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Assessment Date: 7/12/2011
Data Governance: Data Integration Technology Readiness Self-Assessment
Step 1 Within each of the 6 major categories, please enter the % priority weighting for each Data Governance
Readiness Score Weighted
Category Category Name Question % Priority Raw Score
Score
1 3 5
1. Data Accessibility: Provide Access to All Data Types and Formats
How do you integrate different types of data, Our data integration tool is primarily The platform supports access to both We have one common tool that
including mainframe, structured, unstructured for integrating relational data. For structure and semi-structured formats. supports all these data types in an
1 Supported Data Types (e.g., Word documents and spreadsheets), other data types, like mainframe, we We have manual or hand-coded automated fashion, with common 30% 1 0.3
XML and EDI, relational, application, and use scripts and hand-code to get at mechanisms to access unstructured metadata.
message queue data? the data. data.
How do you connect to specific applications, For a lot of our systems, we write Our tool has pre-built connectivity for Our platform has pre-built connectivity
systems, and data sources? custom code to establish connectivity. common systems such as relational to a wide variety of systems, including
databases, SAP, Siebel, and multiple mainframe formats,
2 Pre-built Connectivity BusinessObjects. messaging systems, and numerous 30% 3 0.9
applications.
How do you validate both input and output Our current system does not have The platform validates and reports on The platform validates input/output
Input/Output Data data from all data sources and targets? data input/output validation capability. the input and output data. data, and aids in the development of
3 25% 3 0.75
Validation metadata model.
How do you detect and record data access We log events in the various systems Our data integration tool provides Our data integration tool provides
events including exceptions and failures? and inspect the logs as needed. basic failed session statistics and failed session statistics, error
4 Event Logging error messages. messages, metadata statistics, and 5% 3 0.15
lineage that helps assess the
exceptions and failures.
How do you provide federated access to data? We don't federate data access; we We have a tool that can provide We have one common tool that
physically move or replicate data as federated access to data in-memory. provides both physical and
5 Federated Access needed. It's separate from our physical data virtual/federated access to data. 5% 1 0.05
integration tool.
How do you move data across firewalls, Most of our data movement is within Our tool can move data through Our tool supports secure, highly
irrespective of geographic or functional our own firewalls. firewalls, but security and performant data movement across
6 Cross-firewall Access boundaries? performance are not as good as they firewalls. 5% 1 0.05
should be.
100% 2.2
Created by Informatica Corporation Page 1 Rev June 6, 2006
Assessment Date: 7/12/2011
Readiness Score Weighted
Category Category Name Question % Priority Raw Score
Score
1 3 5
2. Data Availability: Deliver Data Reliably, When and Where Needed
How do you maximize the rate at which your We manually tune our processing and Our tool supports partitioning and Our tool makes it easy to configure
system can process data? workflows to try to increase parallelism, but it requires a lot of multiple performance enhancement
7 Throughput throughput. We can't easily support manual coding and the configuration options including pipelining, dynamic 10% 3 0.3
partitioning. is very cumbersome. partitioning, and smart parallelism.
How do you scale your system to meet We add more hardware to support Our tool takes advantage of 64-bit Our tool takes advantage of 64-bit,
growing demands? growing data volumes, but we're processing to improve scalability. thread-based parallel processing and
8 Scalability getting diminishing returns. grid deployment for near-linear 10% 3 0.3
scalability.
How do you manage failover and recovery We follow a process guideline for Our tool has automatic failover and Our tool has automatic failover and
should your system go down? failover scenarios. Recovery is done recovery capabilities. recovery capabilities, including grid
Automatic Failover and manually. deployments, and provides graphical
9 30% 3 0.9
Recovery status on the grid and other key
indicators.
How do you ensure continuous availability of We do our best to ensure our Our tool supports high availability Our tool enables us to easily
your data? hardware and software stay up and using multiple nodes, but it's very time- configure high availability including
10 High Availability running. We aren't really configured consuming and difficult to configure built-in resiliency, automatic failover 30% 3 0.9
for true high availability across and manage. and recovery, and multi-node/grid
multiple nodes on a grid. deployment.
