The Traditional Shared Services Model

For roughly two decades, labor arbitrage and shared services have operated in close alignment. Shared service organizations are built around functional expertise stacked in layers: infrastructure, security, application development and maintenance, compliance, and so on. Each layer has dedicated champions responsible for delivering that function cost-effectively and at a defined quality level.

Labor arbitrage fits naturally into this structure. Because the work is organized by function rather than by business outcome, tasks within each layer can frequently be performed more cost-effectively by offshore teams. The model rewards low unit costs per function and scales by adding people within those functional layers.

How DevOps Restructures the Stack

DevOps introduces a fundamentally different organizational construct. Instead of aligning work by functional expertise, DevOps aligns work by business service. Cross-functional teams own the entire delivery stack — development, testing, infrastructure, and operations — for a specific business capability.

A useful illustration is the treatment of infrastructure, application development, and testing. In a traditional shared services model, each of these is a separate functional silo with its own management chain. In a DevOps model, these workloads move into a software-defined environment where a single cross-functional team holds end-to-end responsibility. The functional stack effectively collapses into a unified, product-oriented team.

Why DevOps Is Disruptive to Labor Arbitrage

This restructuring creates three specific pressures on the shared services and labor arbitrage model:

1. Fewer people are needed. Automating infrastructure through software-defined environments and shifting operational responsibilities to the development team reduces the total headcount required. When you need fewer people overall, the cost advantage of offshore labor becomes proportionally less significant.
2. Teams gravitate toward the business. Because DevOps teams are aligned by business service, they require tight, continuous communication with business stakeholders. That communication need creates a natural pull toward co-location — same time zone, same building, or at minimum close proximity. The distributed, time-shifted model that underpins labor arbitrage works against this communication requirement. The “follow the sun” productivity argument, which relies on handing off work across time zones, does not translate well to DevOps, where synchronous collaboration is a core productivity driver.
3. The success metric changes. Shared service organizations optimize for low unit cost per function. DevOps teams optimize for high business impact delivered at speed. These are different objective functions, and they reward different organizational designs. As companies commit to genuine DevOps operating models, the metrics that justified labor arbitrage become less relevant.

Offshore DevOps: A Different Pattern

Some large technology organizations — Microsoft among them — do operate DevOps teams in offshore locations. However, the model they use differs materially from classical labor arbitrage. Rather than distributing individual functional specialists across locations, they relocate entire cross-functional teams offshore. The team remains co-located and autonomous; only its geography changes. This preserves the communication and collaboration properties that make DevOps effective, while still achieving geographic cost advantages.

This is a meaningful distinction. Moving a whole product team to a lower-cost location is not the same as disaggregating functional work and distributing it across offshore specialists. The former is compatible with DevOps principles; the latter largely is not.

What This Means for IT Service Delivery

Organizations evaluating or expanding their DevOps adoption should consider the following implications:

• Sourcing strategies need revisiting. Contracts and governance structures designed around functional shared services may not map cleanly onto DevOps team topologies. Re-examine sourcing assumptions as DevOps matures in the organization.
• Co-location or team-level offshoring should be the unit of analysis. If geographic cost savings are still a business requirement, evaluate moving complete product teams rather than individual functional roles.
• Measure business outcomes, not unit costs. Continuing to measure DevOps teams using shared-services metrics (cost per ticket, cost per function) will produce misleading signals. Adopt outcome-focused metrics: deployment frequency, lead time for changes, mean time to restore, and change failure rate.
• Automation investment reduces the labor base. Infrastructure-as-code, CI/CD pipelines, and test automation reduce repetitive manual work — the category of work most amenable to labor arbitrage. The more mature the automation, the smaller the pool of arbitrageable tasks.

Summary

DevOps does not simply speed up existing IT delivery processes — it restructures who does the work, how they are organized, and what they are optimizing for. The functional stack of the shared services model gives way to cross-functional teams aligned to business outcomes. As a consequence, the labor arbitrage equation that sustained shared services for two decades becomes progressively less applicable. Organizations that recognize this structural shift early will be better positioned to redesign their sourcing and governance models before legacy contracts and org structures become blockers to DevOps maturity.