These models are used for planning and managing a company’s financial performance. They typically project revenues, expenses, and cash flows based on historical data, business assumptions, and market trends. Budgeting and forecasting models help companies set financial targets, monitor progress, and make informed decisions.
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- Zero-Based Budgeting (ZBB) – ZBB is a budgeting approach where every budget item starts at zero, and the budget needs to be justified from scratch every time a new budget period begins.
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- Rolling Forecasts – Rolling forecasts are used to update the forecast regularly based on actual results and changes in the business environment. This allows businesses to adjust their plans and strategies quickly to stay on track.
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- Activity-Based Budgeting (ABB) – ABB is a budgeting approach that assigns costs to specific activities or tasks and then uses that information to make more accurate and informed budgeting decisions.
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- Driver-Based Budgeting – Driver-based budgeting is a budgeting approach that uses the business’s key performance indicators (KPIs) as the basis for budgeting. This approach ensures that budgets are aligned with the business’s strategy and goals.
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- Bottom-up Budgeting – In bottom-up budgeting, each department or team within a business is responsible for creating its own budget. The individual budgets are then combined to create an overall budget for the business.
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- Top-down Budgeting – Top-down budgeting is the opposite of bottom-up budgeting, where the overall budget is set by senior management, and then individual departments or teams are given their budget allocation.
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- Cash Flow Forecasting – Cash flow forecasting involves estimating the cash inflows and outflows for a business over a certain period. This helps businesses plan for cash shortfalls or surpluses and make decisions about financing and investment.
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- Monte Carlo Simulation – Monte Carlo simulation is a statistical technique used to model the probability of different outcomes in a situation with multiple variables and uncertainties. This can be used to help with forecasting in situations where there are a lot of unknowns or variables at play.