How do you configure your system to address We do most of our processing on a We have different tools that support We have one common tool which
data with different volume and timing scheduled batch basis. batch vs. message-based delivery. allows data volumes and latencies to
requirements-- from event-driven, message- Our processes have to be recoded be configured to meet business
11 Volume and Timing 15% 3 0.45
based delivery to net-changed to scheduled, and/or recompiled to work in different needs, without any recoding.
large-volume batch delivery? latency modes.
How do you configure your system to deliver We have to recode to handle different We have different tools that support We have one tool that supports all
data via different protocols and methods, protocols and methods based on different data delivery protocols and types of delivery protocols and
including loading physical databases for SQL- project needs. methods. methods via configuration, without
Breadth of Delivery based access, creating virtual data views requiring recoding.
12 5% 3 0.15
Protocols (EII), publishing to a message bus or queue,
and publishing Web Services?
100% 3
Created by Informatica Corporation Page 2 Rev June 6, 2006
Assessment Date: 7/12/2011
Readiness Score Weighted
Category Category Name Question % Priority Raw Score
Score
1 3 5
3. Data Quality: Ensure Accurate, Validated Data
How do you currently profile and understand We run SQL queries and/or scripts We use a dedicated tool to profile We have a tool to profile source data
13 Profiling your data? against the data on an ad hoc basis. data sources and detect potential data that integrates with our data quality 40% 3 1.2
quality issues. remediation and monitoring tools, and
How do you monitor and measure the quality We only check data quality on an ad our monitor key data quality
We have established a few key data We data integration tools. metrics
Monitoring and of your data? hoc basis. We don't us formal metrics quality metrics, but they're not on an ongoing basis and receive
14 or conduct ongoing monitoring. systematically monitored. alerts on items that fall out of 20% 1 0.2
Measurement
acceptable ranges.
How do you cleanse your data and remediate Each time a data quality issue is We have a data quality tool where we We have an automatic capability for
data quality issues, such as accuracy, raised, we address it on a one-off can define business rules to address remediating data quality issues, which
15 Cleansing and Remediation completeness, conformity, integrity, basis, usually via hand-coding or quality issues. also provides historical statistics to 10% 1 0.1
consistency, and duplication? manual scrubbing of data. help root cause analysis.
What types of data are supported by your We do not have specific data quality Our data quality tool is primarily All of our key data types (e.g.,
data quality tools? tools. We address data quality on an focused on name and address data. customer, product/service, financial,
16 Breadth of Data ad hoc basis. employee, etc.) are supported by our 10% 3 0.3
data quality tool.
How easy is it for your business analysts, The business folks have to ask IT to We have a data quality tool, but it's Our data quality tool provides an easy-
data stewards, and other business-oriented run queries for them, and they rely on really designed for IT users. Our to-use interface to enable both
users to understand and address data quality spreadsheets and other manual tools business users can't work with it. business and IT users to visualize and
17 Ease of Use issues? to define data quality business rules. address data quality issues. 15% 5 0.75
How do ensure that your data quality logic We define business rules in We have a data quality tool that The metadata for our data quality
and business rules can be captured as spreadsheets and other manual generates metadata, but it's siloed processes is captured automatically
18 Integrated Metadata metadata and shared with other data documents, so there's no easy way to from our broader data integration and is seamlessly incorporated as 5% 3 0.15
integration processes? share and reuse those rules. framework and other metadata. part of our overall data integration
lifecycle.
100% 2.7
Created by Informatica Corporation Page 3 Rev June 6, 2006
Assessment Date: 7/12/2011
Readiness Score Weighted
Category Category Name Question % Priority Raw Score
Score
1 3 5
4. Data Consistency: Reconcile Data Values, Structure, and Semantics
How do you validate your data models and We manually review documentation We use a design tool to validate our We use a metadata-driven, integrated
relationships? and run queries to validate our data design and mapping. design and mapping tool that
19 Validation model. automatically validates the data model 20% 3 0.6
on-the-fly.
