Transform Your Data Center Strategy With a Business-Driven Approach

Transforming data centers for business resilience and growth

EXECUTIVE BRIEF

Analyst perspective

Rethinking the role of data centers

The role of the data center is evolving from a static, capital-intensive facility to a dynamic enabler of business agility and digital transformation. Infrastructure is no longer just about uptime – it’s about adaptability, efficiency, and alignment with broader business objectives.

Today’s IT leaders must ask whether continued ownership of physical infrastructure truly serves the organization or if alternatives like colocation, modular builds, and edge computing offer more flexibility, resilience, and cost control. The rise of hybrid models reflects a broader realization: There is no one-size-fits-all answer

The shift toward hybrid models reflects a broader need: infrastructure must be flexible, resilient, and optimized for performance and cost.

In summary:

• “One-size-fits-all” is obsolete – hybrid and modular approaches are rising.
• Energy, environmental, and cost factors are redefining what’s sustainable.
• AI, automation, and zero trust are the new default design principles.
• Success lies in aligning infrastructure with business outcomes – not just IT uptime.

John Donovan

Principle Research Director, I&O Practice
Info-Tech Research Group

Executive summary

Your Challenge

Most organizations are facing pressure to modernize aging infrastructure, reduce costs, and support new workloads without a clear plan for how or where their data center fits in.

• Data centers are costly, aging, and often underused.
• Cloud-first strategies are misaligned with legacy workloads.
• Business stakeholders demand agility and availability.
• Power, space, and staffing are harder to scale internally.

Common Obstacles

There is often unclear ownership of the data center strategy across IT, Facilities, and leadership. This can lead to:

• Lack of visibility into what workloads should move and where.
• Power and cooling limitations in existing facilities
• Risk aversion around migrating core or regulated workloads
• No structured process infrastructure footprint for rationalizing

Info-Tech’s Approach

Reframe your data center strategy as a business-driven workload placement decision, not just an infrastructure exercise.

• Focus on key decision areas that impact cost, control, and performance.
• Apply a structured framework to guide infrastructure choices.
• Align workload placement with strategic, technical, and operational priorities.

This approach ensures infrastructure decisions directly support business goals, maximizing value, agility, and long-term sustainability.

Info-Tech Insight

The objective is not to simply exit data centers but to establish a future-ready infrastructure strategy that balances cost, performance, and risk. Success requires aligning workload placement with business value – across cloud, colocation, and on-prem – while embedding security, compliance, and sustainability from the outset.

Market trends and statistics

Key statistics highlighting the need for a data center strategy

Major increase in cloud and hybrid strategies.

73%

73% of enterprises have adopted a hybrid cloud strategy, up to 2025.

(Auvik, 2024)

Power and energy consumption has significantly increased.

44%

44% of data center operators identified costs as a top concern.

(Uptime Institute, 2024)

Decisions on where to place workloads lack strategic direction.

55%

55% of workloads are off-premises.

(Uptime Institute, 2024)

Workload-Driven Decisions Matter

Rethinking data center strategy

Large enterprises are steadily divesting from infrastructure ownership, reinforcing the need for strategic workload placement.

60%

In 2018, nearly 60% of data center capacity was owned by enterprises. By 2024, that figure dropped to just 37% as hyperscalers and co-lo providers expanded their share.

Source: Data Centre Dynamics, 2024

76%

76.4% of organizations rank security as the top factor influencing workload placement decisions in hybrid cloud environments.

Source: Zones, 2021

• Enterprise-owned data centers are shrinking at scale, reflecting a broader shift away from traditional infrastructure.
• Cloud-only is rarely optimal. Hybrid strategies mixing on-prem, co-lo, and cloud have emerged as the strategic norm for most enterprises.

Info-Tech Insight

The data is clear: Enterprise ownership of data centers is shrinking, hybrid strategies are the norm, and energy costs are climbing fast. Organizations need to rethink their infrastructure through the lens of workload fit, operational efficiency, and long-term sustainability – not legacy ownership.

A modern data center is no longer a fixed location – it’s an evolving ecosystem of cloud, colocation, on-prem, and edge computing tailored to business needs.

