THE EVOLUTION OF SIOP DEMAND DEMAND SIOP PLANNING SYSTEM PLANNING SOLUTION D a n i L e g e r B e c c a D a h l e n
The Problem. Existing processes, systems, and tools did not support a rigorous SIOP process or Demand Planning function. • PROCESS: Systematic solution is required to evolve foundational process • SYSTEM CAPABILITY: We are not using current systems to their full potential • ANALYTICS AND ACCURACY: Within our process and business we are data rich and insight poor
OPERATIONAL IMPACT OLD NEW WORLD WORLD BALANCED CONSTRAINED Constrained top down financial forecast Constrained top down balanced against unconstrained bottom financial forecast up Demand Plan PROCESS PROCESS Nimble consensus based, Current state is manual, system supported process rigid, unsustainable, and disjointed TAILORED SOLUTION ONE SIZE FITS ALL Singular perspective, is not Cross functional perspective, scalable to meet all stakeholder scalable to meet all stakeholder needs needs TOOLS & DATA TOOLS & DATA Data and analytics managed All data and analytics systematically in new tool- managed via Microsoft set Excel and Access 3
SYSTEM SOLUTION BENEFITS DEMAND PL ANNI NG CROSS F UNC T I ONAL FORECAST DEVELOPMENT FINANCE Triangulation point to Un-constrained unit validate or influence Demand Plan generated forecast accuracy via statistical model FORECAST ALIGNMENT SALES Data and analytics assist in Financial and demand plans planning profitable connected systematically in promotions new tool-set SUPPLY PLAN SUPPORT SUPPLY CHAIN Unit Plan systematically Inventory improvement, translated to Delivery Forecast, logistics savings, improved disaggregated to size/location first time complete SIMPLIFICATION MANUFACTURING Allows for sun-setting of many Better signal for manual and customized production and workflows manufacturing planning 4
WHY ANAPLAN? • Best user interface, intuitive and easy to use • Flexible platform adaptable to business processes as we continue to evolve • Additional use cases possible with no additional investment • Implementation focused on co-building the solution to enable long term self sufficiency • 12 week implementation timeline 5
D E M A N D P L A N N I N G
M O D E L H I G H L I G H T S DEMAND STATISTICAL DELIVERY FORECAST FORECASTING PLANNING FORECASTING ACCURACY
M O D E L H I G H L I G H T S STATISTICAL FORECASTING • Anaplan gives us the ability to have statistical forecasting to assist in our Demand Planning process • Stat forecast by SKU/Week with the ability to set up alternate history
M O D E L H I G H L I G H T S DEMAND PLANNING CONSENSUS DEMAND DEMAND PLANNING PLANNING DASHBOARD DASHBOARD • View Stat Forecast by Series/Week and compare to LY Sales • Compare Plans (Finance, Stat, Demand) by Series • Override Stat Forecast as needed • Compare by Promotion Period or any date range • Override by Series/Week, Item/Week or Daily Weighting • Enter in a final Consensus Demand Plan
M O D E L H I G H L I G H T S DELIVERY FORECASTING • Anaplan allows us to manage forecasting through a Network Transition by using a hub mapping selection by week • Point of Sale forecast is shifted into a Delivery Forecast based on historical delivery profiles by Item and Location
M O D E L H I G H L I G H T S FORECAST ACCURACY • Anaplan takes out the manual process of searching for significant forecast variances with exception reporting dashboards • With Anaplan, we can now track Point of Sale Forecast Accuracy and Delivery Forecast Accuracy Size/Series/Location Accuracy vs Goal 80% 70% 60% 50% 40% 30% 20%
R O A D B L O C K S & L E A R N I N G S PROCESS LEARNING MODEL DATA READINESS CHANGES CURVE PERFORMANCE
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