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Integrated Energy Strategy: How to capture 20%-30% savings in energy National Energy Efficiency Conference Singapore September 19, 2012 Singapore CONFIDENTIAL AND PROPRIETARY Any use of this material without specific permission of McKinsey & Company is strictly prohibited
Transcript of Integrated Energy Strategy: How to capture 20%-30% … 2012/Presentation Slides... · Integrated...
Integrated Energy Strategy:
How to capture 20%-30%
savings in energy
National Energy Efficiency Conference Singapore
September 19, 2012
Singapore
CONFIDENTIAL AND PROPRIETARY
Any use of this material without specific permission of McKinsey & Company is strictly prohibited
McKinsey & Company
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Industrial companies’ cost base is shifting from ‘variable cost’ to ‘fixed
cost’, largely driven by rising energy prices
50
2510
Fixed
Variable
(energy,
etc)
China 2010
550
90
Western
world 2010
600
75
Western
world 2000
300
50
Clients’ cost structure is shifting dramatically
Example: steel production cost, percent, USD/ton
0
50
100
150
200
250
300
20112 1980 1940 1900
1 Based on arithmetic average of 4 commodity sub-indices of food, non-food agricultural items, metals and energy
2 2011 prices based on average of first eight months of 2011
SOURCE: Grilli and Yang; Pfaffenzeller; World Bank; International Monetary Fund; Organization for Economic Cooperation and Development statistics; UN Food and Agriculture Organization; UN Comtrade; Upstream or downstream? Future value creation in basic industries, BM EMEA Knowledge Day, July 8, 2011; team analysis
A century’s productivity erased in a decade
McKinsey Commodity Price Index (1999–2001=100)1
~10% reduction in energy in China
equals elimination of fixed cost!
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2016 2014 2012 2010 2018 2020
Context of case example: The energy cost is expected to double over the
next 5 years driven largely by rising prices
Power consumption Energy cost
Annual consumption Nominal increase Avg price
2,500 +84 %
2016 Price
increase
900
Volume
growth
300
2010
1,300 Spot 45
19
Energy demand
Fixed contracts
26
21
SOURCE: Disguised client example
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The energy strategy laid out a roadmap to reduce the future cost base by
20-30% through sourcing and efficiency levers
Total
4
Energy sourcing 15-18
Energy efficiency 9-13
24-30
Profitable own
generation
2-4
Eliminations for
double counting
Coordinated energy
efficiency and new
build effort
-6-(-8)
Percent of cost base
SOURCE: Disguised client example
1 Identify and analyze technical
energy improvement
opportunities
2 ”De-mystify” the energy
consumption for operators by
introducing relevant KPIs
3 Introduce energy losses into
performance management
dialogue and benchmark sites
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A comprehensive approach covering technical, management and people
systems is required for successful execution of energy strategy
The technical processes, decision support
tools, systems and resources that create
value
Technical system
The formal performance management tools
and systems supported by the right
organization structure to drive results
Management system
The right people with the right skills,
mindsets, behaviors and ownership, both
individually and collectively
People system
McKinsey transformation approach
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Energy was measured and managed in a rather rudimentary way
SOURCE: Disguised client example
DISGUISED CLIENT EXAMPLE
50
60
70
80
90
100
0 20 40 60 80 100 120
Mätpunkt (timvis uppföljning)
En
erg
ifö
rbru
kn
ing
(k
Wh
/to
n)
Energiutfall
Specific energy consumption
kWh/tonnes
Hourly data points
Tonnes/hour
EXAMPLE WEEK
IN DECEMBER
Specific energy consumption
kWh/tonnes
Production
Tonnes/hour
0
50
100
150
200
250
300
350
400
450
500
0 100 200 300 400 500
Produktionstakt (ton pellets / timme)
Ener
gifö
rbru
knin
g (k
Wh
/to
n) Energiutfall 2010
Typical starting point: Time series provide limited
understanding as energy consumption depend
strongly on, e.g., production level
Best practice: Analysis of energy intensity vs main
intensity drivers, e.g., production level, to enable
