1. technology and computing
2. computer security
3. antivirus and malware

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Manuel Perez, Director of Product Management XVELA
Oscar Pernia, Director of Product Strategy NAVIS
CONNECT.
COLLABORATE.
INNOVATE.
The “truthiness” of KPI
“Truthiness”
Truthiness is the word Stephen Colbert coined to describe the intuitive, not always rational feeling we get that something is just right.
.
.
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Risks of setting a
KPIs suppose to align goals and objective. Primary target is to drive the right behavior.
Wrong, cumbersome, unclear,… KPIs can produce the opposite effect, bringing more harms than benefits.
“Too simple” KPIs can drive the wrong behavior when the KPI leave room for sub‐optimization. There is not a perfect KPI. There are however KPIs thoroughly defined, properly described and well explained across the organization.
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It is inevitable that everyone see their own version of the truth, and some times even make sense that they have different perspectives of the same topic.
However truthiness is unlikely when well defined KPIs are shared.
We might need common KPIs and process measurements across the different parties involved in this business…
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Moves
vessel call
Productivity
3250
Evergreen E 005W
96
2724
Maersk M 1502
60
1817
APL A 004W
90
220
Hanjin H 151N
22
3100
CMA-CGM C 154W
96
• 4750
Berth productivity measurement
OOCL O 001W
112
•
Weighted by the number of moves
Average Productivity: 79.3 mph
Ship Productivity: 92.2 mph
Average Weight Productivity
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Moves
3250
2724
1817
220
3100
4750
vessel call
crane prod
Evergreen E 005W
32
Maersk M 1502
30
APL A 004W
30
Hanjin H 151N
22
CMA-CGM C 154W
32
OOCL O 001W
28
cranes
3
2
3
1
3
4
Total moves: 15,861 moves
Total hours: 184.1 hrs
Avg crane Prod: 29 mph
Avg Prod: 79.3 mph
hours
33.9
45.4
20.2
10.0
32.3
42.4
Productivity
96
60
90
22
96
112

19.7
10.3
10.3
0.3
18.8
33.5
92.9
Partial results
mph
Ship Productivity
Avg Weight Prod
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Moves
3250
2724
1817
220
3100
4750
vessel call
crane prod
Evergreen E 005W
32
Maersk M 1502
30
APL A 004W
30
Hanjin H 151N
22
CMA-CGM C 154W
32
OOCL O 001W
28
cranes
3
2
3
1
3
4
Total moves: 15,861 moves
Total hours: 184.1 hrs
Avg crane Prod: 29 mph
Avg Prod: 79.3 mph
hours
33.9
45.4
20.2
10.0
32.3
42.4
Productivity
96
60
90
22
96
112

19.7
10.3
10.3
0.3
18.8
33.5
92.9
Same Productivity
Same Productivity
mph
Ship Productivity
Avg Weight Prod
Better result
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Moves
3250
2724
1817
220
3100
4750
vessel call
crane prod
Evergreen E 005W
32
Maersk M 1502
30
APL A 004W
30
Hanjin H 151N
22
CMA-CGM C 154W
32
OOCL O 001W
28
cranes
3
2
3
1
3
4
Total moves: 15,861 moves
Total hours: 184.1 hrs
Avg crane Prod: 29 mph
Avg Prod: 79.3 mph
hours
33.9
45.4
20.2
10.0
32.3
42.4
Productivity
96
60
90
22
96
112

19.7
10.3
10.3
0.3
18.8
33.5
92.9
Worse Productivity
Better Productivity
mph
Ship Productivity
Avg Weight Prod
Same result
Same result
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Moves
3250
2724
1817
220
3100
4750
vessel call
crane prod
Evergreen E 005W
32
Maersk M 1502
30
APL A 004W
30
Hanjin H 151N
22
CMA-CGM C 154W
32
OOCL O 001W
28
cranes
3
3
2
1
3
4
Total moves: 15,861 moves
Total hours: 179.1 hrs (+5)
Avg crane Prod: 29 mph
Avg Prod: 79.3 mph
hours Productivity
33.9
96
30.3 ‐15.1 90
30.3 +10.1 60
10.0
22
32.3
96
42.4
112

