Deep expertise in
the tools finance teams rely on.

Planning and Budgeting Cloud (PBCS/EPBCS), Financial Consolidation and Close (FCC), and Profitability and Cost Management (PCM) — certified in all three. I also work with Oracle Smart View and EPM Automate for data integrations and automation.

Yes — reengineering underperforming applications is one of my core specialties. I analyze business rules, calc scripts, metadata outlines, and form design to identify and resolve bottlenecks, often delivering dramatic improvements in calculation and load times.

Yes. I'm based in Toronto but work with clients worldwide. My engagements are fully remote-capable, and I've collaborated with teams across North America, Europe, and beyond. I'm also available for on-site travel when the project requires it.

Yes — ongoing administration is a core part of my practice. I handle monthly maintenance, patch management, environment cloning, user access management, and respond to ad-hoc issues. Many clients engage me long-term after a successful implementation.

It depends on the scope and complexity. A focused Oracle Planning implementation can take 8–16 weeks. A full multi-module deployment including FCC and PCM may run 6–12 months. I provide a clear timeline estimate during our discovery conversation once I understand your requirements.

Absolutely — and I recommend it. Transferring knowledge to your internal team throughout the project means you're not dependent on external support after go-live. I build training and documentation into every engagement.

Yes — Vena is particularly well-suited to mid-market organizations that want CPM functionality with the familiarity of Excel. It removes the manual work of spreadsheet-based planning while keeping the flexibility finance teams rely on. It's a great fit for teams that aren't ready for a full Oracle EPM deployment.

Vena connects to most major ERP systems — including Oracle ERP Cloud, SAP, NetSuite, Dynamics, and others — through direct database connections, flat file ETL, or API integrations. I design the integration architecture during discovery to ensure clean, reliable data flow from your source systems.

A focused Vena implementation typically runs 8–14 weeks depending on the number of templates, data sources, and workflows. I aim for phased delivery so your team starts getting value early — not just at the end of the project.

I offer post-go-live support on a flexible basis — whether that's a retainer arrangement, ad-hoc support, or a structured hypercare period immediately after launch. You won't be left without support the moment the project closes.

NSPB is Oracle NetSuite's built-in planning and budgeting module, powered by Oracle's Hyperion/EPM engine under the hood. It allows NetSuite ERP customers to build structured budget and forecast models, collaborative workflows, and financial reports — all natively connected to their NetSuite data.

Not necessarily — but if your team is still budgeting in Excel and manually pulling data from NetSuite, NSPB eliminates that pain. It brings your planning process into NetSuite itself, automates data loads, and gives your finance team a structured, repeatable process for budgeting and forecasting.

Oracle EPM Planning (PBCS/EPBCS) is a standalone cloud platform suited for complex, large-scale planning across multiple dimensions and modules. NSPB is designed specifically for NetSuite ERP customers and is tightly integrated with NetSuite data. Both use similar underlying technology — which is why my Oracle EPM background directly applies to NSPB implementations.

Yes — this is one of the most common requests I receive. Many NSPB implementations go live in a basic state and never get properly configured. I assess your current setup, identify the gaps, and rework forms, calculations, and data flows to match how your business actually operates.

Both, depending on the use case. AI is genuinely useful today for specific, well-defined tasks — automated variance commentary, driver-based forecasting, anomaly detection, and repetitive data processing. It's still hype for anything requiring judgment, strategy, or nuanced business context. My approach is to identify the use cases where AI saves real time and improves accuracy, and ignore the rest.

Yes — data quality is the most common barrier to AI adoption in finance. Before any AI or ML model can be useful, your underlying data needs to be consistent, well-structured, and reliable. Part of my AI readiness assessment is evaluating exactly this — and if your EPM system is well-implemented, you're already much further ahead than most.

Yes, in different ways. Oracle EPM has native predictive planning features that can generate statistical forecasts using historical data. Vena can be enhanced with AI-generated outputs fed in via integrations. I also build standalone ML models that complement your EPM system — feeding better forecast inputs or surfacing insights your current setup can't generate.

Start with the most painful, repetitive task your team does every close or budget cycle. Variance commentary, data collection emails, manual reconciliations — these are the best first targets because the time savings are immediate and measurable. From there, we build toward more sophisticated forecasting and analysis. I recommend starting small, proving value, and scaling deliberately.