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Migrating from Oracle Demand Planning to Demantra

Migrating from Oracle Demand Planning to Demantra. Changes in Process & Organization By Arun Cavale, NexInfo Tom Buechler, Turquoise Consulting. About us.

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Migrating from Oracle Demand Planning to Demantra

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  1. Migrating from Oracle Demand Planning to Demantra Changes in Process & Organization By Arun Cavale, NexInfo Tom Buechler, Turquoise Consulting

  2. About us Arun Cavale is President of NexInfo. He is a supply chain process consultant specializing in solution design using Oracle’s Manufacturing and Advanced Planning modules Tom Buechler is President of Turquoise Consulting with 11 years of Oracle Applications experience. He specializes in the manufacturing and supply chain applications with a broad knowledge of many areas of functionality and business processes

  3. Assumption on Audience Our presentation is created for an audience that has a working knowledge of Oracle Demand Planning Application and is familiar with Demantra

  4. Agenda • Demantra module overview • Compare Demantra to Demand Planning • Migration Path to Demantra • Process Redefinition for Demantra • Organization Changes for Demantra • Summary

  5. Demantra Overview

  6. Demantra Overview Modules • Oracle Demantra Platform of 6 Solutions • Demand Management • Advanced Forecasting and Demand Modeling • Real Time Sales and Operational Planning • Predictive Trade Planning • Trade Promotion Optimization • Deductions and Settlement Management

  7. Demantra Overview Features Demand Management • Functionality to import data • Statistical forecasting • Reporting and Analysis • Collaboration • Limited Causal and tuning capabilities Advanced Forecasting & Demand Modeling • Additional Forecasting models • Causal contribution analysis & unlimited causal factors • Advanced tuning capabilities (nodal tuning) • Event analysis • Cross correlations – what event or attribute drove demand • Attribute based planning (shape modeling)

  8. Demantra Overview Features Real Time Sales & Operational Planning • Top down and bottoms up plan validation • Supply Series for Demand Supply Matching • Financial Gap Analysis • Worksheets to Support Processes • Sales • Marketing • Supply Planning • New Product Planning • Notes and audit trails

  9. Demantra Overview Components • Collections • Provides ability to collect data from the Source (Oracle EBS or other Transaction Systems) • Dimensions • Provides 2 seeded dimensions Item & Location • Combination defined as a node • All hierarchies created on these two dimensions • Series • Data sets in Demantra identified as Series • Example: Sales History, Booking History etc.

  10. Demantra Overview Components • Forecast Functionality • Ability to create forecast using different Statistical Models based on History Data • Bayesian forecast model • Ability to tune forecast engine at nodal level • Forecast Load / Entry • Ability to manually enter forecasts or load forecasts from files • Worksheets • Worksheet functionality to layout, analyze, manipulate and collaborate • Forecast Upload • Publish forecast to Advanced Supply Chain Plan

  11. Demantra Overview Shows series data in Table, Graph or Calendar view

  12. Demantra Overview Forecasting Methodology

  13. Predictive Model Bayesian Combined Model Bayesian Estimator Demantra Overview Analytics for greater accuracy Statistical Models Promotions Optimal Introduction Seasonality of Products History Effect of Weather on Promotion Effectiveness Multiple Causal Factors POS Baseline Promo Lift Cannibalization Shipments

  14. Demantra vs Demand Planning

  15. Demantra vs Demand Planning Key Features Demantra has excellent performance in the Demand Planning problem functions including Download and Worksheet Manipulation Demantra has enhanced functionality compared to Demand Planning. It is split into multiple modules based on function Demantra has functionality and analytical capability for easier and quicker iterative Sales and Operational Planning Process

  16. Demantra vs Demand Planning Functional Features Demand Planning allows use of multiple Demand Plans Demantra uses multiple series and security to meet the business requirement for multiple plans Demand Planning allows Business Users to create ad-hoc Measures (Formula and Stored) Demantra needs IT to define new Series Demantra has enhancedcolor coding capabilities Demantra does not have one to one match of the Demand Planning drill down capability but has the ability to embed worksheets within worksheets to achieve drilldown functionality Demand Planning has a simple Statistical Model based forecasting Demantra has an advanced ‘Bayesian’ model based forecasting

  17. Demantra vs Demand Planning Functional Features Unlike Demand Planning, Demantra allows creation and use of multiple hierarchies without greatly impacting performance Demantra has Enhanced Alert Functionality and Ability to run Complete Worksheets using Workflow Demantra does not have the Demand Planning “distribute & collect” function. You can configure security rules and workflow at any (group or user) level to achieve the same Demantra does not allow business users to upload Excel Spreadsheets Demantra can currently publish only to a single forecast (in the future – two) whereas Demand Planning publishes multiple forecasts based on plan or scenario definition

  18. Demantra vs Demand Planning Technical Features Demantra system performance is greatly superior to Demand Planning performance Demantra does not use the Demand Planning Fact Data tables to store History & Scenarios (Archives, Forecasts etc) but publishes to the same tables for interface with Advanced Supply Chain Planning Demand Planning processing including Forecast generation in OLAP Demantra Forecast generation takes place in a Windows Client environment Demand Planning downloads data into Express or Oracle OLAP Demantra does not use Express or Oracle OLAP. It uses Oracle Tables for all the processing

  19. Migration to Demantra

  20. Migration to Demantra Key Considerations • Migration to Demantra is not an upgrade • No supported ‘out of the box’ migration path • Complexity in migrating data to Demantra • Change in application architecture • Change in data model • Change in development environment • Change in functionality • No Plan Concept • No ‘Distribute & Collect’ function • Limited published forecasts

