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foresting CHECK LIST

1. Data Collection

Gather historical sales data

Collect data on customer demographics

Compile information on marketing campaigns

Retrieve data on market trends and seasonality

Include competitor analysis data

2. Data Cleaning

Remove duplicates from the dataset

Address missing values appropriately

Standardize formats (dates, currency, etc.)

Validate data accuracy and consistency

3. Data Analysis

Analyze historical sales patterns

Identify peak sales periods and trends

Evaluate the impact of external factors (economic changes, etc.)

Segment data by product categories and customer groups

4. Forecasting Method Selection

Choose appropriate forecasting models (e.g., time series, causal models)

Evaluate qualitative vs. quantitative forecasting techniques

Consider using advanced analytics (e.g., machine learning algorithms)

5. Forecast Development

Develop initial forecasts based on chosen models

Incorporate external factors (market trends, economic indicators)

Adjust forecasts based on expert judgment and insights

6. Validation and Testing

Compare forecasts against actual sales data

Conduct back-testing to evaluate model accuracy

Adjust models based on validation results

Assess confidence intervals and potential variances

7. Implementation

Integrate forecasts into inventory management systems

Communicate forecasts to relevant departments (marketing, supply chain)

Set up a schedule for regular forecast updates

8. Monitoring and Adjustment

Continuously track actual sales against forecasts

Adjust forecasts as new data becomes available

Review and analyze forecasting performance regularly

Iterate on models and approaches based on learnings

9. Documentation and Reporting

Document the forecasting process and methodologies used

Create reports summarizing forecasts and insights

Share findings with stakeholders for transparency and feedback

10. Training and Development

Conduct training sessions for teams on forecasting methods

Encourage ongoing education on market trends and analytics tools

Foster a culture of collaboration and sharing of forecasting insights

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