How do you transform data to reconcile both We hand-code scripts to transform We have a tool with a variety of pre- We have a tool with robust
syntactic and semantic variances across data to resolve syntactic differences built transformations that we can transformation capabilities that
different data structures? across systems. leverage. We largely focus on addresses not only syntactic issues,
20 Transformation syntactic and structural issues. but also structural and semantic 20% 5 1
variances across different systems.
How do you manage your business rules and We implement scripts and other types Our data integration tool generates We use a metadata-driven data
workflows at the logical and the physical of coding to apply business rules, so code to create data integration rules integration tool that deals with all
Logical Design and levels? the logical and the physical design are and manage workflows. design and business rules at the
21 15% 5 0.75
Workflow one in the same. logical level, abstracting them from
the physical layer.
How do you share and reuse business rules, We hand-code scripts to deal with Our tool creates transformation We have one tool that captures all our
workflows, etc? data integration, so it's not easy to mappings and workflows that can be data integration and data quality logic
22 Reusability share the code. reused. and workflows as metadata and 10% 1 0.1
enables sharing at both local and
global levels.
How do you catalog, search and filter Our business rules and relationships We have a basic metadata repository We have a metadata-driven tool so
business rules, entity relationships, and are scattered in different tools and where we try to centralize rules, we can easily search, filter, define,
23 Cataloging domain values in your data integration systems. There is no centralized relationships, etc. and modify data dictionaries and 15% 5 0.75
environment? location for them. business rules.
How do you synchronize data across multiple We have built point-to-point We use EAI and messaging We use a combination of data
systems to ensure consistency? integration between systems to keep technology to keep data synchronized integration and EAI/messaging
data in synch. in real time. technologies to ensure consistency in
24 Synchronization 20% 1 0.2
both context and meaning, as well as
data values.
100% 3.4
Created by Informatica Corporation Page 4 Rev June 6, 2006
Assessment Date: 7/12/2011
Readiness Score Weighted
Category Category Name Question % Priority Raw Score
Score
1 3 5
5. Data Auditability: Establish Audit Trails and Internal Data Controls
How do you show the lineage of data across We review documentation and We have a metadata repository that We have a metadata management
multiple systems and applications, including interview the different system owners helps infer data relationships across tool that graphically displays data
25 Lineage both backward and forward tracking? to try to figure out the data lineage. systems and applications. lineage, with drill-down capabilities. 30% 5 1.5
How do you predict and document the impact We review documentation and Our tool provides metadata and Our tool provides reports on port
of changes across applications and systems? interview the different system owners metadata extension usage reports details, metadata extensions and
26 Impact Assessment to try to figure out the impact of that specify high-level usage across usage, and mapping dependencies 20% 5 1
changes, and then we document them. connected systems. across connected systems.
How do you design and manage workflows We rely on email and shared file Our tool has basic data integration Our tool has robust workflow
for your data integration processes? folders to manage our workflows. workflow design and management orchestration capabilities including
capabilities. support for grid deployments and
27 Workflow 20% 3 0.6
global, cross-team collaboration.
How do you monitor operational statistics and We review the logs and share process Our tool provides a dashboard with a Our tool provides a dashboard with
28 Dashboard provide visibility into exceptions? statistics across the team via high-level summary of workflows, the ability to easily drill down into the 10% 3 0.3
manually-generated reports. processes and status. details.
How do you detect invalid mappings and We run tests to detect errors using a We have a test environment within We have an integrated test
failed sessions? separate tool. our data integration tool to detect environment that helps identify the
29 Testing mapping and session errors. We then root causes of invalid mapping and 5% 3 0.15
run queries for root cause analysis. session errors as part of our data
integration tool.
How do you control and manage different We check dates and timestamps on We rely on a software change Our data integration tool has robust,
versions of your rules and workflows? our data integration code and management tool like Rational to granular version management and
30 Version Control workflows to track versions. manage different versions generated deployment capabilities built in. 15% 1 0.15
by our data integration tool.
