Smarter enterprise tech cost management: How to reduce value leakage

Insights

• Enterprise technology choices are growing more critical as digital platforms expand.
• Organizations investing in technology today may unknowingly commit to systems and architectures that shape their business for years.
• Success depends not just on selecting the right technologies, but on making smart, sustainable decisions that drive long-term agility and growth.

Enterprise technology decisions have never been more consequential or complex. Platforms are expanding at scale, and artificial intelligence (AI) capabilities are accelerating faster than most companies can keep up with. Organizations investing heavily in platforms, licensing models, and large-scale digital transformation initiatives today can, often unknowingly, lock themselves into architectures that will shape their operations for years to come.

Infosys AI Business Value research shows that the most successful companies are those that have committed to transforming their operating models and modernizing their data architecture to unlock the full value of AI. Another study shows that the absence of a clear transformation strategy is as significant a barrier as security concerns, legacy systems, and technical debt. Cloud ecosystems, software-as-a-service (SaaS) platforms, and AI tools are becoming deeply embedded across business functions, from customer engagement to operations, finance, and supply chains. Crucially, these decisions are not easily reversible. Once embedded, enterprise technologies often remain in place for years, influencing architecture, dictating operational processes, and shaping vendor dependencies. Every decision carries long-term implications for cost, agility, and enterprise value.

In this environment, a strong technology strategy goes beyond choosing the right tools. The real advantage lies in consistently making sound technology decisions and sustaining their effectiveness over time.

Where organizations struggle

Nearly 70% of the software powering Fortune 500 companies today was originally built more than two decades ago. Moving between digital platforms and adopting new technologies involves navigating complex integrations with legacy systems, and requires extensive engineering support, employee upskilling, and operational adjustments. Businesses express strong concerns about technical migration challenges (75%), reduced productivity during transition periods (64%), and system downtime risks (63%).

Many organizations struggle to fully understand how their technology investments translate into business value because licensing structures are intricate, vendor contracts are layered with hidden constraints, and platform interdependencies evolve in ways difficult to track. And they enter misaligned contracts or continue vendor relationships that are no longer commercially optimal, accumulate redundant licenses and underutilized platforms, build architectures or maintain systems that don’t align with business needs at that point in time, and pay for capabilities they do not use. Application footprint also embeds long-term cost, risk, and rigidity into the enterprise.

What begins as a series of isolated decisions gradually compounds into structural overspending and turns into significant financial burden. By the time inefficiencies become visible, remediation is often expensive and disruptive. It is a failure of governance, oversight, and commercial discipline.

The gap between what technology costs and what it delivers grows precisely because decisions made under urgency are rarely revisited with the rigor they deserve.

Fewer decisions, better outcomes

Organizations must rethink how they make and manage technology decisions. The goal is to make fewer, better ones. Rather than viewing technology decisions as one-time events tied to procurement cycles, organizations must treat them as evolving commitments that require continuous evaluation, and alignment with business outcomes. Each decision should be assessed for its immediate benefits, long-term commercial viability, architectural fit, and adaptability.

• First, visibility becomes critical. Leaders need a clear and ongoing view of platform usage, licensing structures, and cost dynamics. Without this, it is impossible to optimize investments or identify inefficiencies early.
• Second, flexibility must be built into both architecture and commercial arrangements. Future-ready enterprises design systems and vendor relationships that can evolve with changing needs — whether that involves scaling AI capabilities, adopting new platforms, or renegotiating contracts.
• Third, decision-making must be anchored in value. This means aligning technology investments with measurable business outcomes, rather than treating them as isolated IT initiatives. It also requires integrating commercial, architectural, and operational perspectives into a unified technology decision-making framework.
• Finally, governance must become continuous. Instead of reviewing technology decisions only at the point of purchase, organizations need mechanisms to reassess, refine, and optimize those decisions over time.

The ability to maintain control over costs, risks, and long-term value is particularly important as enterprises add AI to their technology stacks, as platforms will be increasingly interconnected and adaptive. Organizations that master this will avoid inefficiencies and create technology foundations that actively enable growth.

From transactional choices to strategic control

To build this capability, organizations should take a disciplined and proactive approach to enterprise technology decision-making.

Invest in strategic technology advisory capabilities

The complexity of modern enterprise technology — spanning platforms, licensing economics, vendor negotiations, and application portfolios — requires dedicated strategic oversight. Organizations should leverage specialized advisory services to bring clarity to complex technology ecosystems. These services will work across the various ecosystems to ensure that technology decisions are commercially sound, contractually flexible, and aligned to enterprise strategy. They help embed financial and contractual foresight into IT and business strategy, and engineer value at the point of decision, not post-investment.

This includes developing a coherent platform strategy, optimizing licensing economics, strengthening vendor negotiations, and maximizing returns on key investments such as Microsoft ecosystems. A structured advisory approach can also enhance application portfolio rationalization and guide long-term architecture planning, reducing both risk and cost inefficiencies. Organizations that bring clarity to these areas earlier make better decisions, negotiate stronger commercial terms, and avoid the technology value leakage that compounds over time. Research has shown that targeted investments across architecture, infrastructure, and data help organizations curb technical debt.

Infosys Consulting helped a global retail franchise operator identify that it was spending too much on enterprise resource planning (ERP), SaaS, and licensing. The company was buying too many enterprise software licenses, and many were unused or underused. The software licenses were being poorly tracked and managed, leading to waste and inefficiency. The extra IT spend from this was equal to between 4% and 5% of the company’s revenue.

