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;

2

3

4

5

6

7

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;

1

2

3

4

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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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