1. Exit strategies should be based on business value, not just cost-cutting.
2. Cloud is not always the answer – organizations must balance on-prem, colocation, and cloud workloads strategically.
3. Security, compliance, and sustainability must be built into the strategy from the start.

Info-Tech Insight

The goal is not just to exit data centers but to create a future-proof infrastructure strategy that aligns with business growth.

Manage your data centers

Organizations are struggling with legacy data center infrastructure, rising costs, and shifting IT models. The traditional approach of owning and managing a data center is becoming unsustainable for many due to:

• Rising operational expenses (power, cooling, real estate).
• The growing shift to cloud, edge, and colocation models without a clear strategy.
• Security, compliance, and disaster recovery risks of aging facilities.
• The need for more flexible and scalable IT infrastructure.

35%

Data center power consumption has increased by 35% in the last five years, making energy efficiency a critical concern.

(Source: Uptime Institute, 2024)

Organizations are at a crossroads: should they maintain, modernize, or exit their data center? The right strategy enables agility, security, and cost-effectiveness.

Infrastructure, Services, and Utilities

Applications and Services
Business Apps, Collaboration AI/ML, Databases

Middleware and Virtualization
VMs, Containers, APIs, IAM

Compute Layer
Servers, HPC, Cloud Compute, Edge Nodes

Storage Layer
SAN, NAS, Object Storage, Backup & DR

Network Layer
SDN, Load Balancers, Firewalls, Cloud Connectivity

Security & Compliance
Zero Trust, SOC, Compliance Frameworks

Monitoring & Management
DCIM, AI-Driven Optimization, ITSM

Power & Cooling
UPS, Generators, Liquid Cooling, Renewable Energy

Physical Infrastructure
Data Center Building, Fire Suppression, Disaster Resilience

• Electricity – Grid power, renewable sources, UPS
• Water – Cooling systems, chillers, liquid cooling
• Fuel – Generators, backup power
• Connectivity – Fiber, 5G, cloud interconnects

Strategic Decision Framework and Workload Placement

Key Decision Areas

• Workload Types: AI, business apps, databases
• Performance vs. cost balance
• Security and compliance needs
• Resilience and disaster recovery strategies

Decision Framework

• Business Alignment: Revenue, cost savings, innovation
• Technology Fit: Performance, security, compliance
• Financial Impact: TCO, ROI, operational costs
• Future Scalability and Sustainability: AI-readiness, ESG goals
• Risk & Governance: Operational, regulatory, and security risks

Strategic Workload Placement

• On-Prem: Secure, mission-critical apps
• Colocation: Cost-optimized, partial control
• Cloud (Public/Private): Scalability and agility
• Hybrid IT: Balance of security & cloud benefits
• Edge Computing: Real-time processing needs
• HPC: AI, big data, specialized computing

Data center workload strategy framework

A structured approach to data center decisions

Key Decision Areas

What must be evaluated before placing a workload

• Business objectives and growth plans
• Security and compliance requirements
• Application performance and latency needs
• Resiliency and disaster recovery expectations
• Cost sensitivities (power, cooling, OpEx )
• Technology dependencies (e.g. data gravity, AI/ML processing)

Decision Framework

How decisions are made consistently and accurately

• Assess workload type: high performance, storage- intensive, etc.
• Score fit across deployment models: data center, cloud, colocation, edge
• Use weighted criteria: cost, performance, security, control, latency
• Evaluate constraints: geographic, regulatory, architectural
• Apply governance: decision logic embedded in IT strategy and policy

Strategic Workload Placement

What the outcome looks like – optimized placement

• Retain on-prem for tightly coupled systems, regulatory-heavy workloads, and mission-critical apps.
• Migrate to cloud for scalable, bursty, or SaaS-ready apps.
• Colocate to reduce facility cost while maintaining control.
• Deploy at the edge for low-latency or data-intensive near-user services.
• Enable high performance computing (HPC) for AI, big data, and specialized computing.

Executive summary

Info-Tech Insights

Reframe Data Center Ownership

Owning a data center is no longer a strategic differentiator for most enterprises. The true value lies in how infrastructure supports business agility, resilience, and cost optimization. Organizations should rethink physical ownership in favor of flexible delivery models like colocation, cloud, or hybrid environments that align with evolving business needs.

