Chapter 12: IT Service Models for North America
Introduction: The Delivery Model Dilemma
The conversation with the CIO had started promisingly. She was impressed with your proposal for a 5-plant MES rollout across Michigan, Texas, and two Mexico plants. But then came the question that derailed everything:
"So I see your team is 80% offshore in India with a 10.5-hour time difference from our Michigan headquarters. When Line 2 goes down at 3 AM, how exactly does your team in Bangalore help our operators in Detroit?"
You tried to explain: "We have 24×7 coverage... our team is trained... we use remote desktop tools..." But her skepticism was visible.
"Let me tell you what happened with our last offshore partner. We had a P1 production incident at 2 AM. It took 45 minutes just to get someone on the phone who understood our MES architecture. By the time they diagnosed the issue—incorrectly, as it turned out—we'd lost $127,000 in downtime. We fixed it ourselves at 6 AM when our local IT person arrived. Never again."
She's not alone. This conversation happens daily in manufacturing IT.
Here's the challenge: Manufacturing requires 24×7 support with deep domain knowledge, while cost pressures demand global delivery efficiency. The companies that win are those that design hybrid delivery models that balance cost, capability, timezone coverage, and manufacturing domain expertise.
This chapter explores how to structure IT service delivery for North American manufacturing:
- Onshore, Nearshore, and Offshore Models – Trade-offs and when to use each
- Hybrid Delivery Models – Blended teams that combine the best of each approach
- Pricing Models – T&M, fixed price, subscription, outcome-based
- Service Level Agreements (SLAs) – Defining and measuring what matters
- Delivery Models for Multi-Plant Operations – Scaling across sites
- Staff Augmentation vs. Managed Services – When to use each model
- Building Delivery Capability – From boutique to enterprise scale
The goal: design delivery models that reduce cost while increasing quality, speed, and manufacturing domain expertise.
12.1 Geographic Delivery Models
Onshore, Nearshore, Offshore: The Trade-Offs
Table 12.1: Geographic Delivery Model Comparison
| Model | Geography | Cost (Relative) | Best For | Challenges | When to Use |
|---|---|---|---|---|---|
| Onshore | U.S. and Canada | 100% (baseline: $150-$250/hour) | On-site support, workshops, go-lives, change management, domain-heavy work | High cost; talent scarcity in manufacturing IT | Client-facing roles, on-site deployment, domain expertise, regulated industries |
| Nearshore (Mexico) | Mexico | 40-60% ($60-$120/hour) | Development, testing, support with timezone overlap, bilingual teams | Lower manufacturing domain maturity; some U.S. clients resist | Development, testing, L2 support, USMCA-aligned delivery |
| Nearshore (Latin America) | Colombia, Argentina, Costa Rica | 35-55% ($50-$110/hour) | Software development, data engineering, cloud engineering | Timezone overlap good; manufacturing domain limited | Cloud/data work, general software development |
| Offshore (India, Eastern Europe) | India, Poland, Romania | 25-40% ($40-$80/hour) | Development at scale, testing, data engineering, infrastructure | Time zone gap; limited manufacturing knowledge; communication overhead | Backend development, testing, data engineering, infrastructure automation |
| Offshore (APAC) | Philippines, Vietnam | 30-45% ($45-$90/hour) | Application support, help desk, testing, documentation | Timezone gap; manufacturing domain limited | L1/L2 support, testing, documentation |
Key insight: Cost is just one dimension. Manufacturing domain expertise, timezone coverage, and rapid site response matter more for operational systems (MES, SCADA, QMS) than for back-office systems (ERP, PLM).