100% 3.7
Created by Informatica Corporation Page 5 Rev June 6, 2006
Assessment Date: 7/12/2011
Readiness Score Weighted
Category Category Name Question % Priority Raw Score
Score
1 3 5
6. Data Security: Secure Access to Data
How do you classify data based on its Each group makes its own decisions The tool provides a mechanism to The tool supports an enterprise-wide
sensitivity, priority, and usage patterns? about how and whether they classify classify information by data type, strategy on information classification,
31 Data Classification their data, so there's no common priority, usage, locations and user enabling data to be easily grouped 15% 3 0.45
framework. access within specific business areas. and classified.
How do you keep duties or areas of We assign different areas of The tool has a well-defined workflow The tool enables granular segregation
responsibility separate for different users to responsibility to different users, but it's manager and admin functions to of duties, as well as reporting on
32 Segregation of Duty reduce the risk of unauthorized modifications pretty high level and there's no built-in separate tasks for different users. interdependencies of different tasks. 15% 1 0.15
or misuse of data? way to enforce it.
How do you restrict and enforce controls over We assign different privileges to The tool supports user- and role- The tool has robust privilege
the use of features and access to data by different users, but it's not very based privilege management to management capabilities for
different users and administrators? granular and there's no built-in way to manage access to data and key managing and reporting on granular
33 Privilege Management enforce it. features. privileges such as copy object, 25% 3 0.75
maintain labels, and change object
status.
How do you support user authentication The tool has an independent user The tool integrates with LDAP to The tool integrates tightly with LDAP
34 Client Authentication against external lightweight directory access management service and does not ensure appropriate user and has a repository to track the real- 15% 3 0.45
protocol (LDAP)? integrate with LDAP. authentication. time authentication status.
How do you manage Web Services security We're not yet addressing Web Our tool supports SSL and certificate- Our tool supports the latest Web
for data integration? Services security. based Web Service security. Services security standards at both
35 Web Services Security the message and transport layers for 20% 3 0.6
authentication, encryption and
authorization.
How do you securely transmit data? We currently do not transport data in Our tool supports transmission of data Our tool supports encryption and
encrypted format. in encrypted format. secures synchronization across
36 Encryption firewalls leveraging built-in security 10% 5 0.5
with encryption and compression.
100% 2.9
TOTAL SCORE 17.9
OUT OF A MAXIMUM 30
Created by Informatica Corporation Page 6 Rev June 6, 2006
Assessment Date: 7/12/2011
RESULTS of Data Governance: Data Integration Technology Readiness Self-Assessment
Attribute
Attribute Rating Interpretation & Recommendation
Data Accessibility 2.2 You scored low in Data Accessibility, which means that users may have difficulty accessing all
the data they need. You should evaluate more automated approaches to accessing different
types of data. Specifically, consider PowerExchange and PowerCenter Connect Options.
Data Availability 3.0 You scored medium in Data Availability, so much of your data is typically available as needed
by users. However, you may want to evaluate enhancements such as ensuring High
Availability of your critical data, or ensuring that different latencies and volumes are supported
in one common platform. Specifically, you might consider implementing PowerCenter High
Availability Option, or taking advantage of database processing capacity with Pushdown
Optimization.
Data Quality 2.7 You scored low in Data Quality, which means that users may have little confidence in the
data, and your business may be experiencing avoidable errors and duplications. You should
evaluate ways to address data quality issues in a programmatic fashion, leveraging data
quality tools to help automate the process. Specifically, you can start by assessing your
current state with Informatica Data Explorer, and implementing a focused program such as
name and address cleansing with Data Cleanse and Match Option.
Data Consistency 3.4 You scored medium in Data Consistency, so you have likely resolved basic consistency
issues such as syntactic and structural differences between systems. To continue to improve
consistency, you should ensure that you are using a metadata-centric approach, to address
semantic issues and to ensure consistency by capturing business logic in a common glossary
or repository. Specifically, you may consider PowerCenter Advanced Edition, which includes
Metadata Manager for enhanced metadata capabilities.
Data Auditability 3.7 You scored medium in Data Auditability, so you have a good start on ensuring that your data
is well documented and properly controlled. You should continue to leverage metadata for
data lineage and enable impact analysis. You should also look to tools that enable cross-
enterprise visibility and collaboration, with robust dashboard and version management
capabilities. You can take advantage of the Metadata Manager, Data Analyzer and Team-
based Development capabilities in PowerCenter Advanced Edition.
