gaps and give in-house talent ongoing training to ensure they maintain the skills aligned with your long-term goals.


In spite of the fact that it will be difficult to overcome today’s most prominent software development challenges, there is a silver lining: overlapping solutions.

A few key things need to be done for organizations to be successful, whether they want to enter new markets, stay ahead of emerging threats, or meet shifting consumer demands.

In order for these initiatives to succeed, the culture must support them. Across all functions, data literacy must be embedded. The entire data ecosystem of an organization needs to be fully transparent and controlled.

We at Obverse can help your organization tackle the broader industry and business-specific challenges outlined above.

Obverse Inc. is passionate about software development. But there’s more to our company, our Product Mindset makes us stand out. Contact us to learn more.