This chapter summarizes various aspects of large
projects and provides a foundation to consider what a new
Theory of Project Management for large complex projects may
look like.
In the engineering and construction industry governance needs and requirements exist at
multiple levels. These include:
• Governmental and industry level governance (laws, regulations, codes, standards)
• Enterprise level (encompassing social (stakeholder), political, economic (market,
shareholder, financial institutions), cultural (corporate and national/local),
technological)
• Portfolio and programs
• Project
This paper focuses on the portfolio and program level, collectively referred to as program in
this paper.
Application of system life cycle processes to large complex engineering and c...Bob Prieto
The complexity of megaprojects and programs continues to grow and with it the challenges of delivering ever larger and more complex programs. These large complex programs open the door to many new opportunities but also to increased challenges in delivery and sustainment throughout their lifecycle. Prior articles have described the open nature of this large complex program system and compared its attributes to many we find in the world of relativistic physics. These challenges must be addressed recognizing that they arise from a combination of physical, fiscal and human attributes in a realm of complexity which challenges the very foundations of project management theory.
This paper looks at hard systems aspects as contrasted with the soft system aspects more characteristic of an open system. Its purpose is to adapt a systems engineering framework associated with the hard closed elements of these large complex project systems without losing site of the overall open systems nature of large complex programs.
The systems life cycle process codified in ISO 15288 lends itself to application in large complex engineering and construction programs.
This chapter summarizes various aspects of large
projects and provides a foundation to consider what a new
Theory of Project Management for large complex projects may
look like.
In the engineering and construction industry governance needs and requirements exist at
multiple levels. These include:
• Governmental and industry level governance (laws, regulations, codes, standards)
• Enterprise level (encompassing social (stakeholder), political, economic (market,
shareholder, financial institutions), cultural (corporate and national/local),
technological)
• Portfolio and programs
• Project
This paper focuses on the portfolio and program level, collectively referred to as program in
this paper.
Application of system life cycle processes to large complex engineering and c...Bob Prieto
The complexity of megaprojects and programs continues to grow and with it the challenges of delivering ever larger and more complex programs. These large complex programs open the door to many new opportunities but also to increased challenges in delivery and sustainment throughout their lifecycle. Prior articles have described the open nature of this large complex program system and compared its attributes to many we find in the world of relativistic physics. These challenges must be addressed recognizing that they arise from a combination of physical, fiscal and human attributes in a realm of complexity which challenges the very foundations of project management theory.
This paper looks at hard systems aspects as contrasted with the soft system aspects more characteristic of an open system. Its purpose is to adapt a systems engineering framework associated with the hard closed elements of these large complex project systems without losing site of the overall open systems nature of large complex programs.
The systems life cycle process codified in ISO 15288 lends itself to application in large complex engineering and construction programs.
Constructions projects have become of increasing technological complexity with relationships of those involved are also more complex and contractually varied. Additionally global trends are dramatically impacting contracting activity. Success depends on new and innovative ways to manage uncertainty and complexity.
Role of Functional Organization in Large Engineering and Construction ProgramsBob Prieto
Large corporate organizations typically employ some form of matrix organization to ensure a consistent approach in key areas across the organization. The nature and extent of this matrix or functional organization will be driven by:
•common approaches to human resources
•consistent application of legal approvals and reviews of significant actions
•common financial functions related to accounting, cash management, insurance and claims & suits
•common managerial, technical and support functions which accrue benefits from a consistent and coordinated approach
Within a project setting, required resources generally reside at the project level and corporate functional activities extend into the project environment only to the extent required to protect the parent organization, consistent with client requirements and practices.
The situation in large programs, however, is different and a functional organization more akin to the corporate functional organization is often created within the program team. This program level functional organization acts much in the same way as the corporate functional organization but its role and emphasis evolves throughout the programs life.
A typical program management organization will include a functional organization that will provide people, management processes, program-level project control tools, and systems. The program management team will thereby bring enhanced management, quality control, efficiency, and coordination to the entire program.
Addressing the Complex Challenges of Today's Acquisition ProfessionalGovLoop
GovLoop and Integrity Management Consulting are pleased to present a new guide entitled, "Addressing the Complex Challenges of Today's Acquisition Professional." From generating requirements, to planning, obtaining and sustaining capabilities, the acquisition process, if implemented effectively, can contribute significantly to accomplishing an agency’s mission more efficiently. As the largest purchaser of goods and services in the nation, the Federal government's acquisition process is complex and under more pressure than ever with tightened budgets and a shifting workforce.
http://www.govloop.com/profiles/blogs/addressing-the-challenges-of-federal-acquisition-professionals
A research project to identify trends in successful, large IT projects. Tried to identify and understand what project characteristics were present in successful IT projects with budgets greater than $750K.
Six Data Architecture and IT Infrastructure Governance Mandates for Multinati...Cognizant
Banking and financial services institutions operating in multiple countries and executing digital transformation programs can leverage the principles of BCBS 239 to standardize and stabilize their IT infrastructure and related data architecture processes to realize digital business value across their geographic footprint.
Project Server in the Oil and Gas Industry - Enabling Technologies Best Pract...EPC Group
EPC Group's - Project Server in the Oil and Gas Industry - Enabling Technologies Best Practices - Covering EPC Group's Project Server Implementation Strategies
Proven Paradigm for Creating Enterprise Project and Portfolio Management Adop...UMT
Capability Maturity Assessment is one of the tools consistently leveraged by Enterprise Project and Portfolio Manage-ment (EPM) practitioners in the creation of adoption roadmaps for organizations that are creating momentum for change with the objective of improving internal governance. Historically, the problem has been addressed in parallel at the Project, Program, or Portfolio levels, and in many cases the solutions devised have been independent of one anoth-er, potentially missing on integration aspects that could greatly improve overall results. In the past couple of years, new methodologies that attempt to encompass all three disciplines have been developed, including OPM3 from the PMI.
