TPM – REFERENCE MODEL
Develop HighLevel Trade
Promotion
Strategy
1. Define Sales Performance & Product
Objectives.
2. Establish & Re-Evaluate Metrics
3. Determine Funds / Budgets and create
Accruals
1.
2.
3.
4.
Data Analysis against Program goals
Evaluate Brand Performance
Evaluate Promotion effectiveness
Standard Reporting
Post-Promotions
Analysis /
Management
Reporting
1. Allocate funds / accounts
2. Obtain Internal approval
3. Sales forecasting
Develop Budget,
Targets and
Allocate Funds
1. Create Marketing Calendar & promotion
guidelines
2. Promotion Plan & Development
YEARLY
1. Authorize Payments
2. Resolve and reconcile deductions
3. Rebates and Write-offs
Complete
Account/Promotion
Planning
Settle & Reconcile
Claims
ADVANCED CAPABILITIES
1. Integrate Business Planning
2. Demand Planning Integration
Account Execution
and Monitoring
1. Promotion Execution Sell-in Negotiation
2. Activity Management
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TPM - KPIs
CORE KPIs
2
Consumer Units
The key to keeping measurement simple and accurate is to measure
exclusively in Consumer Units. If you want to be consumer-centric, then
you need to measure the same way that the consumer buys
Revenue
Convert the Consumer unit in terms of Revenue
% Lift
% increase in sales resulting from the promotion
Incremental Revenue
Revenue generated solely by the promotion
Incremental Profit
Profit generated solely by the promotion
Spending Efficiency
The correlation between the total profit and the initial trade spending
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TPM - KPIs
SUPPORTING KPIs
3
Cost per Incremental
Unit
Cost of single incremental unit spent during promotion period
Profit per Incremental
Unit
Profit generated by single incremental unit during promotion period
Weighted Weeks of
Support
Number of weeks of promotional activity supported by the retailer
Retailer Margin
Margin generated by the account during the promotion deal
Total Revenue
Total revenue generated during the promotion
Total Profit
Total profit generated during the promotion
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TPM KPI DERIVATION
% LIFT
BASELINE
VOLUME
GENERATION
INCREMENTAL
VOLUME
INCREMENTAL
REVENUE
PROMOTION
OTHER DERIVED
KPIs
RATE
REVENUE
SHIPPING
BILLING DOC
ACTUAL
VOLUME
ACTUAL
SPEND
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SUBJECT AREA MODEL
Customer
Customer Hierarchy
Sales Order
Promotions
Pricing
Product
Product
classification Hierarchy
Tactics
Billing
POS Data
TRADE PROMOTION
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Demand
Finance
Product
TRADE PROMOTION
Master Data
Transactional
Data
Core Business Data
ORDERS
INVOICES
Operational
Data
PAYMENTS
PRODUCT
CUSTOMER
SALES ORG
Reference Data
Strategic
Data
DIVISION
REBATES
PROMOTIONS
CHANNEL
TACTICS
FI POSTINGS
BASELINE
PRODUCT
HIERARCHY
CUSTOMER
HIERARCHY)
KPI
CALENDER
WEEK
CONSUMER UNITS
REVENUE
INCREMENTAL FACTOR
SPEND RATIO
CUSTOMER
PRODUCTS
SHIPMENTS
DISPUTES
DELIVERIES
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Transactional
INVOICE
REBATE
PAYMENT
ACCRUALS
TRADE PROMOTION PROCESS
PROCESS
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INPUT
OUTPUT
DATA
Plan / Approve / Commit
Planning account , Product, Tactics,
week
Pricing Condition Records, Rebate
agreements
Customer Master, Product Master,
Promotion Master data
Pricing conditions
Committed Promotions
Pricing conditions
Sales org, distribution channel, Division,
Customer, Product, Promotion Id,
Tactics
Rebate Agreement
Committed Promotions
Sales Document
Billing document
Customer Master, Product Master,
Promotion Master data, Billing data,
sales Order
Accrue
Billing Document
Accruals created in Atlas at Product
Level. Posted in P&L
Actuals Updated in TPM
Tactics, Invoice, Accrual Method, G/L
Account
Pay
Dispute / Rebate Document
Rebate settlement, Credit Note
G/L Account, Billing Document
Close Tactics / Reverse accrue
Payment Document
Close Tactics / Close Rebate agreement
Tactics,G/L Account, Billing Document
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TPM DATA LIFE CYCLE
Requirement
Baseline create
Data
Birth
shipments
Rest of
Asset Life
Business Operation
Forecast Process
Baseline Update
Asset
Decommission
Legal
Retention
2 years from forecast
Data
Disposal
Snapshot at brand /
customer level
Sales Orders
Promotion create
Business Strategy
Promo History Analysis
New promotion creation in TPM
tool
Actuals
Billing
Promotion update
Billing update
All Tactics closed
Billing closed
Analytics
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Baseline create
Analytics need
Analytics need
Archived in Data Lake
Archived in Data Lake
RECOMMENDATIONS ( 1 – 2)
 General:
– SaaS solution is recommended as cost of ownership is minimal
– Having different flavors of TPM solutions are recommended based on Market volume, NSV and Market
Practice
– Choosing solutions used prevalently in the Region / Market ensures smooth implementation
 Business:
– Keep only the relevant KPI’s necessary for Promotion Analysis in TPM tool.
– Combination of TPM tool and Analytics Data Mart for Decision support
 Integration:
– Real time data extraction if possible
– Support bulk data transfer like API / ETL / SAP Connectors
 Technology
– Automated End to End monitoring solutions to track and fix error
– Choosing data base Technology that can support bulk nightly processing
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RECOMMENDATIONS ( 2 – 2)
 Data / Information
– Choosing a tool that supports or mimics SAP table structure provides smooth integration
– Design efficient data model for transactional and analytical purpose even that means keeping two separate
data Models
– Process data in real time / Near Real time if possible
– Master data governance in place to make sure all transactional systems reflect the same status of Master data
– Data reconciliation process and criteria in place
 Security
– Existing security architecture can be replicated for future solutions
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FUTURE STATE TPM ARCHITECTURE
SOURCE
SYSTEMS
4
TPM
INTEGRATION
LAYER
SRM ANALYTICS
ADMINISTRATION
TRANSACTIONAL
DATA
API / TOOL
AGNOSTIC
INTEGRATION
USER
INTERFACE
DATA
PROCESSING
Master DATA
ANALYTICS
2
1
3
SLT
SLT
SAP HANA
SRM ANALYTICS
DATA RECONCILIATION
5
SPLUNK - MONITORING
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SRM ANALYTICS
AZURE DATA LAKE
HANA
Integration Layer
TPM
ATLAS
APOLLO
1.Transactional Analytics should be performed in the source systems
2.Analytics related to current promotion, Pre-Event Analysis should be performed in TPM tool
3.Current week Analysis / Operation / Regional reporting / Data Reconciliation / Daily Snapshot from
Hana
4.Use Azure data Lake for Post event Analysis / YTD reporting, forecast analysis, statistical Reporting
weekly / Periodic Snapshot and Global Reporting
5.Materialized Data Marts should be used for overcoming the reporting performance in Data Lake
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