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Transforming the company
Avoiding the Black Swans
Success Factors and
core beliefs in
Value Assurance
Istanbul, April 2012
Mobily CIO Summit
CONFIDENTIAL AND PROPRIETARY
Any use of this material without specific permission of
McKinsey & Company is strictly prohibited
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Introducing Enrico Benni
▪ Senior Partner – Abu Dhabi
▪ Managing Partner IT Consulting
Middle East – previously
leading IT consulting in China
▪ Leader of the global ERP/Value
Assurance McKinsey practice
▪ Co-Leader of the global
McKinsey IT architecture
practice
▪ Has served CIOs on large
transformations across
sectors, in particular in
Telecom, High Tech and
Logistics
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To strengthen its client service capabilities, McKinsey created the
business technology office
To enhance our value proposition to clients, McKinsey
launched the Business Technology Office (BTO) in
1997 to build knowledge and expertise in technology
and IT-related matters
Since its launch McKinsey BTO has gained extensive
experience in helping (multinational) businesses with
technology related top management issues. The BTO
has completed 3,600+ projects around the world with
over 920 clients
Over the last years, McKinsey BTO has built up a global
presence in 56 offices in 29 countries to serve
companies in an increasingly global economy
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Today’s presentation
Turning research into action:
Core beliefs in Value Assurance
Collaboration of McKinsey and Oxford:
Research findings about success factors
for large-scale IT projects
Managing strategy
and stakeholders
Excelling in core
project management
practices
Mastering technology
and content
1
2 3
4
Building team and
capabilities
McKinsey & Company
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Today’s presentation
Turning research into action:
Core beliefs in Value Assurance
Collaboration of McKinsey and Oxford:
Research findings about success factors
for large-scale IT projects
Managing strategy
and stakeholders
Excelling in core
project management
practices
Mastering technology
and content
1
2 3
4
Building team and
capabilities
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IT projects are now so large and complex
they can bring whole companies down
▪ Lord Chancellor’s
Department
▪ Courts Computer
System
▪ 328% over budget
▪ 167m USD
▪ Canadian fire arms
registry
▪ 37,000% cost
overrun,
IT system ‘only’
160% over budget
▪ Total cost for the
tax payer 834m
USD and mounting
▪ Design finished in
2001 – differences
in development
software
▪ More than 12
months delay to
market; 26% drop
in share price
▪ Resignation of
Noël Forgeard
▪ After failing a
$1.4bn IT
modernisation
▪ Kmart started a
$500mio SCM
project
▪ The combination of
two failed projects
forced Kmart into
bankruptcy
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Cost overruns in the public sector are not new
6
The citizens of Nicomedia, Sir, have spent 3,318,000 sesterces, on an aqueduct; which they abandoned before it was finished and finally demolished.
Then they made a grant of 200,000 sesterces towards another one, but this too was abandoned, so that even after squandering such enormous sums they must still spend more money if they are to have a water supply.
Pliny to Emperor Trajan (AD 110)
Steps must be taken to provide Nicomedia with a water supply, and I am sure you will apply yourself to the task in the right way.
But for goodness sake apply yourself no less to finding out whose fault it is that Nicomedia has wasted so much money up to date.
It may be that people have profited by this starting and abandoning of aqueducts.
Let me know the result of your enquiry.
Trajan's response
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Key Research Question
Is this anecdotal
evidence represen-
tative for IT projects?
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This McKinsey-Oxford collaboration was chosen
“No. 1 Idea To Watch" by HBR (09/11)
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We studied a total of 2,092 projects,
worth EUR 204 billion
Rest
2
US
Europe
40
Private
Sector
35
Public
Sector
65
Stan-
dard
SW 7
Integration
Project
1
Other
12
IT Archi-
tecture
9
IT Infra-
structure 8
Custom
development
72
Office
Information
9 ERP
28
MIS
25
Other 20
Customer
facing 4
Transaction
2
Administration
12
0.01
10
10
5
1 0.10 100 1,000 10,000
Location Sector Project type System type
Actual Project Size (2010 EUR millions), percent
Largest academic database
▪ 2,092 projects and programmes
▪ Average size of EUR 90m (median 1.8m)
▪ Average duration 2.5 years (median 2 yrs)
▪ Total portfolio value of EUR 204bn
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7 questions I always wanted to ask about projects
Are lines-of-code riskier than steel-and-concrete?