Data Security 2.9 You scored low in Data Security, which means your data has a high risk of being
compromised. You should ensure that you are using a tool that manages and secures access
to your data, and appropriately encrypts the data. You can consider PowerCenter which has
built-in data encryption and fine-grained access control capabilities.
OVERALL 17.9 Overall, you scored low on the readiness of your data integration infrastructure to support your
data governance program. It will be difficult to ensure the ongoing success of your
governance program without additional investment in your infrastructure. You should evaluate
your data governance goals and priorities, and look to tools to help automate data integration
to ensure key data attributes such as quality, availability, and auditability.
Created by Informatica Corporation Page 7 Rev June 6, 2006
Assessment Date: 7/12/2011
RESULTS of Data Governance: Data Integration Technology Readiness Self-Assessment
Data
Accessibility
4
3
Data Security 2 Data Availability
1
0
Data
Data Quality
Auditability
Data
Consistency
Created by Informatica Corporation Page 8 Rev June 6, 2006
Data Governance: Business Value of Data
Step Go to the "Value-Revenue", "Value-Cost" and "Value-Risk" tabs for ideas on ome typical ways in which data
1 impacts business value.
Step For the value areas that are relevant to you, identify the appropriate key business metric(s) for your
2 organization and estimate the impact of improving data integration and governance on those metrics. Feel
free to change the categories to tailor them to your organization.
Step Use this sheet to summarize the key metrics and estimated impact, and to share with your organization for
3 further discussions.
Business Value Category Explanation Key Metrics Estimated Impact
A. INCREASE REVENUE
1 New Customer Acquisition Lower the costs of acquiring new customers
2 Cross-Sell / Upsell Increase penetration and sales within existing customers
3 Sales and Channel Management Increase sales productivity, and improve visibility into demand
4 New Product / Service Delivery Accelerate new product/service introductions, and improve "hit
rate" of new offerings
5 Pricing / Promotions Set pricing and promotions to stimulate demand while improving
margins
B. LOWER COSTS
6 Supply Chain Management Lower procurement costs, increase supply chain visibility, and
improve inventory management
7 Production & Service Delivery Lower the costs to manufacture products and/or deliver services
8 Logistics & Distribution Lower distribution costs and improve visibility into distribution
chain
9 Invoicing, Collections and Fraud Improve invoicing and collections efficiency,and detect/prevent
Prevention fraud
10 Financial Management Streamline financial management and reporting
C. MANAGE RISK
11 Compliance (e.g. SEC/SOX/Basel II/ Prevent compliance outages to avoid investigations, penalties,
PCI) Risk and negative impact on brand
12 Financial/Asset Risk Management Improve risk management of key assets, including financial,
commodity, energy or capital assets
13 Business Continuity/ Disaster Reduce downtime and lost business, prevent loss of key data,
Recovery Risk and lower recovery costs
eeea6930-beca-424e-9860-b1e79b8244d1.xls Value of Data Page 9
Examples of Key Capabilities by Data Attribute
A. INCREASE REVENUE Explanation Typical metrics Data Integration Examples Quality Consistency Auditability Security Accessibility Availability
1 New Customer Lower the costs of - cost per new - Marketing analytics Customer targeting Sharing of correlated Predict the impact of Secure access to Cross-firewall Accelerated
Acquisition acquiring new customer acquisition - Customer data quality and on-boarding customer data with changes, e.g. valuable customer access to third party delivery of sales lead
customers - cost per lead improvement based on accurate sales and third party switching credit lead, financial and customer data e.g. data to appropriate
- # new customers - Integration of 3rd party data customer/prospect/ channels to reduce bureaus or other information credit bureaus, channels
acquired/month per (from credit bureaus, directory market data channel conflict and implementing a new address directories,
sales rep or per services, salesforce.com, etc.) duplication marketing sytem list brokers, etc.
