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Managing and Using Historical Data within RapidResponse

Managing and Using Historical Data within RapidResponse. Kris Reid director, deployment services. Why Keep Historical Data?. Demand Understand forecast accuracy through visibility to forecast vs. actual demand over time

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Managing and Using Historical Data within RapidResponse

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  1. Managing and Using Historical Data within RapidResponse Kris Reid director, deployment services

  2. Why Keep Historical Data? • Demand • Understand forecast accuracy through visibility to forecast vs. actual demand over time • For use in calculating statistical forecasts and forecast disaggregation as part of the S&OP process • Traceability of root cause for inventory liability issues • Supply • Monitor Schedule volatility and attainment by comparing planned production with actual completions • Compare Supplier Performance (Commit vs. Actual Delivery)

  3. Demand - What Data Do I need? HistoricalDemandSeriesDetail HistoricalDemandActual HistoricalDemandSeries HistoricalDemandWaterfall Legend HistoricalDemandHeader Historical Data Needed Can be Autocreated ToleranceProfile HistoricalDemandCategory PartCustomer Input Table Calendar Control Table Part Customer Calculated Table CalendarDate

  4. Demand - What data do I need? • HistoricalDemandSeriesDetail • Series • Series.Id • Series.Header.PartCustomer.Name • Series.Header.PartCustomer.Site.Value • Series.Header.PartCustomer.Customer.Id • Series.Header.Category • BeginDate • EndDate • Quantity • UnitPrice

  5. Demand - What Data Do I Need? • HistoricalDemandActual • Header • Header.PartCustomer.Name • Header.PartCustomer.Site.Value • Header.Category • Date • Quantity • UnitCost • Unit Price • CommitDate (optional) • RequestDate (optional)

  6. Supply - What Data Do I need? HistoricalSupplySeriesDetail HistoricalSupplyActual HistoricalSupplySeries HistoricalSupplyWaterfall Legend HistoricalSupplyHeader Historical Data Needed Can be Autocreated ToleranceProfile HistoricalSupplyCategory PartSupplier Input Table Calendar Control Table Part Supplier Calculated Table CalendarDate

  7. Supply - What Data Do I Need? • HistoricalSupplySeriesDetail • Series • Series.Id • Series.Header.PartSupplier.Name • Series.Header.PartSupplier.Site.Value • Series.Header.PartSupplier.Supplier.Id • Series.Header.Category • BeginDate • EndDate • Quantity • UnitPrice

  8. Supply- What Data Do I Need? • HistoricalSupplyActual • Header • Header.PartSupplier.Name • Header.PartSupplier.Site.Value • Header.Category • Date • Quantity • UnitCost

  9. How to Capture Historical Data • Option 1 : Integrate from existing data stores external to RapidResponse • Demand Waterfalls: • Map HistoricalDemandSeriesDetail (Forecasts) and HistoricalDemandActual (Actuals) • AutoCreate remaining tables • Supply Waterfalls: • Map HistoricalSupplySeriesDetail (Production Plan or Commit) and HistoricalSupplyActual (Completions or Reciepts) • AutoCreate remaining tables • Input files expecting new records only (e.g. ‘net change’ extract)

  10. How to Capture Historical Data • Option 2 : Populate from data contained within RapidResponse using a Scheduled Task (formerly known as Data Change Alert) and Workbook • Create a workbook to capture appropriate Series (Plan) and Actual data • There is an out of the box workbook that can be leveraged as a starting point- S&OP Write History Records • Create a Scheduled Task to perform the capture on a scheduled event • Remember that inputs into this table are expected to be new records therefore your source worksheets have to be showing only new data • Source and Destination Worksheets must have the same type and number of columns in the same order/sequence

  11. Example of Historical Demand Capture Workbook

  12. Demand Waterfall Workbooks

  13. Result in Waterfall Workbooks

  14. Waterfall Workbook Configuration • RapidResponse includes Demand and Supply Waterfall workbooks as PDRs (Predefined Resources). • The workbooks can be configured using Macros to reference the configured Demand and Supply categories (Historical Demand/Supply Category table). See workbook filtering. Macros include: CustomerFcst_Type (Demand) SupplierFcst_Type (Supply) ShipmentType (Both)

  15. Waterfall Macro Configuration

  16. Before You Start – Understand Sizing • Database sizing key inputs • Number of unique part/customer or part/supplier combinations • Number categories (e.g. Forecast, Actual, Supplier Commit, Supplier Delivery) • Number of future looking buckets (e.g. 52 weeks) • Number of historical snapshots (e.g. 18 months) • Sizing ‘rule of thumb’ • Up to 100M records = 32GB server • Up to 250M records = 64GB server • Up to 500M records = 128GB server • Example: • 10,000 part/customer X 52 weeks of forecast X 80 weeks history x 2 categories (Forecast and consensus) = 83M records

  17. Managing Historical Data • As you continue to populate the historical tables with more and more history, they will grow • You need to “prune” them from time to time to keep the Server “healthy” – i.e. so it doesn’t overrun memory consumption • Can create Scheduled System Tasks to manage deletion of older historical data utilizing Delete Data and DeleteEnterpriseData commands (Data and System Admins only)

  18. What Happens If I Have to Do a Full Import? • Generally most customers use Data Update which calculates differences and processes them into the tables without deleting… • However, in cases where a Full Data Import is required generally all data within input tables is deleted • Not to worry…..Historical tables are automatically persisted in the root scenario and permanent scenarios during a full data import

  19. Demo • Use ! Kinexions Historical Demand Series Population Workbook to show how data can be captured for Historical Demand Series • Site = HQ • Customer = ebikes • Part = Cruiser • As of Date = 2011-11-07

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