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KHNC - Retail Deployment Scenarios with Customer case study
Debraj Roy– Customer Solution Adoption (CSA)May, 2012
© 2012 SAP AG. All rights reserved. 2Confidential
The information in this presentation is confidential and proprietary to SAP and may not be disclosed without the permission of SAP. This presentation is not subject to your license agreement or any other service or subscription agreement with SAP. SAP has no obligation to pursue any course of business outlined in this document or any related presentation, or to develop or release any functionality mentioned therein. This document, or any related presentation and SAP's strategy and possible future developments, products and or platforms directions and functionality are all subject to change and may be changed by SAP at any time for any reason without notice. The information in this document is not a commitment, promise or legal obligation to deliver any material, code or functionality. This document is provided without a warranty of any kind, either express or implied, including but not limited to, the implied warranties of merchantability, fitness for a particular purpose, or non-infringement. This document is for informational purposes and may not be incorporated into a contract. SAP assumes no responsibility for errors or omissions in this document, except if such damages were caused by SAP´s willful misconduct or gross negligence.
All forward-looking statements are subject to various risks and uncertainties that could cause actual results to differ materially from expectations. Readers are cautioned not to place undue reliance on these forward-looking statements, which speak only as of their dates, and they should not be relied upon in making purchasing decisions.
Legal Disclaimer
© 2012 SAP AG. All rights reserved. 3Confidential
3
Learning Points
How Retailers can use the power of Hana to impact their Business
Retail Deployment Options
Case- Study, Lessons Learned in different areas of HANA implementation
© 2012 SAP AG. All rights reserved. 4Confidential
Topics1
BW on HANA –Retail Scenarios and Deployments
3
HANA based Retail Scenarios and Deployments
2
HANA for Retail
Customer Case study 5
Q&A
6
© 2012 SAP AG. All rights reserved. 5Confidential
Topics1
BW on HANA –Retail Scenarios and Deployments
3
HANA based Retail Scenarios and Deployments
2
HANA for Retail
Customer Case study 5
Q&A
6
© 2012 SAP AG. All rights reserved. 6Confidential
Retail Information is Exploding
Customer DataCompetitive Prices
GPS
Promotion Planning
Spe
ed
Hot Trends
Multi ChannelSto
re E
nhan
cem
ents
Em
ployee
Records
Suppliers
Purchase Orders
Merchandise Em
ails
Tweets
Planning
Social Media
MobileInstant M
essages
© 2012 SAP AG. All rights reserved. 7Confidential
Successful retail companies…
Deliver products and services that drive loyalty to the brand
Reach millions of consumers with targeted seamless cross channel experiences
Capitalize on new sales opportunities and maximize margin return
Improve customer services to increase competitiveness
Personalizing customer interaction
Identifying and seizing new opportunities
Accelerating fulfillment lifecycle
They do it by…
© 2012 SAP AG. All rights reserved. 8Confidential
SAP HANA for RetailValue Proposition
Simplify and unify business processes
Order fulfillment based on enterprise-wide product availability transforms customer experience
Hourly sales and stock information across all organizations and channels
Access precise data to make informed decisions
Real time profitability analysis at assortment and location helps pinpoint performance issues
Instant calculation of vendor rebates ensure all monies are collected on time
Speed You Need -Where it Impacts Your Business
Respond with personalized and targeted information and offers anywhere, any time
Customer interaction provides insight to develop new and exciting assortments
© 2012 SAP AG. All rights reserved. 9Confidential
1 BillionStore-item quantities by zone
800%Increased reportable detailed sales history from 3 to 24 months
8,100xFaster reporting speed
In-memory Computing Technology ImpactsVelocity - Volume - Value
© 2012 SAP AG. All rights reserved. 10Confidential
Common Retail Scenarios relevant for In-Memory Computing
Discontinued Items Analysis, Non-Moving Articles Analysis
Stock Balance Reports and Stock History
Out Of Stock Analysis (On-Hand Stock(RT), Goods Movement)
POS Data Analysis by Article, Store , Day
Summary Sales Reports
On Shelf Availability (Predictive)
Real Time Stock Position Analysis
Sales Analysis Reports (On-Hand , On-Transit , Sales reports)
Inventory Scenarios
POS Analytics Scenarios
Inventory with POS*
* New Scenario enabled by HANA
© 2012 SAP AG. All rights reserved. 11Confidential
Topics1
BW on HANA –Retail Scenarios and Deployments
3
HANA based Retail Scenarios and Deployments
2
HANA for Retail
Customer Case study 5
Q&A
6
© 2012 SAP AG. All rights reserved. 12Confidential
Retail Reporting Scenarios – Enabled by HANA
Real time visibility into Current stock situation by replicating ECC material master and filtered stock information into HANA
• Discontinued Items Analysis, Non-Moving Articles Analysis -Identify non-moving and discontinued items in real time so that retailers could increase their revenue by creating promotions, transferring to other stores, returning to vendors, making other adjustments, etc
• Stock Balance Reports Store wise visibility into current stock situation /stock summary
Agile stock modeling combining ECC master data and stock information's with non-SAP forecasting information from a 3rd party system
• Stock History Identify historical stock information's in real time so that retailers could see the trend of sales in the past and stock forecasting information stored in 3rd party system at any point of time
Inventory Scenarios
© 2012 SAP AG. All rights reserved. 13Confidential
Retail Reporting Scenarios – Enabled by HANA
Point of Sales Analysisby loading granular POS data (billions of records), into HANA ( billions of records) . Sales Summary and ad-hoc analysis across multiple dimensions like Products, Customers , Time, Stores and multiple sales key figures like total sales, basket sales, Customer spend, etc
POS combined with Inventory
POS Analytics Scenarios
Out Of Stock Analysis (POS*, Inventory Goods Movement)Feeding precise POS data into HANA and combining it with the ECC goods movement can help retailers reduce inventory carrying costs and gain critical insight into customer buying patterns and behavior
*Note that SAP POS DM data can also be loaded to HANA. However it is preferred to migrate to POS DM on HANA to benefit from standard content.
