6 Ways to Improve Forecast Accuracy 

Forecast accuracy is critical for predicting future financial performance, but studies show that only 22% of companies get it right. Plus, 52% of leaders report their organization regularly misses forecasts by 10% or more. When the numbers don't add up, neither will business decisions for budgets, operations, and cash flow. While projected outcomes are never guaranteed, there are strategies to improve financial forecasting accuracy. 

1. Set Sales and Revenue Goals

Before diving into the forecasting process, it is essential to establish clear sales and revenue goals. These goals will serve as a benchmark for evaluating sales forecast accuracy and provide direction for long-term growth plans, resource allocation, and market share targets.  

Setting sales and revenue goals requires a good mix of data and analysis, including:

• Sales data: sales volume, conversion rates, sales cycle, sales revenue, price changes, renewal rates, and inventory levels.
• Market trends: competitor earnings, consumer surveys, market share, and economic reports.
• Financial reports: income statements, balance sheets, cash flow statements, and statements of shareholder equity.

The process of analyzing sales data, spreadsheets, and surveys should align sales and revenue goals with overall business objectives. This alignment ensures everyone is on the same page and moving in the same direction.

2. Choose a Financial Forecast Method

Financial forecasting methods are generally divided into quantitative forecasting and qualitative forecasting. Quantitative methods use historical data to identify trends and reliable patterns. On the other hand, qualitative methods rely on expert opinions and research about market conditions and company performance.  

Quantitative Forecasting Methods

• Historical sales analysis: This is the most basic method that uses past sales data to predict future performance. It assumes trends will continue, like using sales from the previous year to estimate sales for the upcoming year.
• Time series analysis: This method uses mathematical models to analyze historical sales data and identify trends. Time series analysis also accounts for seasonality and cyclical patterns in sales data.
• Regression analysis: This is a statistical method that identifies the relationship between variables and sales. Historical sales data and other factors are analyzed to predict how sales performance will change over time.

Qualitative Forecasting Methods

• Expert opinions: This approach analyzes opinions from industry experts and stakeholders. It relies on the knowledge and expertise of individuals who have experience in the industry or the product category.
• Market research: This research provides insights into consumer behaviour and competitor trends when a company plans to enter a new market. Common types of research include customer surveys, focus groups, and product testing.
• Delphi method: This process involves experts answering a series of questionnaires about sales forecasts. The results are aggregated and redistributed for experts to adjust predictions until there is a consensus opinion.

There's no one-size-fits-all approach to financial forecasting. Each method has its strengths and shortcomings based on specific needs and stages of growth. In practice, most companies use multiple methods to develop more accurate forecasting systems.

3. Frequently Update Financial Records

Incomplete or outdated financial records are the most common culprits of inaccurate financial forecasts. Any errors or duplications will be incorporated into forecasting models that end up driving business decisions down the wrong path.

For accurate forecasting, financial records should be updated on a regular basis. This includes recording sales, expenses, invoices, receipts, and other financial transactions every month or quarter. Not only will frequent updates improve forecast accuracy, but they also make it easier to spot accounting errors before any flawed data makes it into future projections.

4. Consider Seasonality as a Factor

Seasonal fluctuations in sales can significantly impact forecast accuracy. Look at previous periods to pinpoint which weeks, months, or quarters tend to have higher or lower sales. Analyzing these recurring patterns will help determine the impact of seasonality on future demand.

Once seasonal factors are identified, forecasts can be adjusted accordingly. These insights can be used to accurately predict changes in inventory levels, production capacity, and resource allocation. Seasonality can also inform decisions for staffing requirements, marketing campaigns, and finance planning.

5. Incorporate Market Trends and Competitors

Keep a close eye on market trends and competitor activities that could influence sales. For example, if there's a growing trend for eco-friendly products in your industry, you can adjust sales forecasts to account for increased demand in this specific segment. Similarly, a competitor offering discounted prices is bound to put a dent in demand.

Macro and market data can help fine-tune forecast accuracy. This information is available through surveys, news, interviews, data analysis tools, and industry reports. For competitors, monitor revenue, market share, TAM (total addressable market), stock levels, and product or service categories.

6. Review and Adjust Financial Forecasts

Regularly reviewing forecasts will help assess the accuracy of financial projections. The most common metric for measuring forecast accuracy is Mean Absolute Percentage Error (MAPE). The MAPE forecast accuracy calculation provides a percentage difference between forecasted and actual outcomes, which determines the forecast error.

Any deviations between predictions and actual results indicate when forecasts should be adjusted. Making regular adjustments will improve the accuracy of future predictions while keeping forecasts flexible enough to address dynamic market conditions and changing industry landscapes.

Simplify the Forecasting Process

Accurate forecasting needs a clear process, which isn't always easy to nail down. It requires input from every department and consolidating thousands of data points from multiple sources across multiple tools.

If disjointed reports and spreadsheets are impacting your forecasting process, consider outsourcing a fractional financial analyst. These finance professionals work on a part-time or project basis to turn disparate financial data into actionable insights for making informed decisions, reducing costs, and improving overall performance.

Schedule a free consultation to find out how a fractional financial analyst can help improve your forecast accuracy.