The Future of the Technology Industry: Defined by Data

Don’t let the doomsday news cycle mislead you: While some technology companies are having a turbulent year, the industry as a whole is on solid ground. Global IT spending is forecast to climb 5.5% this year and hit $4.6 trillion, according toGartner. While consumers’ purchasing power and their demand for devices has softened, the business world’s appetite for data center systems, IT services, and software continues—with the software market segment alone expected to swell nearly double digits this year.

“Macroeconomic headwinds are not slowing digital transformation,” said John-David Lovelock, distinguished vice president analyst at Gartner, in the firm’s report. AndKPMG’s 2023 “Technology Industry CEO Outlook”found that within the tech sector, nearly two in three CEOs are prioritizing investment in buying new technology, and 70% report having an aggressive digital investment strategy.

Still, economic and supply chain uncertainties and a stubborn skills shortage are undoubtedly reshaping C-suite priorities and pressures. “The definition of success has shifted,” notes Justin Joseph, senior director of product strategy at Workday. “It’s no longer about growing at any cost.”

As technology leaders look to confront near-term challenges while leveraging the full potential of emerging and tipping-point technologies, industry experts examine the trends that can help tech companies move to the front of the competitive pack.

1. Data Architecture Becomes the Great Differentiator

Growth remains the technology sector’s North Star, but companies are increasingly beset by pressure to pursue more measured, sustainable growth. In other words, technology leaders must balance the usual innovate-or-perish imperative against the pressing need to trim costs, amplify efficiencies, and stabilize cash flows.

Half of technology executives surveyed byEYsay their companies lack the right operating model, given the external environment. At the same time, of the executives who made an operating change, 82% realized revenue growth as a result.

Across all corners of the industry, companies are busy seeding digital experiments, brokering new partnerships, testing emerging-tech use cases, and flirting with novel revenue streams. But connecting the dots between R&D and ROI demands data—specifically unified, real-time data that can power relevant decision-making across the enterprise.

That’s a far cry from industry norms, points out Workday’s Joseph. Technology organizations have a reputation for being eager early adopters of niche best-in-breed tools and nascent tech, grafting these slick solutions onto brittle legacy systems. The result is a labyrinth of fragmented data that requires resource-heavy manual interventions to analyze or even aggregate. Data visibility is sharply curtailed, cross-functional collaboration hamstrung.

For European mobile-app company Bolt, “purchasing all these disparate systems didn’t work the way we needed it to,” reflected Jacqueline Broderick, Bolt’s head of finance technology, at Workday Rising EMEA. “We needed to make a decision on how to move forward.” Replacing its patchwork data landscape with a unified, cloud-native platform slashed inventory analysis from weeks to hours, even as company growth accelerated. Teams no longer have to sit idle while numbers are updated and verified, because they have reliable, real-time data at their fingertips—the impact of which “has been phenomenal,” Broderick said.

Compare that enthusiasm to the data leaders surveyed byBCGearlier this year: More than half identified architectural complexity as a significant pain point. As industry calls for faster, more data-driven insights intensify, technology executives must reckon with the stark reality that the costly, complex status quo isn’t cutting it.

WhenWorkday surveyed technology leadersabout the investments they’re prioritizing to meet evolving business demands, the top trio of responses all have one thing in common: data. One-third of technology leaders ranked technologies to unify financial, people, and operational data at the top of their priorities list.

2. Technology Companies Turn to Skills-Based Talent Models

After years of aggressive hiring to meet feverish demand for technology products and services, economic headwinds have ushered in a new era of hiring slowdowns and layoffs for the tech industry. But workforce optimization isn’t merely a matter of adjusting headcount. Technology leaders recognize that they need to cultivate a dynamic mix of skills in order to spur innovation and weather contractions and competitive shifts with greater resilience.

Indeed, a late-2022PwC调查发现,即使在科技、媒体和entertainment execs are more likely than their peers to reduce headcount and implement hiring freezes—the vast majority (88%) are focused on growth. And four in 10 industry leaders rank talent acquisition and retention as a serious risk to their companies.

“Especially for companies that are in tech, time to capability is a key competitive advantage,”托德·斯科特说, director of the Workday Solutions Organization at Cisco Systems. “It’s critical that our workforce systems are positioned to keep up with those constant market transitions and how that impacts our people’s strategies.”

To escape the reactionary cycle of shedding employees one day, only to struggle the next to find the skills they need, technology companies have been some of the earliest to embrace skills-based workforce management. This data-fueled approach eschews the usual emphasis on rigid roles and jobs for a focus on discrete skills.

