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Fulfilling Unfulfilled Dreams: The Last Frontier of MIS Fulfilling Unfulfilled Dreams: The Last Frontier of MIS
Byungtae [email protected]
Graduate School of ManagementKAIST
SERI, July 26, 2003 2003, Byungtae LeeKAIST 2
AgendaAgenda
1. Introduction
2. MIS and Organization
3. EIS and Why Not?
4. Business Simulations/Games
5. Complexity Theory
SERI, July 26, 2003 2003, Byungtae LeeKAIST 3
Business Solution ProductsBusiness Solution Products
ERP, SCM, CRM etc Why didn’t we come up with such solutions first? What’s left then?
SERI, July 26, 2003 2003, Byungtae LeeKAIST 4
Executive Information SystemsExecutive Information Systems
Transactional System
MIS/DSS
EIS
SERI, July 26, 2003 2003, Byungtae LeeKAIST 5
EIS: Unfulfilled DreamEIS: Unfulfilled Dream
IT experts have sold the concept of “Strategic Information Systems” ever since MIS started for more than 5 decades
Promised but never delivered A reason why top executives are not interested in MIS
SERI, July 26, 2003 2003, Byungtae LeeKAIST 6
Why No EIS?Why No EIS?
EIS is not defined well? EIS may be a hype? Executives’ problems can not be helped by computer
systems? Ideals can not be realized due to lack of appropriate
technologies.
SERI, July 26, 2003 2003, Byungtae LeeKAIST 7
Questions?Questions?
Do executives need their own information systems? Does EIS Market exist?
Can we define what is and how to make them?
SERI, July 26, 2003 2003, Byungtae LeeKAIST 8
Today’s ManagementToday’s Management
Destructive Technologies and Innovation Highly Interactive and Empowered Customers (Red
Devils) Globalization and Death of Distance Winner-takes-all (or Almost if not all) More Risk and Uncertainty
SERI, July 26, 2003 2003, Byungtae LeeKAIST 9
Executives ProblemsExecutives Problems
Transactional System
MIS/DSS
EIS
Un
structu
red
ness
SERI, July 26, 2003 2003, Byungtae LeeKAIST 10
Why Can Not They Be Helped?Why Can Not They Be Helped?
Aggregation of Transactional Data seldom gives information and knowledge that executives search
5 key problems of Transactional Systems to Executives: 부족형 편재형 산재형 비유용성 비접급성
SERI, July 26, 2003 2003, Byungtae LeeKAIST 11
Is Management Science?Is Management Science?
Statistics/Forecasting assume continuing fixed environments but today’s management faces destructive technologies
Statistics/Regression deal with “average” behavior of customers but customization and personalization are virtue of today’s strategy
Game Theory and Mathematical Modeling over-simplify the real world
Strategic Consulting produces 2x2 Matrices
SERI, July 26, 2003 2003, Byungtae LeeKAIST 12
DSS, Expert Systems, AIDSS, Expert Systems, AI
Knowledge Representation Knowledge Acquisition World a God (programmer) created
Top-down Approach Pre-cooked Scenarios Equation-based approaches Modelers should know the entire chain of
causalities
SERI, July 26, 2003 2003, Byungtae LeeKAIST 13
Are You Doing These Oxymoron?Are You Doing These Oxymoron?
• Management at Speed of Lights (Bill Gates)
• Management from Guts (Jack Welch)
SERI, July 26, 2003 2003, Byungtae LeeKAIST 14
In the mean time…In the mean time…
CRM promotes customization/ personalization in Products/Services, Prices, Channel, ….
SCM advocates optimization over Business value chains
Capital Market put more pressure to produce immediate results
Management at Speed of Lights
SERI, July 26, 2003 2003, Byungtae LeeKAIST 15
What do Top Managers do?What do Top Managers do?
Strategic Analysis Strategic Planning Strategic Implementation
SERI, July 26, 2003 2003, Byungtae LeeKAIST 16
Strategic Planning FrameworksStrategic Planning Frameworks
Competitive Rivalry from
Existing Firms
TechnologyRegulatory
Environment
Changing Social Values Substitutes
Suppliers
Buyers
New EntrantsEconomic Changes
Demographic Changes
SERI, July 26, 2003 2003, Byungtae LeeKAIST 17
Now You Have Discovered ….Now You Have Discovered ….
Britons are coming…. They seem stronger…
This is where consulting ends and why big firms fall. What will you do?
Re-designing products, processes, organization, channels, ……
Continuous Simulation and Chess Games in Minds
On what bases?