UCISA Toolkit - Establishing a PMO in an HE Environment Mark Ritchie
This toolkit provide guidance for higher education institutions,. and any other organisations, considering establishing a Project Management Office (PMO) function. It includes advice on designing your PMO and on implementation as well as providing a set of example artefacts.
This guide was published by the UCISA Project and Change Management Group in October 2015. This guide forms part of a set of UCISA Project and Change Management publications including the Major Project Governance Assessment Toolkit and the guide to Effective Risk Management for IT and Business Change Projects.
Overview of developments in project management - ICE MPL ProceedingsDonnie MacNicol
Members of the Management, Procurement and Law editorial advisory panel provide overviews of their areas of expertise, highlighting recent and forthcoming developments likely to affect engineers and others working in the fields of management, procurement and law.
The Building Information Model track is planned for EVM World this spring. In the last edition of The Measureable News we had a bibliography of BIM papers. Here are some more.
Constructions projects have become of increasing technological complexity with relationships of those involved are also more complex and contractually varied. Additionally global trends are dramatically impacting contracting activity. Success depends on new and innovative ways to manage uncertainty and complexity.
Role of Functional Organization in Large Engineering and Construction ProgramsBob Prieto
Large corporate organizations typically employ some form of matrix organization to ensure a consistent approach in key areas across the organization. The nature and extent of this matrix or functional organization will be driven by:
•common approaches to human resources
•consistent application of legal approvals and reviews of significant actions
•common financial functions related to accounting, cash management, insurance and claims & suits
•common managerial, technical and support functions which accrue benefits from a consistent and coordinated approach
Within a project setting, required resources generally reside at the project level and corporate functional activities extend into the project environment only to the extent required to protect the parent organization, consistent with client requirements and practices.
The situation in large programs, however, is different and a functional organization more akin to the corporate functional organization is often created within the program team. This program level functional organization acts much in the same way as the corporate functional organization but its role and emphasis evolves throughout the programs life.
A typical program management organization will include a functional organization that will provide people, management processes, program-level project control tools, and systems. The program management team will thereby bring enhanced management, quality control, efficiency, and coordination to the entire program.
Addressing the Complex Challenges of Today's Acquisition ProfessionalGovLoop
GovLoop and Integrity Management Consulting are pleased to present a new guide entitled, "Addressing the Complex Challenges of Today's Acquisition Professional." From generating requirements, to planning, obtaining and sustaining capabilities, the acquisition process, if implemented effectively, can contribute significantly to accomplishing an agency’s mission more efficiently. As the largest purchaser of goods and services in the nation, the Federal government's acquisition process is complex and under more pressure than ever with tightened budgets and a shifting workforce.
http://www.govloop.com/profiles/blogs/addressing-the-challenges-of-federal-acquisition-professionals
A research project to identify trends in successful, large IT projects. Tried to identify and understand what project characteristics were present in successful IT projects with budgets greater than $750K.
Six Data Architecture and IT Infrastructure Governance Mandates for Multinati...Cognizant
Banking and financial services institutions operating in multiple countries and executing digital transformation programs can leverage the principles of BCBS 239 to standardize and stabilize their IT infrastructure and related data architecture processes to realize digital business value across their geographic footprint.
Project Server in the Oil and Gas Industry - Enabling Technologies Best Pract...EPC Group
EPC Group's - Project Server in the Oil and Gas Industry - Enabling Technologies Best Practices - Covering EPC Group's Project Server Implementation Strategies
Proven Paradigm for Creating Enterprise Project and Portfolio Management Adop...UMT
Capability Maturity Assessment is one of the tools consistently leveraged by Enterprise Project and Portfolio Manage-ment (EPM) practitioners in the creation of adoption roadmaps for organizations that are creating momentum for change with the objective of improving internal governance. Historically, the problem has been addressed in parallel at the Project, Program, or Portfolio levels, and in many cases the solutions devised have been independent of one anoth-er, potentially missing on integration aspects that could greatly improve overall results. In the past couple of years, new methodologies that attempt to encompass all three disciplines have been developed, including OPM3 from the PMI.
UCISA Toolkit - Establishing a PMO in an HE Environment Mark Ritchie
This toolkit provide guidance for higher education institutions,. and any other organisations, considering establishing a Project Management Office (PMO) function. It includes advice on designing your PMO and on implementation as well as providing a set of example artefacts.
This guide was published by the UCISA Project and Change Management Group in October 2015. This guide forms part of a set of UCISA Project and Change Management publications including the Major Project Governance Assessment Toolkit and the guide to Effective Risk Management for IT and Business Change Projects.
Overview of developments in project management - ICE MPL ProceedingsDonnie MacNicol
Members of the Management, Procurement and Law editorial advisory panel provide overviews of their areas of expertise, highlighting recent and forthcoming developments likely to affect engineers and others working in the fields of management, procurement and law.
The Building Information Model track is planned for EVM World this spring. In the last edition of The Measureable News we had a bibliography of BIM papers. Here are some more.
The new ‘A and B’ of the Finance Function: Analytics and Big Data - -Evolutio...Balaji Venkat Chellam Iyer
Published in 2013, this White Paper discusses how the finance function would evolve with the combined forces of Big Data and Analytics and the levers that could help catalyze the change and has drawn upon the Global Trend Study conducted by Tata Consultancy Services (TCS) on how companies were investing in Big Data and deriving returns from it.
FIMA's latest whitepaper evaluates how financial services companies are managing the challenges posed by data quality management. By analyzing which data types and data characteristics businesses are struggling with, it uncovers the true business costs associated with data quality. It will also gauge how data governance programs are maturing and how they are being measured. Finally, it assesses how data is being managed within financial institutions.
