Optimizing Financial Processes

FP&A people waste time on: • Formatting reports to look appealing • Debugging error-prone Excel macros • Compiling data from outdated systems • Troubleshooting complex Excel formulas • Responding to low-value ad-hoc requests • Creating static presentations for executives • Chasing department heads for budget inputs • Managing version control across multiple files • Manually entering repetitive data in spreadsheets • Reconciling conflicting numbers from various sources FP&A people must focus on: • Using predictive analytics to forecast trends • Automating routine tasks to focus on analysis • Identifying key drivers of business performance • Implementing rolling forecasts for agile planning • Modeling scenarios to guide strategic decisions • Streamlining the budgeting and planning process • Building dynamic dashboards for real-time insights • Evaluating M&A opportunities and financial impacts • Collaborating with business partners on growth strategies • Conducting variance analysis to improve forecasting accuracy Successful FP&A teams blend financial expertise with technology. They adopt tools that are: - Easy for the team to use - Secure and compliant with data governance - Able to integrate with existing data sources - Focused on automating processes and saving time - Scalable for future business growth - Enhancing cross-functional collaboration FP&A must use new tools and focus on high-value tasks. It's time to change from number crunchers to strategic partners. P.S. Hi, I’m Erik Lidman! I have spent 25 years of my life working in the FP&A, EPM, and CPM spaces. I share daily FP&A tips and talk about finance trends and doing FP&A within Power BI using Aimplan.

There are two non-negotiables in accounting: the books must be correct, and they must be ready on time. For decades, companies have satisfied those constraints through an extraordinary amount of manual effort. Highly trained professionals code transactions, re-approve familiar expenses, reconcile mismatches after the fact, and compress all of it into the ritual of month-end close. It works. But it is fundamentally retrospective. Today, Ramp introduced an Accounting Agent designed around a different premise: what if bookkeeping happened as the business operated, rather than after it? The agent captures, codes, reviews, validates, accrues, and reconciles spend continuously. It learns directly from the people who understand the nuances best, the accounting team itself, and applies that context in real time. At Perplexity, where velocity is core to the company’s identity, this allowed their team to stop choosing between speed and accuracy. The majority of transactions are now coded automatically and audit-ready, enabling close to start on day one instead of day thirty. What’s been most striking is how the system learns the subtle, company-specific logic that historically lived only in human judgment. As Jim Romano, CFO at Stateside Brands, described it, the agent is already identifying patterns like when spend belongs in samples rather than travel and entertainment — the kinds of decisions that typically require institutional memory. As he put it, the goal is simple: finance teams should focus on exceptions, not the easy stuff. We’re also seeing the second-order effects emerge quickly. Teams report spending dramatically less time reviewing transactions and substantially more time on planning, analysis, and growth. As one CFO told us, “What used to take hours of manual review now happens. I’m spending nearly all of my time thinking about where the business should go, not retracing where it’s already been.” There is a broader shift underway in accounting. The central question is moving from “what parts of close can be automated?” to “should close even be an event at all?” One belief that guides our work at Ramp is that information latency inside companies is an invisible tax. When financial truth lags behind operational reality, organizations make slower and often worse decisions. As transaction data becomes inherently digital and systems become capable of learning institutional context, continuous close stops being aspirational and starts becoming inevitable. One thing that surprised us while building this: accounting isn’t constrained by a lack of rules — it’s constrained by how many of those rules are unwritten. Seeing software begin to absorb and apply that tacit knowledge has been a clear signal that accounting is entering a new phase. Accounting has always been the record for business reality. Our goal is to help it become closer to real-time truth. Proud of the team, and grateful to the customers building this alongside us.

