DIGITAL BACKBONEA JOURNEY TO COMPANY WIDE PRODUCT DATA QUALITY MANAGEMENT

Rolf Sint, IT Architect

30.10.2018

Company Introduction

4 |

SWAROVSKI GROUP

EUR 3.5 billion annual turnover generated by the Swarovski

Group

32,000 employees distributed across 170 countries

3 companies Swaroski Crytsal Business, Swarovski Optik, Tyrolit

Headquartered in Austria and Switzerland

5 |

SWAROVSKI CRYSTAL BUSINESS (SCB)Business Units & Brands

ATELIER SWAROVSKI

SWAREFLEX

CONSUMER GOODS

BUSINESS

SWAROVSKI

PROFESSIONAL

LIGHTING BUSINESS

GEMSTONES BUSINESS

SWAROVSKI TOURISM

SERVICES

Executive BoardVon links: Daniel Cohen, Nadja Swarovski, Mathias Margreiter,

Markus Langes-Swarovski, Robert Buchbauer

6 |

EUR 2.7 billion turnover 2017

27,000 employees worldwide

Stores worldwide

1,500 Swarovski Stores

1,500 Partner Stores

Production locations in:

Austria, India, Thailand, Vietnam, Serbia, USA

FACTS

SWAROVSKI CRYSTAL BUSINESS (SCB)

7 |

7

SCB LOCATIONS WORLDWIDE

3,000 Stores worldwide

Status quo and the product master data

management challenge

9 |

CHALLENGE - PRODUCT DATA QUALITY AS A KEY COMPANY ASSET

DIGITAL BACKBONE

Increasing complexity of

our product assortment

Increasing

expectations to the

„Time to Market“

State of the art

IT landscapeData

Analytics

Digital Initiatives (Online

Shops, Mobile Apps,

Online Plattformen, …)

Data Protection

10 |

DIGITAL INITIATIVES (ONLINE SHOPS, MOBILE APPS, ONLINE PLATFORMS, …)IINCREASING NUMBER OF DIGITAL CHANNELS

DIGITAL BACKBONE

• Through different channels (e.g. ecommerce) data (quality)

becomes more visible to our customers

• Insufficient customer experience and lack of ability to

show all available products or connect additional digital

channels

• Quality issues and inefficient processes

• Inefficient processes, redundant data and inflexibility in IT

systems are the reason for manual rework and a low degree

of automation

11 |

INCREASING COMPLEXITY OF OUR PRODUCT ASSORTMENT

Current Assortment

• Swarovski has currently about 61 000 materials (loose crystals) in our product

assortment

• Each material describes a single crystal defined by key attributes like cut, color,

size, effects and foiling. Each material is stored in SAP and has a unique material

number.

Future Assortment: (MTO)

Our MTO assortment covers about ….

• Cuts 533

• Sizes 3 Average available sizes per cut

• Colors 70 Average available colors per cut

• Effects 55 Average available effects per cut

• Foiling 3 Average available

→ The estimated maximum potential product variants cover about

18 Million variants of our crystals

12 |

THE MTO CHALLENGE

PRESENTATION TITLE

• We have to create and maintain feasibility information for 18 000 000 crystals.

30% of these variants are technically not feasible, and another 30% are not feasible from a marketing point of view. So

about 6 Million variants will comprise the final configurable assortment.

• The user should be able to start the configuration on any arbitrary criteria. E.g. size, color, etc.

A lot of product configurators on the market only provide the linear configuration of products. E.g. Most car configurators.

• Complex logic within our product assortment:

Some cuts are only feasible in specific sizes, some effects can only be applied on specific sizes and geometries. Some

refinements can only be used on specific pretreatments. Indeed, various dependencies are possible and their detailed

analysis and definition will be part of the project.

• Integration

The rules will build the core of our future product assortment. So this information has to be integrated by several platforms,

e.g. EShop, B2B Ecommerce, SAP, …

13 |

3D DESIGNS ARE BECOMING ENTERPRISE ASSETS

3D

US

E C

AS

ES

FR

ON

T-E

ND

BA

CK

-EN

D Product costing

Tooling & fixture

productionDemand planning

Production

automation

Online & retailer

catalogues

Virtual try-onsVisual

merchandising

Communication

3D DESIGN IS BECOMING AN ENTERPRISE ASSET

How to guarantee the correctness of the data? What is the best way to distribute the data?