Key findings include:
Data quality has never been more important for financial institutions, but most of those companies feel their data is only mediocre: Quality data serves a myriad of central business goals, from risk reduction to increased productivity. Unfortunately, many businesses continue to struggle with data quality, despite the fact that four-fifths of them have it ranked as a top priority.
The top two business functions impacted by poor data quality are regulatory compliance and risk management: Because these concerns tend to be the most important drivers of data quality, many financial institutions see data governance as a “must-do,” rather than a ROI-boosting activity. Furthermore, the vast majority of financial services companies can not quantify the business cost of poor data quality.
Financial institutions vary greatly in the maturity of their data governance programs: Data governance cannot be overlooked – unsurprisingly, businesses with formalized data governance programs reported that their data was higher quality than most other groups.
Data quality management requires close collaboration between business and IT leaders: That collaboration already exists for 83% of respondents in this study, who say that IT and business leaders work together to manage data quality in their organizations. However, the tools these businesses use to manage their data are not all equal, leading to an uneven allocation of resources.
As businesses generate and manage vast amounts of data, companies have more opportunities to gather data, incorporate insights into business strategy and continuously expand access to data across the organisation. Doing so effectively—leveraging data for strategic objectives—is often easier said
than done, however. This report, Transforming data into action: the business outlook for data governance, explores the business contributions of data governance at organisations globally and across industries, the challenges faced in creating useful data governance policies and the opportunities to improve such programmes.
Reference data management in financial services industryNIIT Technologies
This white paper analyse s the need for Reference Data Management in the financial services industry and elucidates the challenges associated with its implementation. The paper also focuses on the critical elements of RDM implementation and some of the major benefits an organization can derive by implementing a robust Reference Data Management into its IT infrastructure.
Driving A Data-Centric Culture: The Leadership ChallengePlatfora
Embracing data as a corporate asset—and a source of competitive advantage—is not just a “good idea” that companies should consider. Such adoption will help determine the winners and losers across multiple markets and industries in the future.
In the last couple of years, corporate focus has shifted: first, from investing in the right technology and tools; then to acquiring the right talent and skills; and now to building the right organizational culture that can realize the business value of powerful big-data analytic tools.
Most organizations today are still focused on putting in place the right technology and talent, but others have evolved further and are working toward fostering a data-centric corporate culture.
We conducted a groundbreaking survey of the UK’s data and business professionals to get a snapshot of the state of the world of data, uncover some of the issues facing the industry and get a sense of the changes on the horizon. The results were enlightening, and in some cases, very surprising.
Find out:
Why nearly a third of IT Directors feel their organisation uses data poorly
What the hybrid data manager of the future will look like
Why understanding customer behaviour remains the holy grail for so many
We conducted a ground-breaking survey of the UK’s data and business professionals to get a snapshot of the state of the world of data, uncover some of the issues facing the industry and get a sense of the changes on the horizon. The results were enlightening, and in some cases, very surprising.
We conducted a survey of the UK's data and business professionals to get a snapshot of the state of the world of data, uncover some of the issues facing the industry and get a sense of the changes on the horizon. The results were enlightening, and in some cases, very surprising.
Data has become a key focus for corporate leaders today. Chartered Global Management Accountant (CGMA) designation holders are well placed to help translate data into commercial insights and value.
Teaching organizations to fish in a data-rich future: Stories from data leadersAmanda Sirianni
Many organizations are still early in their journey to set up and optimize their analytics function and related capabilities. However, those that are investing in highly skilled data leaders are seeing the business benefits. To learn more, the IBM Center for Applied Insights spoke with some of these leaders.
Through their stories, we discovered the analytics challenges that businesses face across industries and sectors, and how today’s data leaders confront and eventually overcome those challenges. See how these leaders were able to deliver outcomes that far outweighed their early struggles. To learn more: www.ibm.com/ibmcai/cdostudy
Similar to Stewarding data why financial services need a chief data officer (20)
Erdinç Saçan schreef voor het Fontys collega een boek over Inclusieve Artificial Intelligence. Vragen waar in het boek over wordt nagedacht zijn onderandere: “Kunnen we algoritmen inzetten voor het algemene belang, om zo discriminatie en ongelijkheid te bestrijden?” & “Algoritmes nemen steeds meer beslissingen voor ons. Hoe zorgen we ervoor dat dit op een inclusieve manier gebeurt?”
Themabrochure robotisering gerformeerde bond - prof.dr. m.j. de vriesRick Bouter
In de nieuwste themabrochure van de Gereformeerde Bond, getiteld Robotisering, gaat prof. dr. M.J. de Vries in op de voordelen maar ook de gevaren van het inzetten van robots. Voor welke morele keuzes komen we te staan? Moeten robots bijvoorbeeld ook in de zorg worden gebruikt, om zo de werkdruk van het zorgpersoneel te verlichten? In de Bijbel komen robots uiteraard niet voor, maar kunnen we in Gods Woord handvatten vinden om met deze technologie goed om te gaan?
Internet of things and the metamorphosis of objects - rick bouter , gérald ...Rick Bouter
Where in prior times technique was referring to: “a method of accomplishing a desired aim”,
today we speak more of technology. Technology has long been presented as a set of
techniques; today it has become more than a method to accomplish a desired aim. From now
on, we live in ‘the age of makers’. In times when there are more people with mobile phone
access than toothbrushes, everyone has the ability to start up a million euro business from
behind the kitchen table.
Technology does not only affect business any longer; it also affects culture, politics, society
and every element we value in life. Maybe most important of all, it affects the human race as
we know it today. For the reason technology will impact the way we have lived for ages, it is
legitimate to ask whether there is an intersection where humans and objects will find a
mutually beneficial coexistence, or whether one of these entities will rule over the other, or
whether there will be an alliance between the human race and some sort of technology that
represents a global connected world brain.