Monthly End Closing Checklist | Best Practices for Finance Teams A strong month-end close is critical to maintaining financial accuracy, ensuring compliance, and supporting strategic decision-making. Here’s a streamlined checklist every accounting and finance team should follow: ⸻ 1. Reconcile Bank Accounts • Match bank statements with internal company records. • Investigate and resolve discrepancies. 2. Reconcile Credit Card Accounts • Verify credit card transactions against internal records. • Identify and address any inconsistencies. 3. Accounts Receivable Management • Issue all customer invoices timely. • Follow up on overdue accounts. • Write off confirmed bad debts appropriately. 4. Accounts Payable Management • Enter all supplier/vendor invoices. • Process pending supplier payments. • Review and adjust accrued liabilities. 5. Payroll Reconciliation • Ensure payroll transactions are accurately recorded. • Reconcile payroll taxes and benefits obligations. 6. Fixed Assets Update • Record all asset acquisitions and disposals. • Update and apply depreciation schedules. 7. Inventory Management • Conduct physical inventory counts (if applicable). • Reconcile inventory values with accounting records. 8. Prepaid Expenses Adjustment • Record amortization of prepaid expenses. • Prepare entries for newly incurred prepayments. 9. Accruals and Deferrals • Book necessary accruals for expenses and revenues. • Ensure proper period recognition for all transactions. 10. Financial Reporting • Prepare Profit & Loss (P&L) Statement. • Generate Balance Sheet and Cash Flow Statement. • Compare actual performance against budgeted forecasts. 11. Review and Adjust Journal Entries • Validate journal entries for accuracy and completeness. • Post required adjusting entries to the General Ledger. 12. Backup Financial Data • Securely back up all financial records and sensitive data. 13. Management Review and Analysis • Present finalized financial statements to management. • Discuss variances, trends, and any material concerns. ⸻ Key Takeaway: ✔️ A disciplined monthly close improves financial transparency, strengthens internal controls, and empowers strategic business decisions. ⸻ #accounting #finance #financialreporting #monthendclosing #closingchecklist #accountsreconciliation #corporatefinance #financialanalysis #accountingbestpractices

Here's a concise 12-step process for month-end closing: 1) 𝐅𝐢𝐧𝐚𝐥𝐢𝐳𝐞 𝐓𝐫𝐚𝐧𝐬𝐚𝐜𝐭𝐢𝐨𝐧𝐬: Ensure all monthly transactions (invoices, expenses, etc.) are recorded. 2) 𝐑𝐞𝐜𝐨𝐧𝐜𝐢𝐥𝐞 𝐒𝐮𝐛𝐥𝐞𝐝𝐠𝐞𝐫𝐬: Match AR, AP, Inventory, and Fixed Asset subledgers to the general ledger. 3) 𝐑𝐞𝐜𝐨𝐫𝐝 𝐀𝐜𝐜𝐫𝐮𝐚𝐥𝐬: Recognize earned but unbilled revenue and incurred but unpaid expenses. 4) 𝐀𝐜𝐜𝐨𝐮𝐧𝐭 𝐟𝐨𝐫 𝐃𝐞𝐟𝐞𝐫𝐫𝐚𝐥𝐬: Adjust for unearned revenue and prepaid expenses. 5) 𝐂𝐚𝐥𝐜𝐮𝐥𝐚𝐭𝐞 𝐍𝐨𝐧-𝐂𝐚𝐬𝐡 𝐈𝐭𝐞𝐦𝐬: Record depreciation, amortization, and bad debt expense. 6) 𝐏𝐞𝐫𝐟𝐨𝐫𝐦 𝐁𝐚𝐧𝐤 𝐑𝐞𝐜𝐨𝐧𝐜𝐢𝐥𝐢𝐚𝐭𝐢𝐨𝐧: Match bank statements to internal cash records. 7) 𝐑𝐞𝐯𝐢𝐞𝐰 𝐆𝐞𝐧𝐞𝐫𝐚𝐥 𝐋𝐞𝐝𝐠𝐞𝐫: Analyze account balances for accuracy and unusual items. 8) 𝐏𝐫𝐞𝐩𝐚𝐫𝐞 𝐓𝐫𝐢𝐚𝐥 𝐁𝐚𝐥𝐚𝐧𝐜𝐞: Generate an initial summary of all account balances. 9) 𝐌𝐚𝐤𝐞 𝐀𝐝𝐣𝐮𝐬𝐭𝐦𝐞𝐧𝐭𝐬: Record any necessary correcting entries identified during review. 10) 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐞 𝐅𝐢𝐧𝐚𝐧𝐜𝐢𝐚𝐥 𝐒𝐭𝐚𝐭𝐞𝐦𝐞𝐧𝐭𝐬: Produce the Income Statement, Balance Sheet, and Cash Flow Statement. 11) 𝐀𝐧𝐚𝐥𝐲𝐳𝐞 𝐑𝐞𝐬𝐮𝐥𝐭𝐬: Review financial statements for reasonableness and perform variance analysis. 12) 𝐅𝐢𝐧𝐚𝐥𝐢𝐳𝐞 𝐚𝐧𝐝 𝐑𝐞𝐩𝐨𝐫𝐭: Secure records and distribute financial reports to stakeholders.