Align Workloads to Their Best-Fit Locations

Data center strategy should begin with the workload – not the facility. Each workload type has unique requirements for latency, compliance, performance, and cost, which means its placement must be deliberate and data-driven. Enterprises need a clear framework to assess and assign workloads to the right environment, whether that’s on-prem, cloud, edge, or a hybrid mix.

Design for Automation and Flexibility

Next-generation data center environments must be highly automated, modular, and capable of adapting to shifting workloads, power availability, and sustainability demands. AI and orchestration tools are essential for achieving “lights-out” operations and reducing human dependency in core infrastructure management. Flexibility is no longer optional – it’s a design requirement.

Data Center Strategy

From insight to execution: strategic moves for a future-ready data center

Case study

“Workload placement separates the winners from the losers in IT.”

IDC

INDUSTRY

Multiple

SOURCE

IDC Survey, 2024

Challenge

Enterprises were struggling to find the right deployment model for modern workloads (e.g. AI, Gen AI) due to conflicting demands – data privacy, performance, and cost. IDC found that 81% of organizations expected to repatriate workloads from public cloud to private/dedicated environments within 12 months.

Decision-makers needed guidelines to strategically evaluate workload placement rather than default to the public cloud or fully on‑prem.

Solution

IDC built a workload-driven placement framework based on workload type (AI, transactional, storage-heavy).

It conducted a structured evaluation of workload requirements (e.g. data security, performance, regulatory/legal, scalability) and placed workloads based on optimal fit.

• AI and sensitive data → private cloud/on‑prem
• Bursty or scalable apps → public cloud
• Long‑running analytics/storage → dedicated or colocated environments

Results

81% of organizations signaled movement toward private or dedicated infrastructure, reflecting the operational logic of the framework.

34% total infrastructure cost savings were observed in private cloud deployments vs. public cloud.

CIOs confirmed the strategy provided better alignment across performance, compliance, cost-efficiency, and resilience.

Exploring strategic infrastructure options

Choose the right fit for every workload.

On-Prem

Control everything – ideal for sensitive, tightly integrated workloads

Hybrid

Mix of on-prem and cloud- optimized placement based on workload needs

Portable/Containerized Units

Deployable anywhere – suitable for disaster response or field ops.

Colocation

Shared facility, dedicated hardware – good for cost-effective control

Modular Data Centers

Prefabricated, portable builds – scalable and fast to deploy

Green Data Centers

Sustainability-first – uses renewable energy and energy efficient design

Public Cloud

Elastic and scalable – best for bursty or fast-growing workloads

Edge Computing

Computes close to data source – minimizes latency for real-time workloads

HPC

Optimized for compute intensive workloads (AI, simulations, etc.)

Case study

“Right-sizing and optimizing infrastructure to cut $1 million in costs”

GE VERNOVA

INDUSTRY

Energy

SOURCE

AWS, 2023

Challenge

GE Vernova faced escalating infrastructure costs and operational inefficiencies due to a mix of underused cloud resources and legacy workloads that had been migrated without a clear placement strategy.

The lack of visibility into workload behavior led to overspending, suboptimal performance, and governance challenges in a complex hybrid environment.

Solution

GE undertook a structured workload assessment initiative using AWS tools like AWS Compute Optimizer and CloudWatch to analyze performance metrics, use patterns, and architectural fit.

It implemented a targeted workload placement strategy, reallocating certain workloads to better-suited environments, including right-sizing instances, retiring unnecessary resources, and keeping certain workloads on-prem for performance or regulatory reasons.

Results

• Over $1 million in annual cost savings
• Streamlined operations and better performance
• Enhanced visibility and governance across the organization’s hybrid environment
• Strong alignment between workload needs and platform capabilities

The new model allows GE Vernova to align IT operations with business objectives while maintaining flexibility for future growth and innovation.

Building a future-ready data center strategy

A structured, phased approach ensures your data center strategy aligns with business objectives, optimizes performance, and evolves toward future-ready infrastructure – balancing cost, compliance, and innovation at every stage.

1. Business and IT alignment

   • Define growth objectives, regulatory needs, and workload dependencies.
   • Assess cost and risk exposure of current infrastructure.

2. Future-State Infrastructure design

   • Choose between hybrid, cloud-first, or colocation-first models
   • Identify the best mix of on-prem, colocation, cloud, and edge.