Will technology be, like in prior times, a collection of methods to accomplishing a desired
aim, or will the human race be enslaved by technology and ruled by the artificial intelligence
embedded in it?
Trend 1: CITIZEN AI
Raising AI to Benefit Business and Society
Trend 2 EXTENDED REALITY
The End of Distance
Trend 3 DATA VERACITY
The Importance of Trust
Trend 4 FRICTIONLESS BUSINESS
Built to Partner at Scale
Trend 5 INTERNET OF THINKING
Creating Intelligent Distributed Systems
Ai - Artificial Intelligence predictions-2018-report - PWCRick Bouter
Here’s some actionable advice on artificial intelligence (AI), that you can
use today: If someone says they know exactly what AI will look like and
do in 10 years, smile politely, then change the subject or walk away.
Internet of things rapport sogeti - vi nt - rick bouterRick Bouter
Internet of Things for business: from sick(care) to health(care) final thesis Rick Bouter Sogeti VInT (Vision inspiration new technology) verkenning instituut nieuwe technologie
Telegram open network ton will be a third generationRick Bouter
Telegram Open Network (TON) will be a “third generation” blockchain with more efficient transaction and scaling capabilities than current solutions like Bitcoin and Ethereum.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
2. 2
Why Chief Data Officers are a Necessity,
Not a Luxury
The C-suite could soon start to feel a little
crowded, with Chief Digital Officers, Chief
Innovation Officers, Chief Risk Officers
and Chief Data Officers joining the more
established functional leaders. To avoid
C-suite proliferation, companies need to
decide whether to elevate a new functional
role to “chief” based on the strategic
importance of the issue for the organization
and its sector. For example, in many
organizations, marketing will be so essential
to performance that few would deny the
need for a CMO. In financial services, data
has become so mission-critical that the role
of Chief Data Officer is simply essential.
Figure 1: Big Data Opportunities in the Financial Services Sector
Source: Capgemini Consulting Big Data Framework
Between 2008 and 2013,
banks in the US paid
more than $100
billion in penalties
and settlements.
ASilo-edApproachtoData
GovernanceRaisesNon-
ComplianceRisks
Sincethefinancialcrisisin2008,themonetary
impact of regulatory non-compliance has
risen dramatically. Between 2008 and
2013, banks in the US paid more than
$100 billion in penalties and settlements1
.
Tightening regulatory frameworks provide a
telling illustration of why firms need to get
to grips with data. New anti-terrorism and
anti-money laundering legislation requires
that financial institutions track customer
data more closely and report suspicious
activity, or risk attracting enormous legal
fines. Regulations such as “BCBS 239”
developed by the Basel Committee of
Banking Supervision require that banks set
up adequate governance, processes and
systems to ensure the accuracy of data and
the relevance of the reports on which they
base their risk assessment, or risk having
their licenses revoked. Other regulations
- such as the US “Foreign Account Tax
Compliance Act (FATCA)”2
, and the
“Automatic Exchange of Information
(AEOI)” and “Common Reporting Standard
(CRS)” developed by the OECD - demand
that financial institutions provide accurate,
complete and consistent information to tax
authorities to help curb tax evasion.
Despite this pressing need for strong data
controls, the financial services industry still
faces data management challenges, with
institutions struggling with fragmentation,
silos and a lack of clear governance
processes. Critical enterprise information is
often distributed across many operational
systems and databases. In addition, our
research revealed that 54% of financial
services firms lack robust processes to
manage data quality3
. A senior executive
at a leading Australian bank admitted that
“The responsibility around data quality
is fragmented and unclear within the
organization.4
”The responsibility
around data quality is
fragmented and unclear
within the organization.
- Senior executive at
a leading Australian bank
Improve Risks and
Pricing Management
Enhance Customer
Experience
Increase Operational
Efficiency
IdentifyNew
Business Models
Increase credit score accuracy
based on new sources of data
(ex: social media data) for
improved risk control and more
competitive pricing
Personalize offerings, identify new
cross-sell opportunities and control
churn based on deep insights on
customer behavior, drawn from
multiple sources of data
Optimize data management
costs using Big Data
technologies, improve operational
efficiency through straight-through
processing and real-time,
performance management
Monetize raw anonymized
customer data or behavioral
insights that enable improved
market analysis
3. 3
50% of financial
services executives cite
ineffective coordination
of Big Data and
analytics teams as the
biggest challenge in Big
Data implementation.
79% of financial
services executives
believe that the ability
to extract value
from Big Data is an
important factor in
their future success.
Figure 2: Impact of Big Data on the Financial Services Sector
N = 196
Source: Capgemini, “Big & Fast Data: The Rise of Insight-Driven Business”, March 2015
The Lack of Central
Oversight Impacts Effective
Use of Big Data
Aswellastheimportanceofdatamanagement
for regulatory compliance, Big Data is a
significant opportunity for the financial services
sector, from operational efficiency to the
customer experience (see Figure 1). According
to our research, 79% of financial services
executives believe that the ability to extract
value from Big Data is an important factor in
their future success (see Figure 2)5
.
However, once again, a lack of robust
control and coordination affects financial
services firms’ abilities to deliver their Big
Data ambitions. 50% of financial services
executives cite ineffective coordination of
BigDataandanalyticsteamsasthebiggest
challenge in Big Data implementation6
.
Further, 48% of financial services firms
operate with scattered pockets of analytics
resources or with decentralized teams that
function without any central oversight7
.
