Budgeting versus Forecasting for Your Business
Every business needs a budget to operate and a sales forecast for planning. Budget tools are part of the financial system found at the Goalry Mall. Budgeting for business owners with sophisticated sales forecasting is a key component of building wealth.
Budgeting and forecasting work together as a business strategy. The comparison of budgeting versus forecasting shows that, in general, budgeting is an allocation of resources for expenditures, and forecasting is a prediction of sales revenues and/or income.
An Overview Of Budgeting
Every budget is a guideline for what the company thinks it will spend and what the company wants to allocate for each line item. For budgeting, there are fixed costs and variable costs.
Fixed Costs
A budget includes items with a fixed cost, such as the monthly rent or an equipment lease payment.
Other categories of fixed costs include:
Annual Salaries
Property Taxes
Insurance
Depreciation
Loan payments on a fixed amount, such as a mortgage payment
Anything that has a certain monthly or annual expense amount must be paid
Variable Costs
Variable cost items change with the business's activity, such as the cost of goods sold (COGS). The COGS depends on the prices of raw materials, the labor and other expenses that go into producing the goods, and the amount of inventory that is sold.
Other categories of variable costs include:
Hourly Wages
Sales Commissions
Employee Benefits
Shipping and Handling
Interest Expense for a Flexible Credit Line
Credit Card Processing Fees
Any expenses that change based on the business activity or circumstances
Some budget line items must be paid. Those are called mandatory expenses. The most common mandatory expense is the monthly rent due on a lease contract for a company’s facilities.
Other expenses may be discretionary. Discretionary expenses can be adjusted or not spent based on the circumstances. For example, there may be an allocation in the annual budget to construct a new employee lounge, which is a discretionary expense.
If this line item for a new employee lounge was in a company’s budget for 2020 and the pandemic hit, there probably was no need to build one. Many companies had most of their employees working from home. Under such circumstances, it would be prudent for the senior executive of a company to cancel the plans to build a new employee lounge. Since this is a discretionary item, the funds allocated in the budget for the new lounge could be re-allocated to other items with a more urgent need.
Most budgets have the structure of look-back, estimate-forward. Many of the line items in a budget are based on what the company paid for those items the previous year, with some adjustments for price changes.
For example, if the rent was $5,000 a month last year, then allowing for an annual rental increase stated in the contract, the rent might be $5,250 for the upcoming year.
Using a budget tracker is a good way to compare the line items cost for something paid last year with the current cost. It may also be helpful to compare similar periods from historical data with the current period. Moreover, budgets can be set up to track variance from the budgeted amount and flag any line items with an unacceptable variance, which shows an unexpected expense.
For example, if the budgeted rent is $5,250 according to the lease contract and the rent is suddenly higher at $5,500, this should trigger an investigation of why the cost exceeds the budgeted amount. Perhaps there was an unexpected cost that the landlord has the right to add to the rent?
Low - Mid - High Sales Forecasts
Higher sales volumes increase the total CGS. Therefore, forecasting sales is a critical element for creating a budget. Small businesses may benefit by evaluating budgets based on the expectation of sales in three categories :
lower-than-expected,
as expected, and
higher-than-expected
The budget analysis is run using at least three sales volumes to see how they impact the cost of the line items in the budget.
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Cash Flow Forecasting
Along with sales forecasting, cash flow forecasting is extremely important. A company may run out of cash. This may happen even when it has significant sales on the books. A common problem happens if the collection of the sales revenues does not occur at the pace needed to keep up with payments of all expenses.
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Contingency Forecasting
Contingency forecasting is an analytical method to prepare for the worst-case scenarios and have a plan to implement emergency measures if facing a severe setback. Surprisingly, this also includes planning for unexpected success.
A business survives by being able to weather the storm of a major disaster. The pandemic gave us ample evidence of what this looks like across all industry sectors and globally.
Moreover, a business also needs to handle a “success disaster.” An example of a successful disaster would be if major media attention suddenly focuses on a company’s innovative product and the company’s website breaks down because it cannot handle the web traffic that suddenly increases.
In such a case, if there is an advance notice that media attention is likely, as the CEO is scheduled to appear on a national television show, then the website needs to be configured to handle the massive spike of web traffic that might occur. Contingency planning would put a more robust website solution and the ability to handle increased Internet traffic in place before the CEO’s appearance on the television show.
The Benefits of Accurate Forecasting
The deep analysis uncovers lost opportunities, effective sales strategies, and success rates to produce accurate sales forecasts. Sales managers rely on this analysis to develop an actionable sales strategy that improves the customers’ experiences, such as suggesting products that are better suited to meet a customer’s needs.
Artificial Intelligence And Sales Forecasting
Before artificial intelligence (AI) and machine learning were used to analyze Big Data, most companies had somewhat inaccurate sales forecasting models. Using AI for sales forecasting helps make predictions more accurate.
Sales forecasting uses the following parameters:
Quotas: Usually, there are individual quotas for each salesperson, team quotas, and perhaps departmental quotas.
Documentation: The sales processes are documented so that the sales team has procedures to follow.
Tracking: The quota targets are broken down into timelines useful for time-series analysis of daily sales, weekly sales, monthly, and annual sales. Sales are tracked. The volumes are compared to the expected sales.
Forecasting Errors: Forecasted sales are compared to actual sales. A calculation determines the difference between the forecast and what actually happened. It is useful to track the actual dollar amount of the errors and the percentage amount of the errors. A percentage forecasting error allows comparison between different product lines and packaging configurations.
Customer Relationship Management: The CRM system collects data from all the customer touchpoints starting with prospects, leads, and customers. This data set is used for machine learning analysis with AI algorithms to uncover insights about customer behavior.
Internal and External Factors
Sales forecasts are influenced by both internal and external factors. The internal factors that impact sales include changes in personnel, discontinuing products, and introducing new products. The external factors that impact sales include competitors’ offerings, general economic conditions, seasonal demand, and unexpected events such as the pandemic.
To create highly accurate sales forecasts, the following tools are helpful:
Real-Time Accounting System: Accounting data collected in real-time for immediate analysis is far more useful than relying on outdated information. Historical data is useful for trend analysis under normal operating conditions. However, the pandemic is an example of a major disrupter that required all sales forecasts to be recalibrated.
Sales Analytic Platform: A robust online sales-tracking system that integrates with the CRM system allows sales managers to develop a sales campaign, analyze customers' behavior, and track progress.
AI Algorithms: Data mining of large data sets (i.e., Big Data) is typically useful for large enterprises. Machine learning models are applied to analyze the data to uncover trends and patterns that are not readily apparent through casual observation. From these insights, AI algorithms are developed to use as predictors for sales forecasting.
Sales forecasting, which is AI-driven, produces predictive estimates for regions, target market segments, and types of products.
Pandemic Recalibration
In the case of the pandemic, historical data was no longer valid, so as businesses began to start up again, the systems needed recalibration. In most cases, the AI-driven machine learning started again from scratch with the collection of new data about post-pandemic customer behaviors, preferences, and purchases.
Conclusion
Managing a business properly requires understanding the differences between budgeting versus forecasting. Successful business owners apply the best forecasting models possible to empower their company’s budget and make it a viable guide for running their business effectively.