Technology Management
Vasos Panagiotopoulos
Objectives
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How
to manage technology in business
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Will
learn all aspects of management as applied to technology
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For
scientists/engineers as well as managers/financiers to learn how to deal with
technology in business.
–
Team
up with someone who complements not emulates your background
Technology Management
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Change
the rules
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Sometimes
unexpected results
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Risk
& Uncertainty
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Need
for integrated coordination
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Need
for combinatorial diversity
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Complexity
(ie RFPs, matrix
management..)
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disempowering
–
arbitraged,
not obeyed
Technology
Management
IS
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Minimising
steps for robotic assembly then making it even cheaper by hand.
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Designing
drug molecules then making them.
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Using
mammalian cultures instead of just fermentation.
ISN’T
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Replacing
typewriter with a PC, without changing work habits.
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Putting
the same forms on a computer screen.
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Cross-testing
every possible resulting molecule the way you looked for new antibiotics
Groupthink
doesn’t question dominant
function
[Arthur Rock HBR Nov 1987]
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Big Firm : Finance
dominates
–
late
PLC mentality (cost cutting)
–
ignores paradigm
shifts
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Mid Firm: Marketing
Dominates
–
Emphasis
on incr. sales
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Ignores
scale-up, inventory, dim’g returns
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Small Firm: Tek
Dominates
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Thinks
biz skills unintellectual
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Ignores
timing of payables and inventory
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Emphasis
on discovery
Industry Structure
Product vs Process
Research & Design
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Freeze design as late
as possible
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Include order-winning
goals early in process & rewards
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Develop concepts,
processes, platforms and product families before developing products (ie Intel 80x86).
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Speeding a strategic product to market will only accelerate commoditisation
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Scale-up
capability before demand builds
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Improving processes keeps your competitive advantage.
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Knowing
when to stop & redesign process model all over again
Order Winner/Qualifier
Decision Modeling
(Interorganisational)
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Tek Sales or Licensing
-- same method
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Tune perfrmc measures
to customers & strategy
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Search
the decision tree & the org chart
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Relationship or
Attribute selling?
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Relationship might be
heuristic abbrevn of attributes
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Who REALLY decides/influences/approves/uses?
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Is it price, quality,
time, or some hidden agenda?
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Central buying or tek
decentalisation
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Stage
of budget/procure/design cycle, gating, benchmarking
cf HBS-9-582-117
,9-489-084
Chosing Financing Vehicles
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M&A: get quickly, might lose people
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Licence: internal usability/fit
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JV: share, learn but conflicts
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VC: access but entrepereneurial
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Option: (warrant): unproven, modest risk
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Grant:
expand R&D, poor
incentive
The Licensing Deal
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Research Presentation...........3
Months
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Deal
Structuring..................1 Week
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Deal
Pricing.........................1 Month
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Due
Dilligence.....................3 Months
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Termsheet/Ltr
Intent............2 Weeks
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Development
Visit...............1 Month
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Corporate
Approval..............2 Weeks
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Legal
Negotiation..................2 Months
Typical Royalties & Strategies
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25%
of Profits or 5% of Sales
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1-4%
of Sales: Semiconductors, Chemicals (Chem per kg, too)
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5-15% of Sales: Spec Chem, Drugs, Med Devices
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If
you publish, you perish (novelty, prior art)
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Maybe
the guy in Sweden wants the Korean to make it but would get billed double royalties. Allow collab betw
your licensees.
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All
JVs to learn.. are all temporary
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License
the demo in case a rejected vendor takes it to your competitors.
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Cash
flow valuatn:(mkt shar change,royalty relief, resid income,cost savngs)
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DEFINE:
Strategic product identity criteria, royalty base, non cash consideration, income
exemptions (tax, ship, commiss), min perf rqmt for licensee, triggering &
terminating events, derivative products tol modfcns, field of use, need to
know, inspxn of records, tol currency risk, tol sales-rel disclosures,
indemnification for breach
Hi Tek Finance
(for example)
uBeta = 3 software,
7 biotek, not 1
uP:E= 40 not 12
ur= 20% not 5%
beta(x)=covar(x,market)/var(market)
Venture Capital Method
And Overvaluation in the “New” Economy
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INTEREST= REAL (4%=marg prodxvty
capital)+RISK+INFLATION
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= RISKFREE (V LONG T 4%)+BETA*RISKPREM (V
LONG T 4-6%)
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=
([1,1.5]+beta)*4%
(Cash flow, Value Added, Liquidity and risk make capital more
costly in early ventures)
Finding the right variables or proxies is rarely done right. Which
rate? Which growth? (Mystical obfuscation of no dividend hi-tek and tax
effects: Miller Modigliani JB 1961; Farrar Selvin NTJ 1967; Brennan NJT 1970;
Miller Scholes JFE 1978. High future expected growth rates might create bubbles
unanchored by actual dividends.)
