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<\/a><\/p>\nTable of Contents<\/strong><\/p>\n Financial forecasting is often conflated with the other key financial planning<\/a> processes it generally informs \u2014 namely, budgeting. Though the two activities are often closely linked, I think it is important to clearly differentiate between them.<\/p>\n The difference between a financial forecast and a budget<\/a> boils down to the distinction between expectations and goals. I like to remember forecast details as something a business can realistically expect to achieve over a given period.<\/p>\n Forecasting represents a reasonable estimate of how a company will likely perform \u2014 based on current and historical financial data, broader economic trends, foreseeable factors that might impact performance, and other variables that can be viably accounted for.<\/p>\n How to Create Accurate Sales Forecasts in 2024<\/a><\/p>\n A budget, on the other hand, is the byproduct of a financial analysis rooted in what a business would like to<\/em> achieve. It\u2019s typically updated once per year and is ultimately compared to the actual results a business sees to gauge the company\u2019s overall performance.<\/p>\n Now that I have given you an overview of the topic, let\u2019s take a look at some of the most popular financial forecasting models.<\/p>\n <\/a> <\/p>\n Top-down forecasting is a way for a company to make financial predictions by starting with broader market information and working down to estimate its own revenue.<\/p>\n I like how simply Erik Lidman<\/a>, CEO & Founder at Aimplan, explains top-down forecasts. In his LinkedIn post<\/a>, he writes that top-down forecasts:<\/p>\n I think this approach is pretty simple. The company begins by looking at the total amount of money its entire market makes. Then, it calculates how much of that total it thinks it can earn. The calculation is often done with the help of tools such as fp&a software<\/a>, which allows you to collect all the data you need.<\/p>\n Imagine a company that is part of a market that makes about $1 billion each year. If the company believes it can capture 2.5% of that market, a top-down forecast would predict it could make $25 million in the next year.<\/p>\n The \u201cDelphi\u201d method is named after an ancient Greek city<\/a> called Delphi, where people would go to ask a wise oracle named Pythia<\/a> for advice.<\/p>\n In a similar way, the Delphi forecasting method is all about getting advice from experts to help a business make predictions.<\/p>\n Ivan Svetunkov<\/a>, an expert in demand forecasting, explains Delphi forecasting as a method that sidesteps probability. He explains it as follows:<\/p>\n \u201cDelphi method can be used for long term forecasting, but typically focuses on forecasting general tendencies (structure) in the data, ignoring the uncertainty around it.\u201d<\/p>\n Source<\/a><\/em><\/p>\n To explain Delphi forecasting, I have written a simple explanation of how it works:<\/p>\n A business sends multiple rounds of questionnaires related to its finances to a group of experts. After the first round of answers comes in, everyone gets a summary of what the others said.<\/p>\n This way, each expert can see the group\u2019s thoughts and adjust their answers in the next round if they want. The goal is to go through a few rounds of this back-and-forth until the experts agree on predictions the business can use.<\/p>\n A company sends a questionnaire to be filled out by experts. After everyone submits their answers, they all get a summary showing what the other experts think about the company\u2019s financial future.<\/p>\n Seeing everyone else\u2019s thoughts can help each expert think in new ways, so they fill out a new questionnaire with updated ideas. This process repeats, with each round bringing the experts a bit closer in their predictions. Finally, when most experts agree, the company uses this shared view to make its financial forecast.<\/p>\n In my opinion, statistical forecasting is just a fancy way of saying \u201cmaking predictions using numbers and data.\u201d It\u2019s simply a type of forecasting where I can look at data from the past \u2014 like sales numbers or other facts \u2014 and use it to guess what might happen in the future.<\/p>\n Let\u2019s say my company wants to know how much money it might make over the next few months. One way we could do this is by using the \u201cmoving average\u201d method. My company would look at how much money it made each day over the last 100 days, then take the average of those numbers. (I talk more about moving averages in the section below.)<\/p>\n By using this average, my company can make a good guess about how much it might earn over a similar period coming up.<\/p>\n Bottom-up financial forecasting is just the opposite of top-down forecasting. In this approach, a company starts by looking at the details of what\u2019s happening with its customers or products and builds to a bigger picture of its future revenue.