SERI, July 26, 2003 2003, Byungtae LeeKAIST 18
New EISNew EIS
Chess Board for Business Simulations Separation real agents from virtual ones Interactions between Virtual and Real
Agents Agent Technology and Visualization
SERI, July 26, 2003 2003, Byungtae LeeKAIST 19
Business Simulation and Complexity Theories Business Simulation and Complexity Theories
Seamless Interaction between Virtual (passive) and Real (proactive) Agents
Bottom-Up Approach Treat Agents Individually (by types) Paradigm Shift from Reductionism of 20’th
Century Sciences Completely different from Business Games
as you may know it
SERI, July 26, 2003 2003, Byungtae LeeKAIST 20
Learning by Doing Without cost of mistakes
Real WorldEnvironment
Explore, Experiment, Learn, Analyze, Test Predict Implement, Assess
Behaviormodeling,
demographics,and calibration
Data collection,association,
trends, and parameterestimation
TimeCompression
Near exact replicaof the “real” world
SEAS architectureSupports millions ofArtificial agents
Decision Support Loop
SyntheticEnvironment
The user(s) can seamlessly switch between real and virtual worlds through an intuitive user interface.
SCMERPCRMData
Warehouse
Simulation Loop
SERI, July 26, 2003 2003, Byungtae LeeKAIST 21
SEAS Middl ewar e
ServBotsData Base
Data Objects
SysBots DataBots
SEAS VirtualExecution Environment
SEAS Middl ewar e
ServBotsData Base
Data Objects
SysBots DataBots
SEAS VirtualExecution Environment
CRM and IT enables us to captureCRM and IT enables us to capture
Out channels
DNA’s extracted from data
In channels
Environmental Sensors
Total (202)
1st Brigade
(36)
2nd Brigade
(26)
3rd Brigade
(47)
5th Brigade
(53)
6th Brigade
(40)
Plan to continue education 4.13 4.34 3.69 4.32 4.16 3.97Other employment interests 4.00 4.28 3.58 4.26 3.81 4.00Can't get out if don't like the Army 3.61 3.62 3.76 3.37 3.71 3.64Commitment too long 3.60 3.49 3.96 3.57 3.58 3.54Doesn't allow enough contact with family/friends 3.51 3.57 3.81 3.42 3.44 3.44No personal life in Army 3.47 3.54 4.12 3.26 3.43 3.26Want to stay close to home 3.42 3.44 3.65 3.19 3.46 3.49Do not want to be deployed overseas 3.34 3.40 3.58 3.16 3.27 3.42Other military services more appealing 3.26 3.32 3.72 2.91 3.36 3.17Be behind my civilian peers in career 3.25 3.44 3.50 3.14 3.12 3.24Army pay very low 3.20 3.24 4.04 3.02 3.04 3.00Have financial ability to pay for college 3.15 3.49 3.08 3.24 2.88 3.16Army too dangerous 3.15 3.32 3.38 3.17 3.10 2.87Basic training/boot camp too difficult 3.14 3.09 3.58 2.89 3.11 3.21Army life too difficult 3.12 3.20 3.16 2.91 2.96 3.50Family/friends have negative attitude of Army 2.74 2.63 3.12 2.35 2.71 3.13Army has no role to play in global environment 2.73 2.48 2.96 2.57 3.00 2.61Army conflicts with religious beliefs 2.32 2.23 2.38 2.35 2.23 2.46
= Highest mean score= 2nd highest mean score= 3rd highest mean score
The combination of human decision makers (for depth) with artificially intelligent agents (for breadth) allows unmatched flexibility, realism and detail.The combination of human decision makers (for depth) with artificially intelligent agents (for breadth) allows unmatched flexibility, realism and detail.
SERI, July 26, 2003 2003, Byungtae LeeKAIST 22
전통적 마케팅의 실패전통적 마케팅의 실패
4P: Product, Price, Promotion and Place Product
USP (Unique Selling Points) Copycat Economy
Price Price War
Promotion Battle for Eyeballs
Place No time for Shopping
SERI, July 26, 2003 2003, Byungtae LeeKAIST 23
shopbotshopbot
SERI, July 26, 2003 2003, Byungtae LeeKAIST 24
Posted Price MarketPosted Price Market
SERI, July 26, 2003 2003, Byungtae LeeKAIST 25
정보 비대칭성의 상실정보 비대칭성의 상실
전 보험 비교 견적
역경매 시장
SERI, July 26, 2003 2003, Byungtae LeeKAIST 26
Buyers’ Market: 소비자 권력의 증대Buyers’ Market: 소비자 권력의 증대
SERI, July 26, 2003 2003, Byungtae LeeKAIST 27
안티 사이트안티 사이트
SERI, July 26, 2003 2003, Byungtae LeeKAIST 28
Game of Eyeballs and Ears – 광고에 대한 면역Game of Eyeballs and Ears – 광고에 대한 면역
Other Consumer Messages (all media)
Total Internet Consumer Messages
Commercial and Internet Messages per Day per Person
(US)
20 years ago, 80 percent of a target audience in many countries could be reached with one 30-second, off-peak television spot
Reaching the same audience today often requires between 200 and 300 prime-time TV spots.
