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PRIME 1413 June 2019

Feedback from PRIMEKPI’s and Benchmarking Subgroup

2

AGENDA

• Annual PRIME KPIs Report

• Punctuality – Deep Dive and Thematic Report

• KPI & Benchmarking Business Process for 2019/20

3

The season 2018/19 is almost closed and all activities were grouped in 5 main tasks

15 participants contributed to this report -7 new members have joined PRIME’s KPI

benchmarking subgroup

4

Participants in PRIME KPI Report New subgroup members in transition phase PRIME members

Observers:

The KPIs presented in this report include 12 high level industry and 32 benchmarking KPIs

across six dimensions

6

Compared to previous years there is a remarkable increase in data provision for

high level and benchmarking KPIs

Average Punctuality for Passengers has been stable between 2012 and 2017

7

KPI 28

91,3

90,9

92,6

92,1

91,5

90,0

90,5

91,0

91,5

92,0

92,5

93,0

93,5

94,0

94,5

95,0

2012 2013 2014 2015 2016 2017

91,4

Passenger trains punctuality

% of trains• Bane NOR

• Finnish Transport Infrastructure Agency

• Infrabel

• Infraestruturas de Portugal S.A.

• Latvijas dzelzceļš

• PKP PLK

• ProRail

• RFI

• SNCF Réseau

• Trafikverket

Average Punctuality for Freight has been decreasing since 2012

8

Freight trains punctuality

% of trains

KPI 29

• Bane NOR


• Infrabel



• PKP PLK

• ProRail

• SNCF Réseau

• Trafikverket

76,4

72,5 72,672,2

70,9

70

71

72

73

74

75

76

77

78

79

80

2012 2013 2014 2015 2016 2017

72,8

After four years of decrease, the number of serious injuries and fatalities increased in

2017

9

Persons seriously injured and killed

Number per million train-km

KPI 8

• Adif

• Bane NOR


• Infrabel



• Network Rail

• PKP PLK

• ProRail

• RFI

• SBB

• SNCF Réseau

• Trafikverket

0,520,51

0,40

0,43

0,35

0,40

0,45

0,50

0,55

2012 2013 2014 2015 2016 2017

0,43

0,38

Average assets failures have been decreasing since 2014

10

Assets failures in relation to network size

number per thousand main track-km

KPI 51

730,7724,6 723,4

709,0

600

650

700

750

2012 2013 2014 2015 2016 2017

678,9

658,3

• Bane NOR


• PKP PLK

• ProRail

• SNCF Réseau

• Trafikverket

After 2 years of increasing OPEX, costs have been decreasing since 2015

11

OPEX – operational expenditures in relation to network size

Euro per main track-km

KPI 60

• Adif

• Bane NOR

• Infrabel



• Network Rail

• PKP PLK

• ProRail

• RFI

• SNCF Réseau

• Trafikverket

85.418

85.345

89.156

90.04989.371

80.000

81.000

82.000

83.000

84.000

85.000

86.000

87.000

88.000

89.000

90.000

91.000

2012 2013 2014 2015 2016 2017

87.590

Overall, investment level have been decreasing over last 6 years

12

CAPEX – capital expenditures in relation to network size


KPI 66

• Adif

• Bane NOR

• Infrabel



• Network Rail

• ProRail

• RFI

• SNCF Réseau

• Trafikverket

142.408140.211

120.092

110.000

115.000

120.000

125.000

130.000

135.000

140.000

145.000

150.000

2012 2013 2014 2015 2016 2017

139.240136.754

123.455

TAC revenues have a tendency to increase over the last 6 years

13

TAC revenue in relation to network size


KPI 87

• Adif

• Bane NOR


• Infrabel


• Network Rail

• PKP PLK

• ProRail

• RFI

• Trafikverket

36.831

34.859

39.124

30.000

31.000

32.000

33.000

34.000

35.000

36.000

37.000

38.000

39.000

40.000

2012 2013 2014 2015 2016 2017

33.83634.566

35.416

Further analysis should account for underlying root causes and identify

opportunities for improvement• In order to improve safety performance it would be valuable to investigate

the root causes and the programmes that IMs initiated to mitigate them

• Further work is required by the IMs to collect data according to the PRIME definition in order to make punctuality and delays more comparable across the peer group, anyway results are already satisfactory.

• Improving Asset Condition KPIs is one of major technical challenges in current benchmarking.

