Global spending on software will continue to grow despite headwinds in the form of inflation, geopolitical risks and labor shortages, a new report from Forrester shows.

Driven to a large degree by deployment of cloud and enterprise applications, software spending worldwide is expected to grow at a compound annual growth rate (CAGR) of 10.3% from 2021 to 2023—more than two times faster than the rate of spending in other segments of IT, which is forecast to be 4.4%, according to the market research firm.

The report, which is based on a survey of 657 publicly traded software companies, forecasts that dramatic macroeconomic conditions and other factors will have little to modest impact due to the “underlying strength” of the software industry fundamentals.

More than half of the companies surveyed are expected to grow revenue at a medium pace, or between 10% and 20%, the report says, adding that leading software vendors will see another year of solid revenue and profit, albeit at a slower pace than 2021.

The report also shows that software has been the fastest growing category within enterprise IT budgets,  and has delivered high revenue growth rates consistently for vendors.

Cloud to drive enterprise software growth

Enterprise software—including application and infrastructure software—is expected to grow by 12% growth in 2022, buoyed by investment in cloud technology as a result of accelerated digital transformation efforts due to the pandemic, the report says.

“Investment in cloud to modernize legacy applications will drive strong software sales momentum in front- and back-office applications,” the report reads.

The application software market will see a 11.4% CAGR in 2022 and 2023, exceeding $400 billion, Forrester says. Front-office apps—such as CRM software and industry vertical programs—will grow the fastest in this segment, according to the report, which forecasts the $64 billion CRM market to grow by 11.9% in 2022.

ERP application sales are expected to increase at a rate of 10.4% in 2022, also driven by digital transformation efforts. Sales of content and collaboration software, such as Microsoft Teams, Zoom and Slack, are expected to grow at a rate of 11.9%, according to the report.

Sales of custom-built software for various internal divisions across enterprises, which Forrester defines as vertical software, are also expected to grow.

Infrastructure software sales to increase by 12.6%

Infrastructure software sales, meanwhile, are expected to grow at a rate of 12.6% in 2022 and 2023 to exceed $400 billion, driven by the evolution of legacy database technology and investments in devops and database management software, according to Forrester.

Within the infrastructure software category, database management software is expected to grow at 12.8%, driven by demand for real-time analytics.

Further, tech management software, another subcategory within infrastructure software, is expected to maintain growth momentum of 13.1%, driven by the trend for businesses to modernize their tech stacks with complex serverless architectures and containers.

However, security software—also considered by Forrester to be infrastructure software—is expected to grow fastest, at a CAGR of 15.4%, due to multiple attack incidents and geopolitical challenges such as the Russia-Ukraine war.

Software has room for continued growth

Aggregate market capitalization of publicly traded software companies increased from $718 billion in April 2010 to $5.4 trillion currently—equating to a CAGR of 18%, according to the report. The survey also shows that the software sector accounts for only 5.9% of total  global market cap of public companies, indicating more room for growth.

Another reason for continued growth can be attributed to software vendors’ ability to raise prices consistently without losing demand, as software forms a critical part of day-to-day operations, the report says, adding that this strategy results in high and stable margins for vendors.

Companies that have raised prices recently include the likes of Adobe and Microsoft.  

Profit margins, which could be as high as 70% on average, allow software vendors to strategize while weathering challenges such as uncertain macroeconomic conditions, the report says.

Enterprise Applications, Technology Industry

Driven by the ongoing need for companies to automate repetitive tasks, global RPA (robotic process automation) software revenue is expected to reach $2.9 billion in 2022, up by 19.5% from last year, according to a market research report by Gartner.

North America will account for the largest revenue share at 48.5%, followed by Western Europe and Japan at 19% and 10% respectively, Gartner said.

“Organizations will look to increase their spending on RPA software solutions because they still have a lot of repetitive, manual work that through automation could free up employees’ time to focus on more strategic work,” said Varsha Mehta, a senior market research specialist at Gartner.

The demand is also breeding competition among RPA software vendors who, according to Mehta, are pushing beyond a traditional single technology-focused offering to a more advanced suite of tools that encompasses technology including  low-code application development platforms, process and task mining, decision modelling, iPaaS (integration platform as a service), computer vision, and identity management capabilities on top of their existing RPA offering.

RPA embraces tech that will lead to hyperautomation

This phenomenon will enable vendors to offer hyperautomation-enabling technology in the future, Mehta said. Hyperautomation, as defined by Gartner, involves the use of multiple technologies that companies can use use to rapidly identify, vet and automate as many business and IT processes as possible.

However, even though RPA revenue will continue to increase, growth will slow down, Gartner says. RPA software revenue grew at 31% year over year during 2021, higher than the projected growth of 19.5% this year, and next year the market research firm expects that growth will further slow, to 17.5%, reaching $3.5 billion.

