Developing an Enterprise Software Strategy

Whether software is your product or you’re looking to digitize your business to compete at speed and scale, you’ll need to come up with a comprehensive plan of attack.

Many enterprise software projects are poorly-planned, poorly-executed—or both. As a result, organizations end up with a system that’s overly complex, expensive to maintain, and, unfortunately, fails to hit the objectives outlined in the initial plan.

In this article, we’ll go over the core elements that every software development strategy must include to secure and maintain a competitive advantage.

Identify Opportunities for Improvement

Your enterprise software strategy begins with a clearly-defined use case.

Start out by identifying problems that need solving. What are you trying to achieve—and why?

This decision needs to be rooted in real data—think customer feedback channels, security logs, sales metrics, etc.

Once you’ve identified a problem (or several), you’ll also need to figure out how much it’ll cost, what problems you might encounter during development, implementation, and beyond, and get the rest of the organization on board with this decision.

A few things to consider at this stage:

  • New needs and opportunities. Are you having trouble keeping up with competitors? Are there customer needs you’re not currently meeting?
  • Potential risks. What risks might undermine your efforts? Consider how those risks might impact the overall strategy and individual roles. Eventually, you’ll need to create plans for mitigating and responding to each risk, and it’s better to have a sense of what you’re up against before the project gets underway.
  • Communicating value to different stakeholder groups. Consider how you’ll present this idea to the rest of the team. How does this initiative support marketing? How will you convince the CFO this project is good for the bottom line? This is important because it helps you secure buy-in from stakeholders. Later, it lays the foundation for the business requirements and documentation you’ll pass on to your development team.

Finally, it’s important that you also start looking toward the future early on.

Without a strong software development strategy in place, organizations often fail to consider the entire development lifecycle—particularly when it comes to long-term maintenance and upgrades.

Develop a plan for identifying and fixing problems. Having a plan in place will help you keep operational costs to a minimum and also help you identify future improvement opportunities.

Define How Software Projects Will Impact the Business

Your software development strategy should align with specific business outcomes, your current portfolio of services, and market requirements—aka what your customers want and your competitors don’t already provide.

Here are just some of the many (read: endless) ways that software can potentially impact your business:

  • Become more data-driven. The pressure is on for organizations to become more data-driven—at every level. Your enterprise software strategy might focus on building/obtaining AI-enabled BI and analytics tools that make insights accessible (and actionable) for different roles—marketing, accounting, IT, the C-suite, etc.It might also include improving data capture and processing solutions or building a unified data ecosystem that supports organization-wide data literacy with specific reporting tools that match different job descriptions.
  • Unlock new revenue streams. In some cases, investing in software development projects can help organizations create new revenue streams or break into new markets—that might mean building new features or applications that cater to a new audience or investing in more advanced data science solutions that help you understand and reach new potential customers.
  • Streamline internal processes. Companies might also invest in solutions like AI/ML automation, RPA, or IoT solutions that may not directly generate revenue right away but free up valuable time and resources so that their team can focus on core business activities.
  • Prepare for future disasters. For some companies, getting ready for the next big disaster might entail improving their ability to work remotely after dealing with the challenges brought on by COVID. That might mean building solutions focused on enabling access to files and specific data sets, eliminating silos, etc. Other organizations might opt to invest in better predictive tools that help them identify and prepare for potential threats well in advance so that when the next pandemic, natural disaster, or economic downturn hits, they’re already in the process of pivoting.
  • Improve cybersecurity. If you’re focused on improving cybersecurity, you might invest in apps that enable real-time monitoring and automate responses to known threats. You might also focus on automating penetration testing or implementing stronger protections for consumer data.

Whatever the use case, you’ll need to determine how it will improve your business in a measurable way.

Embrace the “as-a-Service” Mindset for Consumer Products

Flexible subscription models are attractive to customers for several reasons:

  • They’re not locked into a contract and can switch providers if they’re unhappy
  • The service provider is responsible for storage, infrastructure, and maintenance
  • They can pay for what they use—scaling up or down as needed

Because of these benefits, the SaaS model (and now, PaaS, IaaS, and so on) is now the default.

Consumers now expect to “subscribe” to software products and services, storage solutions, etc., as easily as the likes of Netflix or Amazon Prime.

But what does that actually mean for businesses?

On a basic level, adopting an “as-a-service” mindset means you’re competing with Amazon—at least when it comes to agility and user experience—regardless of what kind of resources you’re working with.

Organizations have an opportunity to win big by creating recurring revenue streams, as opposed to relying exclusively on one-off purchases.

