Reduce cost, risk, and carbon waste by shrinking complexity without slowing teams down.
Walk into almost any modern organization and you will find it. The “zoo.” A sprawling collection of applications, tools, integrations, and exceptions. Each one was introduced to solve a real problem. Each one made sense at the time. Together, these systems—often numbering in the hundreds at a large enterprise—form an environment that is expensive to operate, difficult to change, and slow to deliver value. This is not just a technology issue. It is a structural constraint on the business, especially as organizations grow in size.
The important shift is this: Simplification is not a cleanup task. It is a delivery strategy.
The zoo is more than tool sprawl
When engineers describe their architecture as complex, they are rarely talking about a single issue. They are describing a pattern of friction that shows up across the system:
- Multiple systems solving the same capability
- Dense dependency graphs with unclear blast radius
- Integration sprawl across APIs, pipelines, and file transfers
- Inconsistent tooling and patterns between teams
- Unclear ownership of systems and interfaces
- Delivery slowed by coordination and risk management overhead
Taken individually, these issues compound over time. However, they tend to reinforce one another over time. What starts as a few reasonable decisions becomes a network of interdependencies that is hard to reason about and even harder to evolve.
Moreover, fragmented and siloed systems also drain productivity. In fact, one study found employees spend about 2.4 hours per day searching for information across disjointed applications, while inefficient and disconnected workflows contribute to an overall 24% drop in output.
As a result, architectural complexity becomes more than a technical concern—it increasingly impacts organizational agility, efficiency, and the ability to scale effectively.
There is also a less visible but equally important effect: Waste. Complexity increases unnecessary compute usage, storage growth, data movement, and duplicated engineering effort. It consumes resources without improving outcomes. For example, industry surveys have found roughly 30% of servers in enterprise data centers are “comatose” (idle), yet still running and drawing power—a clear cost and energy drain that yields no value.
Why complexity accumulates
Most organizations do not intentionally design complex systems. Instead, they accumulate complexity through local optimization. The incentives are familiar:
- Feature delivery is prioritized over decommissioning
- Exceptions are faster than alignment in the short term
- Mergers and reorganizations introduce overlapping systems
- New tools reduce immediate friction for individual teams
- The cost of complexity is delayed and rarely visible in planning cycles
At first glance, these decisions appear rational—and often they are. After all, they help teams move faster, address immediate challenges, and maintain delivery momentum. In many cases, complexity is simply the byproduct of success under pressure.
However, as these decisions accumulate, their long-term impact becomes more apparent. Teams ship quickly, solve immediate problems, and move forward. Yet over time, the landscape becomes harder to manage, more expensive to run, and increasingly resistant to change.
As a result, what once enabled speed and agility can gradually evolve into a source of operational drag, making future transformation efforts significantly more difficult.
The four taxes of complexity
Complexity introduces costs that are not always explicit but are consistently present:
- Speed Tax: Lead time increases as systems become more interconnected. A single change may require coordination across multiple teams, expanded testing scopes, and additional release controls. (High-performing DevOps teams can deploy changes in hours, whereas slower organizations might take weeks or months.)
- Risk Tax: A larger system surface area increases exposure. Inconsistent security practices, outdated components, and fragile dependencies create conditions where small issues can cascade into larger failures.
- Cost Tax: Operational costs grow nonlinearly. Each additional system introduces licensing, support, monitoring, and integration overhead. Much of this effort maintains the status quo rather than creating new value. (Enterprises spend about $3,500 on SaaS per employee each year; redundant or underutilized tools translate directly into wasted budget.)
- Waste Tax: Duplicate pipelines, idle infrastructure, and redundant storage increase energy consumption and environmental impact. Engineers experience higher cognitive load, more interruptions, and heavier reliance on undocumented knowledge.
These taxes rarely appear in a single report, but they shape how fast and how well an organization can deliver value.
Simplification enables delivery
There is a common belief that simplification is something to address after delivery goals are met. However, in practice, simplification is what makes those goals achievable.
Reducing complexity decreases:
- The number of decisions teams need to make
- The level of cross-team coordination required
- The volume of approval and governance steps
- The number of potential failure modes
- The time required to diagnose and recover from incidents
Ultimately, simplification reduces friction in the system. In turn, less friction leads to faster, safer, and more predictable delivery. In fact, organizations that streamline their toolchains and architectures have been shown to deploy far more frequently (on-demand or daily versus monthly) and to recover from failures much faster (often within an hour, compared to days for low-performing peers).
A practical approach to simplification
You do not need a multi-year transformation program to begin. Instead, simplification starts with visibility and deliberate decisions about where complexity adds value—and where it does not.
1. Make the Landscape Visible – You cannot manage complexity without visibility. However, perfect inventories are not required.
Start with three lightweight artifacts:
- A capability map that reflects core business functions
- A mapping of systems to those capabilities
- A high-level view of dependencies and data flows
Then, add two key attributes for each system:
- A clearly identified owner
- A lifecycle state (Invest, Tolerate, or Exit)
To incorporate sustainability, identify hotspots such as:
- High compute utilization or inefficient workloads
- Rapid and unmanaged storage growth
- Heavy or unnecessary data movement
- Duplicate pipelines performing the same work
Together, these elements create an actionable view of the environment without slowing teams down.
