In the last twenty years, enterprise software has gone through two notable phases of evolution. The first came in the late 1990s, when software that lived on servers in offices began moving to the cloud. Later, it broke apart into an ecosystem of small Software-as-a-Service (SaaS) applications able to plug into one another. After about ten years of development, costly and cumbersome suites had given way to modular, cloud-hosted software.
Today, a new phase is beginning — one positioned to deliver real time insights to teams of all sizes. Driving this change are three converging trends: the growing amount of data that systems are sharing among themselves, the increasing capabilities of automation, and the consumerization of business software. Here’s how these factors will contribute to the solutions you’ll be buying and using in the near future.
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The expanding app ecosystem
In the 1990s, enterprise technology was sold in large, expensive packages. System integrations weren’t feasible, so in order to support every process across the organization, enterprise resource planning (ERP) software had to house a vast array of functionality. The system architecture was impenetrable to anyone but an expert. Data was perpetually siloed in monolithic software.
Software-as-a-Service changed that. Because they were originally designed to complement on-premises systems, SaaS apps were built to integrate from the outset. In 2005, Salesforce launched its AppExchange, setting off an explosion of third-party applications.
The new app ecosystem inverted enterprise software strategy. Instead of trying to manage many processes, companies like Salesforce focused on developing a superior single product (in their case, a CRM) that could serve as a platform for third-party components. Each of those, in turn, specialized a specific workflow and shared data freely with one another. Instead of pushing self-contained packages, SaaS companies started to sell flexibility. The more components an application worked with, the more potential users it had. The integration arms race was on, and it continues today.
As a result, enterprise tech stacks are becoming radically customized. Software is more plug-and-play, which means it’s easier to procure and, crucially, swap out. Workflows are getting more efficient as SaaS companies invest all their attention into optimizing specific processes. Data is being generated by many different origin points in a cloud stack and shared throughout the network.
One of the most impactful outcomes of freely shared data has been the growth of intelligent automation. Combined with a data model and processing power, data inputs are one of the critical ingredients of machine learning
. You start by instructing the computer to find a pattern, feed it data in which that pattern is present, and let the computer refine its model over many iterations. The more data the computer sees, the more precisely it will understand what it’s looking for. After enough cycles, the software can spot patterns humans would never be able to see. That, for now, is the primary utility of artificial intelligence in the enterprise.
A.I. is entering businesses gradually, typically in Sales and Customer Service first. Products like Salesforce’s Einstein and SAP’s CoPilot package a primitive version of it, but these tools only hint at the capabilities that A.I. will make available in the next few years. As it becomes stable enough to run financial processes, the finance team will see it emerge in their software.
In the meantime, ordinary automation is proving immensely powerful. It’s able to learn and predict behavior, identify outliers in data sets, trigger activity based on user presets, and empower people with ready, actionable insights. It is not the super-intelligent A.I. you see in TV shows — that technology is purely theoretical and, if even possible, at least a decade away — but it is the cutting edge of enterprise software.
As consumer technology has infiltrated every aspect of our lives, it’s steadily impacted the user experience, or “UX,” of enterprise software. This trend is about more than looking nice. The way that employees interact with a piece of technology can spell the difference between life and death for the implementation.
In the old days, organizations bought software in a rigid, top-down way. An executive tasked with procurement would source feature-heavy solutions that checked all the boxes they could think of.
End users, who often felt like the least important part of the story, didn’t enjoy having to conform to brittle workflows. The largest cause of system failure
was frustrated employees simply refusing to use the new software. Bad UX was like a never-ending technical malfunction.
As technology developed outside the enterprise, corporate software followed slowly behind. The features built into trendy apps usually took a few production cycles to find their way into enterprise tech, but over time, it became more powerful and user-friendly.
Better UX delivers a number of benefits. It drives higher user engagement, which helps software facilitate its intended workflows. Slack, for example, tries to streamline a company’s channels of communication, and it’s more likely to achieve that outcome if more people use the app. At the same time, data quality and quantity improves. Modern software is built to generate feedback at every interaction, so more use translates to more insights.
Most of all, user-friendly solutions allow employees to take on more responsibility. Consumer software is a proxy for what people are accustomed to doing with technology, and thus, what companies can ask of them. Abacus, for example, requests that employees use their smartphones to snap images of receipts. We feel comfortable making this request because, if you haven’t noticed, people love taking pictures with their phones. The same goes for a manager’s expectation that their employees will learn to use mobile software quickly, provided it looks and feels like the apps they use in their free time.
The arrival of real time
These three trends — integration, automation, and consumerization — are the forces driving software into a new cycle of innovation. Data will flow freely through a tightly connected system of applications and output as actionable insights in real time. In the next era of enterprise software, employees will enjoy more power and support from their tools, and more control over what they use in the first place.