  21. Migration to Demantra Solution Considerations • Redefine processes to use Demantra • Use ‘Series’ and security rules to replace Demand Plans • Use workflow and user /group level security to define planning processes • Use workflow and ‘Series’ functionality to support multiple forecasts • Create custom migration path • Map Hierarchies • Map ‘Stream’ Data • Map ‘Measure’ Data • Map ‘Demand Plan’ • Map access controls • Data model changes to support new ‘Hierarchies’, ‘Series’ etc

  22. Migration to Demantra Solution Considerations • Design distributed forecast engine for load handling • Development & infrastructure support • Windows environment for forecast generation • Separate client environment for defining ‘Hierarchies’, ‘Series’ etc • Data model expertise for making data model changes

  23. Client Analysis Client A – Key Characteristics • Manufacturing enterprise with US $ 2 B+ revenues • Multiple Country/Operating Units/Organizations • Customer base – very large • Product base – very large • Seasonal and non-seasonal • Some products use promotions • S&OP Process using ODP, ASCP and Excel spreadsheets • Would like to improve supply chain response

  24. Client Analysis Client A – Pre-Demantra challenges • No customer level forecasting - large customer–item–warehouse combinations • Forecasting at single level - Complexity in segregation • ODP download times lead to long S&OP iteration times • Products with low accuracy statistical forecasts • Single product hierarchy inconvenient to reporting • No analysis of influence factors like currency exchange rates, weather etc. • Forecast cycle spans across countries/time zones and groups with restricted access • Proven data sources and validated data streams used in Demand Planning

  25. Client Analysis Client A – NexInfo Solution • Software profile – Demantra DM, Demantra AFDM, Demantra RTSNOP, ASCP and Inventory Optimization • Forecasting at Item-Location level • Forecast tree determines forecasting level • Excellent performance reduces cycle times • Increased accuracy with advanced forecast tuning • Use multiple hierarchies with no performance impact • Model causal factors to influence forecasts • Use collaboration capabilities in Demantra combined with security/access controls • Map existing data sources and streams to Demantra • Complete S&OP process done quicker and online

  26. Client Analysis Client B – Key Characteristics • Manufacturing/distribution enterprise with US $ 2 B+ revenues • Multiple Country/Operating Units/Organizations • Customer base – small • High collaboration and service level expectations • Product base – not very large • New innovative products with no established market • High product obsolescence • S&OP Process using ODP, ASCP and Excel spreadsheets

  27. Client Analysis Client B – Pre-Demantra Challenges • Inaccuracies in monthly S&OP cycle because customers provide forecasts at different times • End market data available at high level in raw form • Crossover and manual hand off functions between groups not well coordinated • ODP download times lead to long S&OP iteration times • Forecast cycle spans across countries/time zones • Proven data sources, validated data streams and valuable archived data used in Demand Planning

  28. Client Analysis Client B – NexInfo Solution • Software profile – Demantra DM, Demantra AFDM, Demantra RTSNOP, ASCP and Inventory Optimization • Frequent S&OP cycles • Adjust to customer forecast inputs • Manage product obsolescence • Create meaningful end market statistical forecast using raw data and causal factors • Enhanced functionality for new product introductions • Establish customer service level measurements and monitor by exceptions • Use collaboration capabilities in Demantra • Use workflow to control hand offs and notifications • Map existing data sources and streams to Demantra • Convert archives into Demantra

  29. Process Redefinition

  30. Process Redefinition Switching to Demantra • Leverage rich software enhancements to support: • Demand management processes • Sales & Operational Planning • Trade Promotions • Utilize workflow driven environment • Limit number of forecasts published • Reduce ad-hoc definition changes • Predefine worksheets for drilldown

  31. Process Redefinition Switching to Demantra • Improve analysis using Causals, events and nodal analysis • Identify and analyze causal factors • Identify, correlate and analyze events • Nodal analysis of statistical forecast

  32. Process Redefinition Switching to Demantra • Improve Sales & Operational Planning Process • Improve iterative cycle time with reduced latency • Use the Increased analytical capabilities • Multiple pre-defined S&OP worksheets • Analyze and report along multiple hierarchies • Increased support for matching Demand & Supply data • Work concurrently on multiple worksheets • Create complex workflow driven end to end process • Define all steps and exceptions • Control transfer and informational notifications

  33. Process Redefinition Switching to Demantra • Trade Promotions • Compute and analyze lift from specific promotions • Use the simulation and analytical capabilities

  34. Changes to Organization

  35. Organizational Changes Business organization considerations Forecasting & planning organization • Increased statistical analysis strengths • Integrate all planning participants using workflow • Ability to work offline increases scope of participants Sales & marketing organization • to use the ability to track and respond to volatility in product sales • Better organized promotion campaigns Enterprise • Integrate business, financial, sales and supply planning processes

  36. Organizational Changes Business organization considerations Information technology & infrastructure Organization • Technical (IT) involvement in creating / modifying series, hierarchies etc. • Change in IT support Level • Needs Business and Technical knowledge • Windows Client environment support from Infrastructure

  37. Summary

  38. Summary Demand Planning to Demantra • Demantra has rich functionality to support • Sales & demand planning processes • Sales and Operational Planning process • Promotions management processes • Business Process & Organizational Changes • Understanding differences between Demand Planning and Demantra based processes • Technical Support Changes • New level of technical support • Understanding the infrastructure changes • Create customized Migration Path • Understanding Functionality and Technology in ODP and Demantra

  39. More about us Arun Cavale – NexInfo arunc@nexinfosolutions.com 714.338.6165 Tom Buechler – Turquoise Consulting Unlimited tom.buechler@tcunltd.com 310.923.5719 Special thanks to: Sandeep Goyal – NexInfo Sandeep is a Supply Chain Planning Techno-Functional Consultant specialized in implementing Oracle’s Advanced Planning modules

  40. End

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