<\/p>\n Again, I will quote Erik Lidman for his simple explanation of bottom-up financial forecasting. Bottom-up forecasts:<\/p>\n Bottom-Up Financial Forecasting Example<\/strong><\/p>\n Let\u2019s say a company wants to predict how much money it might make next year. It would start by looking at how many products it sold last year and decide how much it plans to charge for each one this year. Then, by multiplying these two numbers, the company gets an estimate of its total sales.<\/p>\n Of course, real forecasting is a bit more complicated than that. A company would usually look at other details too, like how many customers they expect to have or how likely those customers are to stick around. This way, they get a more accurate prediction by building up from the ground level.<\/p>\n Put in simple terms, hierarchical financial forecasting is like creating a roadmap for predictions by organizing data into different levels or categories. Imagine it as a family tree for financial projections, where each branch represents a category, and smaller branches represent subcategories within it.<\/p>\n Source<\/a><\/em><\/p>\n This method is useful because it combines both big-picture (top-down) and detail-focused (bottom-up) forecasting. By doing this, you get a more complete and accurate forecast, capturing trends at each level \u2014 overall and specific \u2014 making it easier to make smarter decisions, like what to stock up on or where to invest resources.<\/p>\n Hierarchical Financial Forecasting Example<\/strong><\/p>\n For example, if you\u2019re forecasting sales, you might start with a top category, like \u201cclothing.\u201d Then you break it down to \u201cmen\u2019s wear\u201d and \u201cwomen\u2019s wear.\u201d You can go further, breaking \u201cmen\u2019s wear\u201d into \u201cshirts,\u201d \u201cpants,\u201d and \u201cties.\u201d This lets you see not only the big picture (overall clothing sales) but also specific details (like how many black ties might sell within men\u2019s wear).<\/p>\n <\/a> <\/p>\n Straight-line forecasting is one of the simplest ways a business can predict its future finances. It\u2019s based on basic math and tends to give rough estimates, unlike some more complicated methods that provide more detailed projections.<\/p>\n In straight-line forecasting, a company looks at how much it has grown in the past and uses that information to predict future growth. It\u2019s usually used when a business expects to see steady, consistent growth over time.<\/p>\n Let\u2019s assume my business has been growing at a steady rate of 5% each year for the last four years. This way, I can use the same 5% growth rate to predict my revenue for the next few years. It\u2019s a simple way to make projections based on past performance.<\/p>\n The straight line forecasting method does not take into consideration the fluctuations in the market and other factors that could impact growth, such as new competitors or shifts in the economy.<\/p>\n Simple linear regression is a way for businesses to make predictions by looking at how two things are connected.<\/p>\n Imagine you have one thing you can control or measure, like the country\u2019s GDP and another factor you want to predict, like how much money the company might make. By studying the relationship between these two, the business can make a good guess about future revenue.<\/p>\n So, if GDP goes up or down, the company can see how this change might affect its earnings.<\/p>\n If you wish to get a thorough step-by-step guide, I recommend reading this article<\/a> on how to forecast sales using linear regression.<\/p>\n Simple linear regression is a good way to make predictions, but it doesn\u2019t always give us an accurate picture of financial performance because there are usually many things affecting the outcome, not just one factor.<\/p>\n This is where multiple linear regression comes in. As the name suggests, it looks at more than one factor to make a prediction.<\/p>\n Source<\/a><\/em><\/p>\n Instead of just focusing on how one thing \u2014 like the price of a product \u2014 might affect a company\u2019s finances, multiple linear regression looks at two or more different factors at the same time to get a more accurate picture of what might happen.<\/p>\n Moving average forecasting is a method often used to track the direction of a stock\u2019s performance, but businesses can also use it to predict their own financial results.<\/p>\n The idea is simple: I take the average of a set of numbers from the past, like sales or revenue, and use that average to estimate what might happen in the future.<\/p>\n I like what Nicolas Vandeput<\/a>, a person who does demand and supply planning, writes about using moving averages<\/a>:<\/p>\n \u201cDon\u2019t compare your forecasting accuracy to industry benchmarks. They\u2019re irrelevant.<\/p>\n \u201cInstead, compare your forecasting accuracy against simple statistical benchmarks such as moving averages. Moving averages are a fair benchmark: They will deliver higher (or lower) accuracy depending on the product, period, and market.