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Devenez expert dans la gestion de la donnée avec Rimes et Forrester

Henry PEYRETPrincipal Analyst

FORREST

Julie ACOSTAVP Sales Manager

RIMES TECHNOLOGIES

Animation RIMESSalon Élysée

Julie Acosta, MBA, CFA

VP Sales Manager

RIMES Technologies France SAS

FOR INTERNAL USE ONLY

Buy-Side Finance Firms: Plot Your

Path To Data Management MaturityForrester Consulting

Henry PeyretPrincipal Analyst

September, 2016

FOR INTERNAL USE ONLY

© 2016 Forrester Research, Inc. Reproduction Prohibited 4

Agenda

›About the Forrester/RIMES Technologies Study

› Study Results

›Recommendations


Agenda


› Study Results

›Recommandations


Executive Summary

›RIMES Technologies commissioned Forrester Consulting to

evaluate the current maturity of data management practices

at buy-side financial services organizations in April 2016.

› Forrester assessed 100 buy-side firms, and included data

users (74%) and data operations/IT professionals (26%).

› Forrester used its existing, proven data management maturity

methodology, re-purposing it for buy-side finance firms.

›We classified respondents into four levels of data

management maturity:

1. Data experts

2. Data strategists

3. Data managers

4. Data tacticians


Data managers: 24% Data experts: 10%

Data strategists: 26%Data tacticians: 40%

Data

execu

tio

n

Data strategy

Only 10% of Buy Side Finance are Data experts

Base: 100 Managers or above with assets under management greater than $10bn, 45% NA, 45% EMEA and 10% APAC

Source: A commissioned study conducted by Forrester Consulting on behalf of RIMES Technologies, April, 2016

Data Strategy

Business alignment

Data Governance

Measurement and metrics

Data Execution

Processes

Organization

Data delivery and use


Agenda


›Study Results

›Recommandations


Buy-side Firms Face Many Data Management And Governance Challenges

Base: 100 data users and data operations/IT professionals at buy-side financial services organizations

Source: A commissioned study conducted by Forrester Consulting on behalf of RIMES Technologies, April 2016

31%

25%

20%

19%

19%

18%

22%

21%

21%

19%

21%

15%

15%

Lack of analytics toolsto process data

Suboptimal dataarchitecture

Outdated and legacyhardware

Integrating new solutions/applications with existing

technology set

Lack of data reportingtools and dashboards

Outdated data reportingtools and dashboards

Inability to manage variety of datatypes and formats

Too many processes and stake-holders require access to the data

Processes are controlled by IT,and business users can’t interact

directly with the data

Inability to handle large datavolumes (both internal and

external data sources)

Data is siloed in separate systemsacross various departments

Unclear business priorities fromcompany leadership

Lack of expertise andskilled personnel

“What are you firm’s biggest challenges toaccomplishing these goals?”

(Select all that apply)

Technology and architecture

Operational management

Organizational alignment


Challenges, continued



31%

25%

20%

19%

19%

18%

22%

21%

21%

19%

21%

15%

15%





technology set

















31%

25%

20%

19%

19%

18%

22%

21%

21%

19%

21%

15%

15%





technology set


















Agenda


› Study Results

›Recommendations


Insights From Experts:

Data

experts

Data strategy 3.21

Business

alignment2.92

Data

governance3.36

Measurement

and metrics3.32

Data execution 3.06

Process 2.98

Organization 2.95

Delivery and

use3.15

6 out 10 experts: “Continuous collaboration between centralized data management

function / IT and business to align data capabilities to business needs, outcomes, and

timetables”

5 out 10 experts: “Our organization has an executive data governance committee and

satellite business unit data governance teams where IT / data management and business

are equally responsible and accountable for data value.”

4 out 10 experts: “We have real-time activity, compliance, and business value visibility that

communicates data value and conditions across, business impact, data governance, and

data management metrics and KPIs using data governance tools, BI, and data discovery

tools.”

3 out 10 experts: “We proactively outreach to business stakeholders to ensure we easily

adjust resources and plans to shifts in strategic, project, and adhoc priorities.”

