2017 Data Management Benchmark Results Available In Pellustro

The EDM Council released the results of the 2017 Data Management Benchmarking Survey.

This marks the 2nd survey, after the introduction of the DCAM Data Management Benchmark in 2015. The DCAM Data Management Benchmark enables for the first time the measurement of progress for the establishment data management capabilities by the financial industry.

The survey is based on the Data Management Capability Assessment Model (DCAM) and includes responses from over 150 financial organizations across the global financial industry for the following 22 questions:


A Setting Up the Data Management Program
1 Our organization has a defined and endorsed data management strategy
2 The goals, objectives and authorities of the data management program are well communicated
3 The data management program is established and has the authority to enforce adherence
B Obtaining Commitment from Stakeholders
4 Stakeholders understand (and buy into) the need for the data management program
5 The funding model for the Data Management Program is established and sanctioned
6 The costs of (and benefits associated with) the Data Management Program are being measured
7 The data management program is sufficiently resourced
8 Data management operates collaboratively with existing enterprise control functions
C Implementing Operational Governance
9 Data governance structure and authority is implemented and communicated
10 Governance “owners” and “stewards” are in place with clearly defined roles and responsibilities
11 Data policies and standards are documented, implemented and enforced
12 The “end user” community is adhering to the data governance policy and standards
13 The business meaning of data is defined, harmonized across repositories and governed
14 Critical data elements are identified and managed
15 Logical data domains have been declared, prioritized and sanctioned
16 End-to-end data lineage has been defined across the entire data lifecycle
17 Technical architecture is defined and integrated
D Control Processes for Data Quality
18 All data under the authority of the Data Management Program is profiled, analyzed and graded
19 Procedures for managing data quality are defined, implemented and measured
20 Root cause analysis is performed and corrective measures are being implemented
E Collaboration with Information Technology
21 Technology standards and governance are in place to support data management objectives
22 The data management program is aligned with internal technical and operational capabilities

*22 DCAM Statements defined by the EDM Council

Data from the EDM Council’s 2015 and 2017 DCAM Data Management Benchmarking Survey can now be accessed and analyzed at no cost in PellustroTM – Element22’s cloud-based platform for DCAM assessments and benchmarking.

Follow this link https://benchmark.pellustro.com to access the results of the survey.

Within PellustroTM you will be able to compare the Data Management Benchmark between 2015 and 2017, but also  filter and compare results by region, tier and firm type, state of data governance, age of data management program, data management drivers and where data management program resides and by participant role or title.

With DCAM and the DCAM Data Management Benchmark, the EDM Council ensures consistent measurement of data management programs, enabling firms to compare themselves with the industry, peers or any other grouping listed above.

Existing Pellustro clients have full access to premium features and can already benchmark their capability against the state of the industry with their existing accounts.

New users have the opportunity to upgrade from the free access to perform their own DCAM Sentiment and DCAM Capability Assessments and compare their scores with the industry and custom peer groups.

A detailed guide on how you can navigate the 2015 and 2017 Data Management Benchmarks with Pellustro can be found in the Pellustro Blog.

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About Thomas Bodenski

At Element22, Thomas' focus is on simplifying work life by improving the maturity of data management organizations, or by transforming financial institutions into analytical innovators and data-driven organizations.

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