What is the value of benefits management?
I
Are private and public sector different? II
Is standard software better than bespoke solutions? III
Should we be afraid of big projects? IV
Should we be afraid of long projects? V
VII
What is the value of experience? VI
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Hypothesis I – Risk of ICT Projects
Engineering
projects are less
risky than ICT – by
a magnitude
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Key finding – Black Swans matter more than averages
in the world of megaprojects
Ø 27%
IT projects
Thin-tailed distribution
Infrastructure projects
1 Thin tails: not more than .7% projects are outliers outside these bounds
0
5
10
15
20
25
30
35
40
45
50
-100 -50 0 50 100 150 200 250 300
Frequency Percent
Cost Overrun Percent
▪ If IT projects had thin tails all1 projects
would end up between
-30% and +48%
▪ In reality 15% IT and 8% infrastructure
projects run out-of-control
▪ IT projects 20 times more likely to run
out-of-control than expected: more than
2300% over-incidence of outliers!!
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Black swans have high cost, schedule and benefit
risks, which are hidden in the fat tails of ICT portfolios Risk comparison, average percent
Outliers
cost overrun
+197 Cost
overrun
+68 Schedule
overrun
All projects
+27
+55
+49 – Benefits
shortfall
Projects with
cost overrun
+70
+60
-1
▪ Even if the average cost overrun is low, risk of cost overruns is high
▪ Black Swans mean very high cost and schedule risks
▪ And all the projects with a downside risk show significant risk
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The commercials The calculus
▪ EUR 10m fixed price
contract
▪ 18 months duration
▪ Costs are equally
distributed over contract
length
▪ 10-30% profit margin
▪ Best case
– 3m profit
– 7m cost
▪ Monthly burn-rate
– Profit: 170 thsd
– Cost: 390 thsd
The impact ▪ 5 months delay wipe out annual profit
▪ 8 months delay wipes out all profits
▪ In the worst case (10% margin) 2 months
eat up all profits
▪ ø55% schedule risk = 18 + 10 months
Schedule risk requires vendors
to respond, e.g., cutting costs
Why are these risks so crucial?
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Hypothesis II – Risk of ICT Projects
Public sector ICT
projects are more
risky than private
sector projects
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0
0.5
1.0
1.5
2.0
-100 -50 0 50 100 150 200 250 300 350 400 450 500
Schedule escalation
Frequency (%)
0
5
10
15
20
25
-100 -50 0 50 100 150 200 250 300 350 400 450 500
Cost escalation
Frequency (%)
Black Swans are as common in the private sector as they
are in the public sector!
Public sector Private sector
▪ Black Swan risk is the same!
▪ Cost overruns and schedule overruns statistically not different
▪ Public sector much larger risk of budget cuts to its projects!
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Hypothesis III – Project Types differ in Risk
Don't do bespoke
software – use tame
technology, ideally
COTS (commercial-
off-the-shelf)!
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Different types of ICT projects have significant differences in performance
Average
High Risk
19%
Custom Development 32%
Standard Software 42%
IT Architecture
0%
27%
IT Infrastructure 2%
Integration Project
71%
26%
20%
18%
43%
26%
75%
45%
50% ()
5%
Project type
Average
cost overrun
Average
schedule overrun
Average bene-fits
shortfall
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Hypothesis IV – The bigger the riskier
Bigger projects are
riskier than smaller
projects
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Surprisingly, smaller projects have higher cost risk variability…
ICT average
ICT projects
Cost overruns Percent
Project Budget EUR millions
750 500 250 2,250 2,000 1,750 1,500 13,750 1,250 1,000 0
-100
0
100
200
300
400
500
600
▪ Very weak linear trend
▪ Bigger budgets don't increase the relative cost overrun
