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Interfaces with Oracle ERP for manufacturing & distribution
Why implement? Tangibles… Positive ROI Reduce inventory Reduce backorders or lost sales Intangibles…. Manage increased business complexity Introduce process stability Reduce dependence on specific individual knowledge Provide foundation for future growth
Why implement…tangible reasons Maximum inventory reduction from forecast accuracy achieved Current forecast accuracy ~90% Variation in supply chain now greater challenge Variations in shipping times Delays through customs Stock discrepancy & quality issues The need to rebalance between nodes without triggering new builds
Why implement…intangible reasons Key drivers for Demantra Increasing distribution complexity Risks associated with reliance on individuals Risks with lack of robustness in existing system Need for seamless global system that facilitates accountability and visibility
Why implement…intangible reasons Key drivers for ASCP Increasing distribution complexity Need for more effective optimisation model Need to remove reliance on individuals Risks with lack of robustness in existing system
Musings about Demantra & ASCP Why Demantra wont improve your forecast accuracy…further Do I have the right people? Getting ASCP & Demantra to work together Tips & traps…I wish I hadn’t done that!
People puzzle… Demantra, & to some extent ASCP evolution will be influenced by… caliber of people available to perform various roles defining ownership between Business Process and IT Degree of autonomy of users
People puzzle… Key users involved with the running of Demantra… System developers Database administrators Power users (demand planners) Casual users
Integrating ASCP & Demantra… Loading forecasts to ASCP Create customer/warehouse combinations in Demantra Load based on warehouse Create customer/region combinations in Demantra Map regions to warehouses through dynamic combinations table
Integrating ASCP & Demantra… Using Customer/Warehouse combinations in Demantra… simple distribution operation creates visibility of warehouse demand in Demantra data integrity for customer/region combinations is not available from source Downside… changes in Warehouse source for a given customer is not easy to update in Demantra…can lead to erroneous forecasts
Integrating ASCP & Demantra… Using Customer/Region combinations in Demantra… allows greater flexibility to change distribution network without impacting forecast could facilitate forecasts by territory/sales person or other similar splits Downside requires available data integrity to support this…ResMed didn’t have this on a global basis
Improving forecast accuracy… Modify buyer behaviour rather than modifying forecasts Many sales incentives encourage customers to buy in erratic patterns. Erratic demand makes forecasting difficult.
Tips & Traps…tips Bucketing of demand Not too much/not too little gives a balance between system performance and quality info ResMed option Capture data by customer for top 50% revenue Bundle data of customers for next 30% revenue Bundle data for remaining 20% revenue
Tips & Traps…tips Capture demand not sales To give true indication of future potential demand Recognises customer orders in the period they were requested, whether shipped or not, as opposed to shipped or invoiced orders Forecasts in future periods are then based on customers desires rather than operation capability at a previous point in time
Tips & Traps…tips Create separate inputs for functions Such as separate series to create visibility of user inputs create clear override hierarchy for forecast modification Creates opportunity for input of reference forecasts for future comparison or negotiation (eg Marketing/Finance series)
Tricks & Traps…traps Maintaining data for full spectrum of items Ignoring data for “inactive” codes may present problems later for things like exception reports Avoid inappropriate use of fields inappropriate/inconsistent use of fields such as “Territory” makes them difficult to use for meaningful data capture later
Conclusion Support through implementation Oracle consultants provided effective guidance in the direction we took This was useful in either tempering our expectations, developing our ideas or providing alternatives to arrive at effective solutions Few changes were made after implementation largely as a result of an effective collaborative approach between Oracle & ResMed during development
Conclusion Future direction Our key challenge now is implementation of ASCP Objective is constraint based optimisation Horizon of at least 12 months to enter this phase Implementation of unconstrained ASCP as precursor to this
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