• Still further work is required by IMs to collect data on possessions, speed restrictions and its impact on train operations.

• Different operational conditions need to be taken into account when identifying financial good practices.

• The utilisation of European railway infrastructure varies significantly, even at national level, and a drill-down into utilisation density in different segments would be valuable for benchmarking purposes.

15

AGENDA




The analysis on punctuality is divided into five sections

16

Overview

Targets and punctuality achieved

Influencing factors and

measurement complexity

Infrastructure related root causes

Infrastructure managers’ initiatives

Punctuality in rail freight

88 %

90 %

92 %

94 %

96 %

98 %

100 %

20172012 2013 20152014 2016

IPFTIA

SBBInfrabel

LG

LDZ ProRail

RFIPKP PLK SNCF R.

TRVNR

Average

Adif

40 %

45 %

50 %

55 %

60 %

65 %

70 %

75 %

80 %

85 %

90 %

85 % 90 % 95 % 100 %

PKP PLK

ProRail

Infrabel

Adif

Passenger train punctuality 2017

Cu

sto

mer

satisfa

ction

EU

su

rvey

LDZ

FTIA

IP

RFI

SNCF R.

TRV

0 %

10 %

20 %

30 %

40 %

50 %

60 %

70 %

80 %

90 %

100 %

Ad

if

LD

Z

FT

IA

Infr

ab

el

IP

SN

CF

R.

LG

PK

P P

LK

NR

Pro

Rail

RF

I1)

SB

B

TR

V

Signalling Telecommunication StructuresPower supply Track Other infrastructure Unassigned asset failures

IM Initia

tiv

e

An

aly

sis

Co

nd

itio

n

mo

nito

rin

g

Failu

re

man

ag

em

en

t

Incen

tiv

es

Inv

estm

en

t

Netw

ork

co

mp

lexit

y

Op

era

tio

ns

Pla

nn

ing

/ t

ime

tab

ling

Ro

les a

nd

resp

on

sib

ilit

ies

Syste

m a

pp

roach

Oth

ers

LDZ Regulations about the performance scheme

basic principles (the value of delays).

LG Getting access to our statistical database so

we can make queries and reports, to do more

accurate reporting

NR NR commenced a process of devolving

accountability to the geographic routes

Introduced concepts such as Intelligent

Infrastructure and Remote Condition

Monitoring that alert infrastructure maintainers

to problems before they cause delay impact

Senior Incident Managers and Route

Operating Centres (ROCs) provide enhanced

spans of control across the network

88 %

90 %

92 %

94 %

96 %

98 %

100 %

20172012 2013 20152014 2016

IPFTIA

SBBInfrabel

LG

LDZ ProRail

RFIPKP PLK SNCF R.

TRVNR

Average

Adif

This section provides developments of targets and

actual levels of punctuality achieved over time and

explores the practices of target setting.

Selected factors forming the concept of measurement

are explained. The level of punctuality achieved is

seen as a result of a complex environment.

Various time series demonstrate the infrastructure

managers trends in technical failures, the delay

minutes associated and the time to repair.

An overview is provided on infrastructure managers’

initiatives to improve performance. They are described

in detail and complemented by three presentations.

The section includes actual and target values for rail

freight. Additional information has been provided by

Rail Net Europe.

Two out of six infrastructure managers usually reach their overall target level or

perform betterPassenger trains punctuality – actuals compared to targets for all services

% of trains

• The graph illustrates the difference between

the actual and the targeted levels of

punctuality

• A negative value indicates that the

infrastructure manager has not reached the

target value

• The range by which infrastructure managers

miss target values is approximately +/- 5% -

with one outlier and some fluctuation over the

years

-6 %

-5 %

-4 %

-3 %

-2 %

-1 %

0 %

1 %

2 %

3 %

4 %

201620132012 2014 2015 2017

LG

Adif1)

RFI1)FTIA

Infrabel

IP PKP PLK

ProRailNR1)LDZ SBB

SNCF R.

TRV

Source: PRIME punctuality questionnaires from IMs to civity & PRIME KPI data as per 19/02/2019

1) Aggregated as weighted average of Passenger trains punctuality compared to targets for long-distance, regional and commuter

Over the years average punctuality in rail freight has declined

Freight trains punctuality – actual values

% of trains

• Punctuality in rail freight has been calculated

on the basis of trains operated and the number

of trains on time in this category

• Values are based on the thresholds defined by

each infrastructure manager

• Hence, the analysis is useful to show individual

trends but not to compare data between IMs

• Several infrastructure managers faced a

decrease of punctuality

40 %

45 %

50 %

55 %

60 %

65 %

70 %

75 %

80 %

85 %

90 %

95 %

20142012 2013 2015 2016 2017

TRV

PKP PLK

Infrabel

FTIA IP

ProRailLDZ

RFI

NR

LG

Adif

SNCF R.

