Author: Brandon Powell

If there is one constant in the world—especially in the digital age—it’s that software development departments live in a never-ending struggle of demand vs. resources.

As data continues to be the gold standard of business success, software and its resulting analytics and business intelligence applications all collide. More so, the desire to also meet and exceed the expectations of end users, all while continually evolving this new data-driven environment, means that talent is stretched on the best of days. So why is that? Is it due to a lack of qualified people? A lack of specific expertise? Or is it a matter of companies struggling to offer its talent pool meaningful projects? The answer to all these questions is yes.

First, let’s look at the perceived lack of qualified people. For many organizations, especially in the pre-COVID era, the idea that talent must be located within one’s own backyard is luckily a fading memory. The idea that anyone can rely entirely on backyard resources in 2021 is downright impossible. The talent and expertise required for modern digital initiatives literally takes a world of people to address. It’s for these reasons alone that remote workers—and the talent that remote work makes available—are indispensable.

Moreover, the opportunity for organizations to partner with companies offering comprehensive nearshore talent often makes for the best of all worlds. Timezone matching aside, cultural and linguistic alignments make for greater talent, less expensive investments, and better results.

Then, of course, there is the expertise issue. Having a robust stable of internal talent is always a good thing. However, the complexity of modern enterprise software is often too much to keep up with. Again, I go back to the data and business intelligence aspect of modernity. Regardless of infrastructure—from cloud storage, to data center technology, IoT, to customer engagement systems and more—every one of these requires specialization. From AI and machine learning, to data and analytics—all of these necessitate expertise that often become too big of a requirement to be able to consistently staff internally.

Again, this is where partnering with external experts can save the day. They can provide the talent when and where required—without the burden of quadrupling internal hiring on a yearly basis—to keep pace with modern requirements.

Lastly, at least for this article, there is the reality that good talent is hard to keep. The fact of the matter remains that we live in a talent-rich economy—one that rightfully caters to those who have expertise. This means that in 2021, employers no longer call the proverbial shots—rather, talent decides which companies are worthy of their presence and dedication.

Enterprise environments—ones that by nature must move slowly and carefully, so as not to disrupt legacy systems and architectures—often find themselves in a precarious position. The talent they have and must retain are those embedded in the legacy aspects of the organization. As such, those employees’ expertise are highly valuable and required, but simultaneously they too cannot be all things to all people. These employees often lack the skill-sets required for highly modernized projects.

This leads to a secondary issue: those same slow-moving enterprise environments do not necessarily attract experts looking for leading-edge work. People in the software development space often dream of the “new,” while shying away for the legacy application world. With enterprise departments firmly rooted in the “slow and steady,” attracting and maintaining new talent is often difficult.

Not to sound like a broken record, but again, the outsourced talent scenario is the best of all worlds. Enterprise environments can maintain their current workforce, ensuring they are happy and working on what they know best, while simultaneously working with top talent in other fields of expertise to move the company forward.

Software development teams can’t be all things to all people, nor can they possibly meet every demand. They can, however, be augmented with external team members to achieve new goals and new heights, all while reducing the stress of trying to be superheroes every minute of every day.

Whether you look at it from the perspective of cloud technologies, digital initiatives, software applications or IT architecture, there is one constant in business: the ever-growing need for analytics. But there is far more to the picture than that.

Sure, analytics are fantastic. But I can assure you that, as an executive, I’ve seen my fair share of analytics and reports. And rarely do they accomplish anything—because they are devoid of context, meaning, or even reality.

Meanwhile, the demand-driven vicious cycle for such analytics seems to permeate the world of business. It usually starts with a senior executive craving data—but they have no idea how to get it, nor do they understand the complexities that come with real data. They still love that adage of “if you can’t measure it, you can’t manage it.” But in this case, they can’t even access it!

And perhaps that’s the biggest issue of all—the complexity, paired with the idea that actionable data is somehow easy. After all, it’s just a dashboard, right? The issue is this: with so many disparate systems residing in modern IT infrastructure, IT teams continually struggle to consolidate and manage data to make it actionable and insightful to key business stakeholders. Ultimately, the data must be transformed into a cohesive and more intuitive model to enhance business intelligence.

The question then becomes, can this process be made easy?

Well, yes and no. Let’s start with the “no” first. Making data truly actionable in the true meaning of business intelligence is not for the faint of heart. In fact, it’s actually REALLY hard. It involves everything from connecting the aforementioned disparate systems, to embracing artificial intelligence and machine learning—and, of course, making it all work together. This is something that I leave to people who truly know this space.

And this is where we get to the better news surrounding the “yes” portion of the question. Making business intelligence a reality is not up to individual departments like sales, marketing, operations, and so on. Nor is it up to IT. Regardless of how smart every one of those people are in every one of those departments, they too have day jobs. And being an AI and machine learning expert ain’t one of them.

Instead, this again falls into the world of Enterprise Software Services—people who live and breathe this world every day, who understand the nuances and machinery that drive true BI. By engaging with the experts—that is, the true data and analytics professionals using the latest data science technology—you can then start to define mission-critical metrics, prototype data visualizations, and develop comprehensive dashboards. Ultimately, this introduces a whole new world of business intelligence to your organization.

The right expert team will specialize in building future-proof, innovative software products powered by AI, machine learning, and real-time user-driven business intelligence. As a result, you’ll be empowered to create meaningful, actionable data to improve, inform and automate your critical business decisions.

This results in access to in-depth, real-time data analytics about customers, products, processes and so much more—in turn leading to smart, proactive, highly informed decision-making, which is critical to gaining that competitive advantage.

Now, if only you knew a company that did all of this and more! 😉