19.7
15.5
6.9
0.3
18.8
33.5
94.6
Better Productivity
Worse Productivity
mph (+1.7)
Ship Productivity
Avg Weight Prod
Better result
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“The industry is stuck at 25 to 30 moves per crane, per hour. We haven’t had any breakthrough development that can get that to 40 to 50 moves per hour,” Soren Skou
Moves
3250
2724
1817
220
3100
4750
vessel call
crane prod
Evergreen E 005W
32
40
Maersk M 1502
30
40
APL A 004W
30
40
Hanjin H 151N
22
40
CMA-CGM C 154W
32
40
OOCL O 001W
28
40
cranes
3
3
2
1
3
4
Total moves: 15,861 moves
Total hours: 133.5 hrs (+50.6)
Avg crane Prod: 40 mph
Avg Prod: 79.3 mph
hours
33.9
27.1
30.3
22.7
30.3
22.7
10.0
5.5
32.3
25.8
42.4
29.7
Productivity
120
96
120
90
60
80
22
40
120
96
112
160

24.6
20.6
9.2
0.6
23.5
47.9
126.3
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Let’s analyze it… from two backgrounds
 Maritime background. Merchant and Military navy
 17 years in Maersk Line
 Agent, Cargo Execution, Stowage planning, Marine
operations…
 GM & Head of Capacity and Marine operations for
the Caribbean and US Gulf region
 GM & Head of Global Efficiency for Maersk Line
Execution
 GM & Head of Maersk Line in-house IT
developments. COMS solution (3000 users)
 Leaded the IT developments for P3 from the
Maersk Line side (tools being used by the 2M)
 IT/OR background. Always working for Ports, focus on
Technology and Process Optimization:
• Doctor in Industrial Engineering
• MsC in Port Management and Logistic Engineering
 7 years in Port Authority:
• IT focus, wide range of Project types

•
•
•
3 years in Hanjin Shipping (TTIA):
Leading TTIA Project implementation (1.6M TEUs, Semi-Auto)
Strong engagement and involvement in OPS
Responsible for OPS Improvements (+7 gmph, -6 €/move)
 3 years in Navis, Product Management & Product Strategy:
• Optimization and Automation focus on N4 3.0
• Next Level of Innovation focus on N4 3.X
•Operational efficiency focused
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Let’s analyze it… from the two angles
Network cost
Rates & Revenue
Financial viability
Operational Sustainability
Financial Profitability
Terminal ROI plan
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Carrier
How are you doing?
$
$$$$$$
I need very expensive assets
Reduce costs
Strategy
Reduce Bunker consumption
Reduce terminal /port costs
Increase rates
In a “overcapacity scenario”
Increase vessel utilization
Terminal
$$
$$$$$$
(Me too)
Maximize vessel productivity
Gang assignment but Cost / Gang productivity but Cost
Squeeze assets efficiency
CHE performance / Yard occupancy / Machinery stress, breakdowns & maintenance
Minimize OPEX and expenses
Gang productivity / Gang utilization / Energy consumption / Gang composition
Maximize throughput and incomes
Throughput / Dwell time / Competitive tariffs / Berthing management
Fuel‐tons per TEU/day loaded
Main Indicators (KPI)
 Increase utilization
 Reduce Bunker consumption
Operating unit cost
 Reduce Terminal /port costs
Network Optimization
Better schedules / simpler Execution
Contingency costs reduction
 Reduce Bunker consumption
 Reduce Terminal /port costs
 Increase utilization
Vessel Productivity
 Crane productivity  Crane split  Call size / Vessel type
Cost per Move
Operational strategy driven by cost impact on




Gang utilization
Gang productivity
Multi‐lift ratio
Energy consumption
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Carrier
Other KPIs
Schedule Reliability
Terminal Productivity
 Increase utilization
 Reduce Bunker consumption
 Reduce Terminal /port costs
Planner KPIs
Reduce Shifting/restows
 Reduce Bunker consumption
 Reduce Terminal /port costs
Increase crane Split (CI) CI= Crane Intensity
 Reduce Bunker consumption
 Reduce Terminal /port costs
Reduce gap between vessel’s real capacity and Nominal capacity
 Increase utilization
Terminal
Equipment performance