SBB

Average

Source: PRIME punctuality questionnaires from IMs to civity & PRIME KPI data as per 19/02/2019

A significant share of freight trains already leaves its origin with a delay

Punctuality on rail freight corridors

% of trains on time

• Rail Net Europe is collecting and publishing

performance KPIs for European rail freight

corridors

• Values represent averages of up to three years

(2016 – 2018)

• The operational KPIs describing the

performance on each corridor include the

punctuality measured at origin as well as the

punctuality measured at destination (both

applying a threshold of <= 30 minutes

Source: RNE, Commonly applicable RFC KPIs, Figures 2016-2018

68

78

70 71

49

61

48

5858

73

59

71

37

52

35

50

Nort

h S

ea -

Meditera

nean

Rhin

e -

Alp

ine

ScanM

ed R

FC

Atlantic

Nort

h S

ea -

Baltic

Meditera

nean

Baltic

-A

driatic

Orient/E

ast-

Med

punctuality at origin punctuality at destination

A wide array of factors influences punctuality – only a selected number can be

considered in this analysisOverview on factors

External factors Internal factors

Time Tabling

concept

Cancellation

policy

Utilisation of the

network

Measuring

concepts

Performance

Complexity of

the network

Fa

cto

rs c

on

sid

ere

d

in th

is r

ep

ort

Oth

er

rele

va

nt

facto

rs

Asset conditionResponse to

failures

Track

access/closureThird parties

Rolling stockTraffic

managementWeather …

An infrastructure manager with a high density of measuring points will probably

count more delaysImpact of different measuring point densities

• Delay minutes per train are captured at

every point as illustrated in the graph,

depending on the density of measuring

points

• In principal, the highest delay is

considered in the infrastructure

managers’ statistics

• Trains can build up delays on the way

but make good for it at their destination

• The likelihood that a delay is counted

decreases with a reduction of

measuring points

Density of measuringDelay minutes at

measuring points

High

Punctuality is

measured at every

departure / arrival

and at additional

measurement points

Medium

Punctuality is

measured at every

departure / arrival

LowPunctuality is

measured at arrival

8 9

3

3

8 9 312 6

Consequences

Thresholds set by infrastructure managers mostly range between 2:59 and 5:59

Delay measurement thresholds

Minutes:seconds

Passenger train categories 2:29 2:59 … 4:59 5:29 5:59 --->>>

Long distance1)

Regional

Commuter

1) Long distance thresholds: Network Rail: 9:59, RFI 15:29

Punctuality is influenced by a large number of factors – some of them are in control of the

infrastructure manager

• Punctuality is complex and driven by a large number of factors, such as:• utilisation and complexity of the network,

• weather and rolling stock in use,

• investment levels,

• Infrastructure Condition,

• Management of assets,

• and many more – inside and outside IM’s scope.

• Furthermore, infrastructure managers achieve punctuality in very different environments: the utilisation and complexity of networks range from smaller networks with lower degrees of utilisation to networks with very high densities of assets and train frequencies

24

AGENDA




25

The PRIME KPI subgroup will start season 2019/20 in a couple of months with an ambitious agenda

What’s next in PRIME KPI’s Subgroup agenda?

Proceed improving the annual PRIME KPIs Report

Upgrade and Review existing KPIs

Improve IT Tool usability and utility to members

Deliver a Thematic Report on “IM’s Financing Mechanisms” in cooperation with

PRIME Finance and PRIME Charges Subgroups

26

Annual Business Process

Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun

Modification of scope

Evaluations and reporting

Collection of feedback

(definitions, IT)

Requirement specifications

Preparation of IT decisions

Update IT-tool

Activity

Update catalogue/IT manual

Data collection

Data extract and validation

Benchmarking

Thematic Report

Milestones IT new version

and definitions

Annual Report

Delivery

Deadline

extract data

IMs / EC EC IT team Consultant

PRIME KPI Meetings

The PRIME KPI subgroup will start season 2019/20 in a couple of months with an ambitious agenda

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