office/store
2 Cross-Sell / Upsell Increase penetration - % cross-sell rate - Single view of customer Accurate, complete, Single view of Improve governance Customer data Opportunity Real-time customer
and sales within - # products/customer across all products, channels de-duplicated customer reconciling of customer master privacy and security identification with analytics enabling
existing customers - % share of wallet - Marketing analytics & customer data to differences in data by maintaining assurance to protect integrated access to tailored cross-selling
- customer lifetime customer segmentation create single view business definitions & visibility into definition customers and CRM, SFA, ERP and at customer
value - Customer lifetime value structures across of and changes to comply with others touchpoints
analysis groups data regulations
3 Sales and Channel Increase sales - sales per rep or per - Sales/agent productivity Completeness and Alignment of Provide traceability Secure access for Incorporation of Continuous
Management productivity, and employee dashboard validity of sales channel/sales for demand and partners/distributors revenue data, availability of lead,
improve visibility into - close rate - Sales & demand analytics activity, pipeline and incentives based on revenue reports to share sensitive internal or external pipeline and revenue
demand - revenue per - Customer master data demand data consistent sales through data lineage demand and revenue SFA data, and data in data to sales,
transaction integration productivitydata information forecast partners and channels
- Demand chain synchronization spreadsheets
4 New Product / Accelerate new - # new products - Data sharing across design, Accurate, de- Consistent Ensuring compliance Improved Access to data in Distributed, round-
Service Delivery product/service launched/year development, production and duplicated product application of with product collaboration on both applications/ the-clock
introductions, and - new product/service marketing/sales teams design and product and service regulations through prototyping, testing systems as well as environment for
improve "hit rate" of launch time - Data sharing with 3rd parties development data definitions and version control and and piloting through design documents collaborative data
new offerings - new product/service e.g. contract manufactuers, across functional and descriptions across view of lineage secure data sharing sharing
adoption rate channels, marketing agencies, geographical functions and with
etc. boundaries partners
5 Pricing / Promotions Set pricing and - margins - Cross-geography/cross- Complete, accurate Global/cross- Rationalization of Segregation of Holistic pricing Real-time pricing
promotions to - profitability per channel pricing visibility product pricing and functional pricing and improved differential pricing management based data to enable
stimulate demand segment - Differential pricing analysis discount/ profitability reconciliation of record keeping for and promotions data on data from constant monitoring &
while improving - cost-per-impression, and tracking data pricing and price changes for different applications, on-the-fly pricing
margins cost-per-action - Promotions effectiveness promotions data customers, channels, including pricing adjustments based
analysis etc. spreadsheets on demand
eeea6930-beca-424e-9860-b1e79b8244d1.xls Value- Revenue Page 10
Examples of Key Capabilities by Data Attribute
B. LOWER COSTS Explanation Typical metrics Data Integration Examples Quality Consistency Auditability Security Accessibility Availability
6 Supply Chain Lower procurement - purchasing discounts - product master data De-duplicated, Reconciled view of Improve governance Encrypted data Access to EDI and Real-time supply
Management costs, increase supply - inventory turns integration complete view of purchases across all of product master data exchange with unstructured data chain management,
chain visibility, and - quote-to-cash cycle - demand analysis products and suppliers to improve by maintaining extended network of (typically in aligned with just-in-
improve inventory time - cross-supplier purchasing materials data to purchasing visibility into definition suppliers/distributors Excel/Word) from time production models
management - demand forecast history improve supply chain effectiveness & of and changes to data suppliers/distributors
accuracy efficiency negotiation stance
7 Production & Lower the costs to - production cycle times - cross-enterprise inventory Improved planning Reconciled product Ensure compliance Role-based access Integrated access to Near real-time
Service Delivery manufacture products - cost per unit (product) rollup and product and materials master with production to critical operational EDI, MRP, SCM and production and
and/or deliver services - cost per transaction - scheduling and production management based data to ensure regulations through data, bsaed on other data transaction data to
(service) synchronization on accurate accurate inventory version control and business need streamline operations
