WOONEUI TAESenior Consultant

Real time S&OP 기반의오라클수요및판촉관리솔루션

Industry Challenge Today..

• Long Manufacturing Lead times

• High Inventory Cost

• Multiple Product Attribute make Demand Planning Challenging

• Promotion fluctuate demand

• Poor collaboration between sales, Marketing, Operations and with Customer

• New Lines, Products & Product Lifecycles

Stock outs & non-availabilityExcessive InventoryLow Service Levels

Promotion’s negative ROILoss of Revenue

NPI Failure

Application Requirements

Comprehensive Demand Management linked to holistic

S&OP process

Analytic, Statistics optimized approach to promotion and

demand management

Detailed, real-time view of supply and demand across

the supply chain

Business Impacts

Increased charge-backs and deductions

Increased vendor-specific programs and products

Increased use of promotions and results of

Out Of Stock

Increased volatility and risk

Market Changes

Shrinking product lifecycle

Increased competition for share and space

Retailer consolidation -emergence of Channel

Masters

Move to lean business practices

Process Implications

Need for Real-time, store/ SKU planning and

execution

Migration of business processes back up the

value chain

Need for well-targeted and optimized promotions

Need for one-number planning and integrated

S&OP processes

Drivers for Advanced Demand Management

Shape Demand

Understand Demand

Respond to Demand

Plan for Demand

Retail Planning & Store

Replenishment

Demand Management

Trade Promotion Management

Trade Promotion Management

Real-Time Sales and Operations PlanningReal-Time Sales and Operations Planning

Business Process PlatformBusiness Process Platform

Demantra’s End-to-End Solution

Demantra’s End-to-End Solution for Demand-Driven Planning

Real-Time Sales and Operations PlanningKPI and Management Dashboards

Demand / Supply BalancingSales and Marketing Forecast

Annual Budget

Trade PromotionManagement &Optimization

Event PlanningFunds Management

Volume PlanningDeductions Management

Promotion Modeling

DemandManagement

ForecastingModeling & Analytics

CollaborationPOS Monitoring

Assumptions Planning

Retail Planning &Store

Replenishment

Assortment PlanningNew Product Introduction

ReplenishmentResets and Openings

Optimization

Demand Management• Statistical Forecasting

• Bayesian-Markov Mixed Model Programming• Causal forecasting• ‘Out of box’ accuracy to the half-hourly bucket• Store level forecasting based on POS data

• Support for Multiple Demand Streams • Consensus Forecasting• High-volume Forecasting• Workflow, Alerts, and Exceptions• Multi-dimensional analysis, reports, and graphs• Flexible OLAP Worksheets

Demand Management Differentiators

• Manage at any level of time, product and location aggregation• New Product Introduction

• Supports product lifecycle management• Chaining capabilities to existing products

• Shape Modeling• Use comparable products demand shapes as input• Generate composite new shape and align to actual demand

• Attribute Based Forecasting• Analyze demand for a group of combined attributes• Uses business rules for product level modeling

• Assumption Planning• Supports qualitative forecasting• Current and past assumptions are modeled

The solution…. is designed to be "complex on the inside, so that it is simple on the outside.“ This means it needs less tuning and less experienced demand planners will find it easier to work with than many solutions. – ARC, June 2006

“From an isolated process to a full Demantra RT S&OP - within six weeks of going live our ‘A-items’ improved 45% in accuracy.” – Sagi Srinivas, Johnson & Johnson MD&D

Past Movement

Data

Bayesian Estimator

Predicted Demand

Estimator’s Models

DemantraModeling Overview

Multiple Causal Factors

Bayesian Combined Model

Superior Bayesian – Markov ForecastingTechnology

Powerful Analytics Yield Maximum Accuracy

Optimal Introduction

Seasonality of Products

Effect of Weather on Promotion

Effectiveness

Baseline

Promo Lift

Cannibalization

Mul

tiple

Cau

sal F

acto

rs

His

tory

PO

SP

rom

otio

nsSh

ipm

ents

Estimator’s Models

Bayesian Estimator

Bayesian Combined

Model

Predictive Model

Powerful Analytics Yield Maximum Accuracy

Optimal Introduction

Seasonality of Products

Effect of Weather on Promotion

Effectiveness

Baseline

Promo Lift

Cannibalization

Mul

tiple

Cau

sal F

acto

rs

His

tory

PO

SP

rom

otio

nsSh

ipm

ents

Estimator’s Models

Bayesian Estimator

Bayesian Combined

Model

Predictive Model

Causal Analysis

Outlier Detection

Promotion Events

Seasonality

Cyclical Patterns

Trend

MAPE – Mean Absolute Percent Error

Measure Performance Forecast Accuracy

MPE - Forecast Bias

Measure Performance Forecast Accuracy

Measure Performance Forecast Accuracy

WMAPE – Weighted MAPEDemantra Customers are weighting by accuracy volume, revenue inventory cost

