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									                                                                                                                                                                                                                     Assessment Date: 2/28/2011

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
                                                                                                            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

                                          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: 2/28/2011

                                                                                                                                          Readiness Score                                                                                       Weighted
 Category           Category Name         Question                                                                                                                                                                     % Priority   Raw 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

                                          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

                                          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: 2/28/2011

                                                                                                                                           Readiness Score                                                                                  Weighted
 Category          Category Name         Question                                                                                                                                                                  % Priority   Raw 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
                                                                                                                                                                        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

                                                                                                                                                                                                                     100%                      2.7

     Created by Informatica Corporation                                                                                      Page 3                                                                                                 Rev June 6, 2006
                                                                                                                                                                                                               Assessment Date: 2/28/2011

                                                                                                                                       Readiness Score                                                                                   Weighted
 Category         Category Name        Question                                                                                                                                                                 % Priority   Raw 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

                                       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: 2/28/2011

                                                                                                                                             Readiness Score                                                                                     Weighted
 Category           Category Name          Question                                                                                                                                                                     % Priority   Raw 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: 2/28/2011

                                                                                                                                               Readiness Score                                                                                    Weighted
 Category         Category Name           Question                                                                                                                                                                       % Priority   Raw 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

                                          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

                                          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: 2/28/2011

RESULTS of Data Governance: Data Integration Technology Readiness Self-Assessment
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

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: 2/28/2011

RESULTS of Data Governance: Data Integration Technology Readiness Self-Assessment

             Data Security              2                    Data Availability


                                                             Data Quality


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
      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
     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
     9 Invoicing, Collections and Fraud      Improve invoicing and collections efficiency,and detect/prevent
       Prevention                            fraud
    10 Financial Management                  Streamline financial management and reporting

    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

      5b4703e9-a063-433f-b2a5-bca41e483db3.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,, etc.)                             duplication              marketing sytem                                      list brokers, etc.

  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

       5b4703e9-a063-433f-b2a5-bca41e483db3.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
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

       5b4703e9-a063-433f-b2a5-bca41e483db3.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)

       5b4703e9-a063-433f-b2a5-bca41e483db3.xls                                                                         Value- Risk                                                                                                            Page 12

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