Initializing SOI
Shared Services & GBS × Chief Financial Officer
Chief Financial Officer Guide:
Shared Services & GBS
For Chief Financial Officers in 2025, the mandate for Shared Services and Global Business Services (GBS) has fundamentally shifted. The era of pure labor arbitrage—simply lifting and shifting work to lower-cost geographies—is effectively over. Today, the CFO faces a paradoxical challenge: while cost reduction remains the primary driver for 90% of organizations, only 41% of companies believe their shared services centers actually create value, according to 2024 data from Auxis. This 'Value Perception Gap' represents a critical liability for finance leaders who must justify continued investment to the board. The traditional GBS model is under pressure from three converging forces: the reversal of global consolidation trends due to geopolitical risk, the urgent demand for Generative AI integration, and a talent crisis where 84% of GBS leaders expect Gen Z recruits to leave within three years.
Furthermore, the operational reality in many organizations remains opaque. Requests for Finance, HR, and IT support still arrive via unstructured channels like email and chat, creating a 'black box' of service delivery that defies measurement. Without a unified operating system that links intake to delivery, CFOs lack the visibility required to optimize capital allocation or prove ROI. This guide moves beyond high-level theory to provide a tactical roadmap for the modern CFO. We analyze why only 25% of shared services leaders consider their organizations 'mature' despite decades of investment, and we outline the specific frameworks required to transform GBS from a back-office cost center into a strategic engine of enterprise value. Drawing on data from Deloitte, SSON, and Auxis, we examine the shift toward geo-aware operating models that prioritize resilience over centralization. We will explore how to close the gap between technology investment and utilization, specifically regarding RPA and process mining, where sunk costs often sit idle. This is not a sales pitch; it is a peer-to-peer strategic guide for navigating the complexities of modern GBS leadership.
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The Friction Points.
The 2025 landscape for Shared Services and GBS is defined by structural inefficiencies that prevent CFOs from realizing the full ROI of their transformation efforts. Through our analysis of current market data and operational realities, we have identified five core challenges that create the 'Value Perception Gap.'
First is the 'Black Box' of Work Intake. In many organizations, up to 70% of service requests bypass formal ticketing systems, arriving instead through email, instant messaging, or hallway conversations. This lack of structured intake makes it impossible to accurately measure demand, forecast capacity, or calculate the true cost-to-serve. When commercial teams spend upwards of 50% of their time on non-core administrative tasks (Deloitte Switzerland), it indicates that the GBS model is failing to absorb the workload it was designed to handle. The business impact is a dual loss: GBS resources are underutilized due to poor visibility, while high-value front-office talent wastes expensive hours on low-value tasks.
Second is the Technology Utilization Gap. While 58% of organizations are aggressively pursuing Generative AI (Deloitte), many are building on shaky foundations. ProHance data reveals that only 25% of shared services operate at advanced maturity. A common scenario involves CFOs approving significant CAPEX for RPA and process mining tools that ultimately see utilization rates below 40%. The problem is rarely the technology itself, but rather the lack of standardized processes to apply it to. Automating a broken process only accelerates the creation of errors. This results in 'zombie bots' and shelfware that depreciate without returning value.
Third is the Talent and Retention Crisis. The labor arbitrage model relied on a steady stream of low-cost, compliant talent. However, with 84% of leaders expecting Gen Z recruits to leave within three years (Auxis), the cost of turnover is eroding the savings margin. In APAC and Eastern Europe, wage inflation and competition have narrowed the arbitrage gap. For the CFO, this manifests as unpredictable OPEX and a constant drain on institutional knowledge, forcing a reliance on expensive contractors to maintain SLAs.
Fourth is the Fragmentation of Service Standards. Regional centers often operate as fiefdoms with divergent workflows. A 'Procure-to-Pay' process in the Warsaw center may look completely different from the same process in Manila or Costa Rica. This inconsistency makes it impossible to implement a global standard or deploy a single automation solution across the enterprise. The financial impact is the cost of redundancy: paying for three different solutions to solve the same problem three times.