2. Reduce and Rationalize – Once visibility is in place, simplification becomes a series of structured decisions.
Evaluate systems across five dimensions:
- Business value and strategic importance
- Operational cost (licenses, support effort)
- Risk profile (security and reliability)
- Ease of change and adaptability
- Resource efficiency (compute, storage, data)
Based on these factors, assign each system a path:
- Invest in systems that are strategic and scalable
- Contain systems that are stable but not worth further expansion
- Exit systems that no longer justify their cost or risk
A practical starting point is duplicate capability clusters. Consolidating overlapping tools—such as multiple integration platforms, workflow engines, or observability stacks—often produces immediate gains: reduced cost, improved operability, and lower resource consumption.
Making simplicity stick
3. Prevent Regrowth – Reducing complexity is only half the challenge. Without guardrails, complexity tends to return.
Therefore, design the environment so the preferred path is the easiest one:
- Define standard architectures and reusable patterns
- Provide preconfigured CI/CD, observability, and security tooling
- Maintain a clear service catalog with guidance on when to use each option
- Introduce lightweight governance for new technology adoption
- Establish clear decision ownership for introducing new tools
Likewise, embed sustainability into these defaults:
- Autoscaling and right-sizing as baseline configurations
- Data retention and storage tiering policies
- Minimization of unnecessary data movement
- Efficient scheduling of batch and background workloads
Ultimately, the goal is not to control every decision. Rather, it is to reduce cognitive load while guiding teams toward consistent, scalable, and efficient solutions.
Measuring progress
Progress should be tracked using a focused set of outcome-driven metrics:
- Simplification – e.g. Reduction in systems per capability; fewer integration points and interfaces; higher percentage of systems with clear ownership and lifecycle state.
- Delivery Performance – e.g. Shorter lead time for changes (moving from weeks to days, or even <1 day for elite teams); lower change failure rate (targeting <5% versus ~50% in low-performing environments); faster mean time to recovery (restoring service in hours rather than days); increased deployment frequency (from monthly or quarterly to daily/on-demand).
- Operational Efficiency – e.g. Improved ratio of build vs. run effort; reduced operational toil and on-call load; lower unit cost per transaction or customer served.
- Resource Efficiency – e.g. Reduced idle or underutilized compute; controlled and intentional storage growth; lower volume of redundant data movement.
These metrics provide a balanced view of progress across speed, cost, risk, and sustainability.
Summary: Key impacts & sustainability benefits
In summary, Schneider Electric’s enterprise-wide simplification program has delivered significant gains, especially considering the scale of its IT landscape. Key outcomes include:
A leaner, faster, and more efficient landscape
- Smaller Footprint: ~37% reduction in the enterprise application portfolio over a few years (from ~770 core applications in 2020 to ~480 by 2026), consolidating hundreds of systems and minimizing technical debt. As a result, the landscape is less duplicative and significantly easier to manage.
- Faster Delivery: Accelerated release cycles by removing friction. Today, many teams now deploy software daily or on-demand instead of monthly, with significantly shorter lead times and quicker incident recovery (hours rather than days).
- Cost Savings: Multi-million euro operational savings (over €10M cumulative) from rationalizing systems and licenses. At enterprise scale, even a modest reduction in application sprawl can translate into substantial cost avoidance.
- Lower Risk & Debt: Simplification has reduced legacy dependencies and overlapping technologies, cutting maintenance overhead and security exposure. Consequently, the IT foundation becomes more resilient, adaptable, and easier to evolve.
Sustainability through simplification
- Sustainability Gains: Eliminated wasteful resources, shrinking IT’s carbon footprint. Retiring redundant and idle infrastructure (noting that an idle server still draws ~30–60% of its full power) has reduced energy consumption, cooling needs, and associated CO₂ emissions across data centers.
- Scale Amplifies Benefits: At Schneider Electric’s scale, simplification yields non-linear returns. The larger and more complex the starting landscape, the greater the payoff in speed, cost, and sustainability. Simplification transforms a big organization’s size from a burden into an advantage, enabling agility and efficiency that smaller, less complex organizations can rarely match.
This executive focus on simplification shows that taming the “zoo” isn’t just housekeeping—it’s how large enterprises like Schneider Electric accelerate digital delivery, improve efficiency, and advance sustainability in a way that grows more powerful with scale.
Sources: Industry research (DORA, CIO Dive, SustainableIT) and Schneider Electric internal results.
About the author
Irine Joy, DCR Chief of Staff & Transformation Leader
Irine Joy is the Chief of Staff and Transformation Leader for Digital Customer Relationship at Schneider Electric, where she drives strategic programs, supports executive leadership, and delivers impactful digital experiences for users and customers.
With over eleven years of experience in digital applications and transformation initiatives, she has built a strong track record in supplier and buyer digitization. Her work consistently enhances efficiency, productivity, and collaboration across sourcing, contracting, and relationship management processes.
Irine combines strong functional expertise with deep technical capabilities in data warehousing, data visualization, and ETL. She is proficient in tools such as Informatica, SQL, Power BI, QlikView, Teradata, and Alteryx, enabling her to translate data into actionable insights and support data-driven decision-making.
She has further strengthened her leadership through the Transforming Schneider Leadership program at INSEAD, reinforcing her ability to lead transformation at scale.
Driven by a passion for innovation, Irine focuses on leveraging her expertise to accelerate value creation and support Schneider Electric’s ambition as a global leader in energy management and automation.
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