5 out 10 experts have a CDO responsible for data strategy and governance

4 out 10 experts: “We provide a wide range of self-service data visualization and data

preparation capabilities to prototype data”


Follow The Path To Data Management Maturity



Data managers Data experts

Data strategistsData tacticians

Da

taexe

cu

tio

n

Data strategy


Priorities And Challenges Vary By Maturity

Data management priorities Data management challenges

Digital Tacticians • Improve business planning

• Monitor process performance

• Inability to management variety of data types

and formats

• Lack of analytics tools to process data

Digital Managers • Monitor process performance

• Support for business change

programs


• Inability to manage variety of data types and

formats

Digital Strategists • Improve business planning

• Increase competitive

advantage


• Data is siloed in separate systems across

various departments

Digital Experts • Expand the scope of data we

leverage

• Support for business change

programs

• Outdated and legacy hardware

• Processes are controlled by IT and business

users can’t interact directly with the data

• Data experts and strategist have invested more heavily in technology that holds business policies and

definitions. Strategists emphasize reference data management over data delivery

• Managers recognize that data needs alignment with business expectations and invests in quality and

metadata tools to improve data integration and delivery.

• Tacticians emphasize data integration and invest in mapping and transformation technologies to improve

integration processes.


Actions For Boosting Data Management Maturity

Based on learnings from data experts, organizations should boost

their data management by:

› Connect governance activities and data metrics to the use of data (data

delivery and services)

› Moving from Data Tacticians to Data Managers means building out the

organization to scale out data delivery and services and introduce data

governance activities to improve connections with the business

› Data Managers transition to Data Strategies by adopting operational and

business metrics

› Data Strategists can achieve Expert status through pragmatic

introduction of governance enablement in data delivery services and

support of technology management in prioritization and deployment of

those services.


Data Governance becomes more dynamic over the Data Management Continuum

Data

Collection

Data

Aggregation

Data

Usage

External

Sharing

Data Management Continuum

Data Governance Focus

Policies and data set preparation feedback, open

collaboration

Feedback and continuous adjustment

Metadata,basic lineage, quality rules,

security and compliance policies

Business Glossary, data

context, advanced lineages


Key Recommendations

› Master data measurement.

› Recognize how the organization

is aligned to data projects.

› Provide data to end users in

repeatable, scalable, self-service

ways.

› Turn data governance into

business as usual.

© 2012 Forrester Research, Inc. Reproduction Prohibited

Different governance objectives for different “system of”

Systems of

engagement

Systems of

recordSystems of

automation

System of

Insights Stakeholders : Back Office

Governance Objectives :: 100%

data quality, compliance, cost

savings, trust reports

Stakeholders : Front Office

Governance Objectives: :

Multiviewpoint, Agility, TTM, Risks

Stakeholders : Operations

Governance Objectives: Data

Context, interoperability, reactivity,

decrease costs of operations


Summary

› Data management maturity really matters to your bottom line.

› The three key areas that are driving data management expertise are:

• Data delivery and use

• Data measurement and metrics

• Data governance.

› The experts realize that data management is not just about getting data

from source to target but understanding it is for a specific purpose and

context. With quicker access to contextually relevant insights, data users

are able to make better decisions to optimize their investment

management and operations processes

Thank you

forrester.com

Henry Peyret

[email protected]


Executive Summary

›RIMES Technologies commissioned Forrester Consulting to

evaluate the current maturity of data management practices

at buy-side financial services organizations in April 2016.

› Forrester assessed 100 buy-side firms, and included data

users (74%) and data operations/IT professionals (26%).

› Forrester used its existing, proven data management maturity

methodology, re-purposing it for buy-side finance firms.

›We classified respondents into four levels of data

management maturity:

1. Data experts

2. Data strategists

3. Data managers

4. Data tacticians


Only Ten Percent Of Firms Were Data Experts

›Regularly exceed profitability targets.

›Have the fastest growing assets

under management (AUM) in the

industry.

