................................................................................................. How to turn challenges into benefits in large scale

Transcription

................................................................................................. How to turn challenges into benefits in large scale
.................................................................................................
How to turn challenges into benefits in large scale
multi-national, multi-vendor EDM projects
NGU Summit 2009
Portugal 25th June 2009
Gerko Baarslag
Managing Director Eneco IT Solutions
Simo Makkonen
CEO, Process Vision
Contents
.................................................................................................
• Context: Eneco and Process Vision shortly
• Customer case: large scale EDM project
– Project drivers and targets
– Challenges and lessons learned
– Successes
– Conclusions
• Hyphotheses and discussion
• Summary
2
........................................................................
Introduction Process Vision: Profile
.................................................................................................
• Process Vision Oy is one of the leading energy IT suppliers
in Europe
• Process Vision provides versatile IT systems, solutions
and services for energy markets
• Process Vision GENERIS energy IT platform delivers
solutions for
– meter data management, meter asset management, energy data
management, contract and porfolio management, trades and risks
management, and billing and customer services
• With over 300 installations and over 200 customers in
Europe, Process Vision has strong footprint and extensive
experience – also for supporting future business needs of
energy market
3
........................................................................
GENERIS
Manage all energy data with one standard product
.................................................................................................
Meter
roll-out
management
Versatile
reporting
Regulatory
compliance
duties
Second generation solution with
over 300 installations for low risk
implementation
Forecasting
Pricing and quotes
management
Open position
management
Meter
asset
repository
Meter
Assets
Mgmt
Extranet
services
Validated
meter
data
Profitability
analyses
Balance
Contract
Settlement & Portfolio
& Mgmt
Mgmt
Trade &
Risk
Mgmt
Control Displays
Meter
Data
Mgmt
Price fixing and
hedging
Scenario
analyses
Validated
billing
data
Billing
Data
Mgmt
Reporting Platform
Info Flow Manager
System Integration & B2B communication
SCADA
NIS
CRM/CIS/ERP
Modularity and scalability
enables extending system
according to business needs for
optimal TCO
Comprehensive task automation
and data quality control save
resources
Optimal user experience with
business process based user
interface improves quality
GENERIS Platform
AMR/AMM/AMI
For electricity, gas, district
heating, district cooling, water
and for all parties for streamlined
IT landscape
Business
partners
Flexibility provides cost effective
regulatory compliancy
........................................................................
Introduction Eneco: Profile
.................................................................................................
• Eneco is among the top energy suppliers in the
Netherlands.
• Eneco has an integrated distribution strategy
covering the generation, transmission, supply,
metering and billing of gas, electricity and heat.
• Eneco Energie serves a total of around 2 million
business en residential customers.
• Eneco employs appr. 5,300 people.
• Eneco Value: continuity of energy on a sustainable
basis
• Eneco Holding consist of three companies: Eneco;
Joulz (Infrastructure) & Stedin (Grid Operator)
5
........................................................................
.................................................................................................
Customer case: large scale
EDM project Aorta
6
........................................................................
Project Aorta introduction
Overview
.................................................................................................
Aorta = Application optimisation for reconciliation and allocation
(balance settlement)
Challenge: deliver and deploy a 4 000 000 metering points
allocation and reconciliation system harmonization project for
electricity and gas
7
........................................................................
Key drivers and targets
.................................................................................................
Project drivers and targets
•To get allocation and reconciliation processes under proper control
and provide correct and timely results.
•To clamp down on administrative losses in allocation.
•Flexible and Future proof IT landscape
•Rationalization of the IT landschape:
– Reduction in Total Cost of Ownership
– Modernization of Process Architecture
8
........................................................................
Key Drivers and targets
.................................................................................................