Fifth is the Geopolitical Risk to Consolidation. For years, the trend was to consolidate into 5-7 mega-hubs. SSON research indicates this trend has reversed. Rising global tariffs, data sovereignty laws in the EU, and geopolitical instability are forcing a distributed model. CFOs who over-consolidated in single regions now face significant business continuity risks. The challenge is how to maintain control and visibility across a fragmented, decentralized footprint without exploding overhead costs.
The Solution
A Smarter Operating System.
To bridge the gap between cost containment and value creation, CFOs must implement a 'Service-to-Value' operating framework. This approach treats GBS not as a collection of people in low-cost locations, but as a digital product platform that serves the enterprise. The transformation requires a four-phase execution strategy.
Phase 1: Unified Intake and Orchestration (The 'Digital Front Door'). The first step is eliminating the 'black box' of email. Organizations must implement a unified intake layer—a single interface for all Finance, HR, and IT requests. This is not just a ticketing system; it is an orchestration layer that uses AI triage to route work. If a request is standard (e.g., 'invoice status'), it is routed to a bot. If complex, it goes to a specialist. By forcing 100% of demand through this digital channel, the CFO gains immediate visibility into who is asking for what, and at what volume. Decision Logic: If unstructured intake > 30%, prioritize Orchestration Layer deployment immediately.
Phase 2: The 'Tower Scorecard' and Process Mining. Once demand is visible, delivery must be transparent. Leading CFOs are moving beyond basic SLAs (Service Level Agreements) like 'speed to answer' toward XLAs (Experience Level Agreements) and business outcomes. A Tower Scorecard for Finance Ops should not just report 'invoices processed' but 'working capital impact' and 'duplicate payments prevented.' This requires deploying process mining tools not as a one-off audit, but as a continuous monitoring layer. This highlights bottlenecks in real-time. Framework: Use the DMAIC (Define, Measure, Analyze, Improve, Control) methodology to standardize processes across regions before attempting automation.
Phase 3: The Automation Value Chain. With standardized processes, automation shifts from 'random acts of digital' to strategic deployment. The CFO must enforce a strict governance model where automation ideas are prioritized based on 'Dollar Impact per Tower.' Instead of asking 'Can we automate this?', the question becomes 'Does automating this release cash or reduce risk?' This phase involves clearing the backlog of technical debt and ensuring that existing RPA licenses are fully utilized before purchasing new GenAI capabilities.
Phase 4: The Geo-Aware Operating Model. To address the reversal of consolidation, the operating model must be 'hub-and-spoke.' A central 'Command Center' (often virtual) sets the standards, governance, and technology stack, while regional 'Spokes' execute delivery with local compliance nuances. This allows for the agility to spin up or spin down locations based on geopolitical risk without reinventing the process stack. The 'Build vs. Buy' decision here is critical: Build the core governance and strategic capabilities; Buy (outsource) the transactional volume that is subject to high volatility.
Measurement Strategy: Success is measured by the 'Touchless Ratio' (percentage of transactions requiring zero human intervention) and 'Cost to Serve per Transaction.' A successful implementation typically sees the Touchless Ratio improve from <10% to >60% within 18 months.
Implementation Guide
Implementing a modern GBS operating model is a 12-18 month journey. CFOs should structure this as a transformation program with clear gates and funding tranches.
Phase 1: Assessment & Design (Months 1-3)
*Goal:* Define the baseline.
*Actions:* Run a 'Voice of the Customer' survey to quantify the perception gap. Map the top 20 processes by volume. Select the Intake/Orchestration technology.
*Team:* Transformation Lead, Process Architect, IT Solution Owner.
*Pitfall:* Spending too long on 'As-Is' mapping. Map enough to understand the mess, then design the 'To-Be.'
Phase 2: Pilot & Stabilize (Months 3-6)
*Goal:* Prove the concept.
*Actions:* Launch the Unified Intake platform for ONE function (e.g., Accounts Payable or IT Helpdesk) in ONE region. Establish the 'Tower Scorecard' for this pilot.
*Success Metric:* 80% adoption of the new intake channel; 0% critical service failures.
*Pitfall:* Over-customizing the tool. Stick to standard functionality for the pilot.
Phase 3: Scale & Automate (Months 6-12)
*Goal:* Expand scope.
*Actions:* Roll out intake to HR and remaining Finance functions. Begin 'Process Mining' on the data generated by the pilot. Deploy first wave of GenAI agents for Tier 0 support.