But—you’ll need to keep working to earn customers’ business so that they don’t leave you for a competitor.

That means your enterprise application strategy needs to include a detailed plan for capturing feedback and using it to improve existing features and add new ones that support changing needs and objectives.

McKinsey analysts advise organizations to focus on digitizing their delivery model if they haven’t done so already.

The report breaks the “as-a-service” transformation strategy into four stages:

  • Product. This includes product management, as well as packaging and pricing. Here, you’ll need to come up with a compelling value proposition, then set pricing that aligns with the perceived value to customers.
  • Operating model. At this stage, you’re working out the logistics of bringing your idea to life. That means making sure you have the right talent to support the project—in development and after—across all functions—sales, service, IT, etc. It also involves ensuring your organization is structured in a way that balances core business goals with innovation and establishing metrics that give investors/finance a clear picture of where the money is going.
  • Getting to market. Next, you’ll need to figure out how you’ll handle deployment, develop a sales strategy to get early adopters on board and make sure your systems/IT are prepared to move to a subscription model.
  • Technology. Finally, you’ll need to make sure you have the right tools in place to provide support service, capture customer insights, and market your solution to prospective customers.

Figure Out Your Data Strategy

It doesn’t matter what you’re building; you’ll need to make sure that the end-product integrates with your entire data ecosystem. Otherwise, it won’t provide much value.

Start by identifying what data you need to collect in the first place.

According to Tiempo’s Angel Almada, “the most important aspect here is identifying what data you need to collect in order to achieve the desired outcome and measure the impact of your efforts.

Everything else is just plumbing (really complex plumbing) that needs to be configured so that you can get that data.”

Next, get a clear picture of what you’re working with:

  • Where are your digital assets currently stored?
  • Is there a centralized location for managing those assets?
  • How are those assets organized?
  • Are there uniform naming conventions in place?
  • Is it easy to find what you’re looking for?
  • Where are you running into problems?

From there, determine how you’ll manage your data. Note: this becomes increasingly important if you’re developing IoT or data streaming software that will bring in a ton of new data.

  • How will you manage data flows? Who needs access to specific data? What policies/controls need to be in place to control its movement?
  • Where will it be stored and how will it be secured? Are there any regulatory requirements you need to consider? Are you handling sensitive information or IP related to your core business?
  • Where will data be processed? In the cloud? At the edge? This decision will depend on whether you need true real-time insights (i.e., continuous uptime is required for safety reasons) or plan on applying insights from your desk—well after data has been captured, cleaned, and categorized (i.e., using customer data to create a digital advertising campaign).

Architecture and Culture Must Support Adaptability, Agility

Cloud is now standard—digital businesses need a flexible infrastructure capable of adapting to change. A “big design upfront” approach doesn’t support the level of adaptability required to compete in today’s fast moving business landscape—strategy should focus on moving fast.

Consider multi-cloud strategies—is there a need to store certain data in a private cloud?
Don’t forget that edge is on the horizon, too.

Even if you’re not quite ready to embrace edge computing, you’ll probably want to look ahead and consider how to incorporate it into a multi-cloud system down the line.

With 5G on the verge of going mainstream and a growing need to process more and more data at rapid speeds, you may be looking at edge providers sooner than you think.

It’s important to note that infrastructure is just one link in the “innovation chain,” a term that describes the layers of technology working together to reduce costs, speed delivery, and ultimately, drive transformation.

According to a recent report from Forrester, “innovation leaders” have a deeper understanding of customer needs, are more likely to invest in adaptive technology platforms, and embrace emerging tech solutions than their competitors.

Organizations can maximize their ROI by building a cohesive network from the ground up—from the physical layer to the technical infrastructure, and then the application layer where the transformation happens—embedding solutions like AI analytics, RPA, and IoT solutions throughout.

This adaptive technology approach also allows organizations to prepare for future transformations on multiple levels. For instance, sales and service teams can leverage real-time data to create a proactive retention strategy that anticipates evolving customer needs. Business leaders, on the other hand, benefit from improved visibility—enabling them to act on opportunities and avoid threats, generate accurate forecasts, and update the strategy as needed.

Development teams can rapidly deploy new solutions using customer feedback to guide the process.

Still, it’s important to note that none of this can happen without the right culture in place

Final Thoughts

Today’s businesses must be able to quickly adapt to changing circumstances and make accurate decisions in real-time—those who fail will, unfortunately, fall to fast-moving competitors better prepared to meet customer needs as they evolve and respond to crises without missing a beat.

To learn more about Tiempo’s services and how we can support your enterprise software strategy, contact an expert today.