For this client, Infosys Consulting began by quickly reviewing the key areas affecting ERP decisions such as platform selection, bill of materials (BOMs), bill of quantities (BOQs), contracts, Microsoft and ERP costs, and the overall application setup, to find where money and value were being lost. This helped the client focus on the most important improvements instead of making isolated changes. Infosys improved enterprise software license management by removing software licenses that weren’t needed or being used. It also reviewed and corrected the client’s software usage rights and ownership records to ensure they are accurate, optimized, and aligned with actual needs, added flexible contract terms, and price protection clauses, fixed mismatches in software quantities and components, and corrected inefficient pricing during usage ramp-up.

In another case, a global grocery retail company was looking for support with transforming and upgrading its ERP system, right from identifying business needs to choosing the right software vendor and setting up the commercial agreements. Infosys Consulting helped the client adopt SaaS more effectively by putting in place an adoption strategy, which reduced the chances of paying for unused annual subscriptions. By simplifying the IT systems, strengthening governance, improving control and oversight, and applying better cost-management practices (FinOps), the company could reduce costs by around 15% to 20%. The company’s leadership team moved from reactive enterprise technology cost management to proactive commercial control, engineering the right licensing models, bringing transparency into what software products were included, and how quantities and pricing were calculated, and embedding governance that can sustain value over time.

For this client, Infosys Consulting helped simplify the company’s data, system integrations, and reporting processes by removing duplicate systems, improving real-time visibility, and building a strong base for using AI in areas like demand forecasting, supply chain optimization, and decision-making. Infosys also evaluated ERP vendors on how well they fit business needs, technical strengths, ecosystem and partner support, flexibility for future growth, and long-term partnership value. It used a structured approach to improve commercial transparency and control by reviewing software component design in terms of BOMs, contract flexibility, ease of implementation, and cultural and business fit.

This helped the client avoid vendor lock-in and reduce overall costs from the beginning. As a result, the client confidently selected scalable, AI-ready, and future-proof platforms that can grow with the business over time. Importantly, this was not only about cutting costs. By simplifying core systems and standardizing data and processes, Infosys created a foundation for AI-driven planning, forecasting, and supply chain optimization at scale for the client. The outcome included a nearly 20% reduction in costs, faster ticket resolution and better service level agreements, more efficient operations, and an AI-enabled ERP system ready to support long-term business growth.

A major factor behind these savings was better planning of BOMs and smarter contract structuring which reduced quoted costs by around 15%, with further savings of nearly 10% achieved through better vendor negotiations.

Continuously reassess technology decisions

Technology choices should not be treated as fixed, long-term commitments. Regular reassessment enables organizations to identify misalignment, optimize costs, and adapt to changing business and technology landscapes, especially as AI capabilities evolve. Organizations must establish regular review cycles to evaluate whether existing platforms, contracts, and architectures still align with evolving business objectives. This continuous reassessment helps identify opportunities to optimize costs, eliminate redundancies, and adapt to new technological advancements.

For a global consumer packaged goods company, Infosys Consulting changed the IT support model from simply reacting to problems and tickets to a more proactive, AI-driven approach. Using automation, self-healing systems, and shift-left support that involves solving issues earlier or through self-service, it reduced the number of IT tickets, improved first-call issue resolution, and increased customer user satisfaction. Infosys also introduced strong training and change-management programs for this client to help employees adopt new systems and tools more effectively. This reduced dependence on the IT helpdesk and encouraged greater use of self-service options.

At the same time, it simplified and improved the company’s core IT systems, creating a stable and well-managed digital foundation, where AI could be effectively used for demand forecasting, supply chain planning, and demand optimization. This was important because fragmented and inefficient IT systems were previously limiting AI adoption.

The overall result was significantly better operational performance, more stable and reliable platforms, a more user-friendly and resilient IT operating model, improved user experience and service quality, and a reduction of between 35% and 40% in total cost of ownership (TCO), while continuing to deliver sustained business value.

The goal for organizations should be to achieve predictable TCO, reduced risks, and disciplined control of technology economics.

Build governance into decision-making across the life cycle

Decision rigor must extend beyond initial selection. Organizations need structured governance for how platforms are evaluated, contracted, and reviewed over time. This means institutionalizing technology decision-making frameworks that guide how platforms are selected, contracted, implemented, and reviewed. It also includes establishing clear criteria for value realization, performance tracking, and renewal or exit decisions, and ensuring cross-functional alignment between business, IT, and procurement teams.

Elevate commercial accountability to leadership

Technology IT spend is too significant and strategically consequential to be owned entirely by procurement or IT. Regaining control of enterprise technology decisions is a board-level imperative. Leadership teams must take active ownership of the commercial dimensions of their technology decisions — understanding the economics, challenging the assumptions, and holding vendors accountable to the value they promised. Business leaders should have visibility into technology spend and be responsible for ensuring that investments deliver measurable value. This visibility across leadership teams in the organization ensures that decisions are aligned with enterprise priorities. It also fosters a culture of shared ownership and accountability for outcomes related to cost, risk, and value.

By mastering technology decision-making proactively, organizations can move from reactive cost management to strategic value creation. They can reduce waste, improve agility, and build scalable, future-ready foundations. Successful organizations will be those that make the smartest decisions about what technology they need, that take control early, govern continuously, and optimize systematically.