79%
79%
75%
57%
% of respondents agreeing with the statement
We are facing increased competition
from data-enabled startups
If we do not embrace Big Data we risk
becoming irrelevant / uncompetitive
The ability to extract value from Big Data is
important for my organization’s future success
Big Data provides new business opportunities
A Leadership Vacuum:Why
Financial Services Firms
Need Chief Data Officers
There is no doubt that financial services
firms need robust data management to
meet growing regulatory pressure. They
alsocannotlettheBigDataprizepassthem
by. Our research shows that appointing a
leader entrusted with enterprise-wide data
responsibilities is critical. Across industries,
organizations that have appointed a Chief
Data Officer (CDO) report a 43% success
rate8
for their Big Data initiatives, compared
to 31% for organizations that have not
appointed a CDO9
.
So, where do financial services firms stand
in terms of appointing CDOs? What is the
role of the CDO in these organizations? To
find the answers to these questions, we
interviewed senior executives from leading
global financial services firms (see research
methodology at the end of this paper).
4. 4
The CDO’s Role in Financial Services Firms
Remains Limited in Scope
Despite Being among the
Earliest to Appoint CDOs,
the Financial Services
Sector has not Fully
Expanded the Role
of the CDO
The financial services industry can
justifiably lay claim to being a pioneer when
it comes to appointing CDOs. The industry
was among the first to designate the role.
US-based bank Capital One appointed
Cathy Doss as CDO as early as 2002.
Cathy Doss is widely considered to be the
world’s first CDO10
. Today, close to 16%
of financial services firms have appointed
CDOs, outstripping many other industries
(see Figure 3)11
. However, our research
revealed that most CDOs focus on specific
aspects of data, such as compliance and
risk management, but only a handful have
mandates that extend to managing their
organization’s overall data strategy (see
Figure 4)12
.
Figure 3: CDO Appointments by Industry Sector
N = 1000
Source: Capgemini, “Big & Fast Data: The Rise of Insight-Driven Business”, March 2015
Process Oriented CDOs
concentrate on defining
data management
guidelines and controlling
their implementation, in
order to comprehensively
address compliance
demands.
16%
15%
14%
14%
11%
10%
9%
9%
7%
Financial Services
Oil and Gas
Engineering
Telecom
Healthcare
Consumer Goods
Public Sector
Media
Utilities
In addition to the Beginners, who are at the
very early stages of their data journey, we
see a range of CDO types.
Process Oriented CDOs. Most CDOs
focus on data management from a
compliance perspective. They concentrate
on defining data management guidelines
andcontrollingtheirimplementation,inorder
to comprehensively address compliance
demands. They oversee a range of
activities including the construction of data
dictionaries, master data management,
identification of critical data domains,
and integration of data quality tools with
legacy systems. These CDOs also strive
to raise awareness of data management
issues across the organization, including
confidentiality and legal aspects. They
also coordinate data management efforts
across IT, business and support functions,
laying out the relevant processes and IT
architecture necessary for an organization-
wide data management program. As the
CDO of a UK-based bank put it: “My overall
objective is to build a stronger control
framework around data.”
Close to 16% of
financial services firms
have appointed CDOs,
outstripping many
other industries.
5. 5
Value Oriented CDOs
focus on innovation
and value creation
through data, but have
limited data compliance
responsibilities.
Figure 4: Maturity of the CDO’s Role in the Financial Services Sector
Source: Focus Interviews Conducted by Capgemini Consulting in Partnership with Efma
ProcessOriented Big Data Ready
Value OrientedBeginner
Big Data Value Creation
Data Management
CDOs that have launched a few
Big Data initiatives but have not
defined a global approach.
CDOs focused on improving
data compliance and quality to
meet regulator expectations.
CDOs focused on generating
new opportunities using Big
Data. Data quality and
compliance is generally
managed by IT in these
organizations.
CDOs responsible for driving
the overall data strategy for
their organizations – comprising
data compliance as well as
value creation from Big Data.
The Office of the Process
Oriented CDO is Usually Part of a
Central Support Function
Process Oriented CDOs are usually part
of a corporate support function such
as the central risk, IT or compliance
department. They rely on a central team
with representatives in different business
units and support functions. Given this
focus on compliance, this configuration
limits the CDO’s ability to address other
business needs and priorities.
Big Data Ready CDOs
have a mandate that
includes both data
compliance as well as
value creation from
Big Data.
Value Oriented CDOs. Some CDOs
focus on innovation and value creation
through data, but have limited data
compliance responsibilities. They focus
on generating new opportunities, looking
at Big Data use-cases such as customer
behavior analysis or digital business
intelligence. However, data quality and
compliance does not fall within the scope
of their responsibilities and is generally
managed by the IT function.
Big Data Ready CDOs. Only a minority of
CDOs are responsible for their organization’s
overall data strategy. These CDOs have a
mandatethatincludesbothdatacompliance
as well as value creation from Big Data. They
identify business-critical data domains,
develop the Big Data investment strategy
Process Oriented CDOs
are usually part of
a corporate support
function focused on
compliance, which
limits their ability to
address other business
needs and priorities.
and roadmap, and prioritize initiatives. When
US-based bank Wells Fargo nominated
A. Charles Thomas as its CDO last year,
it assigned various aspects of a Big Data
Ready CDO’s role to him. Announcing
Thomas’s appointment, the bank said:
“In this new role, Thomas will oversee the
company’s data strategy, provide enterprise
data governance, and determine ways to
leveragedataforimprovedriskmanagement
and customer experiences.13
”
When we look more closely at these
different types, we also see how their
placement in the organization can constrain
their effectiveness. In particular, their ability
to take a genuine, cross-organization view
(see Figure 5).
6. 6
Figure 5: Organizational Models for Data Management
Source: Focus Interviews Conducted by Capgemini Consulting in Partnership with Efma
Value Oriented CDOs
are appointed by a
business unit, which
limits their effectiveness
beyond their own
business unit.