Collaborative Real-Time Sales & Operations Planning

Across Functions

Sales

Marketing

Manufacturing

Finance

ExecutiveProductDevelop-

ment

Consensus

Promotional & Volume Plans

Strategic Plans

Capacity Plans

PhaseIn/Phase Out Products

Demand Plans

Profitability

Service Levels

Inventory Levels

Promotion Effectiveness

Plan Accuracy

Inputs Outputs

Actual Shipments

Promotional Execution

In-FlightConsumption

Data

Sales

Marketing

Manufacturing

Finance

ExecutiveProductDevelop-

ment

Consensus

Promotional & Volume Plans

Strategic Plans

Capacity Plans

PhaseIn/Phase Out Products

Demand Plans

Profitability

Service Levels

Inventory Levels

Promotion Effectiveness

Plan Accuracy

AlertsExceptions

Inputs Outputs

Collaborative Real-Time Sales & Operations Planning

Across Functions

Real-time

RT S&OP Collaborative Process

• Collaborative Process Enablers• Develop Baseline Forecast• Develop Consensus Plan• Introduce New Products• Manage Promotions • Manage Replenishment• Measure Performance

Collaborative Portal2. Integrated,

Configurable KPI’s

1. Real-time Alerts, Exceptions &

Workflow messages

3. Advanced Worksheet tools

Collaborative Worksheets

1. Business Hierarchy

features ease of navigation

2. Comprehensive data series available

out-of-the box

3. Integrated charting is

selectable on-the-fly

4. Online Notes and Audit Trail with digital signature

Develop Baseline ForecastStatistical Forecasting

2. Current date, past & future are color coded for

reference

1. View the statistical plan at any level of

aggregation

3. Planner adjustments can be

entered, copy/pasted, or updated by the

system

4. On approval, system will Alert all participants

Develop Consensus Plan

2. Inputs display from entire

collaboration group – Finance, Marketing,

Operations, etc.

4. Integrated approval workflow

process

1. Each S&OP participant has a

configurable role-based view

3. Review historical accuracy for each

input

Introduce New Products

1. Chain and view demand of comparable

products

2. Run simulation on-the-fly

4. Accurately forecast

demand for the new product

5. Aligns forecast based on

actual demand

3. The system

automatically detects

outliers

Manage Promotions

Manage Replenishments2. View current inventory, along

with min/max levels

1. Adjust policy

parameters as needed

3. View inventory projections based on safety-stock

policies

Measure PerformanceIntegrated KPI’s

1. KPI’s are fully configurable from

standard templates

2. KPI Measures can be in units or currency, at

any level of aggregation

3. KPI Information may be forwarded as Alerts, Exceptions and Workflow messages.

Why Customers Buy Demantra for S&OP

• Gold Standard for Demand Driven Supply Network Vision

• Real-Time, Demand-Driven Planning Applications

• Most Sophisticated Planning Statistics - “out of the box”

• Integrated Analytics Platform

• Collaborative Planning Environment Driven By Workflow

• Technology - Scalability supports granular forecasting• Shelf/Rack/Store/DMA/DC x sku/item x week/day/hour

• Automation and Scalability for Granular Demand Data Visibility

• Business Process Management with Exception Processing

VTech is a global provider of corded and cordless, telephones, electroniclearning products and contract manufacturing services• Challenge

• Improve service levels and on-shelf availability with big box retailers in order to increase revenues, while keeping inventory levels and minimizing logistics costs

• Strategy• Implement a consumer driven planning process with retailers to reach a one-

number plan using POS data and retailer merchandising schedules • Solution

• Real-time Sales & Operations planning• Results

• Rapid time-to-benefit with implementation in 90 days• Increased order fill rate from 55% to over 95%• Increased inventory turns from 3x to 6x per year • Reduced retail compliance fines by 85% • Reduced logistics costs by 65% • Reduced price protection claims by 40%