Most finance transformations do not fail because the strategy is wrong. They fail because a few familiar patterns are allowed to repeat. Six to watch for: → No clear mandate When sponsorship is unclear, momentum disappears as soon as resistance shows up. What works: appoint a senior sponsor with real authority to make trade-offs, and keep them visible when the difficult decisions begin. → Big-bang scope Trying to redesign the full finance function at once creates complexity before credibility. What works: start where value can be made visible quickly, then scale from a stronger position. → Tool before process New systems are often placed on top of old ways of working. The technology changes, but the underlying behaviours do not. What works: redesign the process first, then let the system enable the new way of working, not digitise the old one. → No adoption plan A technically sound solution will still fall short if people are not ready, willing or able to use it. What works: design adoption from day one, with capabilities, routines and behaviours built into the plan. → Success measured by delivery Many transformations are closed when the system goes live. But value only appears when people start working differently. What works: track adoption and behavioural change after go-live, not just milestones and deliverables. → Change fatigue Finance teams are often asked to absorb one more initiative while still dealing with the last three. What works: be honest about capacity. Sequencing is not a project detail; it is a leadership choice. How to break the pattern in practice: 1️⃣ Name a real sponsor: someone who can make trade-offs and stays visible when it matters 2️⃣ Prove it small: start where value can be shown quickly, then scale with confidence 3️⃣ Design for adoption: build capabilities and habits into the plan from day one 4️⃣ Track behaviour: follow how work actually changes after go-live, not just delivery Which of these six patterns is hardest to avoid in your organisation? ♻️ Like, comment, and repost to help more finance teams ---------- 🧑🏼💼 I am a Partner at Implement Consulting Group 🗣️ Reach out to talk about the following: ...Finance Transformation ...Enterprise Performance Management ...Finance Capability Building ...Value Creation