Research reveals the wisdom in this growing shift: According toDeloitte, organizations that focus on skills rather than jobs are more than twice as likely to place talent effectively and 98% more likely to retain high performers. Skills-based organizations are also far more likely to outperform their traditional counterparts in the arenas of innovation, efficiency, and adaptability.

Of course, for technology organizations to shake free of antiquated role-based planning, they need more than workforce data; they need unified, real-time data and panoramic visibility across their entire talent ecosystem.McKinseyestimates that upskilling in-house technology talent costs less than half as much as hiring, and many find the business case for investing in breakthrough technologies easy to make. Think:artificial intelligence(AI) capabilities that can help identify and promote growth opportunities to upskill workers and retain top talent, attract new talent to help fill the skills gap, and create personalized and engaging experiences for employees.

3. Tech Orgs Rethink How They Evaluate M&A Success

Financial volatility may have cooled mergers and acquisitions (M&A) activity in 2022, but technology executives who lived through the 2008 Great Recession seem eager to steal a page from that recession-comeback playbook: Ananalysisof nearly 300 large-cap technology companies found that those that focused on revenue growth during the downturn—particularly by investing in acquisitions—significantly outpaced the performance of their peers focused largely on cash preservation.

For technology companies, transformative acquisitions present a speedy route to move into adjacent verticals—think healthtech, fintech, autotech—or to beef up capabilities, such as AI or virtual reality, that can then be leveraged across the entire portfolio. While 59% of CEOs across all industries plan to pursue M&A in 2023, that figure rises to72%for tech CEOs.

Technology, media, and entertainment dominated the M&A market last year and was a significant hot spot for private equity investors, according toPwC. A tightened regulatory environment is expected to constrain semiconductor deals, but deal-makers anticipate a serious uptick in software and IT services M&A activity as cash-flush organizations seize on opportunities created by lower valuations.

Cloud-based enterprise technology can give those organizations pursuing M&A an edge. Of M&A leaders, 43% are cloud native or fully migrated to a cloud-based ecosystem, and the remaining 57% are on their way to the cloud, according to a report byWorkday and MGI Research. To put that in context: Only 25% of average and below-average companies are fully migrated. As for M&A laggards? Zero say they are cloud native.

Still, M&A success isn’t determined solely by clearing deal-making hurdles. “The technology M&A landscape is changing, and there’s now far more emphasis on ensuring a seamless integration, from a people perspective, to power long-term success and returns,” says Workday’s Joseph.

A common trip wire for acquirers, the haphazard or half-hearted integration of business processes and data can seriously thwart the value realized from M&A. When different organizations hold on to their siloed technologies, they struggle to become one cohesive entity.

“When you have companies come together but everything sits in a different system, it creates a lot of extra work,” said Perri Ma, vice president of global human capital management analytics and operations at Warner Bros, atWorkday Rising. “It’s very important for new leadership—for people who actually make decisions—to have clear visibility into the combined workforce. That may sound very basic, but it’s critical for M&A activity.”

4. As AI and ML Accelerate Exponentially, People Take Center Stage

It’s hard to overstate just how dramatically AI and machine learning (ML) can reshape a tech company’s products, processes, and performance. The industry is already at the forefront of AI adoption (no surprise there), with 72% of technology, media, and telecom leaders strongly believing that AI will be very important to their company’s ability to stay competitive over the next five years, according to an October 2022Deloittesurvey. That’s 12 percentage points higher than any other industry.

While AI’s potential impact on commercial products is a hot topic, no less attention should be paid to AI and ML’s transformative impact on enterprise functions, such as HR, finance, procurement, and logistics. In fact, Deloitte analysts found that technology companies “derive the most value from use cases related to back-end operations that tend to enable standard business practices.” For instance,41%of industry leaders say they’re already using AI in workforce scheduling optimization.

But asSayan Chakraborty, executive vice president of product and technology at Workday, says, “For AI and ML to really deliver on the possibilities it offers, it must be trustworthy and it must augment humans, not displace them.”

AI and ML applied to accounting isn’t worth much if the accounting team isn’t able to quickly and confidently drill down into the underlying data. Likewise, AI that simply generates employee schedules isn’t nearly as useful as AI that delivers recommendations on how managers might want to train and upskill existing employees to optimize future schedules even more.

Cultivating end-user trust and actionable insights is harder to do with stand-alone AI tools simply grafted on to existing systems. As technology companies shift from one-off experimentations to a deeper embrace of AI and ML, those that prioritize the people piece may easily outpace their counterparts.

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