Business-to-Business Marketing
Haas School of Business
UC Berkeley
Fall 2008
Week 2
Zsolt Katona
1
Where we stand
•
Week 1
–
–
•
Week 2
–
–
–
•
Introduction to B2B and Industrat
Decision 1
R&D and Market Research in Industrat
Surprise
Decision 2
Week 3
–
–
Pricing Strategies in Industrial Markets
Room and Haas, Signode case discussions
2
Industrat Stock Prices
3
R&D in Industrat
Internal Transactions
Production
Dept.
Finance
Dept.
R&D
Dept.
Manufact.
Costs
Inventory
Holding
Costs
R&D
Expendditure
Sales
Dept.
Sales force
Expenditure
Technical
Dept.
Technical
Support
Commissions
Corporate
Marketing
Dept.
Corporate
Communication
Expenses
Marketing = Profit Center
4
Feasible Ranges of Physical
Characteristics Min - Max
KOREX
1
2
3
4
Resistance
Suspension
Frequency
Density
(W )
(MSc)
(KHz)
(MGC)
LOMEX
1
2
3
4
Convexity
Conductivity
Purity
Max. Energy
(DE)
(MSc)
(%)
(MW)
-
5
Korex Technologies
Max.
S
U
S
P
E
N
S
I
O
N
Min.
Min.
Tech. limit
RESISTANCE
Max.
6
Korex Technologies
Max.
S
U
S
P
E
(MSc)
N
S
I
O
N
Min.
Min.
Tech. limit
RESISTANCE (0)
Max.
7
Technology Research
Gestation Period
Know How
Critical Mass
Infrastructure
New projects
(products)
using a
technology
Minimum number
of years
Minimum annual
investment
Additional
Investment
8
Research
Technology
Cumulative
investment
Years above
minimum investment
Status
Minimum total
investment
Proposed total
investment
Minimum annual
investment
9
Research
Technology
Cumulative invest
Years above min inv
Status
Min total invest
Prop total invest
Min annual invest
1
2
0
0
NO
3351
6702
1117
5500
2
OK
5585
11170
1675
3
4
8000
0
2
0
OK
NO
5585
8936
11170 13404
1675
2234
5
13050
3
OK
11170
16755
2234
10
Development
Prototype = First Development
Project
Name
Technology
Cum Expenditure
Status
Characteristic 1
Characteristic 2
Characteristic 3
Characteristic 4
Base cost
PLIA
5
13050
OK
17
101
43
224
100
11
Research and Development
Product Development
Period T: Project Specification: •
•
•
•
•
Period T+1: Message from
Development:
Project name
Technology
Budget
4 Physical characteristics
Production base cost
• Project status
• Feasibility of base cost
• Additional budget
necessary
12
Production Costs
Production
cost
Base cost specified to
R&D
Cumulative Production
13
Production Costs
Production
(transfer cost)
Shared
Cost
Actual Base Cost
New Base Cost
Specified to R&D
Experience
Transfer
Technology
Experience
Actual Manufacturing
Method
New Manufacturing
Method
Cumulative Production
14
Production Costs
Production
(transfer cost)
Actual Base Cost
New Base Cost
Specified to R&D
Actual Manufacturing
Method
New Manufacturing
Method
Cumulative Production
15
Development Projects
Project name
Modify existing
KIDU
Introduce KIDA
Complete
Modify KIDU &
introduce KIDA
PKI33
Retain base cost
Incomplete
Continue PKI33
(same tech
and specs)
Tighten base cost
Relax base cost
Terminate project
16
Brand Modification
KIDD
KIDD
Automatic payment
to production
department at
transfer cost
(exceptional loss)
KIDD
KIDD
Period T
Product KIDD
Period T + 1
KIDD
Modified KIDD
17
Loans are available
18
Loans
For R&D only,
line of credit,
equal annual payments
interest on outstanding
balance
19
Loan Repayment Schedule
Loan
Length
Interest
0
0
0
1900
5
10
4500
5
10
0
0
0
0
0
0
Total
zero
one
two
three
four
0
0
570
1882
1754
1626
1498
990
0
0
0
0
0
0
0
0
0
0
570
532
494
456
418
0
0
0
0
1350
1260
1170
1080
990
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
five
0
0
0
0
0
0
0
0
0
0
0
six
0
0
0
0
0
0
0
0
0
seven eight nine
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
20
Collaboration
 Negotiations
Only within approved periods
 Outcome
Licensing and/or joint research
 Terms
Royalties: historically 3%, but deregulated now
Negotiated annual minimum royalties
Other fund transfers
 Process