appropriate target setting w/ dynamic energy targets
ENERGY PER
HOUR 2010
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We have developed an approach analogous to OEE
Actual
output
Quality
Utilization
Availability
Maximum
output
Theoretical
limit
Technical
losses
Planning
losses
Operational
losses
Actual
resource
efficiency
OEE - Established
productivity metric
Percent
New Energy Loss metric
Percent
▪ Comparable across operations
▪ Directly indicates point to root cause and levers
▪ Performance metric cascades additively
OEE Energy
losses
▪ Efficiency of
equipment (e.g.,
motors, pumps)
▪ Maintenance
▪ Variation in
production flow
▪ Production
speed
▪ Operators
capabilities
▪ Quality of SOPs
▪ Technology in
the truck fleet
▪ Maintenance
practices
▪ Route and flow
planning
▪ Dispatch
optimization
▪ Driver behavior
▪ Support
functions (e.g.,
cruise control)
Process
industry Logistics
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A system of KPIs for energy can be designed fully analogously
with the ‘OEE’ concept for manufacturing processes
Example – energy loss curve for a kiln
kWh/ton
1
2
EXAMPLE
SOURCE: Disguised client example
Hourly data point
Best performance
current technology
3
Best performance
with BAT
0
20
40
60
80
100
120
140
160
180
Production Ton per hour
Definition of losses
Indexed (Percent)
1
2
3
43
18
10
29
100
Operational
losses
Actual
intensity
Best achievable
performance
Technical
losses
Planning
losses
Measuring energy losses allows:
▪ Action oriented synthesis of performance
▪ Additive cascading KPIs
▪ Comparability across business units
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In this particular example, energy consumption was reduced by 15% in
just a few weeks by empowering the operators Disguised case example
10795
84 85 85 86 82 81
W47 W45 W46 W51 W50 W49 W52 W48
7
14
W52 W51 W50 W49 W48 W47 W46 W45
6
5
1 0 1 0 1 0 1
1 0 0 0 0
Operational losses
Load losses
-16%
Weekly energy consumption
kWh/ton, 2011 Target Introduction
of KPIs
Weekly energy losses
kWh/ton, 2011
Introduction of KPIs create new
transparency on losses
Reduction of losses
drive improvement
Key operational changes include
▪ Introduction of losses into morning meeting reports
▪ Improved capacity planning across value chain
▪ SOPs updated to include e.g., lower temperature
settings, fewer burners running, lower fan pressures
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The energy strategy laid out a roadmap to reduce the future cost base by
20-30% through sourcing and efficiency levers
Energy sourcing 15-18
Energy efficiency 9-13
Total 24-30
Eliminations for
double counting -6-(-8)
Coordinated energy
efficiency and new
build effort
2-4
Profitable own
generation 4
Percent of cost base
SOURCE: Disguised client example
1 Create transparency of value
creation opportunities through
contracting
2 Make a fact-based market
model
3 Thoroughly prepare for
supplier negotiations
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Three key elements of an integrated energy-sourcing approach
Source: McKinsey
1. Create transparency of
value creation
2. Make a fact-based market
model
3. Thoroughly prepare for
supplier negotiations
▪ Establish consumption
baseline and current
contractual conditions
▪ Map and quantify demand
side flexibilities
▪ Assess efficiency
opportunities
▪ Build a “cost curve” for the
utility market
▪ Map exposure and share of
wallet for each supplier
▪ Establish economics of
adding new capacity (own
generation)
▪ Architect decision tree for
contractual setup to enable
tactical direction changes
▪ Sequence supplier
interactions to maximize
chances for “best outcome”
▪ Follow prepared process
with tailored agenda for
each supplier
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Value at stake for utilities
Ensuring a high demand in the Nordpool electricity market creates
tremendous value for utilities
Base load price
0 10 000 20 000 30 000 40 000 50 000
200
50
Nordpool Marginal Cost curve 2025 – Central scenario EUR/MWh
60 000 Average available capacity GW
0
Peak price
100
150
Average price
Source: McKinsey analysis, Middle case Practice scenario runs
Note: Nordpool includes Norway, Sweden, Denmark and Finland
Operating
interval
▪ Can SMT influence the supply/demand balance to reach the low price level?