440650
2,560
3,000
1985 2000
SERI, July 26, 2003 2003, Byungtae LeeKAIST 29
Where Is Money?Where Is Money?
Decline of Purchasing Prices
0
20
40
60
80
100
120
Maint. CostPur. Cost
Source: HBR,1999Source: HBR,1999
SERI, July 26, 2003 2003, Byungtae LeeKAIST 30
Installed Vs. New PurchaseInstalled Vs. New Purchase
0
20
40
60
80
100
120
OldNew
Old 93.7 95.7 99.3 96.8
New 6.3 4.3 0.7 3.2
Car Train Airline Trackter
SERI, July 26, 2003 2003, Byungtae LeeKAIST 31
(40) (30) (20) (10) 00
20
40
60
80
100
10 20 30 40 50
Revenue change (%)
Customer satisfaction indices
Revenue growth
0 40 80 120 160 2000
20
40
60
80
100
Customer satisfaction indices
Profit
240
Profit
고객만족 수익성고객만족 수익성
0 1 2 3 4 50
20
40
60
80
Customer satisfaction indices100
Revenue
Revenue
SERI, July 26, 2003 2003, Byungtae LeeKAIST 32
75 85 95%
Prudential Property
Liberty Mutual
Aetna Casualty
Farmers Exchange
Allstate
Nationwide Mutual
State Farm
USAA Casualty
Amica
Profitability (combined ratio*)
Customer retention rate
R² = .82
미국 보험 산업 예시
Customer Retention RateCustomer Retention Rate
*Claims and expenses as a percent of premium income
0
50
100
150
200%
SERI, July 26, 2003 2003, Byungtae LeeKAIST 33
0 1 2 3 4 5 6 7-1
0
1
2
3
4
5
6
7
Customer profit pattern
Year
Acquisitioncosts
Base profitNew products
Costimprovements
ReferralsPrice premium
고객당 수익성 추이 예시
Customer RetentionCustomer Retention
SERI, July 26, 2003 2003, Byungtae LeeKAIST 34
0 1 2 3 4 5 6 7-$28.3
$12.4$15.8 $17.5 $18.9 $20.5 $22.3 $24.5
Annual customer profit
Year
Acquisitioncost
Base profit
Revenuegrowth:existingproducts
Revenuegrowth:newproducts
Cost savingsReferrals
Customer payback point
Customer Lifetime Profit : Amazon.comCustomer Lifetime Profit : Amazon.com
Acquisition cost
SERI, July 26, 2003 2003, Byungtae LeeKAIST 35
CRMCRM
다행히 IT 산업의 발전이 은행 서비스를 더욱 발전시켰고 , 은행의 생산성 향상에 크게 … 그러나 은행의 고객층이 천차만별이라는 점을 간과해서는 안 된다 . 즉 인터넷을 사용할 수 있는 고객과 단순히 현금지급기 (ATM) 만 쓸 수 있는 고객 , 아니면 지점을 찾아야 하는 고객 등
데이비드 엘든 (HSBC 회장 , 2002.11.03 조선일보 )
SERI, July 26, 2003 2003, Byungtae LeeKAIST 36
Financial impact of CRMFinancial impact of CRM
Profit Impact of 5% Increase in Rate of Customer Retention
35%
125%
25%
50% 45%35%
0%
20%
40%
60%
80%
100%
120%
140%
Businessbanking
Credit card Creditinsurance
Insurancebrokerage
Industrialdistribution
Softw are
Source: eLoyalty
SERI, July 26, 2003 2003, Byungtae LeeKAIST 37
Progressive Insurance ( 미국 ) GPS/ 위성통신을 통한 보험 가입자의 운행 기록 수집 , 위험
평가 우수 운전자에게 25-50% 보험료 할인
온라인 채널 /CRM 부가가치를 소비자와 공유 많은 조직 , 프로세스의 개선 및 기술 개선 보상 청구 5 년 전에 비해 50% 단축 보상 청구의 57% 는 9 일 이내의 해결
SERI, July 26, 2003 2003, Byungtae LeeKAIST 38
CAPITAL ONE CAPITAL ONE
CRM capabilities CRM offerings
Continuous testing and learning 45,000 tests per year For every product offering For every process change
1,200 CRM 담당직원
미 전체 1/7 가계에 대한 방대한 정보 수집
Innovation to match customers’ changing needs 55% of current offering did not exist 6 months ago 95% did not exist 2 years ago
34백만 고객에게 34백만 상품 제공 Credit card Auto finance Catalogs Mortgage Telecom service (long-distance,
mobile)
For in-bound calls Predict reasons for the call Route the call to the most appropriate
call operator Provide best options for complaint calls Predict cross-sell options
CRM impact
* ?