Financial Services Innovators Are Data-Driven, Cloud-Focused, and Customer-Centric Across Their Value Chains 💡 Banking and insurance cloud innovators are: 👨💻 Data-driven: 🔹 FS cloud Innovators actively use data to support their sales and marketing functions by recommending relevant products to their customers through targeted marketing campaigns. During customer onboarding, innovators use AI to process structured and unstructured data they obtain from their customers and maintain it in a database for future reference, enabling a seamless onboarding process. 🔹 On the banking side, innovators actively use data to identify and prevent fraudulent transactions, calculate customer credit scores to evaluate potential risks, streamline the process of loan approvals, and estimate the probability of loan defaults. 🔹 On the insurance side, innovators integrate traditional and third-party data for the underwriting process to help price policies better. Insurance innovators also actively leverage data during claims process to automate claims triage, identify fraudulent claims, and estimate damage value. ☁️ Cloud-focused: 🔹 They actively leverage APIs to facilitate collaboration between different teams during product development to identifyand integrate best practices. 🔹 Innovators actively use intelligent cloud-based CRM systems to manage customer data and effectively support their various business functions. They also use cloud-based systems to automate the customer onboarding process. 🔹 FS cloud innovators drive contact center modernization with the help of the cloud to enable faster resolution of issues and enhance upsell and cross-sell opportunities. 🙋♂️ Customer-centric: 🔹 Furthermore, cloud innovators have optimized KYC processes for onboarding to ensure that their customers have a seamless experience. 🔹 These innovators provide their customers with an omnichannel experience, ensuring they have straightforward and instantaneous access to their services. They offer their customers comprehensive, personalized financial advisory services in addition to their standard products and services. 🔹 Finally, these organizations leverage intelligent chatbots to assist their customers with the challenges they face during their financial journey. Gen AI helps innovators manage data, re-engineer processes, make realtime automated decisions, and drive simulations to delight customers. Some critical uses of generative AI across the value chain include market forecasting, tailored content marketing, personalized credit analysis in banking and premium calculations in insurance, fraud prevention and management, and intelligent chatbots and virtual assistants. Source: Capgemini - https://t.ly/A5cZC #Innovation #Fintech #Banking #OpenBanking #API #FinancialServices #Payments #Loans #Compliance #AI #Data #Cloud #GenAI

How we saved 10+ hours weekly by giving finance a simple interface. Our finance team was processing invoices the same way for years: 1. Email attachments → 2. Manual download → 3. Print → 4. Physical signature → 5. Scan → 6. Manual data entry The entire cycle took 3-5 days. The request to "build a proper approval system" kept getting deprioritized—it felt like a multi-month project. We reframed the problem: We didn't need a complex system. We just needed to connect two things: the data from our accounting software's API and a simple list where the right people could click "Approve" or "Reject." What actually got built: • A single-page app that pulls unpaid invoices automatically • Logic that routes invoices over $5k to directors, others to managers • A comment field for rejections • A basic audit log showing who approved what and when What changed: ✅ Approvals now happen in under 24 hours ✅ The finance team stopped chasing paper trails ✅ Vendors get paid faster ✅ Every decision is logged automatically The takeaway: Sometimes "digital transformation" isn't about big platforms. It's about giving a team one less PDF to manage by building a simple, focused tool that sits on top of the data they already use. What's the most stubborn, repetitive task in your team's workflow? Often the highest-impact tools are the smallest ones that remove a single point of friction. https://uibakery.io/ #ProcessAutomation #FinanceTech #OperationalEfficiency #DigitalTransformation

Core principles behind great FinOps: ➡️ Assume people are imperfect! Don’t build processes that rely on memory or discipline. People are distracted. Systems should expect that and still work. ➡️ Make cloud waste painful or impossible. If waste is easy, it will happen. Block it, cap it, surface it. No one cares until the pain is visible. ➡️ Put cost data where work happens. If you want engineers to care about cost, show it in CI/CD, dashboards, code reviews. ➡️ The right thing should be the easy thing. Defaults matter. Automate cleanup, force tagging, right-size automatically. ➡️ Kill it if it’s idle. The easiest money to save is from stuff no one’s using. ——— Tips for juniors learning cloud: 💸 If you create or start something, it keeps charging you until you delete it. Learn to clean up everything. 💸 Always check instance sizes, storage classes, retention policies, autoscaling rules. 💸 Tag everything. 💸 Always assume you’ll forget to shut things down. Use automation: auto-delete, auto-stop, lifecycle rules. Don’t rely on memory, you’ll lose money every time. 💸 Use budgets and alerts from day one. 💸 Learn how pricing works for each service you use. Know what costs per GB, per hour, per request. You WILL mess up and that’s ok. 🙏 Then reread this and fix what you thought you’d remember. 😄 Also, if you messed up really bad, contact the cloud provider’s customer service immediately. Be honest, be humble. They might be able to cancel the cost.

