MRP FORECAST ACCURACY REVIEW CHECKLIST

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--- DATA SOURCES AND INPUTS ---
[ ] Primary Data Sources Used (Historical Sales Data, Market Research Reports, Customer Orders, Promotional Plans, External Economic Indicators)
[ ] Percentage of Sales Data Used
[ ] Last Data Refresh Date
[ ] Description of External Data Sources
[ ] Data Source Accuracy Rating (1-5) (1 - Very Low, 2 - Low, 3 - Moderate, 4 - High, 5 - Very High)
[ ] Supporting Data Files (e.g., CSV, Excel)

--- FORECAST METHODOLOGIES ---
[ ] Primary Forecasting Method (Moving Average, Exponential Smoothing, Regression Analysis, Collaborative Forecasting, Qualitative Judgement)
[ ] Moving Average Period (if applicable)
[ ] Smoothing Constant (Alpha) (if applicable)
[ ] Secondary Forecasting Methods Used (if applicable) (Weighted Moving Average, Seasonal Indices, Market Intelligence, Promotional Calendar Data)
[ ] Justification for Chosen Methodology
[ ] Last Methodology Review Date

--- HISTORICAL DATA ANALYSIS ---
[ ] Number of Years of Historical Data Analyzed
[ ] Start Date of Historical Data Review
[ ] Summary of Overall Sales Trends (e.g., growth, decline, stability)
[ ] Identified Seasonal Patterns (Select all that apply) (Annual, Monthly, Weekly, Other (Specify in Long Text))
[ ] Description of any Identified Cyclical Patterns (if applicable)
[ ] Average Monthly Sales Volume (last 2 years)
[ ] Largest Monthly Sales Volume (last 2 years)
[ ] Smallest Monthly Sales Volume (last 2 years)

--- FORECAST ERROR METRICS ---
[ ] MAPE (Mean Absolute Percentage Error)
[ ] RMSE (Root Mean Squared Error)
[ ] Bias (Mean Error)
[ ] MAD (Mean Absolute Deviation)
[ ] Error Metric Threshold (Acceptable Range) (0-5%, 5-10%, 10-15%, 15-20%, 20%+ (Requires Investigation))
[ ] Notes on Error Metric Results

--- COLLABORATIVE FORECAST REVIEW ---
[ ] Review Date
[ ] Attendees & Roles
[ ] Forecast Adjustment Percentage
[ ] Key Discussion Points
[ ] Factors Influencing Forecast (Promotions, New Product Launch, Market Trends, Economic Conditions, Competitive Activity)
[ ] Action Items (Assigned To)
[ ] Due Date for Action Items

--- DEMAND SIGNAL VALIDATION ---
[ ] Actual Demand vs. Forecasted Demand (Units)
[ ] Percentage Deviation from Forecast (%)
[ ] Explanation for Significant Deviations
[ ] Reasons for Deviation (Select all that apply) (Promotional Activity, Unexpected Market Trend, Supply Chain Disruption, Data Entry Error, Other)
[ ] Date of Actual Demand Data
[ ] Demand Category (Finished Goods, Raw Materials, Sub-Assemblies)
[ ] Supporting Documentation (e.g., Sales Reports)

--- SYSTEM CONFIGURATION AUDIT ---
[ ] Forecast Horizon (in weeks/months)
[ ] Demand Forecasting Method (Statistical, Collaborative, Qualitative)
[ ] Safety Stock Calculation Method
[ ] Last System Configuration Change Date
[ ] Data Sources Integrated (select all that apply) (ERP System, CRM System, Market Intelligence Data, Historical Sales Data)
[ ] Description of System Parameters and Data Mappings

--- EXCEPTION REPORTING ---
[ ] Forecast Deviation Threshold (Units)
[ ] Exception Type (Demand Surge, Supply Chain Disruption, Forecast Error, Other)
[ ] Date of Exception
[ ] Description of Exception
[ ] Forecasted Quantity
[ ] Actual Quantity
[ ] Severity Level (Low, Medium, High)
[ ] Corrective Actions Taken

--- ROOT CAUSE ANALYSIS ---
[ ] Describe the specific forecast error observed (e.g., over-forecast, under-forecast, timing issue).
[ ] Detail the initial investigation steps taken to understand the discrepancy.
[ ] Select potential contributing factors (select all that apply) (Data Input Error, System Configuration Issue, Unexpected Market Event, Inaccurate Historical Data, Poor Collaboration, External Factor (e.g., promotion))
[ ] Explain the identified root cause(s) of the forecast error.
[ ] Estimated Impact (in units or monetary value)
[ ] Describe corrective actions implemented to address the root cause.
[ ] Date Corrective Actions Implemented
[ ] Lessons Learned and Recommendations for Future Prevention

--- CONTINUOUS IMPROVEMENT ---
[ ] Describe proposed improvements to forecasting methodologies.
[ ] Target reduction in MAPE (%)
[ ] Date improvement implemented
[ ] Data Sources to be investigated for increased accuracy (Point of Sale (POS) Data, Market Research Reports, Customer Surveys, Social Media Sentiment Analysis, Supplier Forecasts)
[ ] Supporting documentation (e.g., analysis reports, vendor agreements)
[ ] Responsible party for improvement implementation (Forecasting Team, Supply Chain Manager, IT Department)

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