2 Choose an appropriate forecasting method

The next step is to select a forecasting method that suits your data characteristics, business objectives, and available resources. There are various methods of demand forecasting, such as qualitative, quantitative, causal, or machine learning. Qualitative methods rely on expert opinions, surveys, or focus groups to generate forecasts. Quantitative methods use mathematical models and statistical techniques to extrapolate historical data. Causal methods incorporate the relationship between demand and explanatory variables, such as price, income, or weather. Machine learning methods use algorithms and artificial intelligence to learn from data and make predictions. You need to evaluate the accuracy, reliability, and complexity of each method and choose the one that best fits your needs.

3 Use a suitable forecasting tool

The third step is to use a tool that can help you perform demand forecasting efficiently and effectively. There are various tools available in the market, such as spreadsheets, software, or platforms, that can help you collect, organize, analyze, and visualize your data. You need to consider the features, functionality, scalability, and cost of each tool and select the one that meets your requirements. Some of the common features of demand forecasting tools are data integration, data cleansing, data transformation, data analysis, data visualization, forecast generation, forecast evaluation, forecast adjustment, and forecast communication.

4 Validate and adjust your forecasts

The fourth step is to validate and adjust your forecasts based on the actual performance and changing conditions. You need to measure the accuracy and error of your forecasts using metrics such as mean absolute error (MAE), mean absolute percentage error (MAPE), or root mean square error (RMSE). You also need to monitor the changes in your demand drivers and update your forecasts accordingly. You can use techniques such as moving average, exponential smoothing, or trend analysis to smooth out the fluctuations and capture the patterns in your data. You can also use scenarios, simulations, or sensitivity analysis to test the impact of different assumptions and parameters on your forecasts.

5 Communicate and collaborate with stakeholders

The final step is to communicate and collaborate with your stakeholders to ensure that your forecasts are aligned with your business goals and strategies. You need to share your forecasts with your team members, managers, suppliers, and customers and solicit their feedback and input. You can use dashboards, reports, or presentations to convey your forecasts clearly and concisely. You can also use tools such as cloud-based platforms, chatbots, or APIs to facilitate the communication and collaboration process. You need to establish a common language, a shared vision, and a feedback loop with your stakeholders to improve your demand forecasting process.

6 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?