▪ Is there an opportunity to create a structural disconnect between industry
players and the broader spot market through smart negotiations?
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A Total Cost of Ownership approach supports maximum potential savings
with negotiation related tactics offering highest value-add
SOURCE: McKinsey Purchasing practice
Transport Warehousing
Innovation level
Delivery errors
Order mgmt
# of
SKUs
Warranties
Features
Quality
Time to delivery
Administration
Purchase price
Specifications
Total Cost of Ownership (TCO)
Example levers (not all levers valid in all cases) Savings (%)
Supplier
management
1 i. Outsmart suppliers – Know what drives current/potential
suppliers and create a viable alternative/threat, e.g., Statoil,
EON, RWE
ii. Consolidate spend – reduce supplier fragmentation to capture
volume discounts wherever possible
iii. Utilize the market – Consider moving from full service
contracts to traded assets, either with outside support or
building an in-house trading arm
iv. Become a player - Develop own energy related assets
1 - 5
1 - 5
5 - 10
5 - 10
Demand
management
2 i. Optimize demand flexibility –Maximize load-shift to off-peak
power and gas demand and ensure full optimization of buffers
ii. Improve technical system – Ensure best available technology
and technical solution
iii. Operational management – Continuous improvement practices
and improved mindset & behaviour
2 - 5
5 - 10
Process
management
3 i. Reduce maverick spend – ensure compliance with preferred
vendors and demand management policies
ii. Track savings capture – implement tracking tools and
reporting to ensure savings flow to the bottom-line
iii. Manage payables – optimize payment cycle to optimize
reduction in unit prices vs. carrying cost
TBD
5 - 10
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The energy strategy laid out a roadmap to reduce the future cost base by
20-30% through sourcing and efficiency levers
4
Energy sourcing 15-18
Profitable own
generation
9-13 Energy efficiency
Coordinated energy
efficiency and new
build effort
-6-(-8) Eliminations for
double counting
2-4
24-30 Total
Percent of cost base
SOURCE: Disguised client example
1 Identify flexibility
opportunities and match with
intermittency of supply
2 Model cost distributions
instead of point estimates of
total cost of energy
3 Review specific conditions in
detail for investment, don’t
rely on ‘typical cost estimates’
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Almost 50% of energy use was not critical for the core processes
48
16
45
85
176
234
294
310
330
442
26
119
296
5
12
441
Locos
17 Total 2.440 1.982
Other
Surface area
Conveyors
Winders
Winches
Fridges
Fans
Plant
Pumps
Loaders
Leakages
Rock drills
Surface vehicles
LHDs Compressed Air
(electricity)
Electricity (less air)
Fuel
SOURCE: Client example; On-site diagnostic
Non-core
Baseline breakdown for an underground mining operation
TJ p.a.
