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How To Manage Your Data Winery Perspective

WAWGG Conference Feb 4, 2009. How To Manage Your Data Winery Perspective. Jordan Ferrier Hogue Cellars. Wineries are in the middle. Vineyards 3-5 year planning cycle. Plant grapes, deliver annually. Wineries 1-3 year planning cycle. Marketing / Distribution What’s for lunch?.

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How To Manage Your Data Winery Perspective

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  1. WAWGG Conference Feb 4, 2009 How To Manage Your DataWinery Perspective Jordan Ferrier Hogue Cellars

  2. Wineries are in the middle Vineyards 3-5 year planning cycle Plant grapes, deliver annually Wineries 1-3 year planning cycle Marketing / Distribution What’s for lunch? Receive wine, turn when out

  3. Outside Services • Analytical results • Proactive recs • Corrective recs Grower Corporate or Ownership • Stats • Costing • Pricing Information • Pricing Info • Agricultural Expectations • Crop • Harvest date • Cultural practices • Quality • Expected • Desired wine • Resulting quality • Stats • Maturity • Treatments • Crop Estimates • Stats • Pricing • Pesticide use • Water use • Labor Winery Government • Fruit Sources • Pricing Info • Homeland Security? • Sorbanes-Oxley? • Pricing Info • Costing Info • Overall Efficiency • Sorbanes-Oxley? Corporate or Ownership

  4. Winery Makes the RIGHT Wine • Hit volume targets • Not enough - out of stock / capacity not used • Too much – distributor backed up / high costs • Meet quality expectations • Proper profile and consistency • Production goals and origins (labeling) • Lack of flaws – vs. – complexity • Balancing capital and operating costs

  5. PART I: A Plan • HOW MANY CASES OF WHAT WINE? • Evaluate sales plan before harvest • May have to do this YOURSELF • Your conversion factor (tons-to-cases) • ‘Hangtime’ factors (dehydration / water) • Plans for lees loss/recovery • Plans for press wines • Filtration & evaporation losses

  6. Production plan for YUMMY!

  7. Look At Capacity Realistically

  8. PART II: Manage The Grapes • History is better than theory • Early crop estimates require experience • Many ‘yields’ to consider • Contract maximum • Expected yield – what you think will arrive • Target yield – in contract or annual target • CROP ESTIMATES

  9. Crop Estimation • Can use historical data • Visual estimate • Cluster counts • LAG PHASE cluster weights • Can be very accurate • Harvest whole vines: clusters/vine, #/vine • Need vines/acre, % stand, GPS acres • PREDICT GROWTH FACTOR • Historical data helps predictions

  10. TIMING IS IMPORTANT

  11. Good Sample Data Management • Sample Schedule • allows winemaking and laboratory to plan • Sample Log • Tracks maturity progress • Compare w/ previous years • Communicate results to growers • Use to SCHEDULE HARVEST!!!

  12. Example – 2007 Sample Data • No blank lines • Consistent block codes • Able to break out many ways

  13. Harvest Scheduling • Communication

  14. PART III: Make The Wine • Weigh tags • Winetracking software • Grape Payments • Execute the plan

  15. Winetracking • Regulatory Compliance Lifesaver • Inventory maintenance • Volume in tanks and barrels • Composition moves with wines • Analysis (SO2, pH, TA, EtOH, etc…) • Additions (yeast, nutrients, etc…) • Operations (pressing, racking, filtering, etc…) • Costing (grapes, overhead, bottling, etc…

  16. There’s a lot missing • All systems lack a qualitative component • Ferments aren’t ‘special’ and tracked • Quality parameters are missing • No ‘treatment’ activity • Type, rate, and duration • Oak, punchdown/pumpover, MOx, etc… • Can’t split lots to multiple products • Needs to be visual, simple, and persistent

  17. DATA WORK AROUNDS • Long Range Planning Spreadsheet(s) • Capacity Calculation Spreadsheet(s) • Harvest Scheduling Spreadsheet • Red Wine Inventory Spreadsheet • White Wine Inventory Spreadsheet • Red Ferments Spreadsheet • Tank Tracking Database • Winemakers’ Tasting Database

  18. Tracking Red Ferments • All red ferments tracked externally • Used to calculate nutrients, water, etc… • Links to other worksheets by lot name • YAN, Brix, and Phenolics spreadsheets • Pressing characteristics (yield)

  19. Phenolics Tracking

  20. Pivot Table from Data Table • Consistent lot names! • No breaks in data • Pivot table also references 2 other tables • Converts dates for XL to use easily

  21. XL Tools • Build a PIVOT TABLE – trial and error • Select desired data table • Select how you want to slice it: LAYOUT • Row subtotals and sorting • Re-format data output • Reorganize Pivot w/ ‘format report’ • XL Lookups • Use INDEX, MATCH, VLOOKUP • Make sure data’s set up right, catch errors • Filters and data entry aids

  22. Good Data ManagementORGANIZES INFORMATION • For easy sorting and filtering • Easy aggregation of results • means, min, max,… • Easy referencing and recombination • Easy communication, export, sharing

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