You can't treat every forecast the same. More uncertainty means more risk, and you want to deal with it correctly. After building forecasting models at P&G, Unilever, and Squarespace, I've learned there are three ways to manage uncertainty: 𝟭) 𝗔𝘃𝗼𝗶𝗱 𝗔𝘀𝘀𝘂𝗺𝗽𝘁𝗶𝗼𝗻 𝗦𝘁𝗮𝗰𝗸𝗶𝗻𝗴 The more uncertainty, the fewer assumptions you should include. Why? Because if you add multiple variables on top of each other, their margin of error multiplies. If you base the forecast on many assumptions, it's nearly impossible to determine which one was accurate and which wasn't. So, keep your models as simple as possible. Isolate the variables. You can always add additional assumptions later once you better understand the correlations. 𝟮) 𝗥𝘂𝗻 𝗪𝗵𝗮𝘁-𝗜𝗳 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 It's your job as a finance leader to quantify the risk of a forecast. The easiest way to do that is by changing individual inputs and noting how much impact that has on the forecast. For example, if a 5% price change affects the revenue forecast by 25%, that's a major risk you'll need to call out. 𝟯) 𝗦𝗵𝗼𝘄 𝗮 𝗥𝗮𝗻𝗴𝗲 Sometimes analysts make the mistake of assuming ranges make it look like they aren't confident in their forecast. But a well-measured range is critical for two reasons: One, it shows the order of magnitude of risk. Your CFO knows what's a conservative estimate to communicate to investors. Two, it enables scenario planning. Leaders can plan contingency measures if results are at the lower end of the range. 𝗜𝗻 𝘀𝘂𝗺, 𝘁𝗼 𝗺𝗮𝗻𝗮𝗴𝗲 𝘂𝗻𝗰𝗲𝗿𝘁𝗮𝗶𝗻𝘁𝘆 𝗶𝗻 𝗮 𝗺𝗼𝗱𝗲𝗹: 1. Reduce the number of assumptions 2. Estimate the risk by running sensitivity analysis 3. Provide ranges instead of point estimates Which approach do you find most useful? Comment below 👇 -Christian Wattig 📌 Get my 𝗙𝗶𝗻𝗮𝗻𝗰𝗶𝗮𝗹 𝗠𝗼𝗱𝗲𝗹𝗶𝗻𝗴 𝘁𝗲𝗺𝗽𝗹𝗮𝘁𝗲 + 𝟰𝟲 𝗯𝗲𝘀𝘁 𝗽𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀 (free) here: https://lnkd.in/eBAmSF_6 

I've managed $500M+ in budgets across seven industries. The pattern is clear: complexity kills decisions. Clarity wins. Manufacturing. Healthcare. Technology. Aged care. Infrastructure. Mining. Not-for-profit. The scale, the players, and the problems are all different. But what is the dynamic that separates winning organisations from struggling ones? It's always the same. Decision-making slows when information overloads. Leaders become paralysed by detail instead of guided by insight. I once worked with a business facing a critical cash position. The finance team had built a comprehensive model with 70+ variables, scenario analysis, and historical trending. Technically brilliant. Strategically useless. The CEO couldn't act because he couldn't see the signal through the noise. We stripped it back. One page. Three key metrics. Two scenarios: what happens if we act, and what happens if we don't? Suddenly the path forward was obvious. Here's what I've learned: the best financial frameworks aren't the most sophisticated. They're the ones that make complex reality digestible enough for leaders to act on it. Complexity is often mistaken for rigour. But rigour without clarity is just noise. Your job isn't to present every variable. It's to distil reality into the insight that matters most. The CFO who can do that, who can take messy financial reality and make it clear enough to drive decisions, becomes indispensable. Clarity isn't simplistic. It's disciplined. What's one decision in your business that's been delayed by complexity instead of accelerated by clarity?