THE EVOLUTION OF SIOP DEMAND DEMAND SIOP PLANNING SYSTEM - - PowerPoint PPT Presentation

THE EVOLUTION OF SIOP

SIOP DEMAND PLANNING DEMAND PLANNING SYSTEM 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

Nimble consensus based, system supported process

PROCESS

Cross functional perspective, scalable to meet all stakeholder needs

TAILORED SOLUTION

Constrained top down financial forecast balanced against unconstrained bottom up Demand Plan

BALANCED

Data and analytics managed systematically in new tool- set

TOOLS & DATA

Current state is manual, rigid, unsustainable, and disjointed

PROCESS

Singular perspective, is not scalable to meet all stakeholder needs Constrained top down financial forecast

CONSTRAINED

All data and analytics managed via Microsoft Excel and Access

OLD WORLD NEW WORLD

ONE SIZE FITS ALL TOOLS & DATA

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CROSS F UNC T I ONAL DEMAND PL ANNI NG

Financial and demand plans connected systematically in new tool-set FORECAST ALIGNMENT Unit Plan systematically translated to Delivery Forecast, disaggregated to size/location SUPPLY PLAN SUPPORT Un-constrained unit Demand Plan generated via statistical model FORECAST DEVELOPMENT SIMPLIFICATION SALES Inventory improvement, logistics savings, improved first time complete FINANCE Better signal for production and manufacturing planning SUPPLY CHAIN MANUFACTURING Allows for sun-setting of many manual and customized workflows Triangulation point to validate or influence forecast accuracy Data and analytics assist in planning profitable promotions

SYSTEM SOLUTION BENEFITS

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WHY ANAPLAN?

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• 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

D E M A N D P L A N N I N G

STATISTICAL FORECASTING

DEMAND PLANNING DELIVERY FORECASTING FORECAST ACCURACY

M O D E L H I G H L I G H T S

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

• View Stat Forecast by Series/Week and compare to LY Sales
• Override Stat Forecast as needed
• Override by Series/Week, Item/Week or Daily Weighting

DEMAND PLANNING DASHBOARD CONSENSUS DEMAND PLANNING DASHBOARD

• Compare Plans (Finance, Stat, Demand) by Series
• Compare by Promotion Period or any date range
• Enter in a final Consensus Demand Plan

M O D E L H I G H L I G H T S

DEMAND PLANNING

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
• n 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

20% 30% 40% 50% 60% 70% 80%

Size/Series/Location Accuracy vs Goal

DATA READINESS

PROCESS CHANGES LEARNING CURVE MODEL PERFORMANCE

R O A D B L O C K S & L E A R N I N G S