IT systems, data interaction and data objects

15 |

16 |

PRODUCT DEVELOPMENT – MAJOR SYSTEMS

SAP ERP

MDM

Transactions

Hybris PCM

Hybris

Commerce

Mobile App

HCP

B2B Online

Shops

Siemens

Teamcenter

Siemens

NX

Digital Backbone: Focus on MDM

processes in Siemens NX, Siemens

Teamcenter, SAP ERP and PCM

17 |

STATUS QUO

PRESENTATION TITLE

• Highly customized IT application landscape

• No MDM system is currently in use

• Major systems für product master data are Siemens NX, Siemens Teamcenter and SAP ERP

• Siemens Teamcenter and SAP ERP are highly customized and have been developed over the

last

decades

• For a realignment and modernization of these systems the required processes as well as the

future requirements have to be defined

18 |

DEFINITION OF PRODUCT MASTER DATA MANAGEMENT

OBJECTS IN PROJECT SCOPE

DIGITAL BACKBONE

Siemens Teamcenter / Siemens NX

# ID

Descriptions

Classification

Geometric Data

CAD Data

Weight

…

ERP

# ID

Descriptions, Classification

Geometric Data, Weight

Varian Configuration

Plant specific data

Sales specific data

BOM

Routing

Product Documents

…

PIM

# ID

Marketing Data

Translations

Media Assets

Care instructions

…

Product development, data governance and data consumption

In SCOPE:

Out of SCOPE:

• Pricing

• Stock

• Transactional data

• MES

• Sales and Demand Planning Data

• Launch planning

• CRM

Product Master Data creation, maintenance and control

Data Requirement:

Customer requirement

Product specifications

Assortment data

Launch information

…

Data Consumption:

Purchasing

Production

Logistic

Sales / E-Commerce

Analytics

…

Project objectives of the digital backbone project

20 |

WHAT IS THE DIGITAL BACKBONE

DIGITAL BACKBONE

What is the digital Backbone about?

The main objective of the digital backbone project is …

• the identification of existing pain points in the product creation and maintenance process.

• the implementation of quick wins throughout the project as well as the development of an

implementation roadmap

• to establish a state of the art IT architecture to support current and future business needs

For this the following three dimensions have to be considered:

• Business Processes

• IT Systems and Tools

• Product Master Data Quality

21 |

WHAT IS THE DIGITAL BACKBONE

PRESENTATION TITLE

What is the result of this project?

As a result of the digital backbone a future IT architecture in the areas of product master

data will be established. This will form the digital backbone as a basis for the realization of

future requirements in product management.

22 |

PRINCIPLES

• Product master data is maintained fully, correctly and on time

• Product master data is accessible be requesting persons and

systems

• Individual responsibilities regarding data quality management

processes are transparent and executed professional

• KPIs which indicate a high master data quality level are

measured and checked regularly regarding completeness,

consistency, correctness and actuality

• Causes of data quality issues are detected and fixed rapidly

23 |

PROCESS

How does the process haveto change so that we can

significantly improve alongthe defined dimensions?

TECHNOLOGY

Which digital technologiescan fuel the product

development process?

ORGANIZATION CAPABILITIES

DATA

PEOPLE

Which skills and compentencies are required

to effectively operate in such a product

development environment?

THE 6 BUILDING BLOCKS FOR PRODUCT DEVELOPMENT IN A DIGITAL WORLD

24 |

DIGITAL BACKBONE IS A MAJOR ENABLER OF SWAROVSKI´S DIGITALIZATION

AND FOCUSES ON EACH OF THESE BUILDING BLOCKS

DIGITAL BACKBONE

Roles & Skills

Digital

Business

Models

Digital

EnterpriseDigital

Customer

Organization

System / Architecture

Processes

DataCapabilities

Product

master

data

SWAROVSKI´s

Digital Backbone

Roadmap

26 |

DIGITAL BACKBONE – PHASE 1

DIGITAL BACKBONE

• Timeline: 26 weeks

• Evaluation Phase Deliverables/Activities:

Activity

0 Identify Stakeholder

1 Define business capabilities and requirements

2 Map future system architecture to capabilities

3 Asses status quo data objects and processes

4 Define current "data owner“

5 Define future IT architecture

6 System application assessment (cleanup, adopt, replace)

7 Define implementation activities

27 |

A JOURNEY TO COMPANY WIDE PRODUCT DATA QUALITY MANAGEMENT

Develop

2.Define

3.Determine

4.Analyze

5.Improve

6.Monitor

Identify relevant product

masterdata objects

guidelines and data

quality rules

current data quality

reasons for quality

issues and impact

monitor data

quality

Data quality and

governance

Digital Backbone

28 |

IT OPPORTUNITIES & NEXT STEPS

IT opportunities

• Establish a state of the art software architecture to support efficient business processes

• Introduce a MDM Tool to realize data governance ( including Workflows and Rule engines) (e.g. MDG / BRO / …)

• Introduce workflows to support processes

• Increase efficiency by increasing the level of Standardization

Next Steps:

• High level documentation and status quo analysis of involved IT systems

• Get Business Vision, Business Objectives and Business Requirements

• Establish a target architecture together with business and based on business requirements

• Establish implementation roadmap

29 |

FUTURE IT ARCHITECTUREEstablish a target architecture including ….

MDM SYSTEM SAP S/4 HANA

WorkflowsBusiness Rules

USER Interaction

ACTIVE WORKSPACEVariant Configuration and CPQ

THANK YOU