Written contract and approval (arbitration in case of violation)
 Implementation
Compatible decisions entered by both parties
 Risk
Government invalidates contract in case of antitrust action
21
Market Research
Objectives:
Understanding
Markets
Monitoring
Identifying threats
& opportunities
Forecasting
Methodology:
Market Segmentation:
Analysis of
Survey Data
None, Specified or
Statistical Optimum
22
Survey Types
• About Supplier (Studies 1 and 2)
– Awareness and preference for each supplier by
decision maker
– Importance of and ratings on technical,
commercial aspects and reputation
– Ideal Points
• About Products (Studies 3,5 and 7,8)
– Awareness, preference and market share for
each product
– Importance and ratings of product attributes
– Ideal Points
• Buying process (Study 6)
– Who is the decision maker?
• Market demand and forecast (Studies 4,9)
• Competitive Information (Study 16)
23
Perceptual maps
24
Prediction Markets
• 1988 Iowa Electronic Market (IEM)
– A University of Iowa experiment
– Securities traded are linked to outcomes of political elections
(e.g. you get $1 is B. Obama wins the presidential)
– Does better than polls (75% of the time)
• IEM is but one example…
–
–
–
–
Sports
Movies (HSX)
Financial and Economic data
etc.
25
Examples of Prediction Markets
Market
Iowa Electronic
Market
TradeSports
Economic
Derivatives
Status
Run by University of Iowa
For-profit company
Run by Goldman Sachs
and Deutsche Bank
Newsfutures
For-profit company
Foresight Exchange
Nonprofit research group
Hollywood Stock
Exchange
Owned by Cantor
Fitzgerald
Focus
Typical turnover
on an event ($US)
Small-scale election markets
for US elections.
Tens of thousands
(limited to $500
positions)
Trade in a rich set of political
futures, financial contracts,
current events, sports and
entertainment.
Hundreds of
Thousands
Large-scale financial market
trading in the likely outcome
of future economic data
releases.
Hundreds of
Millions
Political, finance, current
events and sports markets.
Also technology and
pharmaceutical futures for
specific clients.
Virtual currency
redeemable for
monthly prizes
Political, financial, current
events, science and
technology events suggested
by clients.
Virtual currency
Success of movies, movie
stars, awards, including a
related set of complex
derivatives and futures.
Data used for market
research.
Virtual currency
26
Predictive performance of the
Hollywood Stock Exchange
27
External validity: Saddam security
and oil prices.
28
Potential corporate applications
• More complex securities
– Security pays $1 for each additional percentage point in vote.
Market price reflects expected proportion of votes earned.
– Security pays according to square of percentage vote. Allows to
calculate market’s confidence in estimated proportion of votes
earned.
– Pay $1 if percentage vote is exactly x, y, z….
– What if a contract is contingent on another event (e.g. contract on
oil price if Saddam is in power vs. one contingent on the opposite.
Difference tells effect of Saddam’s ousting on oil prices.)
• Prediction markets in the enterprise
– Variety of contexts (scheduling, product success, technology
trends)
– Examples: HP, Intel, Siemens, Google, Eli Lilly, Arcelor…
– Information generated is confidential so more incentive to create
the market.
– Will traditional market research disappear then?
29
Surprise
• We will run a prediction market
• There will be 5 securities (one for each
firm)
• The winner security pays 100 points at
the end, the others pay 0
• Winner: the firm that makes the highest
total net marketing contributions in the
last three periods
• “Alternative stock price”
30
Before we go
• faculty.haas.berkeley.edu/zskatona/teaching.html
• Industrat teams
• Decision deadline: 17:00 (set at startup)
31