This is because other technology improvements—such as modernization of integration strategy, distributed cloud storage, and spending on cloud-native applications—to achieve business architecture composability is taking precedence over automation or process efficiency demands, the company said. Composable architecture treats IT resources as services that can be made available on an as-needed basis, depending on the needs of different applications and users.

“Slow implementation across one or multiple business functions slows down the ROI cycle—one of the causes of slow spending on RPA,” Mehta added. He said that one reason for slow deployment is that RPA projects are usually focused on a particular process or initiative, which then pose scalability issues for tailoring  RPA bots to varying organizational or business function needs.

Enterprise Applications, Robotic Process Automation

With more than 30,000 employees spread across more than 60 affiliate locations and 14 manufacturing sites around the world, pharmaceutical company Eli Lilly operates at a truly global scale. Operating at that scale comes with issues, not the least of which is sharing accurate and timely information internally and externally.

“From internal training materials to formal, technical communications to regulatory agencies, Lilly is translating information often,” says Timothy F. Coleman, vice president and information officer for information and digital solutions at Eli Lilly and Co.

For years, Lilly relied on third-party human translation providers for the bulk of its translation needs. Although public web translation services are available, confidentiality requirements meant those services did not meet Lilly’s standards for information security. Even with a footprint of more than 400 translation vendors, the process was slow.

“Lilly engages with costly third-party human-translation providers across the organization to provide verified and reliable translations,” Coleman says. “Depending on the requirements, the planning, translation, and verification of these engagements can take weeks to complete.”

Coleman adds that many bilingual Lilly employees were also being tapped to provide translations in addition to their current scope of work.

To address these challenges, the pharmaceutical firm developed Lilly Translate, a home-grown IT solution that uses natural language processing (NLP) and deep learning to generate content translation via a validated API layer, Coleman says.

“This innovative application of natural language technology enables Lilly to achieve greater efficiency gains, significant cost reduction, higher quality content, and lead the way for future tech innovations using natural language technology to achieve enterprise value at scale,” he says.

Passion project pays off

Coleman says Lilly Translate started as a passion project by a curious software engineer who had an idea for addressing a pain point of the Lilly Regulatory Affairs system portfolio: Business partners continually experienced delays and friction in translation services.

“That married up well with an opportunity to explore and learn emerging technologies,” he says. “It became a great opportunity that a Lilly software engineer picked up and ran with, initially as a great learning opportunity.”

After sharing the idea and technical vision with peers and managers, the project immediately garnered support from leadership at Eli Lilly Global Regulatory Affairs International, who advocated for investment in the tool. Coleman’s team worked closely with Regulatory Affairs to identify requirements around document types, languages, and so on.

The Lilly Translate API and UI are delivered via a serverless tech stack built on Node.js, Python, .NET, and Docker. It can be accessed via mobile devices, web browsers, and programmatically through the secure API.

The service, which earned Eli Lilly a CIO 100 Award in IT Excellence, provides real-time translation of Word, Excel, PowerPoint, and text for users and systems, keeping document format in place. Deep learning language models trained with life sciences and Lilly content help improve translation accuracy, and Lilly is creating refined language models that recognize Lilly-specific terminology and industry-specific technical language, while maintaining the formatting requirements of regulated documentation.

“The product was developed via a DevSecOps agile framework,” Coleman says. “Initially, we did not have a dedicated Scrum master and product owner, but later we were able to adjust that. The increased focus helped us accelerate our delivery efforts.”

The project took about a year to get to MVP, with several iterations and pilots needed to achieve the level of translation quality needed to meet business expectations.

“The level of quality of the translation output was an initial challenge we faced where the team had to work through various services to figure out how to improve the overall general level of quality,” Coleman says. “Once improved, we had to work diligently to ramp up our [organizational change management] efforts to gain confidence in the tool.”

With the tool fully deployed, a process that required the creation of work orders and days or weeks to complete now takes just a few seconds or minutes. The automation has also led to a big cost savings.

“In surveys distributed across the company there is consistent feedback that Lilly Translate is saving time across multiple business processes as well as getting answers to questions faster,” Coleman says. “Lilly Translate touches every area of the company from HR to Corporate Audit Services, to Ethics and Compliance Hotlines, Finance, Sales and Marketing, Regulatory Affairs, and many others. The time savings is extensive. Translations are now taking seconds instead of weeks, providing key resources time to focus on other business-critical activities.” 

CIO 100, Natural Language Processing

Anil Bhatt, Global Chief Information Officer at Elevance Health, joins host Maryfran Johnson for this CIO Leadership Live interview, jointly produced by and the CIO Executive Council. They discuss using AI in predictive healthcare, blockchain collaborations, the future of digital healthcare, global innovation trends and more.

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