Coming SAP HANA for Retail Solution · Coming –SAP HANA for Retail Solution Septembar 23, 2015...
Transcript of Coming SAP HANA for Retail Solution · Coming –SAP HANA for Retail Solution Septembar 23, 2015...
Coming – SAP HANA for Retail Solution
Septembar 23, 2015Miroslav Kržić
Coming, Belgrade
New Idea & Modis, Moscow
MODIS – Leading Russian Fashion Brand
География присутствия и план развития
• Федеральный охват – свыше 125 магазинов в 65 городах. В 2014 году количество магазинов превысит 140
• Общая площадь магазинов – в 2014 году достигнет 170 000 м2. Средняя площадь магазина составляет 1 200 м2
Общее население в городах, где представлен МОДИС – более 48 млн. человек, в том числе:
• 15 городов – 1 млн.+
• 15 городов – 500 тыс. +
• 28 городов – 200 тыс.+
• 9 городов – 100 тыс.+
Modis: Aplikaciona/Virtuelna InfrastrukturaIntegracija
Applications landscape
Core IT Infrastructure in M1 datacenter
Compute resources (5 hosts/servers) Disk storage resources
HP 3PAR HP EVA
Core networking (SAN/LAN Switches)
VMware vSphere Virtual infrastructure with centralized management and monitoring
H1 H2 H3 H4 H5 D2D Backup
Disaster Recovery Datacenter for Core Business Services
(applications)
VMware SRM (DR extension)
TEST
SAP Retail ERP Landscape
DEV
PRODDB+CI
APP1
APP2
TESTDEV PROD
Datawarehouse Landscape (SAP BW)
New POSPOS Srv
POS Landscape BI (BO) Server
PI Server
Other Virtual Servers –
Exchange, AD, File/Print,
SharePoint...)1CHANA Phase 1HANA Ph2
POSDM CRM
Modis applications and virtual infrastructure landscape
Existing
Project in progress
MAP
HANA Appliances
© TeamIdea, 2011 6
Modis Application Integration and BI
New design - based on SAP HANA
© TeamIdea, 2011 7
SAP HANA – New Modis Analitical Plaftorm
SAP ERP, POS, CRM Data Sources Real Time Data Replication SAP HANA – Analytics, Forecasting, MAP, Replenishment, Markdown
New
Modis Sales Transactions – volume
RETAIL co. - POS - volume of
transactions
Volume of sales 2.500.000.000 $
Avg sale amt 25 $
Avg no of items 3 8$ per
item
No of receipts/invoices 100.000.000 per
year
No of recpt lines 300.000.000 per
year
data warehouse 5 years recpt history 500.000.000
recpt lines 5 year 1.500.000.000
No of SKU 25.000
% of new SKU per year 40%
no of new SKU 10.000
SKU total 65.000
no of recpts/day (300 working days) 333.333
no of SKU/day 1.000.000
no of trans/sec (12 hours working day) 8
no of stores 400
no of billed customers per store per day 833 ?!
data volume (dw no compression)
dimension keys:
store 4
datetime 8
sku 18
tt 2
payment type 2
consumer type 4
repeating cust. 4
sku group 2
sku type 2
sku number 2
sku design/color 2
store region 2
uom 2
discount type 2
measures:
qty 8
price 8
cogs 8
discount 8
hard currency val 8
total bytes 96 ~100
Expected value (bytes) 100
fact table size (bytes) 150.000.000.0
00
B
fact table size (GB) 150 GB
Merchandise and Assortment Planning
© TeamIdea, 2011 10
MAP Project Goals and Objectives
PROJECT GOALS
1 Create flexible and simple to use planning methodology;
Bring best practice planning process for Fashion Retail;
Improve the manageability of the planning process;
Improve transparency of the planning process in company
Improve planning result accuracy and reduce planning error;
Involve business users into the planning process with
strictly defined roles;
Reduce user mistake;
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PROJECT GOALS
Analyze current process gaps and requirements received
from the business team responsible for financial, retail,
assortment and purchasing plan;
Develop one centralized, easy to use and flexible planning
platform for all MAP planning activities using SAP
technology;
Involve business user in planning process with planning
SAP tool with strictly defined roles and responsibilities;
Improve master data quality used for planning process;
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Demand planning – structure and requirements
Strategic PlanningSales Budget at Sales org., distribution channel, brand and country
Sales Budget
Breakdown at division, agent, customer and product class
MerchandisePlanning
Breakdown at division, product class and prod. group
StorePlanning
Forecast
Calculate forecast from actual sales Options
Planning
Plan number of options per store cluster
PurchasePlanning
Evaluate global demand (wholesale and retail) and release quantities to create purchase orders
AssortmentPlanning
Country Manager
Wholesale Manager
RetailManager
Retail ProductManager
Sales Agent
PurchaseManager
Breakdown at store, division and product class
Plan quantities at SKU level per store cluster
TOP-DOWN PLANNINGSTRATEGY
Design, sales and purch.
Capsule Definition
Decide capsule configuration and deliv. dates
Board of directors
Fashionworks has a Merchandise and Assortment Plan solution for the Retail Fashion business that has evolved to amore flexible environment, SAP IP, conserving its integration quality with the transactional system.
Planning for retail overview – real time requirements
Strategic Planning
Merchandise Planning
Store Planning Assortment Planning
Capacity Planning
OTB
End of season
Promotions
Markdown planning. Replenishment
Purchasing
Update OTB
PLANNING
In Season
Pre Season
Modis – Forecast Replenishment and Markdown Modules
© TeamIdea, 2011 14
Forecast modulePOS (dataset from
point of sales system)
Stock ad DC/Store (dataset from ERP)
Markdown/Clearance module
Allocation/Replenishment
module
Transactions flow (goods movement and status change trans.)
Control flow/data input
New modules (blue) and integration with datasources (green)
Key Modules for Effective Execution
© TeamIdea, 2011 15
Store replenishment – real time and reliable forecast
Forecast flow
•Manual selection
•Automatic system selection
Define Forecast model
•Specify model parameters
Model Initialization •Stock withdrawn from the
warehouse
•Enter manually or interface
•Reference material consumption
•Alternative historical data (AHD)
Creating historical data
•Calculated by the system
•Enter manually
Create forecast values
© TeamIdea, 2011 17
© TeamIdea, 2011 18
Modis – Transformation of Data Processing
SAP NetWeaver BW - New Architectural Paradigm
SAP NetWeaver BW
Data Modeling
HANA
Data Management
Data Storage
Analytical / PlanningEngine
DBMS
SAP NetWeaver BW
Data Modeling
Analytical / PlanningEngine
Relational Database
Data Management
Data Storage
SAP HANA Platform for Real Time Business
Big Data Bundles for Retail from SAP
Information Management & Real-Time Data Movement
Transactional Data
Management
In-Memory Data
Management
Analytics EDW Data
Management
Mobile Data Management
Co
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Des
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&
Mo
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Envi
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men
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dscap
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Open APIs and Protocols
SAP real time data platform
Federated Access
SAP Predictive Analysis
SAP VisualIntelligence
R, SAS, SPSS, etc.BusinessObjectsBI Suite
3rd party, open source
analytic tools
The Future of Modis: HANA + HadoopEnriching Retail POS with Customer Product Interest