CorporateFunctions
CorporateFunctions
Board/
CEO
CRO*
CDO CDO
CDO
CDO
COO CIO BU Head
(1)
BU Head
(2)
Board/
CEO
CRO* COO CIO BU Head
(1)
BU Head
(2)
Board/
CEO
CRO* COO CIO BU Head
(1)
BU Head
(2)
CorporateFunctions
*CRO – Chief Risk Officer
Process Oriented Value Oriented
Big Data Ready
“ProcessOriented” CDOsbelong
to acorporate supportfunction
such asrisk, complianceorIT
“ValueOriented” CDOs
belongtoa businessunit
“BigDataReady” CDOs lead an
independentunitwith representatives
inall business unitsandfunctions
Value Oriented CDOs Usually
Reside in Business Units with a
Business-Specific Mandate
Value Oriented CDOs tend to be
appointed by a business unit. The CDO’s
office has relatively strong links to the IT
function. Multiple business units may
have their own CDOs to look after their
individual priorities. Such a configuration
limits the CDO’s effectiveness beyond
their business unit.
Big Data Ready CDOs Lead
through an Independent
Structure
Our research shows these CDOs
operating their function as a shared
services center for the entire firm, with
representatives in all business units and
functions. Within such a set up, the
CDO can collaborate effectively with
IT, business and functional leaders to
influence data governance, roadmap,
and policies and drive implementation.
7. 7
Source: Focus Interviews Conducted by Capgemini Consulting in Partnership with Efma
Figure 6: The Journey to Big Data Readiness
The Road Ahead:How Can Financial Services
CDOs Lead their Organizations towards
Big Data Readiness?
Establish Data as a
Corporate Asset with an
Enterprise-wide Data
Governance Structure
In order to build data-driven organizations,
CDOs will need to begin by ensuring
that data is recognized as a central asset
throughout the organization. This requires
a compelling vision, an expanded scope
of data governance, and a system of
accountability for data.
Align the organization around a
common vision for Big Data. CDOs
should focus on creating a compelling
vision of the role that Big Data can play in
Big Data Value Creation
Data Management
ProcessOriented Big Data Ready
Value OrientedBeginner
1
2
Recommended path for CDOs who have
developed strong capabilities around data
management. Enables “Process Oriented” CDOs
to extend their influence from managing data
quality for compliance, to applying high quality
data to address business challenges.
Recommended path for CDOs
who have a strong understanding
of the business value of Big Data.
Enables “Value Oriented” and
“Beginner” CDOs to extend their
influence from managing a limited
set of Big Data use-cases, to
rallying the organization around
large scale Big Data initiatives.
1
2
helping the organization achieve its business
objectives. They should also ensure that this
vision is communicated to leaders across
lines-of-business, in order to establish a
common understanding around the need for
data-driven decision-making.
Expand the scope of data governance.
Data governance in financial services
firms has traditionally focused on internal,
structured data. However, in a Big Data
world, CDOs will need to expand the scope
of data governance to manage data quality,
privacy and security across varied data
formats – structured and unstructured – and
from internal as well as external sources.
Establish accountability for data.
To ensure that an enterprise-wide data
governance program is effectively
implemented, CDOs will need to identify
individuals with explicit responsibility for
enforcementofdatapoliciesandprocedures.
At US-based brokerage firm TD Ameritrade,
CDO Derek Strauss worked closely with the
heads of the firm’s various business units to
identify “data officers” and “data stewards”
who were responsible for data quality and
control for their business units14
.
In addition, financial services CDOs will need
to take proactive measures to expand their
existing roles. These measures vary based
on the current maturity of the CDO’s role (see
Figure 6).
8. 8
CDOs should focus on
creating a compelling
vision of the role
that Big Data can
play in helping the
organization achieve
its business objectives.
Beginner CDOs Should
Focus on Demonstrating
the Value of Big Data
Given that most financial services
organizations have existing functions that
manage compliance requirements, we
recommend that Beginner CDOs focus
their efforts on Big Data value creation.
However, obtaining resources for large
scale Big Data initiatives can be difficult,
as it is no easy task to define a clear return
on investment. To address this challenge,
Beginner CDOs should first assess the
data landscape within their organizations
to identify existing assets and capabilities,
as well as business problems that can
be addressed rapidly through data. They
should then rollout focused, short-term
projects to address these problems.
This approach demonstrates the value
of Big Data to business leaders and
can persuade them to invest in more
ambitious initiatives.
Process Oriented CDOs
Should Focus on Creating
More Value from Big Data
Process Oriented CDOs will need to
graduate from managing data quality for
regulatory purposes, to generating value
from data.
Tackle Business Challenges
through Big Data
In order to expand their sphere of
influence beyond compliance, Process
Oriented CDOs will need to train their
sights at addressing business challenges
through effective use of data. Global
insurance major MetLife, for instance,
conducted an event that brought together
data scientists and analytics leaders from
diverse departments and business units,
with the aim of sharing best practices
and generating new ideas around the
use of Big Data. At the event, teams of
data experts worked together to identify
ways in which MetLife could address
three major challenges – new product
development, improving customer
retention and increasing operational
efficiency, by harnessing new types of
data and using Big Data technologies.15
“
Address Data Privacy Concerns
The use of data to generate customer
insights and develop new services
raises new challenges with data privacy.
As such, Process Oriented CDOs will
need to take proactive steps to protect
customer data privacy and ensure that
data usage complies with legal and
ethical frameworks. Proactively informing
customers about how their data is
used, and how they can opt-out of data
sharing, are necessary steps to safeguard
the interests of consumers. They will
also need to develop strong policies
and procedures to handle confidential
customer data with care. For instance,
removing any Personally Identifiable
Information (PII) associated with customer
data before it is used can significantly
reduce the risk of privacy breaches.