*Team:* Add Change Management leads (critical for adoption).
*Pitfall:* Ignoring the 'Shadow IT'—commercial teams hiring their own admins to bypass the new system.
Phase 4: Optimize & Innovate (Months 12+)
*Goal:* Value realization.
*Actions:* Shift focus to XLAs. Benchmark cost-to-serve against industry peers. Evaluate location footprint for consolidation/expansion.
*Success Metric:* 20-30% reduction in transactional operating costs; measurable improvement in internal NPS.
Global Context
Regional Intelligence.
Operating a Global Business Services organization requires a nuanced strategy that respects the distinct regulatory, cultural, and economic realities of North America, Europe, and APAC. The 'one size fits all' approach is a primary cause of transformation failure.
North America (The Innovation Hub):
*Market Context:* The US and Canada host approximately 25% of the world's shared service centers. The focus here is high maturity and high cost.
*Strategic Focus:* NA operations should focus on 'Centers of Excellence' (CoE) for high-value work like FP&A, Data Science, and AI governance.
*Regulatory/Cultural:* Minimal labor rigidity allows for rapid pivoting, but high turnover is a risk. The culture values speed and innovation over process adherence.
*Tactical Advice:* Use NA centers as the 'sandbox' for piloting GenAI initiatives before rolling them out globally. Expect higher OPEX but higher strategic output.
Europe (The Compliance Fortress):
*Market Context:* Europe is characterized by fragmentation. A center in Poland is distinct from one in Portugal.
*Regulatory Focus:* GDPR is the overriding constraint. Data regarding European employees or customers often cannot legally leave the EU, complicating 'follow-the-sun' models that rely on offshoring to India or Manila.
*Cultural/Labor:* strict labor laws (e.g., Works Councils in Germany/France) make restructuring or RIFs (Reductions in Force) slow and expensive.
*Tactical Advice:* Establish regional hubs (e.g., Poland or Hungary) that act as data-compliant fortresses. Do not attempt to service EU volume from APAC without a rigorous legal review of data transfer mechanisms. Leverage the high educational standards in Eastern Europe for complex accounting and engineering tasks.
APAC (The Scale & Growth Engine):
*Market Context:* While India and the Philippines remain the titans of volume, the narrative is shifting. Deloitte's 2025 survey indicates APAC CFOs are moving from cost control to growth.
*Regulatory:* China's PIPL (Personal Information Protection Law) creates a digital firewall similar to GDPR. Vietnam and Malaysia are emerging as alternatives to saturated markets.
*Cultural:* High respect for hierarchy and process adherence makes APAC ideal for standardized, high-volume transactional work. However, the 'Talent War' is fiercest here; wage inflation is real.
*Tactical Advice:* Diversify beyond a single APAC country to mitigate geopolitical risk. Shift the metric for APAC centers from 'FTE count' to 'Outcome delivered.' Invest heavily in retention and upskilling, as attrition rates here can cripple service continuity.
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Proof it Works
Navigating the GBS technology landscape requires a CFO to distinguish between 'Systems of Record' (ERPs like SAP/Oracle) and 'Systems of Action' (ServiceNow, Salesforce, specialized GBS tools). The most common error is assuming the ERP can handle service orchestration. ERPs are databases; they are not workflow engines designed for service delivery management.
The Platform Approach vs. Point Solutions:
Platform Approach (Recommended for Maturity): Investing in an overarching orchestration layer (e.g., ServiceNow, dedicated GBS platforms) that sits on top of all ERPs and legacy systems. Pros: Unified data model, single view of truth, easier to scale GenAI across functions. Cons: Higher initial licensing cost, longer implementation (6-9 months).
Point Solutions: Buying specific tools for specific problems (e.g., a dedicated AP automation tool, a separate ticketing tool for HR). Pros: Faster deployment for specific pain points. Cons: Creates 'data silos,' difficult to get a holistic P&L view, higher long-term integration costs.
Build vs. Buy Considerations:
When evaluating GBS capabilities, the 'Buy' (Outsourcing/BPO) option is increasingly viable for standardized, high-volume tasks where the provider has already invested in the GenAI stack. 'Build' (In-house GBS) is preferable for high-value, judgment-based processes where institutional knowledge is a competitive advantage.
