Modernization that earns its spend
You can’t fix everything, so fix what counts
The question isn’t, why do we need to modernize?
As technology leaders, you know the stakes:
Obsolescence is a threat. 70% of enterprise software is over 20 years old, and the talent pool that knows how to maintain it is shrinking.
Innovation is kneecapped. 60%-80% of IT budgets are gobbled up by maintaining mainframes and static, legacy systems that aren’t designed for current or future business needs, like adaptability and AI transformation.
Every moment without modernization compounds opportunity costs. From technical debt and talent risk to security exposure and slow, siloed decision-making, legacy infrastructure puts growth and long-term value generation in a lockbox.
The question is actually two parts: what do we modernize first, and how do we know it’s the right call for the best ROI?
Legacy still running the show? Modernize what matters.
Modernization only matters if it unlocks adaptability. Turn intent into measurable outcomes with Slalom.
Scatter-shot modernization and lift-and-shift exercises are wasted effort
Modernization isn’t operational maintenance. It’s not even systemic technology upgrades or a one-time, everything-at-once transformation that IT owns all by itself.
Modernization is an enterprise-wide effort in reimagination and reinvention, so you can use intelligent operations with AI transformation, data strategy, and adaptable workflows as (you guessed it) strategic levers that unlock new value via new business models, customer channels, and workforce productivity.
The good news?
- 60% of CIOs consider IT modernization their top priority. (Info-tech, 2025)
- 75% have already completed small-scale modernization efforts. (Redhat, 2024)
- Another 18% have already achieved their goals for continuous modernization. (Redhat, 2024)
- Only 6% of CIOs say they’re doing nothing to modernize. (Radix, 2025)
- 87% say modernizing critical apps has been a key success driver, setting them apart with new competitive advantages. (Business Wire, 2023)
The bad news? Most digital transformation spending fails to meet business outcomes when leaders spread it across too many priorities.
Typical enterprise modernization entry points, by industry
Organizations that focus on modernization efforts where they matter most can cut, automate, or optimize the systems that slow them down—then double down on the capabilities that drive growth.
Here are some of the typical entry points we see organizations invest in first:
- Core replacement
- Customer 360
- Regulatory automation
- Omnichannel fulfillment
- Demand forecasting
- Inventory optimization
Healthcare
- Clinical decision support
- Master patient index
- Telehealth modernization
Manufacturing
- Plant uptime and throughput
- Critical equipment failure prevention
- Recall readiness (quality traceability)
Technology
- Product platform consolidation
- Unified data for personalization
- Release risk detection and rollback
Energy & natural resources
- Grid resilience and restoration
- Safer asset performance and uptime
- Forecast-driven dispatch
Media & communications
- Personalized retention targeting
- Real-time ad yield
- Rights valuation and bidding
Life sciences
- Trial activation speed
- Biomarker patient matching
- Safety signal detection
Public & social impact
- Benefits renewal automation
- Improper payment prevention
- Crisis triage and routing
Three ways to keep modernization tied to outcomes
While your organization is doing the hard work of modernizing, it’s incumbent upon executives and key leaders to avoid overloading your teams with too many priorities. Here are three strategies to help you avoid sinking into distractions and instead unblock real advantages.
1. Stay business outcome-oriented
Modernization begins by aligning on your organization’s priority business outcomes:
- Are your customers demanding access through new channels of communication? Do they expect intelligent, engaging, immediate service? (Renown Health’s did. Same with United Airlines.)
- Are you trying to fast-track R&D and bring new bets to market quicker than your competition? (Takeda Pharmaceuticals and PUMA understand.)
- Do you need to reskill and upskill teams into AI fluency, so they’re supervising AI agents or designing AI automations with new data capabilities and efficiency standards? (Clariant pulled it off with precision, too.)
Document your current state, envision your future state, name the gaps, and agree on how to fill them. Also agree on (and document) how your team and other stakeholders will partner with explicit roles and responsibilities. This alignment and visibility will help you map modernization to outcomes.
