In large oil and gas organizations, workforce visibility is often a lot harder than it should be.
SOW and contingent talent are essential across enterprise business units, supporting both ongoing work and project-based initiatives. But as organizations scale, workforce data spreads across teams, vendors, and systems, making it harder to see total spend, track compliance, or forecast accurately.
This fragmentation creates friction for hiring managers, procurement, and finance: information lives in different places; reporting is manual; and no one has a complete, real-time view of SOW and contingent talent across the organization.
As a result, many enterprise teams start looking for ways to bring more structure and consistency to how this work is managed.
How SOW and contingent talent are typically used at scale
In enterprise oil and gas environments, SOW generally falls into two categories. The first is time-and-materials work, where consulting firms or service providers supply talent aligned with ongoing needs. The second is milestone-based project work, structured around defined deliverables, timelines, or SLAs.
Well established and widely used across business units, both models often exist alongside W-2 and other contingent labor models, sometimes within the same organization or project portfolio.
The challenge isn’t the model itself. What it really comes down to is managing all of this consistently when multiple teams, vendors, and systems are involved.
Where visibility starts to break down
As organizations grow, workforce data rarely stays centralized.
Hiring managers may track work progress in one system, while vendors submit hours or milestone updates elsewhere. Compliance documentation lives in separate tools or spreadsheets, and finance relies on reports that lag on actual activity.
And when this information is fragmented across business units and providers, it becomes difficult for anyone to answer basic questions with confidence. For instance, procurement can’t easily assess consistency, finance struggles to forecast, and leadership lacks a consolidated view of total workforce spend.
Research from Deloitte’s 2025 Global Human Capital Trends highlights how large organizations increasingly struggle with workforce complexity as data is spread across systems, vendors, and teams, making it harder for leaders to gain a coordinated view of their workforce and support decision-making at scale.
However, this isn’t unusual in enterprise environments. It’s a natural outcome of scale.
Compliance adds another layer of coordination
Oil and gas organizations operate in heavily regulated environments, where compliance requirements are generally well understood. But the challenge is coordinating those requirements across systems and stakeholders.
That often includes managing:
When credential tracking and compliance workflows aren’t centralized, delays are common, and approvals take longer than expected. Teams also lack real-time insights on who’s cleared to work (and where).
In the end, this coordination gap increases administrative effort and limits visibility into workforce readiness across business units.
Why fragmented data makes spend harder to manage
From a procurement and finance perspective, managing workforce spend becomes more difficult when SOW and contingent data lives in different places.
Without a unified view, teams struggle to:
PwC research has also found that many senior leaders lack a clear understanding of their total workforce cost when data is spread across different labor models, systems, and vendors—making it harder to manage spend and plan effectively at the enterprise level.
Even when SOW is being used appropriately, limited visibility can prevent organizations from understanding where small inefficiencies accumulate over time.
This is often when leadership asks for better reporting and clearer data—not to change existing models, but to manage them more effectively.
What clearer visibility enables
When SOW and contingent workforce data is brought into a more unified view, teams gain the ability to manage complexity without disrupting how work is delivered.
For example, clearer visibility helps organizations see SOW and contingent engagements in one place; track hours, milestones, and credentials consistently; standardize onboarding and compliance workflows; reduce manual reporting and reconciliation; and provide procurement and finance with reliable data.
Over time, this clarity supports better decision-making on how different engagement models are used, based on cost, risk, and operational needs. It also creates stronger governance around how SOW and contingent talent fit into the broader workforce strategy.
Centralizing workflows without disrupting existing models
Enterprise teams are understandably often cautious about disruption. Existing SOW relationships and delivery models, which serve important purposes, are not easily replaced.
That’s why many organizations focus on centralizing workflows rather than changing engagement structures, respecting how SOW is used today while making it easier to manage at scale.
A more streamlined approach typically includes things like:
What a smoother model looks like in practice
In a more coordinated workforce model, teams spend less time chasing information or reconciling reports. Instead, they have one place to understand who’s working (and under what model), as well as visibility into hours, milestones, credentials, and total workforce spend. They also gain more standardized compliance processes across business units and more predictable reporting for the procurement and finance teams.
For enterprise oil and gas organizations, this level of structure doesn’t remove complexity, of course. It makes it manageable. And over time, improved visibility and consistency create opportunities to reduce overall workforce spend without compromising on delivery.
If you’re looking to bring more visibility and consistency to how SOW and contingent talent are managed across business units, AllWork can help support that model. Learn more about contingent workforce management for oil and gas.
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