© 2012 SAP AG. All rights reserved. 14Confidential
Inventory and POS Data Analysis Scenarios –Deployment with HANA
Pure Inventory Scenarios with SAP ECC
SAP HANA
SAP ERP
SAP BO Clients
ReportingSQL / BICS
Sou
rce
Sys
tem
Inventory, Master Data
Stock AnalysisModels
SLT/ real-time
Current Stock
Article Mvmt. …
Master Data HANA-View
Inventory and POS Combined - SAP & Non–SAP Source Systems
SAP HANA
SAP ERP
SAP Business Objects Clients
ReportingSQL / BICS
Sou
rce
Sys
tem
Master Data Stock AnalysisModels
SLT/ real-time
Non SAP / DW
Inventory
Data Services
SAP BO ClientsStock history
Sales Analysis.
Master Data
HANA-View
POS
Sales Data as FlatFiles Data Services
© 2012 SAP AG. All rights reserved. 15Confidential
Topics1
BW on HANA –Retail Scenarios and Deployments
3
HANA based Retail Scenarios and Deployments
2
HANA for Retail
Customer Case study 5
Q&A
6
© 2012 SAP AG. All rights reserved. 16Confidential
Retail Reporting Scenarios – Enabled by BW on HANA
Inventory BW Content• Inventory value monitoring• Returns analysis for supplier/ customer returns• ABC classification• Cross selling / substitutions analysis
Near real-time Custom Content : • On-Hand , On-Stock report provide an overview by site
showing on hand sales units, on hand dollars, on order units, on order dollars. Provides stores with a snapshot of relevant inventory data for making present and future ordering decisions
• Stock Balance Reports Store wise visibility into current stock situation /stock summary)
Inventory Analytic Scenarios
Value Proposition:Revenue due to managed inventory (promotion, sales, return to vendors, etc)
© 2012 SAP AG. All rights reserved. 17Confidential
Retail Reporting Scenarios – Enabled by BW on HANA
Near Real-time Basket Analysis.