Before Aorta situation
Gegevensregister
Mecsico
e-Netbeheer
Reconciliatie G
GENERIS
XIB
RIA
Reconciliatie E
ARIE
Allocatie E
TENNET
Mecsico
Allocatie G
MVS
Kopie
AR
EHTO/
GENERIS
Reconciliatie G
XIB
NetBeheer Message Handler (NBMH)
ECH
HERA+
Allocatie G
ENBU
Contracten & Billing
Logisch Aansluit Register (LAR)
SVO
berichtenverkeer
Reconciliatie E
Allocatie E
Targeted situation
SVO berichtenverkeer
Contracten & Billing
Gegevensregister
9
Allocatie G
Additionele
functionaliteit
CAS1
Additionele
functionaliteit
Additionele
functionaliteit
GENERIS
XIB
Huidige
knelpunten
Huidige
knelpunten
HERA+
functionaliteit
Reconciliatie G
Reconciliatie E
Huidige
knelpunten
........................................................................
Allocatie E
TENNET
NetBeheer Message Handler
(NBMH)
ECH
Procesondersteuning
Challenges and lessons learned
Challenges
.................................................................................................
Main challenges:
•Initial project plan: too optimistic;
wishful thinking planning
•Requirements based on as is
situation
•Too many layers of
communication between different
parties (in Netherlands & Finland)
•Master data quality dubious
•Advanced database settings and
fine-tuning as data amount
increased
10
........................................................................
Challenges and lessons learned
Lessons learned
.................................................................................................
•Too many cooks spoil the broth – get a few good
ones, and then:
•Involve all parties in project planning and steering
groups since the beginning
•Do not underestimate efforts needed to verify,
correct and maintain master data quality
•Enough technical & functional expertise shall be
involved during the comple project timeline and onsite!
11
........................................................................
Situation today
.................................................................................................
New system architecture implemented and in
production since March 2008 for allocation and since
September 2008 for the complete project scope
Application is stable and the allocation and
reconciliation processes are in control for all 4 000
000 metering points. Results are up-to-date
Administrative losses reduced by 30%
12
........................................................................
Conclusions
.................................................................................................
Project was challenging from very beginning but
ended up with great success.
The persistance of Eneco and the project team to ’get
it done’ pulled the project through some rough
patches.
Trust, and good, direct communication are crucial.
The GENERIS platform that was selected for its high
performance and flexibility showed its strengths by
supporting performance and usability targets well
over the limits.
13
........................................................................
.................................................................................................
Hypothesis and discussion
14
........................................................................
Hypotheses – EDM project
.................................................................................................
1. Implementation: Challenge with EDM is NOT software
but real issues are
–
Expectation management
–
Data cleansing
2. Go Live: After implementation EDM project should do a
‘change stop’
15
–
Forces the users to get used to the system
–
Stabilize processes and software version
........................................................................
Hypotheses – Future aspects
.................................................................................................
1. The amount of energy measurement data will
increase dramatically during the next decade due to
- Smart metering
- EU 2020 objectives
- Environmental awareness lures citizens to ask for more
information
 Future EDM project will require much more attention and
budget than earlier; are you prepared to put more
management attention to information management in the
future?
16
........................................................................
Hypotheses – Future aspects
.................................................................................................
2. Challenges to gather, validate and store all the
measurement data will increase due to
- Data volumes are extremely large
- Privacy policies and confidentiality will be increasingly
discussed
 Is your organisation ready for the big change that will
take place in the future?
17
........................................................................
Hypotheses – Future aspects
.................................................................................................
3. In the future, measurement data will be utilized by
increasing number of processes and users which
requires re-thinking of IT system architectures like
- Billing engine only one user of the measurement data
- EDM used only for market regulatory compliance
 MDM required as a central hub to manage new needs. Is
your IT landscape ready for this change?
18
........................................................................
Summary
.................................................................................................
The experiences in large scale EDM projects shows that
– implementation project requires more resources than
usually is expected e.g. due to data cleansing
– EDM and MDM solutions are critical and should not be
under estimated by top management
The
–
–
–
–
19
future proven EDM must take into consideration
increased number of meter data
new architecture by separating MDM from EDM
flexibility in system integration
increased number of data users
........................................................................
Q&A
.................................................................................................
Thank you for your attention!
20
........................................................................