Gang productivity CHE duty cycle
CHE Waiting Time
Exceptions
Productive Moves
Throughput
Operational profitability driven by:
 Berth utilization
 Dwell time / Yard occupancy
 Income per move
Maximize Berth Productivity
 Maximize multi‐lift
 Maximize Gang productivity
Minimize Cost (OPEX) OPEX= Operational Cost
 Maximize Gang productivity
 Maximize productive moves
Keep Operational Balance
 Balance buffers on Berth utilization
 Yard congestion and Dwell time
 Machinery stress and Maintenance
WHAT
SAY ABOUT
 _“We speeded up my vessel to make my window on time and she didn’t berth. You didn’t suggest me to slow her down. We could save 21,000 $.”
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WHAT
SAY ABOUT
 _“You are always late, one day you arrived on time you complained because the vessel didn’t berth. You don’t mind about cost impact due to last‐minute changes”.
 _“My vessel completed operations 3 hours in advance! You didn’t tell me so, neither to my agent. We could save 54,000 $ slowing her down to the next port”.
 _“We are a ‘pit stop’ for you , and that’s fine. You think this is Amazon online store: you come, buy and go. And use our Terminal as a ’24x7 warehouse’ destroying our Dwell Time”.
 _“You altered my crane split and pushed the maximum number of cranes to the night shift when we pay more per move. In return you don’t even want to report move‐count at shift level in the TDR…”  _“We are willing to assign more cranes and to increase berth productivity, of course in our interest. Efficiency but they don’t care about the processes and data quality. Huge investment on IT but we are working as 20 years ago…”.
 _“We had to omit the port because the terminal is congested. We had to call two different ports to discharge the cargo on board and load the exports. We hired feeder services to move the majority of the cargo discharged in the alternative ports to the terminal omitted, your terminal. Shouldn’t you offer me a compensation somehow?”
 _“Your stowage planners works without a strict process, take a decision port by port and don’t care about the impact on next call. They work by intuition and destroy our operational strategy. Good question on compensation, I will pay you every time we will take a decision together, OK?”.
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Terminals are part of a network
Ocean Carrier 1
Ocean Carrier 2
Ocean Carrier 1
Feeder Carrier 2
Feeder Carrier 1
Terminal 2
Terminal 1
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I recognize…
that...
•
•
•
•
that...
We cannot control our data quality because we have obsolete systems and very poor processes.
•
We plan too many vessels without the relevant information needed and we incur in constant last minutes re‐planning.
•
We don’t have optimization tools to drive operations across the whole berth‐vessel‐yard constraints
Sometimes I dont even know that my vessel is • We don’t have tools to react to planning changes, awaiting outside because the communication with our current interaction make process really slow the captains is far from ideal.
and sensible to human mistakes We ignore our own cost and we sometimes dont • We don’t have full operational control, so a know what is the cheapest option, we almost “play demand on extra‐capacity for vessel operations by ear” when taking a cost related decision.
always ends on big loses for us
I have a limited number of KPIs available, not real BI supporting operational decisions: be transparent is costly for us, because data is not meaningful nor useful today
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• Stable productivity
Predictability – What can we expect?
Allow us to plan more efficiently
(long and short term)
• Berthing windows compliance
Allow us to create good schedules focus
on applying the correct buffers and
vessels’ speed fine-tuning
• Actionable visibility
When things go different than plans
we need time to re-plan in the most
efficient manner, and this includes
when the vessel ops are completed
earlier.
• Detailed performance reporting
To create better schedules (proforma),
We need the data that support further
analysis , a constant feed back loop.
This information is the sources of the
KPIs and the future improvements.
 Reduce bunker costs
 Maximize Vessel productivity
 Operating unit cost
 Maximize Throughput
 Network Optimization
 Minimize OPEX
 Increase crane Split (CI)
 Minimize Dwell Time


Terminal Productivity
 Reduce Shifting/restows
Maximize Assets profitability
 Operational ‘sustainability’
• Planning Process / Data Quality
Allow me to provide Vessel productivity.
Accuracy and engagement for planning
decisions
• Arrive on time / Schedule reliability
Allow me to keep my Operational
Strategy. Please care about cascading
effects due to contingencies
• Engagement and Real‐time interaction
We need to take operational decisions
together: contingency management and
the trade-off between productivity and
operational cost must be a joint goal
• Detailed performance reporting
We are find providing visibility, but
operational reality need to be used in a
positive way always
stowage communication
experience creative
terminals future unique
information
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platform transparency Actionable
collectively Utilization pro‐active
collaboration
visibility
shared efficiencies information real‐time
safety goal advance
inspirational
community execution
Network
industry Optimization notifications
technology innovation