For finance leaders operating on SAP, the transition to automated Financial Planning and Analysis (FP&A) is often hindered by the complexity of legacy data structures and the technical challenge of integrating with modern cloud data warehouses. Choosing between an in-house build and an external partner is a pivotal decision that impacts long-term scalability and reporting accuracy. This guide provides a practical, criteria-based framework to evaluate consulting services, ensuring your partner can navigate the specific nuances of SAP data while delivering a robust cloud-based analytics foundation.
Read more: How Perceptive Analytics Automates FP&A with Modern Data Engineering
Perceptive Analytics POV:
“Automating FP&A on SAP isn’t just a visualization task; it’s a rigorous data engineering challenge. We frequently see firms struggle because they focus on the ‘dashboard’ before fixing the pipeline. A successful partner must understand SAP’s underlying table logic—like FAGLFLEXA or ACDOCA—as deeply as they understand cloud architecture. Without that dual expertise, you’re simply automating the delivery of inconsistent data. We believe the goal isn’t just to move data to the cloud, but to transform it into a governed, real-time asset for strategic modeling.”
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7-Point Checklist for Choosing Your FP&A Automation Consulting Partner
- Proven SAP + Cloud Data Warehouse Integration Experience: The technical “last mile” of extracting data from SAP ECC or S/4HANA into a cloud warehouse (like Snowflake, BigQuery, or Azure Synapse) is where most projects stall.
- Do they have experience with SAP-specific extraction methods (e.g., ODP, SLT, or specialized connectors)?
- Can they demonstrate a track record of handling massive SAP table structures without compromising system performance?
- How do they handle the reconciliation between the cloud warehouse and the SAP “Source of Truth”?
- Do they understand the difference between SAP’s functional modules (FI, CO, SD, MM) and how they impact FP&A modeling?
- Domain-Specific FP&A Expertise: A generalist IT firm may understand data pipelines, but FP&A requires a partner who speaks the language of the CFO.
- Does the team include former finance professionals or CPAs who understand P&L hierarchies and consolidation?
- Can they build complex “What-If” scenario models that reflect actual business drivers?
- Do they have a library of pre-built financial logic or accelerators to speed up the implementation of standard KPIs?
- Value vs. In-House Capabilities: An external partner should provide specialized knowledge and speed that an internal IT team, often bogged down by maintenance, cannot match.
- What proprietary frameworks or “best practice” blueprints do they bring to the table?
- How will they accelerate the time-to-value compared to a 12-month internal build?
- Can they provide an objective, cross-industry perspective on how other firms solve similar FP&A bottlenecks?
- Security, Compliance, and Controls: Finance data is highly sensitive and subject to strict regulatory requirements like SOX, GDPR, or industry-specific audits.
- How do they implement Row-Level Security (RLS) to ensure regional managers only see their specific data?
- What is their approach to data encryption and identity management (IAM) within the cloud warehouse?
- Can they demonstrate alignment with SOC 2 or ISO 27001 standards?
- How do they ensure auditability and data lineage from the dashboard back to the SAP source transaction?
- Cost Structure and Commercial Models: FP&A automation is an investment, and the pricing should reflect the risk and complexity of the SAP environment.
- Do they offer a fixed-fee discovery phase or a Proof of Concept (PoC) to prove technical feasibility before a full rollout?
- How do they balance Time & Materials (T&M) for complex engineering with fixed-fee for standardized reporting?
- What are the estimated ongoing “run costs” for cloud consumption vs. the savings from reduced manual effort?
- Case in Practice: A property management firm utilized a Budget Comparison Dashboard to identify that a $62,985 target miss was due specifically to building repair overspending. The ROI was immediate because the automation allowed for a swift corrective action that manual reporting would have missed.
- Post-Implementation Support and Enablement: A common pitfall is being left with a “black box” system that the internal team cannot maintain.
- Do they offer a structured “Hypercare” period immediately following go-live?
- What does their training and skills-transfer program look like for your internal analysts?
- Do they provide managed services or an enhancement backlog to handle evolving business requirements?
- Case in Practice: For a real estate client, we implemented Profit & Loss Reporting that allows stakeholders to drill down into transaction-level details (e.g., a sudden rise in event hosting income). Ensuring the client knew how to navigate these drill-downs was as important as the build itself.
- References, Case Studies, and Success Metrics: Proven success in similar SAP environments is the strongest indicator of future performance.
- Can they provide a reference from a client with a similar scale (e.g., 500+ employees or 1M+ customers)?
- Do their case studies mention specific, quantified outcomes like “reduced monthly close by 3 days” or “90% efficiency gain in data synchronization”?
- Case in Practice: Our work with a Global B2B Payments Platform involved achieving a 90% efficiency gain by integrating CRM data with Snowflake, ensuring 98.48% data synchronization accuracy—a critical benchmark for any high-growth enterprise. Read the complete case study – Optimized Data Transfer for Better Business Performance
Learn more: How to Choose Cost-Effective AI-Ready Data Integration for Snowflake
Putting the Checklist to Work
When preparing your RFP or shortlisting partners, use these points to challenge generic consulting proposals. The right partner will be able to speak specifically to SAP’s technical constraints while keeping the business outcome—faster, more accurate financial decisions—at the forefront. By focusing on data engineering rigor, security, and long-term enablement, you can ensure your FP&A automation project delivers a sustainable competitive advantage.