Monitor & Report

Budget, Volume & Spending

Post-Event Analytics

Promotion Planning Process

Pre-Event Analytics

Trade Promotion Management

1. Define Trade Funds including fixed and

variable funding rates

2. View Fund Budget, Allocation

and Balances

3. Monitor Sales vsQuota

Screenshot

Budget, Volume & Spending

4. View Cannibalization across Brands &

Promotional Groups

2. Cost/Benefit review of Planned

Promotions

1. Drill-down into an individual

promotional event

3. Decompose lift to identify components

such as Pantry Loading

Screenshot

Pre-Event Analytics

2. Monitor base and incremental volume

1. Report on Forecast vs Plan

3. Receive early warning on potential out-of-stock

4. Review Promotion Calendar

Screenshot

Monitor & Report

3. Color coding highlights when results are better (green) or worse (red)

than planned

1. Drill-down into an individual promotional event

4. Decompose lift to identify components such

as Cannibalization

2. Compare Planned vs Actual Results

Screenshot

Post-Event Analytics

Baseline

Manufacturer Retailer

Incremental

CompetitiveBrand

Switching

BrandGrowth

Pre/PostPromoEffect

BrandCannibalization

Baseline

CompetitiveAccountSwitching

CategoryGrowth

Pre/PostPromoEffect

Baseline

NetLift

Data Intelligence

Traditional Promotion Evaluation

CategoryCannibalization

Demantra’s Promotion Evaluation

Decomposition of the Promotional Lift

Why Customers Buy Demantra for Trade Promotion Management

• Improve the efficiency and effectiveness of their trade dollars• Increase their promotional impact without increasing their trade budget

• Reduce their trade budget while maintaining the same level of promotional impact

• Predict the impact of future promotions• Base and Incremental Volume

• Cost, Profitability, and ROI

• Optimize promotions based on • Goals - profit, revenue, units and constraints - budget, timing, retail margin

• Calculate the true “Net Lift” of a promotion by identifying cannibalization and pantry loading

• Collaborative solution that can be extended to additional functional areas both internally (sales, marketing, finance,…) and externally (brokers, distributors, retail partners,…)

Customer: Welch’s• Welch’s is the world’s leading processor and marketer of grape-based products• Challenge

• Manage, analyze and understand the effectiveness of the thousands of trade promotions that run annually

• Improve sales force productivity• Analyze risks with respect to spending, revenues and profits

• Strategy• Integrate trade promotion management, demand planning and promotion

analytics to provide an accurate one-number plan across the company• Automate trade promotion management and sales planning to increase sales

force productivity, increase promotion ROI, and drive supply chain efficiencies• Solution

• Demand management, Trade Promotion Planning and Optimization• Results

• One-number Plan, with increased SKU-level accuracy• Overall reduction in trade spending• Significant savings in supply chain costs• Productivity improvements in headquarter sales, field sales and broker sales force

• Database - Oracle 9i, Oracle 10G, MS SQL Server 2000, MS SQL Server 2005

• Application Server - Websphere, Weblogic, IAS, Jrun, Apache, Tomcat

• Platforms - AIX 5.2L or 5.3L, Solaris 9, Windows 2000 or 2003• HP and Linux under testing

• Net Weaver Certified

Demantra Infrastructure

Medical Devices

Media & Entertainment

Consumer Packaged Goods

Quick Serve Restaurants

Consumer Durables

Demantra’s Key Customer Segments

“Six months after implementing Demantra Real Time S&OP we have seen a dramatic increase in forecast accuracy. This resulted in an immediate 20% inventory reduction.” – Wendy Malloy, Wilton Industries

What do Customers Say

“From an isolated process to a full Demantra RT S&OP - within six weeks of going live our ‘A-items’ improved 45% in accuracy. Today we load daily bookings against the forecasted Plan and feed production management to align back-end production based on the true feed of real-time demand.” –Sagi Srinivas, Johnson & Johnson MD&D

Global Medical Devices & Diagnostics Group• The Company is the world’s most comprehensive and broadly based

manufacturer of health care products, as well as a provider of related services, for the consumer, pharmaceutical, and medical devices and diagnostics markets.

• Challenge• MD&D Supply Chains become highly-reliable, effective, efficient and

synchronized to global product consumption • Strategy

• Implement global customer demand-driven planning processes to support Demand Planning, Supply Planning and Manufacturing at multiple World-Wide Franchises and Regional Order Processing / Distribution.

• Solution• Demand management

• Results• WW Franchises implemented• Reduced inventory days of supply• Reduced receivable days outstanding• Forecast accuracy levels increased dramatically• Customer service levels increased

Fairfax is Australia’s and New Zealand’s largest publishing group (Sydney Morning Herald, The Sun-Herald, The Age,…)

• Challenge• Improve demand forecasting (at the kiosk-rack level)• Improve supply allocation• Reduce waste levels and stock-outs

• Value• Scalable forecasting at the most granular level• Effective management of a perishable product (short shelf

life)• More frequent calculation of outlet supply quantities

• Solution• Real-time Sales & Operations Planning, Demand

Planning