• Customer Loyalty Analysis becomes supercharged with total customer attributes and behaviors by combining customer data with POS data
• Replenishment quantity Analysis by merging sales data with real consumption data from non-SAP sources, will provide the ability to plan correct replenishment quantities
• Sales and Forecast Analysis down to the lowest level of detail to identify key value items while integrating customer buying patterns to drive profitable promotions
• EDW Reporting Services provided by the Global Retail Hub
POS Data Analytic Scenarios
Value PropositionSLA to process POS sales data within agreed processing windows
© 2012 SAP AG. All rights reserved. 18Confidential
Retail Reporting Scenarios – Enabled by BW on HANA
Near Real-time Stock position
• Stock Trend Analysis (POS Data, Inventory Goods Movement) Feeding NON SAP POS data into BW on HANA and combining it with the ECC goods movement or NON SAP goods movement help retailers to reduce inventory carrying costs and gain critical insight into customer buying patterns and behavior
• Out Of Stock Analysis (POS Data, Inventory Goods Movement) Feeding NON SAP POS data into BW on HANA and combining it with NON SAP goods movement help retailers to monitor stock Level and active promotions to optimize Material Store availability and Level of Stock value
Inventory + POS Data Analytic Scenarios
Value PropositionMonitoring of Stock Level and active Promotions to optimize Material Store availability and Level of Stock value
© 2012 SAP AG. All rights reserved. 19Confidential
Stock Position – Deployment options with BW on HANA at a glance
SAP & Non–SAP
SAP HANA SP3
SAP ERP
SAP Business Objects Clients
ReportingSQL / BICS
Sour
ce
Syst
em
Master Data
SAP BW 7.3 SP5ETL /Extractors
Non SAP
POS Data ETL
SAP BO ClientsOn Hand Stock
On Hand Stock
Out Of StockOut Of Stock
…
Master DataMulti-
Provider
POS DSO
Inventory Inventory DSO
SAP HANA SP3
SAP ERP
SAP Business Objects Clients
ReportingSQL / BICS
Sou
rce
Sys
tem
Master DataSAP BW 7.3 SP5
BW Virtual Provider
ETL /Extractors
Non SAP
POS DataETL
SAP BO ClientsOn Hand
StockOut Of Stock …
Master DataMulti-
Provider
TLOGF Analytic View
Inventory
BW InventoryContent
SAP & Non–SAP
SAP HANA SP3
SAP ERP
SAP Business Objects Clients
Reporting
SQL / BICS
Sour
ce
Syst
em
Master Data
SAP BW 7.3 SP5ETL /Extractors
Non SAP
POS Data SLT
SAP BO ClientsOn
Stock
On Hand Stock
Out Of StockOut Of Stock …
Master Data Multi-Provider
Inventory
Inventory*
TLOGF
Analytic View
BW Virtual Provider
SAP BW Inventory + Real time POS Extraction Based
Near Real Time
* Inventory data from SAP ERP can also be replicated realtime to HANA data marts
© 2012 SAP AG. All rights reserved. 20Confidential
Topics1
BW on HANA –Retail Scenarios and Deployments
3
HANA based Retail Scenarios and Deployments
2
HANA for Retail
Customer Case study 5
Q&A
6
© 2012 SAP AG. All rights reserved. 21Confidential
Customer Scenario–Use Case
Why HANA•To drive in store consumer traffic and sales by having the right product in stores at right time (detect and replace non-moving, discontinued articles)
•Reducing Inventory costs for non-moving and discontinued articles •Strategic advantage with vendors – by negotiating lower rates/discounts for non moving articles
•Gain visibility into discontinued articles in near real time
Benefits•Multi-million dollar increase in store sales by accelerating the replacement of non-moving articles
•Reduction in non-moving articles from 5% to 2% annually leading to multi-million dollar savings on a yearly basis
© 2012 SAP AG. All rights reserved. 22Confidential
Case Study –Project Scope and components
SAP Project Scope
•Near real time Inventory reports –Catalog of 8 M articles, combination with
100 stores,(approx. 800 M information ,1M record per material/store)
•Total data volume 2.84 GB,100 users
•SAP Components: HANA-SLT-BI (Webi, Explorer)
•Hana - Two Boxes 256 GB (DEV) and 512GB(PROD), 120 GB DB
© 2012 SAP AG. All rights reserved. 23Confidential
Inventory Scenarios -Before and after HANA
• Not having real time visibility into current stock situation
• Higher storage costs for stock
• Opportunity cost of lost sales
Business Pain Points before HANA
• Reduce the long processing times to analyze non-moving articles and discontinued articles.
• Reduce Large infrastructure maintenance costs (Heterogeneous landscapes with sometimes multiple Inventory systems per DC)
Advantages after HANA
© 2012 SAP AG. All rights reserved. 24Confidential
Landscape at Customer-Before and after HANA
Customer Landscape before HANA
SAP ERP SAP BW[Optional]
BW StockContent
Customer Landscape after HANA
Inventory Master Data
SAP HANA
Stock AnalysisModels
SLT/ real-time
Master & Stock Data HANA-CA View/SQL Script
BO ReportsBO Reports
ECC BW
SAP ERP
Inventory Master Data
ECC
© 2012 SAP AG. All rights reserved. 25Confidential
Lessons Learned – Project Management
Scope small and take phased roll out approach for fast and successful implementation
Adopt ideas as appear Adopt ideas as appear in implementation/testing phase rather than trying to obtain full proof solution in blueprinting phase
Often Data provisioning is most common underestimated task in the project plan
HANA Rev’s are released frequently, be prepared to put enough placeholders in the plan
© 2012 SAP AG. All rights reserved. 26Confidential
Project Plan and Time line
Duration of the project : 30 weeks
Project Timeline Reference
Weeks
