Implementation failures rarely stem from technology limitations. They happen when ownership remains unclear, data quality issues surface late, or teams treat automation like an ERP migration requiring months of planning. The shift to AI-native platforms changes this dynamic entirely, putting finance teams in control of timelines and outcomes.
This isn't about replacing your accounting infrastructure. It's about upgrading specific workflows on your own terms, starting with the processes causing the most pain and expanding as you prove value.
Why Implementation Stalls and How to Avoid It
Three common blockers derail close automation projects before they deliver value. Understanding these patterns helps teams navigate around them.
Unclear ownership creates coordination breakdowns
When IT owns the project but finance defines requirements, miscommunication creates delays. When finance owns the project but lacks technical confidence, teams hesitate to make decisions. Modern platforms designed for finance team operation eliminate this conflict by removing technical barriers that previously required IT involvement.
Messy data surfaces during integration
Organizations discover their chart of accounts contains duplicates, inconsistent naming, or dormant accounts. Intercompany transactions follow informal patterns that never got documented. Currency codes don't match between systems. These issues exist regardless, but integration exposes them.
The solution isn't perfect data cleanup before starting. It's acknowledging current state reality and addressing issues systematically as they surface. Modern platforms help identify and resolve data inconsistencies rather than requiring perfection upfront.
Over-reliance on IT creates dependencies and delays
Traditional implementations required IT resources for API connections, data mapping, and ongoing maintenance. This dependency model works poorly for month-end processes where finance teams understand requirements better than IT staff who lack accounting context.
AI-native platforms shift this model by handling technical complexity automatically. Finance teams configure business logic and workflow approvals without writing code or waiting for IT availability.
The First 30 Days: What a Smooth Implementation Looks Like
Modern implementations are complete in weeks rather than quarters. The first month establishes a foundation, validates the approach, and delivers initial value.
Week 1: Foundation and Connection
Implementation begins with data integration between existing ERPs and the automation platform. API connections provide continuous data flow without manual exports. Finance teams verify that trial balances, journal entries, and entity structures flow correctly.
Chart of accounts mapping occurs during week one. Modern systems suggest mappings based on account names and historical patterns, requiring finance review rather than manual configuration of every account. Entity structures, currencies, and ownership relationships get defined. The platform uses this structure to automate currency translation and eliminate entries.
Week 2: Workflow Testing and Refinement
Week two focuses on testing one core workflow end-to-end. Organizations typically choose their most painful manual process. Testing with recent actual data reveals how automation handles real-world complexity.
Finance teams refine matching rules, threshold settings, and exception handling. AI systems learn from corrections, becoming more accurate with each refinement. Parallel processing continues, with automated results running alongside manual processes to validate accuracy.
Week 3: Team Onboarding and Expansion
The third week brings broader team members into the platform. Staff accountants, controllers, and entity finance leads receive training focused on their specific workflows. Modern platforms require hours of training rather than days.
Teams expand automation to additional workflows once initial testing validates the approach. Organizations that started with consolidation add reconciliation automation. Early wins create momentum for broader adoption.
Week 4: Production Transition and Optimization
By week four, teams transition primary workflows from manual to automated processes. The platform becomes the source of truth for consolidated results or matched transactions. Manual processes shift to validation and exception review.
This phase includes documenting new procedures, updating close checklists, and communicating changes to stakeholders. Early results get shared with leadership to demonstrate progress.
Helpful resource: AI Implementation: A Strategic Roadmap for Finance Teams
Checklist: What to Prepare Before You Start
Successful implementations begin with preparation that clarifies scope, identifies resources, and documents the current state.
Who Needs to Be Involved
- Executive sponsor (CFO or Controller) who removes blockers
- Implementation lead from finance who owns the timeline and decisions
- Entity finance contacts who understand local processes
- IT contact for API access and security review (limited involvement)
- Key users who will operate the platform daily
Chart of Accounts Review
Identify duplicate accounts, inconsistent naming conventions, and dormant accounts. Perfect cleanup isn't required, but addressing known problems prevents confusion during data mapping. Document non-standard accounts that might need special handling.
Close Checklist Documentation
Document your current close process, including task sequence, ownership, dependencies, and timeline. This clarifies what to automate, identifies pain points, and establishes a baseline for measuring improvement.
Sample Intercompany Transactions
Gather examples of typical intercompany transactions, including sales between entities, cost allocations, and management fees. These examples help configure elimination logic and matching rules. Include both standard transactions and edge cases.
Avoid the most common implementation pitfalls. Use our free Implementation Readiness Checklist to prepare your team, clean up data, and set clear ownership before launch.
[BANNER CHECKLIST]
Change Management for Finance Teams
Technology implementation succeeds or fails based on people's adoption. The most sophisticated platform delivers no value if teams continue working around it in spreadsheets.
Communicate the Why Clearly
People resist change when they don't understand its purpose or fear negative consequences. Frame automation as eliminating tedious manual work rather than replacing jobs. Be specific: fewer late nights during close, less time fixing errors, more capacity for analysis that advances careers.
Start with the Most Painful Manual Workflows
Initial automation should target processes that create obvious frustration. When teams experience relief from work they actively dislike, enthusiasm for broader automation grows. Success with painful workflows creates advocates.
Highlight Wins Early and Specifically
Generic claims about improvement convince nobody. Specific examples resonate: "Consolidation that took four days now completes in two hours." Track and share these wins visibly. Quantify impact because numbers make improvement concrete.
Involve Skeptics Early
The loudest skeptics often become the strongest advocates once they experience benefits. Involve them during implementation to provide input on workflows. Their buy-in influences peers more effectively than a leadership mandate. Listen to skepticism seriously rather than dismissing it.
Nominal's Implementation Model
Nominal's approach prioritizes finance team ownership and rapid value delivery over traditional methodologies that emphasize comprehensive planning and lengthy configuration.
Finance-led implementation
Controllers and senior accountants drive decisions without dependency on IT resources. The platform handles technical complexity automatically while exposing business logic configuration that finance teams understand.
Prebuilt logic for common workflows
Standard patterns for consolidation, eliminations, and reconciliation come configured based on thousands of implementations. Finance teams review and refine this logic rather than building from scratch.
Real-time collaboration
Implementation happens through Slack integration that feels like working with an internal team. Issues are resolved in hours rather than waiting for support tickets.
Risk-free evaluation period
Organizations test full platform capabilities with real data before committing. This evaluation typically lasts three months, providing multiple close cycles to validate accuracy and measure impact.
Making Implementation Stick
Initial implementation represents just the beginning of automation value. Organizations that treat go-live as the finish line miss opportunities for continuous improvement.
Plan regular refinement sessions to review automation performance and identify optimization opportunities. AI systems improve with feedback, becoming more accurate at matching transactions and identifying exceptions. Monthly reviews ensure continuous learning.
Expand automation systematically rather than attempting everything simultaneously. Organizations typically implement in waves: core consolidation first, then reconciliation, then variance analysis. This staged approach builds expertise and proves value incrementally.
Document new procedures as automation changes workflows. Update close checklists, train new team members, and maintain institutional knowledge about configuration decisions. The goal is a sustainable operation that doesn't depend on individuals who remember implementation details.
Most importantly, maintain focus on business outcomes. Success means faster closes, fewer errors, and increased capacity for strategic work.
Ready to start your implementation? Book a demo with Nominal to discuss your specific situation and explore how these principles apply to your organization.
Next: See automation in action with Chapter 7: Webinar - A Real Close with Nominal.