▪ Expected risk in monetary terms grows linearly not exponentially
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Hypothesis V – The longer the riskier
Longer projects are
riskier than shorter
projects
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The longer the project, the higher the expected cost overrun
Cost overrun
Percent of initial budget
Project duration
Months -100
0
100
200
300
400
500
600
0 12 24 36 48 60 72 84 96 108 120 132 144 156 168 180
ICT average
ICT projects
▪ Every additional year increases the
expected cost overrun by 16.8% and
schedule overrun by 4.8%
▪ As project duration lengthens,
the probability of becoming an outlier
increases, esp. for projects > 3 yrs
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Black Swan risk highest for large projects, however expensive
is better than long Probability of Cost Black Swans
10-30
million
20%
L
6%
1-2 years
29%
30-350
million
XL
31%
2-3 years
Cost Black
Swans
Cost Black
Swans
Actual size
Duration
11%
>350
million
XXL
27%
4+ years
▪ Highest risk =
stuck in the middle
▪ Short is better
than small
▪ Expensive better
than long
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Black Swan risk highest for large projects, however expensive
is better than long Probability of Cost Black Swans
5-20
million
9%
L
12%
1-2 years
14%
20-200
million
XL
28%
2-3 years
Cost Black
Swans
Cost Black
Swans
Planned size
Duration
13%
>200
million
XXL
41%
4+ years
▪ Short and small is
best
▪ Expensive better
than long
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Hypothesis VI – We need Masterbuilder
More experienced
project managers are
a key to successfully
managing risks
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Is grey hair an achievement? Risk profile
Work experience
<10 10-14 15+
Cost overrun 16% 1% 32%
Schedule
overrun 2% 15% 61%
Benefits
shortfall -49%
Black Swan
events 0% 0% 19%
▪ Initial hypothesis:
the more work
experience, the
better the project
performance
– Mind over
machine
– Young brains –
new methods
▪ However, we find a
struggle between
"Master builder"
and "Fire fighter"
Ø size (m) 0.9 4.3 141
Ø duration
(months) 9 11 32
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Is grey hair an achievement? Risk profile adjusted for size and duration effects (ANCOVA)
Work experience
<10 10-14 15+
Cost overrun 40% 28% 23%
Schedule
overrun 4% 18% 63%
Benefits
shortfall -48%
Black Swan
events 8% 7% 17%
▪ Initial hypothesis:
the more work
experience, the
better the project
performance
– Mind over
machine
– Young brains –
new methods
▪ However, we find a
struggle between
"Master builder"
and "Fire fighter"
Ø size (m) 0.9 4.3 141
Ø duration
(months) 9 11 32
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Hypothesis VII – Benefits management is key
Lack of benefits
management is the
single most important
deficiency in ICT
project performance
management
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A key challenge to projects is Benefits Management Risk profile
Cost overrun Schedule overrun Black Swans
Benefits not
measured 32% 36% 17% 85%
Benefits
measured -7% 122% 7% 15%
▪ Benefits force projects to think about
output and outcomes
▪ Cost-benefit-based performance
management seems to motivate
managers to trade off schedule for
cost/benefits
▪ With benefits management black swan
risk decreases
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The challenge is
black swans, more
than it is average
overruns
7 answers to re-think megaproject management
Are lines-of-code riskier than
steel-and-concrete?
What is the value of benefits management?
I
Are private and public
sector different?
II
Is standard software better
than bespoke solutions?
III
Should we be afraid
of big projects?
IV
Should we be afraid
of long projects?
V
VII
What is the value
of experience? VI
Knowing output and
outcomes reduce risks
Not on average, but
more Black Swans!
Budget cuts are the
only unique issue!
No – one is late, the
other more expensive!
