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Traditionally, businesses close their books at the end of the month, a process that demands significant time, effort, and resources to ensure accuracy and compliance.  This approach often leads to a buildup of tasks, particularly at month-end, when finance teams are burdened with reconciling accounts, reviewing financial statements, and addressing discrepancies. The result is a time-consuming, manual, and error-prone process that delays critical decision-making and hampers overall financial transparency. Daily soft closings address these challenges by providing a continuous, real-time view of financial health. Rather than waiting until the month’s end, businesses can perform regular daily reviews and reconciliations, ensuring financial data remains up-to-date and accurate. This shift reduces the stress and labor-intensive tasks typically associated with the month-end close, allowing finance teams to allocate their efforts more efficiently throughout the month. The soft close approach contrasts sharply with the traditional hard close, which often requires last-minute efforts to reconcile accounts and validate financial statements, increasing the risk of errors and delays. By spreading the workload and focusing on continuous financial oversight, businesses are better positioned to make more informed and strategic decisions. For companies seeking to modernize their bookkeeping practices, adopting a soft close represents a significant mind set change, a leap forward, transforming what was once a slow, manual process into a more agile, efficient, and automated approach. There are AI driven cloud-based tools and technologies now available that facilitate daily soft closing together real-time financial tracking, and continuous reconciliation empower businesses to gain deeper insights into their financial performance, enhance forecasting, and optimize resource allocation, ultimately fostering a more responsive and data-driven decision-making process.        For more information, please contact: Samagato Saha Director, Finance Transformation 📧 sam@finarticonsulting.com

When it comes to SaaS metrics, leveraging the right KPIs is essential to driving growth, improving performance, and optimizing decision-making. Here’s a breakdown of key SaaS metrics you should be leveraging and their significance: 1.  Customer Acquisition Cost (CAC): Measures the cost to acquire a new customer. Formula: CAC = (Sales & Marketing Expenses) / (Number of New Customers Acquired). 2. Lifetime Value (LTV) of Customer Predicts the total revenue a customer will generate over their life-time. Formula: LTV = (Average Revenue Per Customer × Gross Margin %) × (Customer Lifetime) 3. Monthly Recurring Revenue (MRR) Shows predictable, ongoing revenue from subscriptions. Formula: MRR = (Number of Customers) × (Average Revenue per Customer per Month) 4. Annual Recurring Revenue (ARR) Total revenue expected from annual subscription contracts. Formula: ARR = MRR × 12 5. Customer Churn Rate Measures the percentage of customers who stop using the service. Formula: Churn Rate = (Lost Customers / Total Customers at the Start) × 100 6. Net Retention Rate (NRR) Measures growth by tracking expansions, contractions, and churn. Formula: NRR = (Revenue from Existing Customers – Churned Revenue + Expansion Revenue) / (Revenue from Existing Customers) 7. Gross Margin Indicates the profitability of a SaaS business. Formula: Gross Margin = (Revenue – Cost of Goods Sold) / Revenue 8. Annual Contract Value (ACV) Represents the annualized value of a customer’s contract. Formula: ACV = (Monthly Recurring Revenue) × 12 9. Product-Market Fit Score Measures how well the product solves customer problems. Common survey-based metric: Net Promoter Score (NPS) or Customer Satisfaction Score (CSAT). 10.Payback Period ( in months or years) Time it takes to recover the CAC from the revenue generated by the new customer. Formula: Payback Period = CAC / (MRR or ARR) 11. Churned Monthly Revenue (CMR) Monthly revenue lost from churned customers. Formula: CMR = (MRR at the Start of the Month – MRR at the End of the Month) 12. Expansion Revenue Revenue growth from existing customers through upselling and cross-selling. Formula: Expansion Revenue = (New MRR from Upgrades + Add-ons – Downgraded MRR – Contractions) Tracking these metrics helps SaaS businesses understand their growth trajectory, optimize customer acquisition strategies, improve retention, and ultimately enhance profitability. For more information, please contact: Sanjay AgarwalDirector, CFO Services sanjay@finarticonsulting.com 

We refer to it as Evolution, not Maturity. The journey unfolds across five distinct stages, each marked by significant milestones or transformative, game-changing experiences. 1) Basic FP&A : At this stage, the focus was on establishing foundational financial reporting and basic budgeting processes. The emphasis was on tracking historical data, ensuring accuracy in financial statements, and providing basic financial insights to support decision-making. 2) Advanced FP&A : Building upon the basics, this stage introduced more sophisticated financial modeling, variance analysis, and deeper financial insights. Companies began to enhance their capabilities in forecasting, scenario planning, and identifying trends, providing more actionable insights for strategic decision-making. 3) Digital FP&A : In this phase, technology became a critical enabler. Automation of routine processes such as data collection, reconciliation, and reporting allowed FP&A teams to shift focus towards more value-added activities like data analysis and real-time reporting. Tools like ERP systems, cloud-based platforms, and integrated dashboards became integral to providing real-time financial insights and enhancing accuracy. 4) Predictive FP&A : The focus shifted towards leveraging advanced analytics, machine learning, and artificial intelligence to develop predictive models. FP&A moved beyond historical data to forecast future outcomes, identifying key drivers, and enhancing the ability to simulate various scenarios. This stage enabled more proactive planning and helped anticipate risks and opportunities. 5) Virtual FP&A : At the most advanced stage, FP&A evolved into a virtual function, emphasizing data-driven decision-making in real-time across distributed teams. Advanced analytics, AI, and machine learning were fully integrated into the workflow, supporting dynamic and automated insights that enabled agile and strategic decision-making. Virtual FP&A teams leveraged cloud-based platforms, real-time collaboration tools, and automated systems, reducing manual processes and improving the accuracy and speed of financial analysis. Throughout these stages, the FP&A function transformed from a reactive reporting role to a strategic partner providing forward-looking insights, driving business performance, and supporting complex, data-driven decision-making. For more information, please contact:Sanjay AgarwalDirector, CFO Services 📧 sanjay@finarticonsulting.com