Re-engineering the Production Process

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Re-engineering the Production Process

EGOWS

15th June 2004

Peter Trevelyan & Graham Mallin

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Why Re-engineer?

Greater flexibility & scalability in meeting new and changing customer requirements.

Provide the platform for new products & services for the future.

Reduce the costs involved in the supply of products and services to customers.

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Benefits being deliveredFlexibility

• Responsive to data requirements

• IT more responsive to demand

• Developments quicker to market

• New services quicker to market

Cost savings

• Reduced costs of obs supply

• More cost efficient development

• Reduced costs of IT infrastructure

• Reduced costs of telecomms

• Reduced costs of Forecast Production

• Reduced cost of service creation

Maintaining Improvements

• Maintain capability and reduced cost base

• Metrics to allow better business decisions

• Service delivery management

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Six main work streams

IT Infrastructure – Delivering a scalable, flexible IT infrastructure which meets the needs of the future Met Office.

Adding Knowledge and Value – To take data and information and add knowledge and value to it to allow service creation and delivery.

Obtaining data & Information – A scalable and cost effective observing network that supports more than just ‘meteorological’ observations.

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Six main work streams

Service Creation & Delivery – Ensuring that our Re-engineering project delivers what the Met Office needs …… and is ready for what Re-engineering will deliver.

People – To effectively manage the people transition

Process - To enable and facilitate Re-engineering to deliver an updated set of business processes.

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Re-engineering Operating Principles

The Core Re-engineering team will act as ‘Design Authority’

– Determining new environment and processes

– Co-ordinate & provide guidance to projects / programmes

– Each Development project will have a ‘Re-engineering review’ milestone before commencing.

– Managing the overall Re-engineering Programme

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Re-engineering Operating Principles

Programme Priority – V High. Programme starts in earnest April 04. 2 year implementation.

– Sets the foundation for ongoing improvement. Regular deliverables. Stick to the target architecture - challenge all

exceptions. External expertise where it can add value will be

used.

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Some of the challenges

Implementing lasting change. Priority of Re-engineering v other key

objectives. Learning curve for the organisation. Involving customers. Managing the programme and not the

detail. It’s not a panacea!

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Adding Knowledge and Value

A consistent set of high quality products efficiently produced to enable the cost effective creation of services for customers.

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Adding Knowledge and ValueDeliverables

Centralisation of product creation Increased automation of product creation Meteorologically consistent products Increased flexibility in the creation of

services from products. Changed forecaster roles to include

consultant meteorologist

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Obtaining Data and Information

A scalable and cost effective observing network that supports more that just ‘meteorological’ observations

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Obtaining Data and Information Deliverables

More scalable and flexible observing systems Standard data processing methodologies Targeted Observing and Virtual Observations

introduced Reduced manual involvement in observation

creation, collection and processing Centralised observing network support function

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Service Creation & Delivery

Ensuring that our Re-engineering project delivers what the Met Office needs …

and is ready for what Re-engineering will deliver.

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Service Creation & Delivery Deliverables

Detailed business requirements in order to guide Re-engineering Roadmap

Ensuring that we deliver what the business needs

Migration of customers to new architecture.

Introduction of Service Delivery management

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IT Infrastructure

Delivering a scalable, flexible IT infrastructure which meets the needs of the future Met Office

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IT Infrastructure Deliverables

More Distributed and scaleable IT Architecture with common standards and support tools – leading to systems and support that are more responsive to changes in demand

Unified Development Process – using up to date efficient tools with highly skilled development staff – quicker and cheaper to deliver software.

Clearer “cost of development” model, with Unified Development model.

Removal of redundant architecture and legacy systems – reduce IT costs

Improved IT Governance Ability to collect metrics

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IT Infrastructure Benefits

IT systems and support more responsive to changes in demand

Developments quicker to market More cost efficient development Reduced running cost of IT infrastructure Reduced running cost of telecoms Improved IT Infrastructure governance Improved production process metrics

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IT Infrastructure – Issues

New technologies Development Process Demonstrate capability early MoD, security etc Some customers have long timescales Logical Data Store (LDS) will take time! E-commerce strategy

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IT Infrastructure Timeline

Enterprise architectur

e

Apr04 Apr05 Apr06 Dec06

Governance adopted

Web portal established

LDS design

Complete development process roll-

out

LDS fully operational

Telecoms infrastructure

GPCS migration complete

Applications migrated

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IT Architecture

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Strategic IT themes

Flexible, resilient, highly available, secure Distributed, component-based framework

– Java J2EE (where fit for purpose)

– Service Oriented Architecture

– Middleware … the “glue”

Exploit existing “legacy” systems– We’re not starting from scratch!

Consolidation of the “multitude” of platforms Linux

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Architecture Roadmap

Component ModelComponent Model

DataModelData

ModelOperational ModelOperational Model

OverviewOverview

Specification LevelSpecification Level

Physical LevelPhysical Level

Conceptual LevelConceptual Level

PrinciplesPrinciples

ContextContext

Management

Process

Management

Process

IT StrategyIT Strategy

RequirementsRequirements

Business Requireme

nts

Business Requireme

nts

IT Requireme

nts

IT Requireme

nts

Implementation PlanImplementation Plan

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Architecture Context

ResearchSystems andResources

External WebServices

Directories

DeliveryBureaux

ExternalSystems

External DataSources

ExternalSystems

WirelessDevices

Browser-based Internet

Clients

MeasurementInstrumentation

Existing(Legacy) IT

Systems andPackagedSolutions

VoiceTelephonyNetworks

DesktopHardware

DesktopApplications

Browser-based Intranet

Clients

DesktopServices

SupportingInfrastructure

Met OfficeIT Architecture

Met Office Users,Systems andResources

Customersand

Partners

Third PartyService

Providers

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Architecture Overview

PresentationServices

(Web)

