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

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.

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.

If you have an emergency need for cash, get lender referrals at Cashry.

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.

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.

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.