›Deliver exceptional customer

experiences.

›Data experts direct data from a

strategic vantage point of business

outcomes while executing data

management operations in line with

business data demand.

Data experts:


Data Experts, continued

›Have overcome data silos.

›Can link business processes and

decisions to data.

› Are exploring ways to deliver

continuous improvement.

›Stood out in their data measurement

and metrics ability, business

alignment, and data governance

effectiveness.


Major Study Findings

› Firms are leveraging data

management to support strategic

business objectives.

›Buy-side firms struggle with

technology and data deficiencies.

›Buy-side firms must take a holistic

view of data management.

›Enhancing measurement

capabilities underpins data

management maturity.

› The paths to data management

maturity are clear.


Survey Demographics: Country And Industry

North America

45%

EMEA45%

APAC10%

Base: 100 Managers or above with assets under management greater than $10bn, 45% NA, 45% EMEA and 10% APAC


“”In which country are you located?”’

Greater than $10b but less than

$29b; 19%

Greater than $30b but less than $49b; 6%

Greater than $50b but less than $99b; 6%Greater than

$100b but less than

$499b; 42%

Over $501b; 27%

“Using your best estimates, what is the value of your assets

under management (AUM) for your most recently concluded

accounting year?


Survey Demographics: Financial Services Industry

74%

29%

23%

17%

17%

15%

15%

14%

12%

11%

8%

8%

5%

4%

Investment/asset management

Wealth management

Insurers

Private banking

Investment bank

Hedge fund

Pension fund

Commercial banking

Credit card issuers

Credit unions

Consumer lending

Mortgage and nonmortgage loan brokers

Custodian bank/asset servicers

Management of companies and enterprises

Base: 100 Managers or above with assets under management greater than $10bn


“To which financial service industry would you say that your firm/organization belongs?” (Select all that apply)


Survey Demographics: Number Of Employees And Revenue

13%

33%

24%

23%

500 to 999

1,000 to 4,999

5,000 to 19,999

20,000 or more

Base: 100 Managers or above with assets under management greater than $10bn


“How many employees work for your organization?

1%

19%

10%

20%

50%

$100 - $199m

$200 - $499m

$500 - $999m

$1bn - $2bn

$2bn+

“Using your best estimate, what is the

approximate annual revenue?”


Data Management Practice Maturity Highly Correlated With Business Success

38%

48%

Profitability / operatingmargin goals: We

easily exceed or meetour goal everyquarter/period

AUM growth rate: Weare the fastest growing

/ among the leaders

Data experts Data tacticians

“In your opinion how does your profitability and AUM

growth rate compare with others in the industry?”

6 out of 10

8 out of 10

Base: 100 data users and data operations/IT professionals at buy-side financial services organizationsSource: A commissioned study conducted by Forrester Consulting on behalf of RIMES Technologies, April 2016


78%

50%

47%

41%

40%

Improve business planning

Monitor process

performance

Support for business

change programs

Enhance information value

Protect brand reputation/

customer trust

“Which of the following are your organization’s top

goals for data management?”

(Showing responses ranked first)

Improving Business Planning Is The Top Goal For Data Management




Characteristics Of The Maturity Levels

Data tacticians Data managers Data strategist Data experts

Data strategy 54% 55% 73% 80%

Business alignment 55% 51% 63% 73%

Data governance 56% 61% 73% 84%

Measurement and metrics 52% 54% 82% 83%

Data execution 51% 72% 54% 77%

Process 60% 66% 59% 75%

Organization 52% 75% 54% 74%

Delivery and use 47% 75% 52% 79%

Weak Strong

Scale: Percentages were calculated using the capability score divided by 4 (the maximum score available).Base: 100 data users and data operations/IT professionals at buy-side financial services organizationsSource: A commissioned study conducted by Forrester Consulting on behalf of RIMES Technologies, April 2016

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Devenez expert dans la gestion de la donnée avec Rimes et ... · Base: 100 Managers or above with assets under management greater than $10bn, 45% NA, 45% EMEA and 10% APAC Source: