Author: SANJEEB BHATTA

1. Lead the budgeting and forecasting cycle by running variance analysis and building rolling forecasts.

Budgeting and forecasting are more than just maintaining budget spreadsheets because anyone can fill numbers into the sheet. Building a dynamically interlinked budgeting and rolling forecast model helps support variance analysis and solves the mentioned critical business challenges:

• Robert Kaplan, professor and researcher at Harvard Business School (HBS), reports that 90% of organizations fail to successfully execute their strategies. The Economist Intelligence Unit found that 61% said their organizations struggle to link strategy formulation to day-to-day implementation. This model bridges high-level strategic objectives with monthly tactical targets.
• Adaptive insights with visuals are often lacking in the traditional budgeting and forecasting models. This model is designed to provide visual adaptive insights and variance analysis at a glance.
• Traditional annual budgets quickly become obsolete due to shifting market conditions. Replacing static budgets with rolling forecasts keeps plans dynamic and realistic, allowing quick adjustments to budgets based on changing scenarios.
• Recognizing revenue on an accrual basis without tracking actual cash timing might lead to liquidity crunches. This model links revenue recognition to accounts receivable schedules and cash collection timing. So, we can monitor receivables and manage working capital effectively.
• Human capital costs and headcount planning are often modelled in isolation. This model directly connects human capital scheduling, available capacity days, and salary/bonus accruals to project deliverables, and the ripple effect of any changes is directly reflected in integrated financials.
• Aggregate top-line reporting hides operational inefficiencies. Without breaking down variance into price, volume, usage, and employee pay components, management cannot identify the root causes of variance and areas to focus on for improvement. This model is designed to identify the variance and its root cause and provide insights for improvement.
• This model is designed to automate the manual consolidation. The monthly financial statements are consolidated into quarterly and annual reports; hence, it is a big time saver during month-end reporting.

2. Methodologies & Techniques Used

To address these business challenges, the Excel-based budgeting and rolling forecast model uses international best practices in designing a model. This model is user-friendly and is easy to use, review and audit. Furthermore, the consolidation of reports is automated, which saves a huge amount of time during month-end and year-end reporting.

• Incorporates dynamic monthly switches (1 for Actuals, 0 for Forecast) across time horizons, allowing seamless rolling updates without breaking model formulas or hardcoding overrides.
• Projects top-line revenue using specific revenue schedules, contract durations, and accrued revenue recognition metrics rather than arbitrary percentage growth assumptions.
• Built on a fully dynamic master budget framework where the Income Statement, Cash Flow Statement, and Balance Sheet feed directly into one another. All these financials are also directly linked to the outcomes of the schedules, making the model dynamic.
• Numbers in blue font are hard-coded (i.e., input manually), and all numbers in black font are either linked to other cells or calculated using a formula.
• Combines annual salary baselines, scheduled vs. available working days, employee benefits, and bonus accruals across organizational tiers (from Analyst to Director) to ensure accurate COGS and SG&A projections.
• Tracks receivables opening balances, monthly additions, collections, and ending balances to forecast net cash generated from operating activities accurately every month.
• Incorporates visual reporting dashboards with monthly and quarterly granularities for key metrics like Revenue and EBITDA Margins, Net Income Margin and available cash balance, adhering to best practices in financial dashboard design.
• The dashboard presentation is clean with the right level of detail that decision makers highly rely on. The dashboard design is customizable and can be prepared to address the needs of the decision maker.

3. How the Model Connects Strategies to Action and drive financial success

  [Strategic Plan & Targets]
              │
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  [Driver-Based Operating Budgets] ──► (Revenue,                     Headcount, Operating Expenses)
              │
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  [Dynamic Rolling Forecast 1/0 Toggle] ──► Integrates Actuals in Real-Time
              │
              ▼
  [3-Statement & Working Capital Integration] ──► Cash & Liquidity Visibility
              │
              ▼
  [Variance Analysis & Dashboards] ──► Uncovers Root Causes & Guides Decision-Making

A. Dynamic Rolling Forecast vs. Static Annual Budgeting

Traditional annual budgets force companies to stick to outdated targets made months in advance. By applying dynamic monthly binary flags, this model transforms rigid annual budgets into a continuous rolling forecast. As actual results are loaded each month, the model updates forward-looking quarters automatically, providing executive leadership with continuous real-time visibility. Any changes in scenarios might lead to changes in the assumptions, which ultimately change the key drivers. The ripple effects of changes in the key drivers on the financial results are automatically calculated without the need for preparing separate financial reports periodically.

B. Direct Alignment Between Capacity, Payroll, and Delivery

Projects frequently fail due to headcount shortages or cost overruns. The model includes an Employee Scheduling & Totals engine that maps total scheduled days against available working days across staff levels. It automatically alerts managers to scheduling conflicts while simultaneously calculating precise salary, benefits, and bonus costs.

C. Cash Liquidity and Working Capital Management

Profitability does not equal liquidity. By establishing dedicated schedules for Accounts Receivable and Cash Receipts, the model isolates accrued revenue from actual cash inflows. This gives finance teams early visibility into potential cash requirements, line-of-credit needs, or working capital shortfalls before they occur.

D. Actionable Variance Analysis & Root-Cause Pinpointing

When performance deviates from target, simple top-line variance numbers are insufficient. The variance tracking framework isolates key cost and revenue drivers. For instance, if labour expense exceeds budget, the model enables finance professionals to determine whether the variance was driven by pay rates (price variance) or extra time (quantity/volume variance), enabling targeted corrective actions.

4. Key Highlights & Conclusion

This dynamically linked Budgeting and Forecasting Model offers an end-to-end framework designed to replace static, prone-to-error spreadsheets with an integrated, driver-based 3-statement financial model. Built upon international best practices in modelling, it connects high-level strategy to monthly operational performance.

Key Highlights:

• Integrated Model: Fully connected Income Statement, Balance Sheet, and Cash Flow Statement linked to related schedules.
• Rolling Forecast Functionality: Dynamic monthly 1/0 actual vs. forecast toggles enable rolling monthly updates.
• Granular Human Capital Modelling: Built-in workforce planning modules that evaluate capacity, billable/scheduled days, salaries, benefits, and bonuses.
• Working Capital Precision: Detailed Accounts Receivable roll-forwards that reflect actual cash generation from working capital change.
• Executive Dashboarding: Clean monthly and quarterly chart visualisations designed for high-level decision-makers, eliminating visual clutter.

1. Want to achieve broader organizational goals by focusing on operational efficiency? Then a dynamic driver-based operational model is the best solution.

Many organizations and finance professionals focus heavily on capital structure, debt sizing, and valuation ratios while treating the underlying operations as a simple percentage of revenue. Thoughtfully built dynamic operational models successfully connect strategies/actions to broader organizational goal by providing key insights into operational efficiency. This model acts as a decision-making tool and helps to track and focus on operational efficiency improvement.

Here are the 5 key problems this operational model solves:

• Instead of relying on high-level estimates, the model breaks operational performance down into granular drivers like daily production volume, plant capacity, pricing power, and cost inflation.
• It resolves capacity constraints by linking daily sales volume directly to physical plant limitations and flagging when plant capacity needs to be improved.
• By strictly separating fixed and variable costs, the model reveals how fixed overhead impacts profitability or heightens risk when production volumes fluctuate. This gives an overview of operational efficiency.
• This model reconciles book depreciation (IFRS/GAAP) with accelerated tax depreciation to accurately predict cash tax liabilities and deferred taxes.
• It quantifies the exact cash use or cash generation resulting from changes in operational efficiency metrics like Accounts Receivable (A/R) days, Inventory days, and Accounts Payable (A/P) days. This helps in working capital management efficiently and effectively.

2. Key Methodologies and Techniques Used

To ensure structural integrity, transparency, and scalability, the model is built using standardised international best practices:

• Separate Schedules (Building Blocks): The model is segregated into self-contained, repeatable schedules (Revenue, Cost, Working Capital, Depreciation, Asset, and Tax) that link directly into a summarised Income Statement.
• The “Enter-Calculate-Exit” Flow: Every individual schedule follows a strict top-to-bottom layout:
  1. Enter: Raw operational inputs enter at the top.
  2. Calculate: Formulas operate in the middle section.
  3. Exit: Output totals exit at the bottom to feed other schedules or financial statements.
• Unit-Level Cost and Price Forecasting: Revenue is calculated by increasing the previous year’s revenue by the assumed sales growth rate. Variable costs are adjusted for assumed inflation, forecasted on a per-unit basis and then aggregate dollar amounts are calculated. In contrast, fixed costs are forecasted in aggregate dollar amounts, adjusting for assumed inflation, and then per-unit measures are calculated.
• Standard Practices are Followed: Using uniform column structures, consistent colour-coding (inputs vs. formulas), and predictable schedule layouts makes models easier to audit, review, and maintain.
• Dynamic Model Alerts: Conditional formulas check operational thresholds (such as whether daily unit volume exceeds daily plant capacity) to immediately alert users when additional capital expenditure is required.
• Corkscrew Roll-Forward Formulations: Asset schedules utilise corkscrew roll-forwards (Beginning Balance + Additional CapEx – Depreciation = Ending Balance) to track Property, Plant, and Equipment (PPE) across both accounting and tax bases.
• Accrual & Matching Principles: Revenue and Cost of Goods Sold (COGS) are aligned to unit sales volume within the exact operating periods they occur, supporting internal control and compliance with accounting and financial reporting standards.

3. How the Model Solves Operational Challenges

This model empowers management, analysts, and investors to make data-driven decisions in several practical ways:

• Capacity Planning & CapEx Triggers: By evaluating daily sales volume (units/day) against maximum plant capacity (e.g. 1,500 units/day), the model provides early warnings when sales unit volume hits $100% operational efficiency (i.e. plant capacity). This signals exactly when the business must be prepared for additional capital expenditure.
• Operational Leverage Stress-Testing: Splitting costs into fixed (e.g., labour, utilities, insurance) and variable (e.g., raw materials, packaging) allows finance professionals to monitor operational leverage during growth and downturn so that they can effectively recommend effective resource allocation strategies (e.g. fixed and variable cost management). Because higher leverage amplifies the outcomes, which means during growth it accelerates profit, and the same thing happens during the downturn as it exacerbates the loss.
• Working Capital Management: By converting collection and payment terms into explicit metric days (A/R Days, Inventory Days, and A/P Days), the model quantifies how quicker cash collections or stretching supplier payables supports cash flow management decisions. This model is completely dynamic, and any changes in the metric days show changes in working capital cash flow.
• Tax Optimization & Loss Management: By parallelly tracking IFRS financial reporting and government tax rules (incorporating accelerated tax depreciation rates and loss carryforward pools), the model provides a clear view of actual cash tax outflows versus non-cash deferred tax liabilities.

4. Conclusion & Key Highlights

An operational model is the crucial decision-making tool for finance professionals. By removing capital structure complexity and concentrating on unit-level analysis, cost behaviour, and operational efficiency, finance professionals can gain a clear understanding of what truly drives business performance and cash generation. Since the model is dynamically linked and formula-based, if the assumption about inflation or any key drivers is changed, then the model can provide adaptive insights efficiently and effectively for quick decision-making. The model is user-friendly, so stress-testing scenario-based assumptions is quicker and easier.

1. Cash is the lifeblood of the business, and managing it successfully is what sets finance professionals apart. A monthly cash flow model helps the finance team solve the following issues;

• Uncover Short-Term Liquidity & Funding Gaps: While traditional annual models are useful for high-level valuation and long-term strategic planning, they fail to reveal a microscopic view of intra-year cash shortfalls, potentially hiding critical cash crunches occurring mid-year. So, this model helps finance professionals to monitor the cash flow throughout the year.
• Captures Business Seasonality Patterns: Annual models flatten seasonal variations, whereas a monthly model tracks peak and off-peak operational cycles in revenue, costs, and working capital demands.
• Tracks Payment & Accrual Timing Mismatches: Cash inflow/outflow timing often deviates from revenue/expense recognition. Monthly modelling explicitly separates cash payments from non-cash accruals (e.g., quarterly tax payments vs. monthly tax accruals, or dividends declared vs. paid).
• Pinpoints Capital Expenditure (CapEx) Timing: Major fixed asset purchases and debt servicing schedules require precise cash management on a month-by-month basis to ensure adequate funds are available when obligations come due.
• Improves Working Capital Management: By monitoring monthly movements in Accounts Receivable, Inventory, and Accounts Payable, the model helps finance managers actively optimize working capital throughout the year rather than relying on year-end static balances.

2. Methodologies & Techniques Used

• Integrated 3-Statement Dynamic Model: Built an interconnected dynamic system linking the Income Statement, Balance Sheet, and Cash Flow Statement across continuous monthly periods.
• Separate Schedules Prepared: Utilized dedicated schedules such as Working Capital (Days Metrics), PP&E (Depreciation/CapEx), Tax Payments, Debt/Revolver, and Equity/Dividends to finalise the dynamically connected integrated model.
• Automatic Revolving Credit Facility & Debt Payment: Incorporated logic to dynamically calculate cash available/required, automatically drawing on a revolver to fulfil cash deficits or paying down debt during surplus months.
• Financial Modeling Best Practices (Inputs, Processing, Outputs): Strict separation of hard-coded inputs (formatted in blue font) from dynamic formula calculations and summary output reporting to keep the model auditable and transparent.
• Model Integrity & Audit Controls (Conditional Formatting & Data Validation): Integrated conditional formatting rules (e.g., highlighting balance sheet imbalance checks, showing error alerts) and data validation input constraints to prevent human entry errors.
• Direct & Indirect Cash Flow Reconciliation: Derived operating cash flows systematically from Net Income, non-cash adjustments (Depreciation), and period-over-period working capital changes.

3. The model helps decision-making in the following ways

• Provides Real-Time Visibility for Decision-Making: By moving from an annual view to a monthly 12-month horizon, finance managers can foresee exact months with net cash usage and proactively plan fund requirements.
• Dynamically Manages Debt Servicing & Cash Buffer: The automated debt schedule calculates precise monthly interest expense, interest payable, scheduled principal amortization, and revolver draws/repays.
• Accurately Shows Periodic Cash Outflows: Allows for custom quarterly timing triggers (such as tax payments in designated months) and dividend payables, preventing surprise cash shortages.
• Reflects Store-Level / Unit-Level Operational Drivers: Uses direct operational inputs (e.g., store count, square footage, sales per square foot, and percentage-based COGS/SG&A drivers) to show how operational changes impact cash flow.

4. Conclusion & Key Highlights

• The Granularity Advantage: Transitioning from annual to monthly cash flow modelling equips the finance team with the precision required for operational liquidity, solvency management, and capital planning.
• Balance Between Transparency and Detail: The core goal of monthly cash flow modelling is creating the right balance, keeping formulas robust and transparent while providing enough operational detail to support executive decisions.
• Key Model Takeaways:
  • Core Structure: Inputs, Processing (Schedules), and Outputs (Integrated 3-Statements).
  • Dynamic Checks: Automated Balance Sheet balancing checks and visual error handling (Conditional Formatting) ensure 100% integrity.
  • Practical Relevance: Indispensable decision-making tool for financial planning & analysis professionals, corporate development teams, and financial consultants managing working capital and short-term debt facilities.

1. Problems the Monthly Rolling-Forecast and Variance Analysis Model Solves:

In fast-paced business environments, relying solely on an annual target creates significant operational blindsides. Building a dynamic Monthly Rolling Forecast and Variance Analysis Model directly addresses the following core challenges:

• Traditional variance analysis only compares actuals against the original budget, missing crucial insights on how the forward-looking outlook evolves month-over-month compared to the previous forecast.
• Traditional annual budgets quickly lose relevance due to market volatility, inflation, or demand shifts, leaving leadership with outdated benchmarks for decision-making.
• Annual plans lack an agile framework to continuously incorporate actual monthly performance while maintaining a constant 12-month forward-looking horizon.
• Without separating sales volume from unit pricing, management cannot easily tell whether a revenue exceed or shortfall was driven by customer demand (volume) or pricing power/discounting strategy (price).
• Without automated date logic, merging historical actuals with future forecast months requires manual copy-pasting, which increases formula errors and delays month-end reporting.

2. Methodologies & Techniques Used

To solve these financial planning issues, the model applies international best practices in designing monthly rolling-forecast and variance analysis model:

• Dynamic “Latest Actuals” Timeline Switch: Utilizes dynamic date toggles and logic switches (Latest Actuals input) to automatically overwrite historical forecast periods with closed actuals across the rolling timeline without breaking downstream formulas.
• Dynamic Graphing & Toggle Data Bridges: Features dedicated graphing data structures linked to user toggles (e.g., Actuals, Forecast, Budget), enabling dynamic visual charts for executive dashboards.
• Dual-Layer Variance Analysis Framework: Computes variances across two key dimensions:
  1. Forecast vs. Original Budget (to evaluate performance against annual strategic targets).
  2. Current Forecast vs. Previous Forecast (to measure re-forecasting precision and month-over-month trajectory changes).
• Isolating YoY & Unit Growth Metrics: Incorporates Year-over-Year (YoY) percentage changes and unit variance tracking to monitor growth momentum and volume trends month by month.
• Integrated Driver-Based Design (Volume, Pricing, & Revenue): Rather than forecasting top-line revenue as a static number, the model builds bottom-up schedules where Total Revenue is dynamically calculated from Volume (Units) and Pricing ($/Unit) drivers.
• Standardised Model Structure: Strictly separates hard-coded inputs, operational driver schedules, calculation outputs, and visualisation layers for transparency and ease of auditability.

3. How the Model Solves the Problem

This rolling forecast model transforms raw monthly financial data into actionable management insights through several key operational mechanisms:

• Maintains Continuous 12-Month Visibility: As each month closes, updating the Latest Actuals date automatically rolls the forecast window forward, ensuring leadership always maintains a full 12-month forward view rather than only looking at yearly progress.
• Pinpoints Root Causes for Faster Decision Making: By splitting revenue into distinct Volume and Pricing schedules, commercial teams can pinpoint whether missed revenue targets require price adjustments, promotional incentives, or sales support.
• Facilitates Agile Resource Reallocation: Tracking variance against the Previous Forecast allows finance managers to spot early trend deviations, enabling proactive budget reallocations before quarter-end surprises occur.
• Automates the Financial Planning & Analysis Monthly Cycle: Automated schedule linking minimizes manual adjustments during the monthly close, reducing month-end close time and enabling financial planning & analysis professionals to shift focus from data entry, report preparation to strategic analysis.

4. Conclusion & Key Highlights

Moving from a static annual budget to an automated 12-month rolling forecast and variance analysis is one of the most impactful upgrades an organization can make to its financial planning process.

Key Highlights:

• Two Variance Lenses Are Better Than One: Comparing current forecasts against both the original budget and prior-month reforecasts provides a complete picture of operational momentum and forecasting accuracy.
• Driver-Based Forecasting is Superior: True financial visibility comes from understanding underlying operational drivers such as volume and price rather than modelling top-line numbers in isolation.
• Automation Protects Model Integrity: Leveraging dynamic timeline toggles ensures smooth month-to-month transitions while eliminating manual tasks and maintaining model integrity. The model is user-friendly and provides actionable insights for decision-makers.

If you are among the CFO who are facing the mentioned issues, then the Power BI financial statement Model is the best solution that makes work-life easier while allowing the team to focus on productive tasks.

1. The finance team spend so much time on manual work to finalize the financial statements.
2. During the manual work process, the chances of human errors and manual intervention are higher, which requires extra time for reconciliation.
3. Every time the reports are prepared the outcomes are different due to the manual errors.
4. There is always a time pressure to deliver the financial reports at month-end close time.
5. It is difficult to connect the financial data to real-time dashboards highlighting key indicators of interest.

Approaches to resolve the issues: I have used the skills that I have learned during the Business Intelligence & Data Analysis professional certification from Corporate Finance Institute to build this dashboard.

1. Use Azure Data Studio to extract data from the database.
2. Connect to the database using Power Query Editor in power BI. Navigate to the SQL view and load as a Staging Query.
3. Create the Fact and Dimension tables by referencing the Staging Query.
4. Load and relate the queries to create the data model.
5. Create a DAX measure to aggregate the GL Transaction Amount column.

This Power BI Financial Model is designed to solve problems and make work-life easier in the following ways while increasing productivity:

1. Automate the financial statement preparation task, which is a big-time saver.
2. It eliminates the manual reconciliation task for preparing financials, simultaneously improving the accuracy.
3. Reduces the manual intervention on data maintaining the data integrity.
4. High level summary is reflected in the real-time dashboard and that is customizable as per the need of executive leadership.
5. Trends in the financial data can be easily reflected in the dashboards through DAX measures and time intelligence.
6. Maintain a single source of truth and consistency in reporting.
7. The dashboard is interactive, so users can dive deeper into the analysis, focusing on certain key areas of interest. Users can use the analysis tool in Power BI to uncover insights hidden behind the numbers.

Key financial highlights of the report:

1. Gross profit margin falls down from 22.57% in December 2019 to 18.41% in February 2020 and we can see steady growth then after.
2. Gross margin and operating margin are 21% and 5% on average across three given years.
3. The lowest current ratio across three years is on Q4 of 2020.
4. Cumulative Amount for Current Assets trended up between January 2019 and October 2021 with a rise of 3.1M which is around 51% rise.
5. Current Ratio trended up between January 2019 and October 2021 with a rise of 0.02 from 2.25 to 2.26 with quarterly fluctuation over the three years.

Why do we need financial models?

Forward-looking insights and recommendations that drive the organisation forward with confidence while minimising financial uncertainty are equally important as understanding the financial health of a business thoroughly.

Well-designed financial models are effective decision-making tools that finance professionals use to provide data-driven insights and recommendations so that the decision-maker can rely on and act with greater confidence.

When decisions affect growth, spending, funding, or cash, preparing the 3-statement financial models is crucial.

1. It shows the full financial picture.
   It connects profitability, cash flow, assets, liabilities, and equity, not just the income statement.
2. It separates profit from cash.
   A company can report profit while cash declines because of inventory, receivables, capital spending, or debt repayments.
3. It reveals financial ripple effects.
   For example, higher sales can increase receivables; a new asset creates capex, depreciation, and potentially financing needs. Supporting schedules make these links visible.
4. It converts assumptions into forecasts.
   Revenue growth, margins, hiring, payment terms, and capex assumptions can be translated into projected financial statements.
5. It makes uncertainty measurable.
   A model can test base, upside, and downside cases. Changes in assumptions can ripple through cash flow, break-even timing, and returns.
6. It identifies funding requirements early.
   The model helps show whether future cash generation can fund operations and growth, or whether debt or equity may be needed.
7. It supports valuation and transactions.
   The 3-statement model is the foundation for DCF valuation, scenario analysis, capital raising, M&A, and LBO models.
8. It improves decision discipline.
   Decision-makers must state assumptions explicitly instead of relying on vague expectations or isolated spreadsheet calculations.
9. It helps find inconsistencies.
   A balanced, controlled model provides checks that can expose formula errors or conflicting assumptions before a decision is made.
10. It improves credibility with stakeholders.
    A clear model gives lenders, investors, executives, and business partners a transparent explanation of how a plan affects profit, liquidity, and funding.

Conclusion: A 3-statement model is not just a spreadsheet. It is a decision-making tool that shows whether a business plan is profitable, financeable, and cash sustainable.

How we prepare financial models?

We prepare financial models based on a thorough understanding of the key drivers of the business’s performance, addressing key questions about the business. The income statement shows a meaningful measure of profitability. The cash flow statement assesses the management of cash. The balance sheet reviews assets and how they are financed.

Financial models are prepared following a structured process to support decision-making and clear communication. We start with the output in mind, that include the user-friendly dashboard and then decide the inputs, that includes key drivers of the business, and finally design the model, which includes financial statements, operational schedules and structures. We follow the mentioned steps to prepare models.

• Prepare reports to evaluate business.
• Add clear schedules to support them.
• Link the financial statements together
• Confirm that they balance correctly
• Review the model for integrity
• Setup for presentation and printing

We start by organising all of the company’s figures and then construct schedules to share various details about the company. Each of these schedules shows different aspects of health (i.e., financial statements). Finally, we use these schedules to get a more wholesome view of the health of the company. Financial models are prepared in a structured way so that they can guide through the ambiguity and help drive the organisation forward with greater confidence while minimising uncertainty and surprises.