ApplicationServices(J2EE)

System, Network and Security Management Services

IntranetClients

PresentationServices

(Web)

ApplicationServices(J2EE)

SupportingServices

(i.e. CRM, HR,Finanace)

IntegrationServices(Process,

Application andData Integration)

Logical DataStore

(Oracle)

Core ProductionSystems

(Non J2EE)GatewayServices

VPNs /PrivateLinks

ExternalServices

SensorNetwork

ProductCreation and

AnalysisServices(J2EE*)

AuthenticationServices

* Native J2EE orJ2EE Integrated

Logical DataStore -

ReplicatedSubset(Oracle)

ProductCreation and

AnalysisServices(J2EE*)

Web ServicesGateway

Internet

InternetClients

ExternalServices

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Revised Business Processes

To enable and facilitate Re-engineering to deliver an updated set of business processes which:

– reflect the changes resulting from the Programme and

– meet the evolving future needs of the Met Office.

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Revised Business Processes Deliverables

To enable and facilitate Re-engineering to deliver new production process map new overall Met Office process map new organisational structure continued ISO9001 certification demonstrated process improvements using

new performance measures.

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Creating the 4D Data Cube

The source of “Environmental Intelligence”

Need to transform the output from the forecaster into a form that can be used by cooperating processes.

The majority of the content needs to be digital as it is not easy to make quantitative use of a picture.

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Creating the 4D Data Cube

The forecaster needs tools that enable them to “digitally” edit the atmosphere and in particular gridded data (“On Screen Field Modification”).

»The edit needs to be in time and space.»The process must be intuitive to the

forecaster.»The edit process needs to be scientifically

sound i.e. the “balance of the atmosphere needs to be maintained.

»The forecaster need only edit one field and all others be changed.

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Forecasting Process

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The transform of the Meteorologist’s View of the world into one that forms a

key component required by the “Product Tailoring Process” and also a key

element of the “Common Operating Picture” required by all Key Decision

makers.

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Adding value to model data Field modification

Griddeddata set

from NWP

Gridmodification

Modified griddeddata set

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OSFM A tool that allows the forecaster to edit, in four dimensions

NWP data. The resultant amended data is saved in the database and

therefore available to all other “down stream” process. The forecaster edits fields on the basis of supporting data. The resulting digital database will form the basis of most down

stream product creation. The scales can vary from Global to high resolution Meso-Scale

models. The OSFM process can be proved to add value through

objective verification.

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The OSFM User Interface and Display

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Mesoscale OSFM

Developed in 2002 to augment OSFM Expanded parameter list includes fog

probability and cloud prediction Model merge facility from successive runs

or different models Ability to apply operators (multiply, add

etc) to selected cloud and precipitation fields

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Proving the value of FITL

Met Office routinely proving the value of human forecaster with verification stats

Quantifying the value of modifying certain model fields (cloud, precip, fog etc)

Recognize models are increasingly reliable In JET need methodology for how forecaster

will operate in future

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OSFM Benefits

Enables forecasters to provide best guidance More emphasis on understanding models Generates graphical guidance information Excellent “what if” analysis tool Allows the forecaster more time for

‘meteorology’ Modified gridded data for use in automated

product generation

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Adding value to model data Derived Data

Calculate derived data for special applications

CAT, Icing, Thunderstorm Indices etc Either as “one-off” or routinely Only need to send model data to user

– Reduce transmissions

– User creates data required

– Flexibility to use different model data

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Medium-Range Forecasting - The Effect of Chaos

The atmosphere is a chaotic system: “… one flap of

a seagull’s wing may forever change the future course of the weather”, (Lorenz, 1963)

Up to about 3 days ahead we can usually forecast the general pattern of the weather quite accurately

Beyond 3 days Chaos becomes a major factorTiny errors in how we analyse the current state of the atmosphere lead to large errors in the forecast – these are both equally valid 4-day forecasts!

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Ensembles...

time

Forecast uncertainty

Climatology

Initial Condition Uncertainty

X

Deterministic Forecast

Analysis

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Ensembles

In an ensemble forecast we run the model many times from slightly different initial conditions

These provide a range of ‘equally probable’ forecast solutions

Allow forecasters to:

– Assess possible outcomes

– Estimate risks and probabilities

– Gauge confidence

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ECMWF Ensemble prediction System (EPS)

51 members:– Control run from

unperturbed ECMWF analysis

– 25 perturbations, each added to and subtracted from the control analysis to create a pair of runs

ECMWF model at 80km resolution

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Summarising information

The Ensemble contains a huge amount of information – need to summarise

Tubing (left) identifies most probable (top) and most extreme (below) forecasts

Clustering groups together similar forecasts

Cyclone Tracking (right) shows low centres

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EPS Meteogram

Plot of ensemble spread

– Box shows 25-75% range

– Whiskers show 95% confidence range

– Central bar shows median – can indicate most probable

Summarises forecast at one location for 10 days ahead

Met Office calibrates ensemble forecasts to improve quality

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Probability Forecasts from Ensembles

Ensembles help forecasters assess the most probable weather

Probability forecasts help end users to assess and manage risk in an uncertain world

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Tropical Cyclone Probabilities Tropical Cyclones are quite small but very damaging Forecasting the exact position of landfall is important but

difficult Ensemble provides a range of tracks

From these we can estimate theprobability of a storm strike in

the next 3 days

Hurricane Isabel, September 2003

Re-engineering the Production Process

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