12.2 Hybrid Delivery Models for Manufacturing
The "Pod" Model: Onshore Leads + Nearshore/Offshore Delivery
Most successful manufacturing IT services firms use a blended pod model:
Table 12.2: Hybrid Delivery Pod Structure
| Role | Location | % of Team | Responsibilities | Why Located Here |
|---|---|---|---|---|
| Solution Architect | Onshore (client site or nearby) | 5-10% | Requirements, design, client relationship, site deployment support | Client trust; domain knowledge; rapid site response |
| Delivery Manager / Scrum Master | Onshore or Nearshore | 5-10% | Project management, stakeholder communication, risk management | Timezone overlap with client; communication skills |
| Manufacturing SMEs (2-3) | Onshore or Nearshore | 10-15% | Domain expertise (MES, OT, quality, supply chain), training, UAT support | Manufacturing knowledge; plant floor experience |
| Lead Developers (2-3) | Onshore or Nearshore | 15-20% | Technical leadership, code reviews, integration architecture | Complex problem-solving; mentorship; client interaction |
| Developers (5-10) | Nearshore and Offshore mix | 40-50% | Feature development, integrations, bug fixes | Cost efficiency; scale; follow-the-sun development |
| QA Engineers (2-4) | Nearshore or Offshore | 10-15% | Test automation, regression testing, performance testing | Cost efficiency; parallel test execution |
| DevOps / Infrastructure (1-2) | Nearshore or Offshore | 5-10% | CI/CD, environment management, monitoring | Automation focus; around-the-clock coverage |
Total team: 15-25 people blended across locations
Example blended cost:
- 10% onshore at $200/hour = 160 hours/month × $200 = $32,000
- 30% nearshore at $80/hour = 480 hours/month × $80 = $38,400
- 60% offshore at $50/hour = 960 hours/month × $50 = $48,000
- Total: $118,400/month for 1,600 blended hours = $74/hour blended rate
Compare to 100% onshore: 1,600 hours × $200 = $320,000/month (2.7× more expensive)
12.3 Work Allocation Strategy
What Work Goes Where?
Not all work is suitable for offshore delivery. Use this framework to allocate work:
Table 12.3: Work Allocation Framework by Location
| Work Type | Proximity Needed | Domain Knowledge Needed | Onshore | Nearshore | Offshore | Rationale |
|---|---|---|---|---|---|---|
| On-site deployment & go-live | High | High | ✓ Primary | ✓ Support | ✗ | Must be on plant floor; understand manufacturing processes |
| Requirements workshops | Medium-High | High | ✓ Primary | ✓ If bilingual | ✗ | Face-to-face builds trust; nuance matters |
| Solution architecture & design | Medium | High | ✓ Primary | ✓ Contribute | ✓ Review | Onshore leads; others contribute |
| Manufacturing domain SME work | Medium | High | ✓ | ✓ (Mexico plants) | ✗ | Requires plant floor experience |
| Integration development (ERP↔MES) | Low | Medium-High | ✓ Lead | ✓ Primary | ✓ Support | Nearshore can lead; offshore supports |
| Custom development (reports, workflows) | Low | Medium | ✓ Spec | ✓ Primary | ✓ Primary | Detailed specs enable offshore |
| Testing (functional, integration, regression) | Low | Medium | ✓ UAT | ✓ Lead | ✓ Execute | Offshore execution; nearshore lead; onshore UAT |
| Infrastructure & DevOps | Low | Low-Medium | ✓ Design | ✓ Implement | ✓ Execute | Automated workflows enable offshore |
| Data engineering & migration | Low | Medium | ✓ Spec/validate | ✓ Primary | ✓ Execute | Clear data models enable offshore |
| Documentation & training materials | Low | High | ✓ Review | ✓ Create | ✓ Format | Manufacturing knowledge needed for content |
| 24×7 support (L1 Help Desk) | Low | Low | ✗ | ✓ (Americas hours) | ✓ (EMEA/APAC hours) | Follow-the-sun coverage |
| Support (L2 Application) | Low | Medium-High | ✓ Escalation | ✓ Primary | ✓ Tier 2 | Manufacturing context needed for L2+ |
| Support (L3 Subject Matter Expert) | Medium | High | ✓ Primary | ✓ Limited | ✗ | Deep expertise required |
Critical principle: Don't offshore work that requires rapid site response or deep manufacturing domain knowledge. Offshore work that is repeatable, well-documented, and doesn't require real-time plant floor interaction.