Short and small are
best, long is worse
than big
Master builders matter
McKinsey & Company
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Today’s presentation
Turning research into action:
Core beliefs in Value Assurance
Collaboration of McKinsey and Oxford:
Research findings about success factors
for large-scale IT projects
Managing strategy
and stakeholders
Excelling in core
project management
practices
Mastering technology
and content
1
2 3
4
Building team and
capabilities
McKinsey & Company
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Risk comparison
1 Cost increase over regular cost
SOURCE: McKinsey Oxford Reference Class Forecasting for IT Projects Study
Root cause analysis identifies 4 key dimensions
that explain most project failures
"Missing focus"
▪ Unclear objectives
▪ Lack of bus. focus
"Content issues"
▪ Shifting requirements
▪ Technical complexity
"Skill issues"
▪ Unaligned team
▪ Lack of skills
"Execution issues"
▪ Unrealistic schedule
▪ No active project
planning
Rough cost overrun disaggregation (percent)
Projects >EUR 10M with cost overrun
+44%
-67%
Cost overrun1
Schedule overrun
Benefits shortfall
+90% 2
1
23
16 18
90
Unexplained
cause
21
11
3
4
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Turning research into action: core beliefs in mega-project management
along 4 dimensions
Based on empirical findings,
successful mega-project delivery builds on 4 pillars
… leading to a
"Value Assurance" framework
organized in 4 building blocks
Delivering value
Mastering
content
Excelling in
project delivery
Building
team &
capabilities
▪ Project focus is "on time, in budget, in scope" and not enough
"in value" (only 15% of projects measure value)
▪ Value focus is essential in all project phases to ensure
alignment with business
1
▪ Mastering and reducing complexity (e.g., by modularizing
ambitious technology efforts) is key to success
▪ Built on solid understanding of technology, masterful design,
focusing on functionality that "makes a difference", ensures
effective solutions for front-line use
2
▪ Only "team of experts" bringing together best internal resources
across organizational boundaries and external specialists can
deliver a transformation
▪ At same time, organizations seek to sustainably improve
internal delivery capabilities, reducing dependency on external
vendors
3
▪ Research shows long projects are more likely to fail –
requirements change, momentum suffers, people rotate over time
▪ Squeezing time out of project schedules and adhering strictly
to schedules is a key to success
4
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▪ Project creates vendor dependency
▪ Project manager is subject-matter
specialist with limited project manage-
ment experience
▪ Project team that's available
▪ Users "accept"/Users are "trained"
From (traditional approach) To (holistic approach)
▪ Unspecified goals
▪ Scope grows over time
▪ Unclear business case
▪ IT-driven project
▪ IT goals ("output")
▪ Realistic, concrete goals
▪ Stable scope
▪ Solid budget, clearly articulated value drivers
▪ Business-driven project
▪ Business goals ("outcome")
▪ Project creates new legacy system
▪ 1000-pages+ design documents
▪ Ivory-tower solutions
▪ Technical migration
▪ Solution contributes to IT strategy
▪ Design excellence where it makes a
difference
▪ Solutions with front-line impact
▪ Full-scale organizational mobilization
▪ Client remains master of own destiny
▪ Project manager is empowered expert or
“Master Builder”
▪ Project team that's capable
▪ Users specify, design, test, coach, etc.
▪ Risks reported
▪ Focus on cost/budget
▪ Administration of project plan
▪ Issues are surprises, long debated
▪ Risks managed
▪ Focus on value delivery
▪ Progress and critical path transparent
▪ Issues identified early, problems solved fast
Delivering value
1
Mastering content
2
Building team & capa-bilities
3
Excelling in project delivery
4
Traditionally
neglected
Achieving a step-change improvement in mega-project delivery
requires a much more holistic approach in all dimensions
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1 Content may depend slightly on project subject (e.g., ERP, Core system replacement, O&O, PMM)
The “Value Assurance” approach combines key capabilities
in the 4 dimensions
Building team &capabilities
2 3
4
1
Deliveringvalue
Masteringcontent 1
Excelling inproject delivery
Objectives Key capabilities
▪ IT architecture, infrastructure1
▪ Functionality design/optimization1 ▪ Quality assurance1 ▪ Migration and roll-out strategy (technology,
organization)1 ▪ Project scoping/scope control1
Address all content
aspects involved in the
project, and ensure
they are addressed in
best possible way
2
▪ Team alignment (e.g., stakeholders, project) ▪ End-to-end-change mgmt. (organization and
mindset) ▪ Capability building (incl. Master Builders)
Address cultural
aspects through
"softer tools"
3
▪ PMO and project set-up ▪ Requirements and change request mgmt. ▪ Masterplan mgmt. incl. critical path ▪ Status reporting ▪ Issues/risk mgmt. ▪ Rollout control and quality gates
Execute project mgmt
processes with rigor
and professionalism
4
Examples follow
▪ Continuous alignment with business strategy ▪ Stakeholder mgmt.
▪ Proactive risk identification and mitigation
▪ Business case mgmt. ▪ Vendor mgmt. (incl. selection, contract
negotiation)
Continuously ensure
aspired value delivery,
involving all
stakeholders
1
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Starting point for proactive risk identification is framework
of 13 typical risk/success factors in 4 categories …
Proactive risk identification and mitigation
VALUE ASSURANCE 360
Overarching goal
Minimize project
risks
Project risk factors
Qualified and motivated project team?
Sustainable mix of internal and external resources?
Experienced project manager?
User involvement to shape solution?