Adapt Data Sourcing and Storage
Practices for the Digital Age
To maximize the value of Big Data,
Process Oriented CDOs will need to
adapt their organizations’ data sourcing
and storage practices. Retail banks
and insurers, for instance, will need
to source data from multiple sources
including market data feeds, social
media, securities repositories, corporate
directories, credit bureaus and Know
Your Customer (KYC) utilities. In addition,
Process Oriented CDOs will also need
to develop strategies to minimize data
storage costs by identifying data that can
be stored in-house, or kept off-shore.
Process Oriented CDOs
will need to graduate
from managing data
quality for regulatory
purposes, to generating
value from data.
Proactively informing
customers about how
their data is used, and
how they can opt-
out of data sharing,
are necessary steps to
safeguard the interests
of consumers.
9. 9
Value Oriented
CDOs will need to
progressively adapt
the data management
framework to the needs
of the organization,
extending it gradually
to diverse data sets.
Value Oriented CDOs
focus on making data
available to business
teams in simple, intuitive
and easily digestible
formats that encourage
business executives to
make use of data on a
regular basis.
Value Oriented CDOs
Should Standardize Data
Management and Expand
the Scope of Big Data Usage
Establish an Enterprise-wide
Data Governance Framework to
Industrialize Big Data Initiatives
and Address Compliance
Requirements
High-quality data is a prerequisite not only
for growth, but also for compliance. As
such, Value Oriented CDOs will need to
develop a data management framework
that supports large-scale Big Data rollouts
and which also allows the organization
to meet regulatory demands. Given the
challenges of managing the high volume
and variety of data in financial services
firms, Value Oriented CDOs will need to
progressively adapt the data management
frameworktotheneedsoftheorganization,
extending it gradually to diverse data sets.
For instance, they could begin with defining
rules for the prioritization, storing and
sharing of internal data, before graduating
to external data aggregation and finally,
creating an integrated set of master data
and metadata spanning internal, external,
structured and unstructured data sources.
Actively Promote New Uses of
Data across the Enterprise
Value Oriented CDOs should look to
expand the scope of Big Data usage
beyond the limited number of use-cases
that they typically work on. To achieve
this, they should focus on making data
available to business teams in simple,
intuitive and easily digestible formats that
encourage business executives to make
use of data on a regular basis. Ali Farahani,
CDO for Los Angeles County, for instance,
is focused on making data readily available
to users: “I want to promote a model
where we look at data as a service,” he
says. “The purpose would be to make it
available to all consumers of data, to make
it more readable, in a standard format,
almost as a plug-in so that any consumer
of data in the county can access data
without worrying about what platform it is
in, without worrying about building bridges
to access that data.16
” Value Oriented
CDOs should be similarly mindful of end-
user needs, in order to achieve the shift
towards a data-driven organization.
While the road to Big Data readiness may
be challenging, it promises to lead financial
services firms towards a more secure
future. Process Oriented CDOs must
realize that Big Data initiatives demand
high quality data as they rely on drawing
linkages between internal and external
data. A mature implementation of data
management rules, tools and processes
accelerates the industrialization of Big Data
initiatives. As such, their efforts on building
data quality control mechanisms to meet
compliance requirements, also gives them
a solid foundation on which to launch Big
Data initiatives. Value Oriented CDOs, on
the other hand, may face the difficult task
of building a data management framework.
However, having demonstrated the
value of Big Data as part of their existing
mandates, they are likely to find it easier
to secure funding for a large-scale data
management program.
The perception of data has changed
fundamentally. Data is no longer just seen
as an enabler, but as an organizational
asset that is key to how financial services
firms compete, innovate and grow.
However, many financial services firms,
while realizing the opportunity at hand, are
struggling to seize it. This is why the role of
Chief Data Officer is growing in importance.
It is seen as a means to define and deliver
a coherent, enterprise-wide data strategy.
However, as we have shown, “CDO” is
simply a title. What is more important is
how organizations define the role behind
the title and what power and influence they
give the title-holder. In this paper, we have
outlined how organizations can design a
CDO role that fits with their stage of data
evolution and which maps out how a CDO
can help them achieve a step-change in
their Big Data performance. In this way,
the Data Officer will have earned their
place alongside their CMO, CFO, and CIO
colleagues in the enterprise C-suite.
10. 10
Crafting a Comprehensive Data Strategy at TD Ameritrade
In 2012, TD Ameritrade, the American online brokerage firm, appointed Derek Strauss as Chief Data Officer. When Strauss took
over, TD Ameritrade lacked a data governance group, its analytics teams were dispersed across the organization, and it relied
solely on an enterprise data warehouse. During the first six months, Strauss spent time understanding the needs of the business,
establishing the scope of his role, and charting out a data strategy for the organization. Over the next few years, he set up the
Enterprise Data and Analytics Group, brought the disparate analytics teams together, built nearly ten new technology capabilities,
and set the stage for targeting high-value business use-cases. In a recent interview, Strauss explained the five key pillars of his role:
Data Governance: Working with the heads of all lines of business to determine ownership of data. Each line of business appoints a
“Data Steward” or “Data Officer” who acts as a local champion for data control, quality, and day-to-day operations. Strauss’s team
works with them to manage and control data-related activities across the organization.
Technology Platforms: Setting up enterprise-wide platforms that allow teams across the firm to leverage data that was previously
inaccessible to them. These include a Hadoop data store, a metadata repository and reference data management system among
others.
Data Science: Building a team of data science professionals to develop best practices and demonstrate how data analytics can
be integrated with business processes.
Data Architecture: Managing data modeling, data quality, metadata management and master data management.
Data Asset Development and Maintenance: Managing the hardware and software-related aspects of the enterprise data warehouse,
the Big Data store and data virtualization.
