How do you handle uncertainty and volatility in your sales forecasting process?

1 Understand your data sources

The first step in any sales forecasting process is to collect and analyze your data sources. These can include your CRM system, your sales history, your market research, your customer feedback, and your industry trends. You need to understand where your data comes from, how reliable it is, and how it relates to your sales cycle and your customer journey. You also need to identify any gaps, inconsistencies, or biases in your data that might affect your forecast accuracy.

2 Choose your forecasting method

The next step is to choose your forecasting method. Depending on your business model, sales strategy, and data availability, you may use historical forecasting, intuitive forecasting, or quantitative forecasting. Historical forecasting takes your past sales performance as a basis for future projections, though it may not account for seasonality, growth, or market changes. Intuitive forecasting relies on personal knowledge and insights to predict sales outcomes; however, it may be subjective or biased. Quantitative forecasting uses mathematical models and algorithms to calculate projections; though it is objective and precise, it may also be complex or costly.

3 Adjust your forecast regularly

The third step is to adjust your forecast regularly. No matter how good your forecasting method is, you will always face some uncertainty and volatility in your sales environment. You need to monitor your actual sales performance, your pipeline changes, your market fluctuations, and your customer feedback, and compare them with your forecast. You also need to update your assumptions, your variables, and your models based on the new information and insights that you gather. You should review and revise your forecast at least monthly, quarterly, and annually, depending on your business cycle and your goals.

4 Communicate your forecast clearly

The fourth step is to communicate your forecast clearly. Your sales forecast is not only a tool for yourself, but also for your team, your stakeholders, and your organization. You need to share your forecast with them in a clear, concise, and consistent way. You need to explain your forecasting method, your data sources, your assumptions, and your expectations. You also need to highlight your confidence level, your margin of error, and your scenarios. You should use visual aids, such as charts, graphs, and tables, to make your forecast easy to understand and follow.

5 Learn from your forecast errors

The fifth step is to learn from your forecast errors. No matter how careful you are, you will inevitably make some errors in your sales forecasting process. You may overestimate or underestimate your sales potential, miss some opportunities or risks, or face some unexpected events or changes. Instead of ignoring or hiding your errors, you should embrace them as learning opportunities. You should analyze your errors, identify their causes and effects, and find ways to improve your forecasting process. You should also solicit feedback from your team, your stakeholders, and your customers, and use their input to refine your forecast.

6 Use tools and technology

The sixth step in the sales forecasting process is to use tools and technology to support your efforts. CRM software can help you manage customer relationships, track sales activities, and generate reports on performance and pipeline. Forecasting software can apply different methods, models, and algorithms to your data, producing accurate forecasts with various scenarios and probabilities. Artificial intelligence technology leverages machine learning, data mining, and natural language processing to improve data quality, accuracy, and insights, as well as detecting patterns, trends, and anomalies in the sales environment.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?