Project Preparation 2Business Blueprint 4Realization 18Final Preparation 4Go Live and Post Production Support
2
© 2012 SAP AG. All rights reserved. 27Confidential
Resources
Resource Name
Project Manager
HANA,SLT, BI Inst / Maint Expert
HANA Modeler / SQL scripting Lead
HANA Modeler
BI 4.0 Architect & DeveloperQA HANA Deployment
MM Business consultant
© 2012 SAP AG. All rights reserved. 28Confidential
28
Critical Areas-Most time spent
Modeling
Data transformation and provisioning
Performance Tuning
© 2012 SAP AG. All rights reserved. 29Confidential
Lessons Learned – Data Compression in HANA
02468
1012
Compression Ratio
Compression Ratio
The best compression can be achieved in HANA if the data in source system is un compressed
© 2012 SAP AG. All rights reserved. 30Confidential
Lessons Learned – Data Provisioning using SLT
Some extra attention needed for cluster table load (For Example partitioning, parallel load mode etc)
Source system information filtering capabilities are available from SP3 onwards (Before SP3 through an SAP note 1625755),so filter as much as you can in the source system)
Common configuration problemWhen creating a new schema in SLT system, you get the error message “Error when connecting to Source system” in the WebDynpro.Possible reasons
1.Missing add-on DMIS_2010 in your source system.Check and make sure that in your source system you have installed the required add-on DMIS_2010.(Please refer to SAP Note 1468391)
2. Missing proper roles for the RFC userIn the system log (SM21) and ABAP Check if role SAP_IUUC_REPL_REMOTE assigned to the RFCuser. Assign the role if it isn’t assigned yet
© 2012 SAP AG. All rights reserved. 31Confidential
Lessons Learned – System Installation and Maintenance
Backup the log file ,archive it and clear it frequently, otherwise you will encounter out of memory problem as log files grow very quickly
Keep a system landscape diagram handy before starting installation or configuration
In the SLT system tune up the SLT batch processes, make enough free process available for replication
In the SLT system tune up the SLT batch processes, make enough free process available for replication
Take considerable time to do Sizing of the source(determination of the compression ratio),Sizing of the HANA box (For concurrent user and increase of the memory at runtime)
© 2012 SAP AG. All rights reserved. 32Confidential
Lessons Learned – HANA Modeling
Query to Analytical view is faster than calculation view ,ideally keep CA view simple with minimal parameters and joins
Unions of Analytical views in Calculation views are faster than joining Analytical views
Model the business logic first then find the attributes, thus joining with minimal master data tables
HANA doesn’t have ABAP like statements, something to keep in mind for the modelers, only supported language is SQL script so
looping could be expensive
Push the filters in Attribute view level , putting the condition in where clause within HANA SQL script is very expensive in terms
of performance
© 2012 SAP AG. All rights reserved. 33Confidential
Lessons Learned – BO Integration
Keep array size more (5000) in universe to prepare a bigger record set (set in the connection definition (CNX) file)
In order to benefit of HANA performance in calculations you should always try to retrieve the least quantity of data in your report for example aggregate data, not detailed information
Measures defined in the information model will be seen as dimensions in the information design tool (as any other field of the table). Make sure you turn them to measures
© 2012 SAP AG. All rights reserved. 34Confidential
Lessons Learned – Authorization
Analytic privileges can be transported using import/export method and it needs to be done manually
SAP HANA Template roles are quite useful
CONTENT_ADMIN
MODELING
MONITORING
Do not change this roles, copy and change the name to use.
The number of invalid log on attempts can be reset using the following SQL command (useful to unlock locked users)
ALTER USER <USER_NAME> RESET CONNECT ATTEMPTS;
© 2012 SAP AG. All rights reserved. 35Confidential
Lessons Learned – Performance Tuning
Best practice is to partition tables containing more than 2 B data to reduce the merge time and memory consumption
If there is a need to join tables on a calculated attribute, the workaround is to have an additional column in the table itself with the calculated value populated which is faster in terms of reporting as well
The SQL Parser will create a composite key for the fields joined which will in theory is more performance demanding than a filter. So avoid join tables on MANDT fields ,instead use filters.
© 2012 SAP AG. All rights reserved. 36Confidential
36
Key Learnings
How Retailers can use the power of Hana to impact their Business
Retail Deployment Options
Case- Study, Lessons Learned in different areas of HANA implementation
© 2012 SAP AG. All rights reserved. 37Confidential
Resources
How to get HANA now (29 Nov 2011)
http://en.sap.info/rds-hana-erp-implementation/61898
SAP HANA Adoption (Dec 13 2011) :
http://www.sap.com/corporate-en/press/newsroom/press.epx?pressid=18063
© 2012 SAP AG. All rights reserved. 38Confidential
Questions
Thank You!
Debraj RoySolution Expert HANA Application I Customer Solution Adoption (CSA) SAP Labs I M +1 480 401 6600 I mailto:[email protected]
© 2012 SAP AG. All rights reserved. 40Confidential
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