제조업 사례로 살펴본 “Big Data ROI 측정 및 투자”

김기남 Manager / SK 텔레콤 Data사업본부

Consideration for Big Data in Manufacturing

Areas of Greatest Benefits for Manufacturing

Source: A TCS 2013 Global Trend Study

#1. Big Data 투자, ROI에 대한 고민

ROI Calculator

Source: TDWI

ROI Calculator

Company Profile

Labor Cost

HW, SW Cost

Direct Cost Savings

Productivity

Revenue Increase ROI

ROI 등식

Cost of Investment - Gain from Investment = ROI

Server Perpetual Licenses

Storage ) (

Support Subscription Licenses Network and Security

Customizations Cloud

( )

CapEx OpEx Revenue

Optimization Cost

Optimization + - -

) New Revenue

Existing Revenue + (

Employee Average Cost per Hour x Total Number of Increased Productivity Hours ( )

+ Human Capital Gain

Existing Solution Gain + ( )

Running Costs Efficiency + Value of Minimized Revenue Risk ( )

Revenue Optimization

Big Data ROI에 대한 OTL

#2. Big Data Infra 투자를 통한 현재 가치만 계산

자동제어 / 실행

Big 데이터 분석

데이터 센싱/수집

지능형 의사결정

제조 Intelligence를 첫 단계

Bottom Line Contribute

Revenue Optimization

Cost Optimization

CapEx OpEx + - - ROI =

Net present value 만 고려

Bottom Line Contribute

Big Data Preparation SCM

ERP

P&S

MES

• Planning • Scheduling • Real Time

Dispatching

• Execute Prod • Inventory Mgt.

• Material Mgt. • History Mgt.

YMS

• Yield Mgt. • Quality Analysis • Statistical Analysis

Enterprise

MES

Level

생산시스템, IT부서 Data

DW

Data Lake

①

②

Ingestion

Transformation

Barriers to Entry

Data Lake

DW

#1 Application

#2 Application

#3 Application

#4 Application

#5 Application

#6 Application

Leverage existing SQL query language and existing BI tools against data within Hadoop

Barriers

But.... More Data, Bigger Challenges

Data quality rules

Data catalog Metadata

store Data lineage

Big Data Governance

• Management Scalability • Metadata Tools • Business monitoring

It's not all 100% there

OpEx

Hadoop 운영

인건비 증가

1) What do we know about our information? 2) Where did this data come from and who can use it? 3) Does this data adhere to company policies and rules?

Ingestion

Data Lake

Cleansing

Transformation

#3. Big Data 분석을 활용한 Business 미래가치 증명

자동제어 / 실행

Big 데이터 분석

데이터 센싱/수집

지능형 의사결정

제조 Intelligence를 위한 다음 단계

Business Insight Contribute

Revenue Optimization

Cost Optimization

CapEx OpEx + - - ROI =

? ? ? ? Biz 가치 증명 예산 부족 인력 부족 Biz 가치 증명

?

Investment

Small Start with Small Team

PoC

Dot’ know the Result

Small Team Exploration Test & Valuation

Revenue Optimization

? Biz 가치 증명

Cost Optimization

? Biz 가치 증명

Data Lake

#1 Application

#2 Application

#3 Application

DW

Data sandboxes

• Individual data views in the data lake

• Self-Discovery-BI

• Advanced Analysis

Explore Raw Data Sets

CapEx

예산 부족 Data scientists and other analysts need to be allowed to explore raw data sets in an unfettered way

Data Exploration

Data Agility

Machine Learning

Metatron for Big Data Discovery

데이터 수집

저장 & 처리

분석

시각화

데이터 패턴 탐지 / 실시간 수집

Sub-second 처리 엔진

In-memory Grid 시각화

A A A

Hadoop 에코시스템

Big Data Storage

Industry 특화 고급분석(DNN ML, etc.)

모니

터링

및 관

리/보

안

• Workspace: 개별 유저가 독립적인 분석

공간을 논리적으로 할당 받으며, 해당

공간에서 수집, 처리, 분석, 시각화를 수행

탐색 분석(Discovery/리포팅) SQL 분석 (Ad-hoc Query)

심층 분석(R, ML, Python) ETL/Workflow

Rethinking Business

분석 전문업체 무상 PoC Evaluation Investment AS - IS

TO - BE Proof of concept business

model with a partner

Evaluation Cultivate

New business with a partner

OpEx

기술 인력 부족

Revenue Optimization

Biz 가치 증명

CapEx

예산 부족

Rethinking Business with SKT

Let's put your data to work

Unlock operational efficiency

Capture new growth opportunities

Let's build something together

Solution for Business Excellence with partners

Big Data Analysis Professional Service

On-Premise or Cloud

Data Collection Data

Processing

Data Model Manager

Data Preparation

ML / DNN Algorithm

예지 정비

Appl.

품질 관리

Appl.

운영 최적화 Appl.

....

Thank you!

김기남 Manager

kinam.kim@sk.com