<\/p>\n \u201cThat\u2019s perfect. Also, they\u2019re free.\u201d<\/p>\n The moving average method works best for looking at short-term trends, like weekly, monthly, or quarterly changes, rather than long-term projections. It helps businesses see patterns and make educated guesses about what\u2019s coming next.<\/p>\n <\/a> <\/p>\n To get the most out of a financial forecast, I like to know why I\u2019m using it in the first place. I start by asking myself questions such as:<\/p>\n Only when I have a clear intent behind my financial forecast will I be able to have a more concise and clear result to search for once I begin.<\/p>\n To track the progress of my financial forecast, I should have a good idea of my current and past finances. Here, I give myself time to analyze the historical financial data and records, including:<\/p>\n My forecast will only be as accurate as the information I collect, so I try to get as much relevant data as possible for better results and understanding.<\/p>\n I decide how far into the future I need the documentation for in order to evaluate a business\u2019s financial performance. This can look like weeks, months, quarters, or even years of data collection.<\/p>\n It\u2019s most common for a business to conduct a forecast over the course of a fiscal year, but it can be unique for every business.<\/p>\n I choose from one of the four financial forecasting methods mentioned above. Before choosing one, I see if it aligns with my previously declared purpose and goals.<\/p>\n As the financial forecast delivers new data, it is time to monitor and analyze the data differently. Some different ways that data can be used are as follows:<\/p>\n For example, if expenses are higher than anticipated, a business can identify the cause and take corrective action to prevent it from negatively impacting financial performance.<\/p>\n Weighing financial results against these goals enables a business to measure its progress toward achieving them. This can help the business identify where it is falling short and adjust to get back on track.<\/p>\n By understanding how much cash is coming in and going out, a business can make smarter decisions about budgeting and spending.<\/p>\n And it doesn\u2019t have to be a tedious task to analyze your financial data \u2014 thankfully, there are plenty of forecasting, decision-making, and financial-planning tools available for this purpose. Let\u2019s go through some of my favorites. To give you an overall view of the software, I have also included comments from users who have actively used each of the software.<\/p>\n <\/a> <\/p>\n Pricing:<\/strong> Contact for pricing<\/a><\/p>\n Best for:<\/strong> Collaboration<\/p>\n Sage Intacct is a multifaceted accounting and financial planning software with an accessible interface and a suite of features that can streamline your financial forecasting time by over 50%.<\/p>\n The platform\u2019s automated forecasting resources effectively eliminate the stress, legwork, and room for error that often come with spreadsheet-based planning.<\/p>\n What I like: <\/strong>Sage Intacct separates itself from similar applications through its accessibility and room for collaboration. The software is particularly user-friendly and offers a singular, centralized solution for virtually any stakeholder within an organization to easily contribute to and make sense of financial projections.<\/p>\n Comments<\/strong> From Users<\/strong><\/p>\n Pricing:<\/strong> Plans start at $83\/month<\/a>.<\/p>\n Best for: <\/strong>Pure financial forecasting<\/p>\n PlanGuru is a specialized financial forecasting tool that offers 20 different forecasting methods, allowing you to project financial outcomes for up to 10 years. What\u2019s unique here is how easily you can bring non-financial data into your forecasts, which means you can consider factors beyond pure financials.<\/p>\n Plus, its scenario analysis feature gives you the power to explore the impact of potential events on your business. For most small and medium businesses, PlanGuru offers flexible pricing that makes it accessible. I suggest starting with the basic plan at $83 per month, then adding users as needed for an additional $25 per user.<\/p>\n What I like: <\/strong>Unlike some broader accounting platforms that include forecasting as just one of many features, PlanGuru is specifically built for financial projections.<\/p>\n It\u2019s built to support strategic planning with its range of 20 forecasting methods and other features that help you look ahead. If you\u2019re searching for a budget-friendly platform focused solely on financial forecasting, PlanGuru is worth a closer look.<\/p>\n Comments From Users<\/strong><\/p>\n Pricing:<\/strong> Contact for pricing<\/a><\/p>\n Best for:<\/strong> A dynamic range of forecasting options<\/p>\n Workday Adaptive Planning offers a powerful blend of accessibility and functionality in financial forecasting, making it adaptable to a variety of business needs.<\/p>\n With its capability to integrate real-time financial and operational data, the software allows building and comparing different what-if scenarios that reflect accurate, effective projections.