- straight-through- materials, inventory and production view of lineage
processing rate and order data planning
8 Logistics & Lower distribution costs - distribution costs per - integration with 3rd party Reduction in logistics Consistent definition Predict the impact of Encrypted data Bi-directional Availability of order
Distribution and improve visibility unit logistics management and and distribution errors across extended changes, e.g. flagging exchange with integration of data with status and delivery
into distribution chain - average delivery times distribution partners with accurate, ecosystem of key data dependencies on a extended network of 3rd party logistics and data on a real-time,
- delivery date reliability validated data such as ship-to, 3rd party provider's logistics partners, distribution partners as-needed basis
delivery information data distributors and
customers
9 Invoicing, Improve invoicing and - # invoicing errors - invoicing/collections Reduced errors in Reconciliation of Detection/prevention Secure customer Integration of Hourly or daily
Collections and collections - DSO (days sales reconciliation invoicing/billing to purchase orders to of inefficiencies or access to billing and historical customer availability of
Fraud Prevention efficiency,and outstanding) - fraud detection accelerate collections invoices to payments fraud though payment data data with third party reconciled invoicing
detect/prevent fraud - % uncollectable across geographies, dashboard and alerts data to detect suspect and payments data
- % fraudulent organizational transactions and
transactions hierarchies prevent fraud
# Financial Streamline financial - End-of-quarter days to - Financial data Improved fidelity in Consistent Built-in audit trail on Segregated, secure Incorporation of On-demand
Management management and close warehouse/reporting financial management interpretation of chart financial reporting access to sensitive spreadsheet data availability of financial
reporting - Financial reporting - Financial reconciliation with accurate, of accounts across all data to ensure financial data with data from management data to
efficiency - Asset complete financial functions and transparency and financial management business users
- Asset utlization rates management/tracking data geographies regulatory compliance and reporting systems
eeea6930-beca-424e-9860-b1e79b8244d1.xls Value- Cost Page 11
Examples of Key Capabilities by Data Attribute
C. MANAGE RISK Explanation Typical Metrics Data Integration Examples Quality Consistency Auditability Security Accessibility Availability
11 Compliance (e.g. Prevent compliance -# negative audit/inspection - Financial reporting Proactive reduction Reconcile data Ensuring compliance Secured, encrypted Leverage compliance On-demand,
SEC/SOX/Basel II/ outages to avoid findings - Compliance monitoring & of data conformity being reported on data integrity reporting data metrics tracked in continuous
PCI) Risk investigations, - probability of compliance reporting and accuracy issues across groups, through version available to spreadsheets, along availability to
penalties, and negative lapse through scoring and functions to ensure control and data authorized, with system-based reporting and
impact on brand - cost of compliance lapses monitoring consistency lineage designated personnel data monitoring systems
- audit/oversight costs
12 Financial/Asset Improve risk - errors & omissions - Risk management data Continuous data Validation of Visualize data Ease management Integrate financial Real-time availability
Risk Management management of key - probability of loss warehouse quality monitoring correlated data for relationships and oversight through and risk of key financial and
assets, including - expected loss - Reference data integration to maintain fidelity on financial reporting dependencies at access records and management risk indicators for
financial, commodity, - safeguard and control costs - Scenario analysis financial data and risk management both business and IT granular privilege systems data with ongoing monitoring &
energy or capital assets - Corporate performance level management spreadsheet-based prevention
management data
13 Business Reduce downtime and - mean time between failure - Resiliency and automatic Updated, de- Synchronized data Impact and Secure cross- Access to off- High availability and
Continuity/ lost business, prevent (MTBF) failover/recovery for all data duplicated data across primary and dependency firewall access for premise data to automatic
Disaster Recovery loss of key data, and - mean time to recover integration processes reduces and backup systems analysis across operations from support failover/recovery to
Risk lower recovery costs (MTTR) simplifies data multiple applications secondary data secondary/backup prevent or minimize
- recovery time objective storage and and systems for centers systems downtime
(RTO) management continuity and
- recover point objective requirements recovery planning
(RPO-- data loss)
eeea6930-beca-424e-9860-b1e79b8244d1.xls Value- Risk Page 12