12.4 Pricing Models
Choosing the Right Commercial Model
Table 12.4: Pricing Model Comparison
| Model | How It Works | Best For | Advantages | Disadvantages | Client Preference | Vendor Risk |
|---|---|---|---|---|---|---|
| Time & Materials (T&M) | Bill actual hours at agreed rates (e.g., $180/hour onshore, $70/hour nearshore) | Discovery, undefined scope, staff augmentation | Flexibility; easy to start; low vendor risk | Unpredictable cost; no incentive to be efficient | Low (open-ended cost) | Low (paid for all effort) |
| T&M with Cap | Bill hours up to a maximum cap (e.g., not to exceed $500K) | Moderately defined scope with unknowns | Flexibility with cost certainty; shared risk | Complex tracking; disputes if cap hit | Medium (some cost certainty) | Medium (cap limits revenue) |
| Fixed Price | Fixed fee for defined deliverables (e.g., $1.2M for MES implementation per SOW) | Well-defined scope; client wants cost certainty | Cost predictability; vendor incentive to be efficient | Scope disputes; change orders; vendor assumes risk | High (known cost) | High (scope creep, estimation errors) |
| Milestone-Based | Payment tied to milestones (e.g., 20% at design approval, 30% at FAT, 30% at SAT, 20% 30 days post go-live) | Phased projects; aligns payments to value delivery | Risk shared; pay for progress | Milestone definition disputes; delays impact cash flow | High (pay for value delivered) | Medium (delayed payments if milestones slip) |
| Subscription / Managed Services | Fixed monthly/annual fee for defined services and SLAs (e.g., $45K/month for MES app management) | Ongoing support and operations | Predictable cost; vendor incentive to automate; long-term relationship | Annual escalations; scope creep | High (budget predictability) | Medium (must manage scope, automate to maintain margin) |
| Outcome-Based / Gain-Share | Payment tied to business outcomes (e.g., % of OEE improvement, cost savings achieved) | Strategic partnerships; high-value transformations | True alignment; client pays only for results | Complex metrics; long payback; high vendor risk | Very High (pay for results) | Very High (outcome dependent on client factors outside vendor control) |
| Hybrid (T&M + Fixed + Subscription) | E.g., fixed price for pilot, T&M for customizations, subscription for managed services | Complex, multi-phase engagements | Flexibility + certainty where appropriate | Complexity to manage | Medium-High | Medium |
Recommended approach for manufacturing:
- Assessments & Pilots: T&M or fixed price
- Implementations: Fixed price or milestone-based (clients want cost certainty)
- Managed Services: Subscription with tiered SLAs
- Strategic Partnerships: Hybrid with outcome-based components
12.5 Service Level Agreements (SLAs)
Defining What Matters
Manufacturing SLAs must align to business impact, not just IT metrics.
Table 12.5: Manufacturing-Aligned SLA Framework
| Service | SLA Metric | Business Context | Tier 1 (Bronze) | Tier 2 (Silver) | Tier 3 (Gold / Mission-Critical) |
|---|---|---|---|---|---|
| MES Application Availability | % uptime during production hours | Line downtime = $15K-$50K/hour lost revenue | 99.0% (7.2 hours downtime/month) | 99.5% (3.6 hours/month) | 99.7% (2.2 hours/month) |
| P1 Incident Response (production down) | Time to respond (human on call) | Every minute counts during production outage | <30 minutes | <15 minutes | <10 minutes |
| P1 Incident Resolution | Mean time to resolution (MTTR) | Production stopped until resolved | <4 hours | <2 hours | <1 hour |
| P2 Incident Response (degraded performance) | Time to respond | Production continues but at risk | <2 hours | <1 hour | <30 minutes |
| P2 Incident Resolution | MTTR | Workaround acceptable short-term | <8 hours (business hours) | <4 hours | <2 hours |
| P3/P4 (minor issues, enhancements) | Response and resolution | Non-production-impacting | <1 business day / 5-10 business days | <4 hours / 3-5 business days | <2 hours / 1-3 business days |
| Scheduled Changes | Change success rate | Failed changes cause downtime | 90% success | 95% success | 98% success |
| Monitoring & Alerting | Time to detect (MTTD) | Proactive detection prevents outages | <30 minutes | <15 minutes | <5 minutes |
Table 12.6: SLA Penalties and Credits
| SLA Breach | Penalty / Service Credit | Example |
|---|---|---|
| Availability <99.0% (2 consecutive months) | 10% monthly fee credit | $50K/month managed services → $5K credit |
| P1 Response SLA miss (>3 in a month) | 5% monthly fee credit | Patterns indicate support inadequacy |
| P1 Resolution SLA miss (>2 in a month) | 10% monthly fee credit + escalation to exec steering | Serious service delivery issue |
| Chronic underperformance (3 consecutive months) | Right to terminate without penalty + transition assistance at no cost | Client needs exit path if service persistently poor |
Key principle: SLAs should hurt enough to drive accountability but not bankrupt the vendor. Typical penalty caps: 20-30% of monthly fees.
12.6 Delivery Models for Multi-Plant Operations
Scaling Across Sites
Table 12.7: Multi-Plant Delivery Models
| Delivery Approach | How It Works | Pros | Cons | Best For |
|---|---|---|---|---|
| Plant-by-Plant Sequential | Implement at Plant 1, then Plant 2, etc., with 3-6 months between each | Learn and refine with each plant; less resource-intensive | Slow; last plants wait years; inconsistent versions | Small # of plants (2-5); heterogeneous plants requiring customization |
| Pilot + Rapid Rollout | 6-month pilot at Plant 1, then parallel rollout to remaining plants (3-6 plants simultaneously) | Faster; template-driven; economies of scale | High resource demand; complexity managing parallel deployments | 5-15 plants; standardized manufacturing processes |
| Cluster Approach | Group plants into clusters (e.g., by geography, product line) and roll out cluster-by-cluster | Balances speed and learning; manageable resource demand | Moderate timeline; need to manage cluster differences | 10-30 plants; some variability across clusters |
| Global Template + Local Variation | Define global standard (80%), allow local variation (20%), deploy via regional teams | Standardization + flexibility; enables global analytics; sustainable support model | Upfront template design effort; governance to prevent template drift | 20+ plants; multinational; need global visibility |
| Factory-in-a-Box | Pre-configured, containerized solution deployed with minimal customization | Fastest; repeatable; very low cost per plant | Least flexible; requires high process standardization | Highly standardized plants (e.g., electronics assembly, food packaging) |
Recommended approach: Pilot + Template + Rapid Rollout for most manufacturers with 5-20 plants.
12.7 Staff Augmentation vs. Managed Services
Table 12.8: Staff Aug vs. Managed Services Comparison
| Dimension | Staff Augmentation | Managed Services | When to Use Each |
|---|---|---|---|
| Model | You hire our people to work under your direction | We own outcomes and deliver services with SLAs | Staff Aug: Gaps in your team, need flexibility. Managed Services: Offload operations entirely |
| Control | Client has full control; directs day-to-day work | Vendor manages team; client defines outcomes and SLAs | Staff Aug: Want control. Managed Services: Want accountability |
| Accountability | Client accountable for outcomes | Vendor accountable for outcomes | Staff Aug: Client owns success/failure. Managed Services: Vendor owns |
| Pricing | Hourly or monthly rate per person | Fixed monthly fee for service delivery with SLAs | Staff Aug: Variable scope. Managed Services: Predictable cost |
| Team Stability | Individuals may rotate; client manages | Vendor provides stable team; handles attrition | Staff Aug: Less stable. Managed Services: Vendor buffers attrition |
| Scalability | Client must scale team up/down | Vendor scales resources transparently to meet SLAs | Staff Aug: Manual scaling. Managed Services: Vendor auto-scales |
| Best For | Short-term needs, specific skill gaps, co-located teams | 24×7 support, application management, infrastructure operations | Staff Aug: Projects, temporary capacity. Managed Services: Ongoing operations |
Evolution path: Many relationships start with Staff Augmentation (low-risk, try before you buy), evolve to Managed Services (proven capability, client wants to offload burden).
Chapter Summary
Table 12.9: Chapter 12 Key Takeaways
| Topic | Key Insight |
|---|---|
| Geographic Models | Onshore ($150-$250/hr) for domain expertise and site work; Nearshore Mexico ($60-$120/hr) for development with timezone overlap; Offshore ($40-$80/hr) for scale. Manufacturing prefers hybrid blended models. |
| Hybrid Pods | Onshore solution architects and SMEs + Nearshore/Offshore development teams. Typical blended rate: $70-$90/hr vs. $200/hr fully onshore. |
| Work Allocation | On-site deployment, workshops, and manufacturing SME work must be onshore/nearshore. Development, testing, and infrastructure can be offshore with proper specs. |
| Pricing Models | T&M for discovery; Fixed Price or Milestone for implementations; Subscription for Managed Services. Manufacturers want cost certainty. |
| SLAs | Align SLAs to business impact (production downtime, not just uptime %). P1 response <15 min, resolution <2 hours for mission-critical. Include penalties to drive accountability. |
| Multi-Plant Delivery | Pilot at Plant 1, templatize, then rapid rollout to Plants 2-N. Standardize 80%, localize 20%. |
| Staff Aug vs. Managed Services | Staff Aug: client controls, vendor provides people. Managed Services: vendor owns outcomes via SLAs. Transition from Staff Aug → Managed Services as trust builds. |
Discussion Questions
-
Offshore Trade-Offs: Is offshore delivery viable for mission-critical manufacturing systems (MES, SCADA)? Under what conditions?
-
Nearshore Mexico: How do you build manufacturing domain expertise in your Mexico delivery centers to compete with onshore-only competitors?
-
Blended Rate Transparency: Do you show clients the blended rate ($80/hr) or itemized rates by location (onshore $200, nearshore $80, offshore $50)?
-
SLA Design: How do you design SLAs that drive the right behavior without creating a "gotcha" relationship?
-
Multi-Plant Complexity: Client has 15 plants with 8 different MES platforms. Do you standardize or support heterogeneity?
-
Managed Services Transition: You've been doing staff aug for 2 years. How do you transition the relationship to managed services with SLA accountability?
-
Hidden Offshore Costs: What's the true TCO of offshore delivery when you account for coordination overhead, travel, rework, and knowledge loss?
-
Client Resistance: Client says "We only work with U.S.-based teams due to security concerns." How do you respond if you have nearshore/offshore delivery?
Further Reading
Books:
- The World Is Flat by Thomas L. Friedman (globalization)
- Offshoreology by Dr. Martyn Hart (offshore delivery best practices)
- Managed Services in a Month by Karl Palachuk
Industry Resources:
- Everest Group: Global delivery model research
- ISG: Managed services and outsourcing insights
- Deloitte: Global manufacturing delivery models
- IAOP (International Association of Outsourcing Professionals)
What's Next?
Chapter 13: Structuring the Practice covers how to build and scale a manufacturing IT services practice:
- Practice structure: Centers of Excellence, verticals, horizontal capabilities
- Hiring: What roles, what skills, where to find manufacturing IT talent
- Training and certification: Building domain expertise at scale
- Go-to-market strategy: How to generate leads and build pipeline
- Partnerships: Rockwell, Siemens, SAP, Microsoft, AWS—which ones matter and how to leverage them
- Scaling from $2M to $20M to $200M in manufacturing IT services revenue