<\/p>\n It\u2019s essentially a software that I can use to forecast over any timeframe, whether daily, monthly, quarterly, or long-term, ensuring flexibility no matter the planning timeframe.<\/p>\n What I like: <\/strong>One of the standout features of Workday Adaptive Planning is its support for both detailed bottom-up and top-down forecasts, which gives businesses of all sizes a tailored approach to financial projections.<\/p>\n Whether I\u2019m creating forecasts based on executive targets or operational data from the ground up, this tool enables precise, impactful insights. If you\u2019re looking for forecasting without compromising on accuracy, I recommend Workday Adaptive Planning as a tool well worth considering.<\/p>\n Comments From Users<\/strong><\/p>\n Pricing:<\/strong> Contact for pricing<\/a><\/p>\n Best for:<\/strong> A familiar, Excel-like experience<\/p>\n Limelight is an integrated, web-based financial planning tool that provides businesses with a centralized solution for almost all of their forecasting needs. The software is designed with finance and accounting teams in mind. It provides powerful automation and seamless data integration to simplify the forecasting process, all while maintaining accuracy and quality.<\/p>\n What I like: <\/strong>If you\u2019re like me and have spent a lot of time using Excel, you\u2019ll appreciate how Limelight\u2019s user experience is designed to mirror it.<\/p>\n This makes it especially easy for CFOs, controllers, budget managers, and other finance professionals to jump in and start using it without a steep learning curve.<\/p>\n If you\u2019re looking for a forecasting tool that\u2019s both powerful and user-friendly, I definitely recommend considering Limelight.<\/p>\n Comments From Users<\/strong><\/p>\n\n
Forecasting vs. Budgeting<\/strong><\/h3>\n
Financial Forecasting Models<\/strong><\/h2>\n
1. Top-Down Financial Forecasting<\/strong><\/h3>\n
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Top-Down Financial Forecasting Example<\/strong><\/h4>\n
Benefits of Top-Down Forecasting<\/strong><\/h4>\n
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Drawbacks of Top-Down Forecasting<\/strong><\/h4>\n
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2. Delphi Forecasting<\/strong><\/h3>\n
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<\/p>\nDelphi Financial Forecasting Example<\/strong><\/h4>\n
Benefits of Delphi Forecasting<\/strong><\/h4>\n
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Drawbacks of Delphi Forecasting<\/strong><\/h4>\n
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3. Statistical Forecasting<\/strong><\/h3>\n
Statistical Financial Forecasting Example<\/strong><\/h4>\n
Benefits of Statistical Forecasting<\/strong><\/h4>\n
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Drawbacks of Statistical Forecasting<\/strong><\/h4>\n
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4. Bottom-Up Financial Forecasting<\/strong><\/h3>\n
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Benefits of Bottom-Up Forecasting<\/strong><\/h4>\n
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Drawbacks of Bottom-Up Forecasting<\/strong><\/h4>\n
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5. Hierarchical Financial <\/strong>Forecasting<\/strong><\/h3>\n
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<\/p>\nBenefits of Hierarchical Forecasting<\/strong><\/h4>\n
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Drawbacks of Hierarchical Forecasting<\/strong><\/h4>\n
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Financial Forecasting Methods<\/strong><\/h2>\n
1. Straight Line<\/strong><\/h3>\n
2. Simple Linear Regression<\/strong><\/h3>\n
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<\/p>\n3. Multiple Linear Regression<\/strong><\/h3>\n
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<\/p>\n4. Moving Average<\/strong><\/h3>\n
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<\/p>\nHow I Do Financial Forecasting<\/strong><\/h2>\n
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<\/p>\n1. Define my purpose for using a financial forecast.<\/strong><\/h3>\n
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2. Gather historical data.<\/strong><\/h3>\n
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3. Set a time frame for my forecast.<\/strong><\/h3>\n
4. Choose a forecasting method.<\/strong><\/h3>\n
5. Monitor and analyze forecast results.<\/strong><\/h3>\n
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Financial Forecasting Software<\/strong><\/h2>\n
1.<\/strong> Sage Intacct<\/a><\/strong><\/h3>\n
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2.<\/strong> PlanGuru<\/a><\/strong><\/h3>\n
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3.<\/strong> Workday Adaptive Planning<\/a><\/strong><\/h3>\n
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4.<\/strong> Limelight<\/a><\/strong><\/h3>\n
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