Share of electricity use
Percent
37
23
40
Core
Non-core
23
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Simulations suggests that wind in many cases could become an
attractive alternative to CCGT
SOURCE: Energy Information Administration; Annual Energy Outlook 2011, December 2010, DOE/EIA-0383(2010);
Wikipedia; team analysis
Probability distribution of LCE for plants coming online by 2016; USD (2009) per MegaWattHour
INDICATIVE
Wind has a wider spread
due to high uncertainty of
capacity and capital costs
CCGT has a fat
high tail due to
potential price
spike in gas prices
Key assumptions: Capacity factor (Wind 34% +10%, -5%) (CCGT 87%, +/- 2%); Capital cost (Wind 83.9 USD +5%, -33%), (CCGT 17.5 USD +/-5%);
Variable O&M (e.g., fuel price) (Wind 0 N/A), (CCGT 45.6 USD, +50%, -20%)
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Eliminations for
double counting
Energy sourcing
Profitable own
generation
Total
Energy efficiency
Coordinated energy
efficiency and new
build effort
16
Questions
Percent of cost base
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APPENDIX
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We help our clients achieve a step-change in sophistication and mindset
… To From …
▪ Clearly defined loss categories
with associated operational KPIs
▪ Well defined breakdowns of
losses into actionable, quantified,
improvement levers
▪ No clear view of underlying
drivers
▪ Low understanding of root
causes
Understand
▪ Loss categories cascaded to
all levels
▪ Integrated performance
discussions on energy and
operational KPIs
▪ Energy metrics not cascaded to
shop floor
▪ Energy consumption drivers not
measured / followed up
Measure
▪ External and internal benchmark
on all loss categories
▪ Targets informed by stringent
analysis
▪ Targets on all energy losses
▪ Energy performance impossible
to compare
▪ Targets set arbitrarily
▪ Improvements only target
technical (capex) solutions
Set targets
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Starting point: Tracking of energy consumption is measured but with
limited ability to explain variation in intensity
50
60
70
80
90
100
0 20 40 60 80 100 120
Mätpunkt (timvis uppföljning)
En
erg
ifö
rbru
kn
ing
(k
Wh
/to
n)
Energiutfall
Specific energy consumption
kWh/ton
Hourly data points
Specific energy consumption; kWh per ton
EXAMPLE WEEK
IN DECEMBER
SOURCE: Disguised client example
±20% from
average
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However, sorting of the data indicates a clear connection between energy
consumption and load
Specific energy consumption
kWh/ton
Throughput
Ton/hour
0
50
100
150
200
250
300
350
400
450
500
0 100 200 300 400 500
Produktionstakt (ton pellets / timme)
Ener
gifö
rbru
knin
g (k
Wh
/to
n) Energiutfall 2010
SOURCE: Disguised client example
Energy load curve; kWh per ton; 2010
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The energy loss concept is applicable and relevant across industries
(examples)
SOURCE: McKinsey
Technical
losses 3
Planning
losses 2
Operational
losses 1
Process industry
▪ Efficiency of equipment
(motors, pumps, etc)
▪ System setup
▪ Maintenance practices
▪ Variation in production flow
▪ Variability of process
▪ The operators’ ability to run
the process efficiently
▪ Quality of SOPs
Logistics
▪ Technology in the truck fleet
▪ Maintenance practices
▪ Route and flow planning
▪ Dispatch optimization
▪ Driver behavior
▪ Support functions (cruise
control, etc)
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Fast reduction of energy usage possible beyond the “standard”
technical levers
-16 %
Weekly energy consumption
kWh/ton, 2011
Weekly energy losses
kWh/ton, 2011
w45 w46 w47 w48 w49 w50 w51 w52
w45 w46 w47 w48 w49 w50 w51 w52
Planning loss Operational
loss
Target
Immediate reduction of >15% achieved
Key operational changes include
▪ Improved capacity planning across value chain
▪ SOPs updated to include e.g., lower temperature settings,
fewer burners running, lower fan pressures
Introduction of KPIs create
new transparency on losses
Reduction of losses
drive improvement
Significant shift in mind-set of facility
From… …to
▪ Considering Energy
to be non-
comparable
▪ Poor understanding
of root causes and
drivers
▪ Managing only on
highest level kWh/t
for each unit
▪ No improvement or
performance targets
and a loosely
managed capex
portfolio
▪ Benchmarking
performance across
production lines
▪ Direct transparency
of root causes from
clear KPIs
▪ Cascades KPIs to
each level in
company
▪ Specific targets
beyond technical
levers and a robust
portfolio management
process
SOURCE: Client Case Example