2. Set, communicate, and benchmark against clear governance structures and KPIs
Make your success criteria clear, measurable, and accountable. Consistently update your team and organization on how the efforts are going. Leaders who define the work, the process, the guardrails, and desired outcomes get tangible results that often exceed expectations.
Here are some examples of strong modernization KPIs:
|
Poor modernization KPIs |
Strong modernization KPIs |
Rationale |
|---|---|---|
|
% of applications migrated to the cloud |
% of application portfolio meeting target architecture standards |
It doesn’t matter where the app runs. It matters if the app is cheaper to operate, easier to change, and more failsafe. |
|
IT cost reduction YoY |
Run-rate cost per business transaction (or customer or unit of revenue) |
This reframes IT from a budget line to a business engine. It rewards modernization that lowers unit economics without starving security or innovation. |
|
% of data sources onboarded |
Time to deliver a new analytics or AI use case from idea to value |
Platforms only matter if they accelerate outcomes. This KPI rewards ingestion over impact and exposes over-engineered foundations immediately. |
|
Enterprise data quality score |
Data accuracy and timeliness at the decision point for priority use cases |
Perfect data nobody uses is worthless. Tie data quality to business-critical outcomes. |
|
# of AI models/use cases in production |
AI-driven outcomes and use cases realized (cost avoided, risk reduced, revenue generated) per model |
This kills pilot purgatory. Models that don’t earn their keep get retired. |
3. Figure out your funding models
Here are a handful of typical modernization funding models:
- Annual CapEx program funding for continuous modernization
This multi-year “big rock” model works well when scope is clear and when you have the flexibility to shift the funding across a run-grow-transform framework quarter-by-quarter. - Tranche-based funding for risky or novel initiatives
If your gates aren’t bureaucratically problematic, this incremental, stage-gated approach to modernization is also effective. Especially if you hybridize the approach with product- or domain-based funding where teams own outcomes, not delivery milestones. - Self-funding loops for cloud and automation
In this OpEx reallocation, modernization is funded by cloud cost savings, vendor consolidation, and automation/toil reduction. Savings are explicitly recycled into modernization. This CFO-friendly funding model forces ROI discipline and can responsibly signal the “kill switch” if revenue dips below your strategic number. - Mandated funding only where risk is existential
Boards understand downside risk, and this funding is justified when you need to meet regulatory requirements, derisk your security posture, address end-of-life risk, or operate under resilience mandates. The key is not to overscope “must-have” work, so you’re not starving out innovation opportunities. - Technology partner funding for enterprise modernization
This isn’t a blank check or a venture-style co-investment. This is incentive-based, usage-tied, and contractually-governed commercial support that reduces friction and accelerates time-to-value. Boards like it because it reduces near-term cash outlay, brings in scarce expertise and partners who can upskill teams (not just modernize systems), and de-risks early modernization phases.
Modernization is a leadership discipline not a tech project
Modernizing systems unlocks the ability to reimagine and rebuild process workflows, internally and externally. This reinvention and adaptability allow for more effective, rewarding ways to work, engage customers, and propel your organization into the future.
Teach your old code new tricks.
FAQs
Enterprise modernization is often funded through a mix of models, including multi-year CapEx programs, tranche-based or stage-gated funding for higher-risk initiatives, self-funding loops driven by cost savings and automation, and mandated funding for regulatory, security, or end-of-life risks. The right mix balances flexibility, risk management, and ROI discipline.
Organizations should measure modernization success using outcome-based KPIs rather than activity-based metrics. Examples include run-rate cost per transaction, time to deliver analytics or AI use cases, data accuracy at decision points, and realized business outcomes from AI models. These measures focus on value, adaptability, and operational impact rather than technical completion.
Organizations decide what to modernize first by aligning modernization initiatives to priority business outcomes, such as improving customer experience, accelerating product development, reducing operational risk, or enabling AI-driven capabilities. This typically involves documenting the current state, defining a future state, identifying gaps, and sequencing investments based on value and feasibility.
Modernization ROI is calculated by measuring improvements in unit economics, speed to value, risk reduction, and operational efficiency. Common indicators include reduced run costs, faster delivery of new capabilities, improved resilience, and measurable revenue or productivity gains tied to modernized systems.