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P:E=(1/(r-g)) =NPV([ONES],-4%(1+beta), neg=> forward
looking
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=(1-growth/(ROI(1+beta))/(WACC-growth))
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=(ROE-DivddGro)/(DisctRt-DivddGro)/ROE
HBS VC Method 9-288-006
p12 footnote 5; HBS Valn Models
9-281-067 p5; Copeland, Valuation, Wiley, 1990 p79
Options Pricing
(Contingent Claims Analysis)
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Hi r
diminishes NPV input from distant earnings
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Discounted
Binomial ProbabilisticDecision Tree
–
matches
milestone structure common in tek xfr
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Merck
& J&J use Options for R&D budgets
(Lewent HBR 2/94; HBS Conting Clms
9-286-114, Trigeorgis, Real Options, MIT.
Merck worked
but not J&J because of trust – managers didn’t arbitrage inputs)
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Crudely with Black-Scholes
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S=PV(proj
fin val); X=Launch Cost; t=time to launc
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r=WACC
for proj; Dividend Yeild = 0
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sigma=est
from pul-trad compar proje (subtract for attrbn)
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Russ
Parr of AUS says can’t measure Excercise price
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Volatility
also hard to Guage
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Complexity is
disempowering
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Look
good if suggest but not if implement
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Hire
an expert to do it; for strategic initiatives only
Hi Tek Proj Management
Intellectual-Process PERT/CPM
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Teks
are lousy estimators of cost and time
–
they
simplify in order to think thru
F
good
for tek
F
lousy
for biz
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rough
fudge is 2.3 times their estimate
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Gurus
do 80% of work for team
–
gurus overestimate not
underestimate
–
never
hesitate to grant gurus overtime
–
go
out of your way to keep them for life
Tek Life Cycle
Sales=a*tanh(b*t)+c
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Idea, plan, identify customers
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Prove
concept, feasibility, id enabling tek
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Design,
protoype, patent
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Validation,
test
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Scaleup, commercialise
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Build
up market share
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Maintenance, Creative destructn/substitn
Pr Nelson Fraiman’s
17 Step Tek Change
(Columbia B9811x95,8827x96)
INFORMATION TECHNOLOGY
u Info is dear, data is cheap
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Longterm
firm-wide intercompatibility
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Vendor
reliability or source code in escrow
u INVARIANT:1 man-hr per line of code (fully debugged, documented,tested,
maintained)
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Dominant
design (microchannel vs AT)
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Other
issues: data-flow, work-flow, requirements, prototype, recovery, distrib contention/integrity..
Regulatory Effects
eg Drug Discovery & Approval $2.5 BN
Dollars below are minimal prepartnering budgets,
valuation reward
Difference is because failures aren’t counted and attributed
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Discovery
(5yrs) (10,000 compounds;
Screening leads, rational synthesis)
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Preclin (lab & animal, pharmacology,
toxicology) (6.5 yrs) (250 lead candidates) $.6MM
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IND
(Investig New Drug) applxn; Corp IND vs Physician’s IND
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GMP
(Good Mfgg Proc) pilot plant built & subseq scale-up
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Phase
I (25 non-ill voltrs for
safety & dosage) (1.5yr) (80%
of 5 candidates pass) $.7MM, $25MM
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Phase
II (200 vol patients for
efficacy & side-effects) (2yrs)
(30% pass) 1.4 MM,$75MM
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Phase
III (2500 vol patients to mon
long-t rxn) (3.5 yrs) (80% pass) $7MM,$250MM
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NDA
(New Drug Application, 100,ooo+
pages!)
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FDA
Review & Approval $.1MM
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Post-Marketing
& Phase IV (1.5yr)
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Orphan
Drug - fewer than 200k potl pt 7yr exclusivity
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Dx is
right only on third try, fouls up trials, cf openclinical.org
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Adaptive
Max Likelihood trials
Where to get more information
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These
Slides at
biostrategist.com/BzTekMgt.pdf
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Innovation
Management Seminar
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IRI/RTM
1550 M NW #100 WDC 20005-1708
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Samani Marions Panyaught Consultancy