Standardized, proven software technology?
Proven methodologies and tools?
Reliable estimates and plans, appropriate transparency
about project status?
Well-defined business case?
Alignment of major stakeholders?
Minimized, stable project scope?
Robust vendor contracts with clear responsibilities?
Executive support?
Clear objectives?
Insufficient
capabilities?
Unproven
technology?
Non-robust
project mgmt
practices?
Missing/insuf-
ficient strategic
alignment?
Categories
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… where “good” is defined by simple “Golden Rules”
Categories Golden Rules – In a well-run project …
… the project motivation is 1 sentence, the project objectives fit on 1 page
… the business case is still positive if the costs double and the benefits are halved
… there are clear decision rules how to overcome a deadlock between
stakeholders (there is a final decision maker)
… delivery is broken down in modules that do not last longer than a year
… contracts assign end-to-end responsibilities
… there are monthly one-on-ones between project manager and executive
sponsor(s)
… the project manager has done it before
… everyone in the leadership team has a clear leadership role
… leadership is not outsourced
… frontline users are continuously involved
… there are not only green lights in the status reports, but they show a "healthy
level of pain"
… every approach, every tool has been used before
... the underlying technology is not "bleeding edge", but has been proven in
comparable references
Missing/insuf-
ficient strategic
alignment?
Insufficient
capabilities?
Non-robust
project mgmt
practices?
Unproven
technology?
Proactive risk identification and mitigation
VALUE ASSURANCE 360
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Client example – Stopping a too expensive and too long
healthcare system implementation
Client situation
▪ Revamp core Health
Care Mana-gement
System USD 500m
invest
▪ Planned
implementation time
of 8 years
▪ Project at green-light
decision
What was the output?
▪ Project stopped
at green-light
decision
▪ Rightsizing of
project together
with McKinsey
team started
▪ Aligning
duration and
cost of the
project with risks
of HCMS
projects
▪ Project compared to similar projects
▪ Schedule too long for invest and invest
too high – making it a high risk project
▪ Comparable HMS projects invested max.
USD 250m and needed max. 3-4 years
Question
▪ Are these estimates
realistic?
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Performance of IT Mega projects (1/2)
Total Project Spend
($ MM)
300-400 400-500 500-600 600-700
Number of Companies 12 7 6 11
Number of Projects 15 8 6 12
Average spend ($ MM) 352 451 540 647
Average time to
completion (Months)
44 56 49 33
Cost Overrun (%)
Average Overrun (0.9) 25 (1.8) (0.9)
25th percentile (1.8) (1.4) (3.5) (1.8)
75th percentile 200 200 60 26
NOT EXHAUSTIVE
Development type • Supply Chain
management
• Operations
Management e.g. call
center, work force
management etc
• Case management
system for managing
healthcare costs
• GIS systems
• Operations management
(e.g. fleet management,
facility management etc)
• Content management
systems
• Document management
systems
• Emergency management
Spend on services and
development(%)
~80% ~80% 80-90 80-90
Geographies • US • US • US, Germany • US
Total Man hours* (MM) • 3.7 • 4.8 • 5.7 • 6.8
* Back calculated using spend on services, assuming average rate of $80 per hour
Across Industries
Cost over runs are measured from the point when the project got Green light for execution
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Performance of IT Mega projects (2/2)
72
NOT EXHAUSTIVE
* Back calculated using spend on services, assuming average rate of $80 per hour
MaximumAverage
Healthcare N=20
Total Project Spend
($ MM)
~4707216
Average time to
completion (Months)
34 4824
Minimum
Cost over runs ( %) 25 270(1.8)
Man hours (MM) * .76 5.0.17
Cost over runs are measured from the point when the project got Green light for execution
Examples of Projects ▪ Federal Health Information Exchange of the Dept. of VA
▪ Integrated Clinical Database of the U.S. Airforce
▪ HC Claims Management of Dept. of Health
Geographies
represented
Geographies
represented
▪ US
Business Case Management
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5 questions to take away
What risk do I carry around in my IT project
portfolio?
All traffic lights green, on time, in budget – but
how are my most critical projects REALLY doing?
Are my project managers empowered enough –
are they allowed to “refuse take-off”?
As the stakeholder, am I “reported to” – or am I
actively solving problems?
Who is calling the shots – me, the customer,
or the vendor?