CAPITAL ONE ( 미국 )*
고객수 1998년 16.7백만에서 2001년 34백만으로 성장
불만고객 50-60% 잔류 결정
57% 신규 고객 1 년 내에 다른 상품 구매 (Up-sale, Cross-Sale)
SERI, July 26, 2003 2003, Byungtae LeeKAIST 39
CRM Scope – Not every CRM is good for youCRM Scope – Not every CRM is good for you
개인화 중심의CRM
개인화 중심의CRM
전략 중심의CRM
전략 중심의CRM
아마존 , 야후의 개인화 중심의 CRM 은고객의 특성에 맞는 차별적인 제품과 서비스를 제공하는 논리를 디자인해야 한다
아마존 , 야후의 개인화 중심의 CRM 은고객의 특성에 맞는 차별적인 제품과 서비스를 제공하는 논리를 디자인해야 한다
고객 접점중심의CRM
고객 접점중심의CRM
•영업사원 중심 CRM – SFA
•서비스 중심의 CRM (CTI 또는 인터넷 중심 ) 은 역시 수십 - 수백억의 비용이 들어 고객 서비스 강화를 목적으로 한다
•영업사원 중심 CRM – SFA
•서비스 중심의 CRM (CTI 또는 인터넷 중심 ) 은 역시 수십 - 수백억의 비용이 들어 고객 서비스 강화를 목적으로 한다
데이터 베이스중심의 CRM
데이터 베이스중심의 CRM
Data warehouse구축은 수십 -수백억의 비용이 든다
Data warehouse구축은 수십 -수백억의 비용이 든다
분석 중심의 CRM
분석 중심의 CRM
Data mining장기적인 관계를 통한Cross-sellingUp-selling 지향
Data mining장기적인 관계를 통한Cross-sellingUp-selling 지향
SERI, July 26, 2003 2003, Byungtae LeeKAIST 40
Best customers
Other customers
Households Annual variable contribution
Fully-costed contribution
(50%)
0%
50%
100%
150%
Not All Customers Are Kings…Not All Customers Are Kings…
SERI, July 26, 2003 2003, Byungtae LeeKAIST 41
Customer PortfolioCustomer Portfolio
Customers: Return and Risk Marketing and Demarketing – on What bases? With what gut?
Low Return High
Lo
w R
isk Hig
h
SERI, July 26, 2003 2003, Byungtae LeeKAIST 42
Best Mix and Match - Very Complex System Problem Best Mix and Match - Very Complex System Problem
지주회사
은행 신용카드 증권
..Service Bank
Product Bank
Sales Bank
High Net Worth
Affluent 고객
Mass Affluent
Mass 고객
Sub-prime Accounts
BranchBranch
ARS ARS
ATM ATM
InternetInternet
Mobile Mobile
TV TV
은행
보험
신용카드
증권
SERI, July 26, 2003 2003, Byungtae LeeKAIST 43
서비스
영업 기회
신규 고객화 및 기존 고객
활성화
마케팅
고객 DB
Customer Creation
Customer Developme
nt
Customer Retentio
n
고객관점 기능관점
고객 정보의 지속적 축적
영업
SERI, July 26, 2003 2003, Byungtae LeeKAIST 44
Demo Demo
From Analytical CRM to Product/Service/Marketing Strategies
Demo
SERI, July 26, 2003 2003, Byungtae LeeKAIST 45
Beyond RepastBeyond Repast
J2EEJ2EE
Biz. Logic Layer (Engine)
Presentation Layer
Persistence Layer
Environment
RDBMSSQL 을 이용한 분석 Tool
분석 문서
시뮬레이션 환경 설정
시뮬레이션 환경 설정 : 기초 데이터
Application Layer
rule
Detector
Effector
Human Agent
Relational Database Management System
input
output
SERI, July 26, 2003 2003, Byungtae LeeKAIST 46
ChallengesChallenges
Something Very New Poor Knowledge Management Causality (Business Model)
Control Explanation
SERI, July 26, 2003 2003, Byungtae LeeKAIST 47
Vision of Next EIS-SAPVision of Next EIS-SAP
Industry 1 Problem Domain 1
….. Problem Domain m
Industry 2
…..
Industry n
Q&AThank YouThank You