In his role as CDO, Strauss has closely aligned TD Ameritrade’s data strategy with its business strategy. In Strauss’s words, “the
chief data officer and the data team are responsible and accountable for the four A’s of data: keep it Accurate, allow it to be
Accessible, make it Actionable, and use advanced Analytics to deliver results.”
Source: Network World, “How TD Ameritrade’s Chief Data Officer is driving change”, January 2015; The 8th Annual MIT Chief Data Officer Information Quality
Symposium, “How to Establish a CDO Office in Your Organization”, January 2014; LinkedIn, “Derek Strauss, Chief Data Officer at TD Ameritrade”, Accessed
March 2015; Hoovers, “Making Room for the Chief Data Officer”, 2014
Research Methodology
In H2 2014, Capgemini Consulting and Efma, the global non-profit association of retail financial services companies, interviewed senior
executives from financial services firms to assess the maturity of the role of the Chief Data Officer in these firms. The assessment
was based on a set of nearly 50 questions around data governance mechanisms, the roles and responsibilities of the CDO, and the
alignment of the CDO organization with business, IT and support functions.
The findings in this report are also based on two recent surveys conducted by Capgemini:
I. A survey to assess the extent to which Big Data sources and technology are being adopted across different sectors and regions
of the world. About 1,000 senior decision-makers from across nine industries including financial services, and 10 countries
worldwide took part in this survey. The study explored the impact of Big Data on businesses and markets and how the acquisition
ofdataisbreakingdowntraditionalindustryboundaries.Thestudyalsolookedathowbusinessesareadaptingtothesechanges.
II. A survey of 226 senior Big Data executives across Europe, North America and APAC, spanning multiple industries including
financial services. The survey targeted senior executives from the Analytics, Business and IT functions, who are responsible for
overseeing Big Data initiatives in their organization. Respondents were asked questions around their organization’s approach to
Big Data governance, data management, skill development, and technology infrastructure.
11. 11
1 Financial Times, “Banks pay out $100bn in US fines”, March 2014
2 Treasury.gov, Foreign Account Tax Compliance Act (FATCA)
3 Capgemini Consulting, “Cracking the Data Conundrum: How Successful Companies Make Big Data Operational”,
January 2015
4 Focus Interviews Conducted by Capgemini Consulting in Partnership with Efma
5 Capgemini, “Big & Fast Data: The Rise of Insight-Driven Business”, March 2015
6 Capgemini Consulting, “Cracking the Data Conundrum: How Successful Companies Make Big Data Operational”,
January 2015
7 Capgemini Consulting, “Cracking the Data Conundrum: How Successful Companies Make Big Data Operational”,
January 2015
8 Success rate refers to the percentage of initiatives that were either “successful” or “very successful”. An initiative was
considered to be “successful” only if it met most or all of its objectives, and “very successful” if it exceeded its objectives.
9 Capgemini Consulting, “Cracking the Data Conundrum: How Successful Companies Make Big Data Operational”,
January 2015
10 GE Software, “Rise of the CDO (Chief Data Officer)”, May 2014
11 Capgemini, “Big & Fast Data: The Rise of Insight-Driven Business”, March 2015
12 Focus Interviews Conducted by Capgemini Consulting in Partnership with Efma
13 Wells Fargo Press Release, “Wells Fargo Names A. Charles Thomas as Chief Data Officer”, February 2014
14 Networkworld.com, “How TD Ameritrade’s Chief Data Officer is driving change”, January 2015
15 InformationWeek, “MetLife Hosts Big Data Party”, October 2013
16 Govtech.com, “Chief Data Officers: Shaping One of the Newest Positions in Government”, March 2015
References
12. 12
Jerome Buvat
Head of Digital Transformation
Research Institute
jerome.buvat@capgemini.com
Laurence Chretien
Vice President,
Big Data and Analytics,
Capgemini Consulting France
laurence.chretien@capgemini.com
Christophe Le Vaillant
Managing Consultant
christophe.le-vaillant@capgemini.com
Jerome Dejardin
Senior Consultant
jerome.dejardin@capgemini.com
Stanislas de Roys
Head of Banking Market Unit,
Capgemini Consulting France
stanislas.deroys@capgemini.com
Digital Transformation
Research Institute
dtri.in@capgemini.com
Jean Coumaros
Head of Financial Services
Global Market Unit
jean.coumaros@capgemini.com
Authors
Capgemini Consulting Contacts
Global
Jean Coumaros
jean.coumaros@capgemini.com
Norway
Jon Waalen
jon.waalen@capgemini.com
United States
Scott Tullio
scott.tullio@capgemini.com
France
Stanislas de Roys
stanislas.deroys@capgemini.com
Germany/Austria/Switzerland
Christian Kroll
christian.kroll@capgemini.com
BeNeLux
Robert van der Eijk
robert.van.der.eijk@capgemini.com
Spain
Christophe Mario
christophe.mario@capgemini.com
United Kingdom
Keith Middlemass
keith.middlemass@capgemini.com
India
Natarajan Radhakrishnan
natarajan.radhakrishnan@capgemini.com
Asia
Frederic Abecassis
frederic.abecassis@capgemini.com
Sweden/Finland
Johan Bergstrom
johan.bergstrom@capgemini.com
Efma Contact
Karine Coutinho
Deputy Managing Director,
Head of Content & Partnerships
karine@efma.com
Rémi Chossinand
Managing Consultant
remi.chossinand@capgemini.com
Jacques Richer
Principal
jacques.richer@capgemini.com
Amol Khadikar
Senior Consultant, Digital
Transformation Research Institute
amol.khadikar@capgemini.com
Aurelien Grand
Principal
aurelien.grand@capgemini.com
The authors would like to thank industry participants to the study for their time and insights during interviews. The authors would also
like to acknowledge the contributions of Roopa Nambiar from Digital Transformation Research Institute and Karine Coutinho from Efma.