3. Cost Optimization and Efficiency

   • Optimize power and cooling (liquid cooling, free-air cooling).
   • Improve networking and interconnectivity (SD-WAN, 400G Ethernet).
   • Implement AI-driven automation and AIOps for operating efficiency.

4. Security and Compliance

   • Implement zero trust security (microsegmentation, IAM).
   • Ensure backup, disaster recovery, and business continuity.
   • Improve physical security and regulatory compliance (GDPR, HIPAA, ISO27001).

5. Phased Execution Plan

   • Short-term: Optimize existing infrastructure and reduce cost.
   • Medium-term: Implement a hybrid or colocation strategy.
   • Long-term: Transition to automation and AI-driven operations. Focus on continuous optimization of workload placement, dynamic scalability, and alignment with evolving business needs and goals.

Challenges and solutions

How to approach the challenges and their impact on a data center

Sample challenges

Case study

Unlocking environmental sustainability and savings through data center transformation

Hitachi Vantara

INDUSTRY

Industrial Technology & Digital Infrastructure Services

SOURCE

Hitachi Vantara

Challenge

• Rising power and cooling costs: Hitachi Vantara faced escalating OpEx and an oversized, inefficient facility.
• Security and compliance needs: Mission-critical systems (e.g. Oracle ERP) required guaranteed control and uptime.
• Limited scalability in legacy DC: Aging racks and storage constrained growth and performance.
• IT skills and capacity bottlenecks: Manual operations and legacy tools increased the risk of downtime.

Solution

Hitachi Vantara consolidated 180 racks down to 74 by migrating to modern, high-density Hitachi VSP 5600 and DS 120/220 servers.

To reduce power demands, the organization optimized server room layout for airflow, replaced storage hardware, and upgraded networking.

It shifted noncritical workloads to the cloud but kept core ERP on-prem for data control and compliance.

It improved monitoring and automation to simplify operations and reduce manual intervention.

Results

• Reduced DC footprint by 59%, with power consumption halved and power usage effectiveness improved from 1.6 to 1.3.
• Achieved estimated 50% total cost savings, including OpEx and e-waste elimination.
• Enhanced security and reliability of core systems, supported by zero‑downtime deployment.
• Streamlined IT operations and boosted sustainability, laying the groundwork for future automation and ESG goals.

Execution planning and workload alignment

Turn strategy into infrastructure decisions that align with business goals.

This phase shifts from strategy to execution – helping you translate planning into concrete decisions around infrastructure modernization. At the center of this is a guided workbook activity designed to assess your current environment, constraints, and goals. By answering targeted questions, you’ll receive recommendations on optimal workload placement – whether that’s on-prem, in the cloud, at the edge, or a hybrid mix. The goal is to align each workload with the infrastructure option that best balances performance, compliance, cost, and scalability.

Workload location assessment

Evaluate workload characteristics to align placement with business priorities and infrastructure capabilities.

This activity guides you through a series of questions designed to determine the optimal hosting environment for your workloads – whether that’s on-prem, hybrid, edge, or public cloud. Use the workbook to evaluate factors such as:

• Security and compliance requirements.
• Application performance and latency sensitivity.
• Data residency or sovereignty.
• Cost constraints (CapEx vs. OpEx).
• Scalability and automation needs.

Download the Data Center Strategy Workbook

Document your current reference architecture

Establish a clear baseline for your existing infrastructure before planning the next step.

Before determining where your workloads belong, it’s critical to understand your current environment. Use this section of the workbook to capture key components of your data center reference architecture, including:

• Server types (rack, blade, tower).
• Storage options and hypervisor platforms.
• Database hosting models.
• Redundancy and backup strategies.
• Network connectivity and hybrid cloud readiness.
• Management platforms, software licenses, and power usage.

Download the Data Center Strategy Workbook

Costs to consider apart from hardware – power consumption and real estate

Power consumption costs are a significant portion of the total cost of ownership (TCO) of an on-prem data center. Energy costs, including electricity for servers, cooling systems, and other IT equipment, can take up a significant portion of your operating budget. By understanding and optimizing power consumption, organizations can control costs and use financial resources efficiently and responsibly.

See Tab 5, Power Consumption Tracker, in the Data Center Strategy Workbook