Evaluation Criteria Checklist:
- Integration: Does the tool offer native connectors to your existing ERPs? (Custom APIs are a hidden cost sink).
- Multi-Geo Compliance: Does the platform support data residency requirements for GDPR (Europe) and PIPL (China) out of the box?
- GenAI Readiness: Is the AI embedded in the workflow, or is it a bolt-on 'copilot' that requires separate training?
- User Experience: Will business stakeholders actually use it? (If the UI is clunky, they will revert to email).
Key Question for Vendors: 'Show me how your tool handles cross-tower workflows (e.g., Onboarding involving HR, IT, and Finance) without manual handoffs.' Most point solutions fail this test.
FAQs
How long does it take to see a positive ROI from a GBS transformation?
Typically, organizations begin to see 'break-even' results between months 12 and 18. The initial 6-9 months involve 'J-curve' investment costs related to technology licensing, transition management, and potential severance. However, by implementing Quick Win automations in the first 6 months (e.g., automated invoice triage), you can self-fund portions of the longer-term transformation. A fully mature GBS model should deliver 3-5x ROI over a 3-year period through labor arbitrage, automation, and process standardization.
Should we build our own GBS center or outsource to a BPO?
This is a strategic 'Control vs. Speed' decision. Build (Captive) is best for functions requiring deep institutional knowledge, high compliance sensitivity (e.g., R&D finance), or where the process is a competitive differentiator. Outsource (BPO) is superior for highly standardized, high-volume transactional work (e.g., general ledger entry, payroll processing) where providers have better economies of scale and existing AI investments. Most mature organizations use a Hybrid model: keeping the 'brain' (governance/strategy) in-house and outsourcing the 'hands' (execution).
What are the biggest risks with Generative AI in Finance/GBS?
The primary risks are 'Hallucinations' (inaccurate financial data generation) and Data Privacy leakage. Unlike deterministic RPA, GenAI is probabilistic. If a GenAI bot misinterprets a tax regulation or exposes PII (Personally Identifiable Information) to a public LLM, the liability is massive. CFOs must enforce 'Human in the Loop' (HITL) protocols where AI drafts the work, but a human approves the final transaction, especially for external-facing outputs. Additionally, there is the risk of 'Model Drift' where the AI degrades over time without maintenance.
How do we handle the resistance from business units who don't want to 'give up' control?
Resistance stems from a fear of service degradation. You cannot win this argument with cost savings data alone; business unit leaders do not care about your savings if their operations slow down. You must sell 'Capability.' Demonstrate that the GBS can offer capabilities they cannot build themselves, such as 24/7 coverage, automated analytics, or specialized talent hubs. Use a 'Pull' strategy: create a Center of Excellence that is so effective that business units *ask* to join, rather than a 'Push' mandate.
How does the location strategy change with the new global tax and tariff environment?
The era of the 'Mega-Hub' is ending. The Global Minimum Tax (Pillar Two) reduces the tax arbitrage benefits of certain traditional low-cost locations. Furthermore, tariffs and trade wars require supply chain resilience. The new best practice is 'Multi-Shoring'—having redundant capabilities in distinct geopolitical zones (e.g., one hub in Latin America for NA time zones, one in Eastern Europe for EU, and one in APAC). This ensures that if one region goes offline or faces sanctions, the others can absorb the load.
What creates the 'Value Perception Gap' and how do I fix it?
The gap exists because GBS typically reports on 'Output' (tickets closed, calls answered) while the business cares about 'Outcome' (working capital optimized, days to hire reduced). To fix it, you must change your scorecard. Stop reporting operational metrics to the Board. Instead, report on 'Business Impact.' For example, don't report '99% AP accuracy'; report '$2M in duplicate payments prevented.' You must translate GBS activity into P&L language.
15-25% → 60-75%
Touchless Processing Ratio
Requires unified intake and standardized data inputs
12-18 months → 6-9 months
Implementation Timeline
Accelerated by using pre-configured industry standard templates
3-5% → 8-12%
Annual Productivity Savings
Driven by continuous process mining and automation backlog management
30-40% → >85%
Automation Utilization Rate
Avoiding 'Zombie Bots' through strict governance and maintenance
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