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Step by Step Creating Workflow in Informatica - Excel

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					                                                                                                                                                                                                                         Assessment Date: 8/18/2011


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 for   The platform supports access to both     We have one common tool that
                                         including mainframe, structured, unstructured   integrating relational data. For other       structure and semi-structured formats.   supports all these data types in an
      1      Supported Data Types        (e.g., Word documents and spreadsheets),        data types, like mainframe, we use           We have manual or hand-coded             automated fashion, with common               30%            1         0.3
                                         XML and EDI, relational, application, and       scripts and hand-code to get at the          mechanisms to access unstructured        metadata.
                                         message queue data?                             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 data The platform validates and reports on The platform validates input/output
              Input/Output Data           data from all data sources and targets?        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 error failed session statistics, error
      4       Event Logging                                                                                                   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 performance performant data movement across
      6       Cross-firewall Access       boundaries?                                                                                 are not as good as they should be.      firewalls.                                     5%            1         0.05


                                                                                                                                                                                                                            100%                     2.2




     Created by Informatica Corporation                                                                                      Page 1                                                                                                        Rev June 6, 2006
                                                                                                                                                                                                                          Assessment Date: 8/18/2011


                                                                                                                                              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 is      options including pipelining, dynamic        10%            3         0.3
                                                                                         partitioning.                              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 configure
                                          your data?                                     hardware and software stay up and          using multiple nodes, but it's very time-   high availability including built-in
     10       High Availability                                                          running. We aren't really configured for   consuming and difficult to configure        resiliency, automatic failover and           30%            3         0.9
                                                                                         true high availability across multiple     and manage.                                 recovery, and multi-node/grid
                                                                                         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 needs,
     11       Volume and Timing                                                                                                                                                                                              15%            3         0.45
                                          based delivery to net-changed to scheduled,                                               and/or recompiled to work in different      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 (EII),                                                                                      requiring recoding.
     12                                                                                                                                                                                                                       5%            3         0.15
              Protocols                   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: 8/18/2011


                                                                                                                                              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 data We have a tool to profile source data
     13       Profiling                  your data?                                        against the data on an ad hoc basis.     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 on
              Monitoring and             of your data?                              hoc basis. We don't us formal metrics quality metrics, but they're not                 an ongoing basis and receive alerts on
     14                                                                             or conduct ongoing monitoring.        systematically monitored.                        items that fall out of acceptable               20%            1         0.2
              Measurement
                                                                                                                                                                           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 data We do not have specific data quality         Our data quality tool is primarily     All of our key data types (e.g.,
                                         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, data   The business folks have to ask IT to We have a data quality tool, but it's      Our data quality tool provides an easy-
                                         stewards, and other business-oriented users       run queries for them, and they rely on really designed for IT users. Our        to-use interface to enable both
                                         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 and    We define business rules in              We have a data quality tool that       The metadata for our data quality
                                         business rules can be captured as metadata        spreadsheets and other manual            generates metadata, but it's siloed    processes is captured automatically
     18       Integrated Metadata        and shared with other data integration            documents, so there's no easy way to     from our broader data integration      and is seamlessly incorporated as part           5%            3         0.15
                                         processes?                                        share and reuse those rules.             framework and other metadata.          of our overall data integration lifecycle.


                                                                                                                                                                                                                           100%                     2.7




     Created by Informatica Corporation                                                                                         Page 3                                                                                                    Rev June 6, 2006
                                                                                                                                                                                                                Assessment Date: 8/18/2011


                                                                                                                                       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 data Our tool creates transformation          We have one tool that captures all our
                                       workflows, etc?                               integration, so it's not easy to share mappings and workflows that can be       data integration and data quality logic
     22      Reusability                                                             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 we
                                       business rules, entity relationships, and     are scattered in different tools and    where we try to centralize rules,   can easily search, filter, define, and
     23      Cataloging                domain values in your data integration        systems. There is no centralized        relationships, etc.                 modify data dictionaries and business             15%            5         0.75
                                       environment?                                  location for them.                                                          rules.

                                       How do you synchronize data across multiple We have built point-to-point integration We use EAI and messaging             We use a combination of data
                                       systems to ensure consistency?              between systems to keep data in          technology to keep data synchronized integration and EAI/messaging
                                                                                   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: 8/18/2011


                                                                                                                                             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 tool
                                           multiple systems and applications, including   interview the different system owners    helps infer data relationships across     that graphically displays data lineage,
     25       Lineage                      both backward and forward tracking?            to try to figure out the data lineage.   systems and applications.                 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 that     details, metadata extensions and
     26       Impact Assessment                                                        to try to figure out the impact of          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 for We rely on email and shared file             Our tool has basic data integration       Our tool has robust workflow
                                           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 the
     28       Dashboard                    provide visibility into exceptions?           statistics across the team via manually- high-level summary of workflows,           ability to easily drill down into the        10%            3         0.3
                                                                                         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 our     We have an integrated test
                                           failed sessions?                               separate tool.                           data integration tool to detect mapping   environment that helps identify the root
     29       Testing                                                                                                              and session errors. We then run           causes of invalid mapping and session         5%            3         0.15
                                                                                                                                   queries for root cause analysis.          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: 8/18/2011


                                                                                                                                               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 and       15%            3         0.45
                                                                                           framework.                               access within specific business areas.    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-based        The tool has robust privilege
                                          the use of features and access to data by     different users, but it's not very      privilege management to manage                management capabilities for managing
                                          different users and administrators?           granular and there's no built-in way to access to data and key features.              and reporting on granular privileges
     33      Privilege Management                                                       enforce it.                                                                           such as copy object, maintain labels,        25%            3         0.75
                                                                                                                                                                              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 the
     35      Web Services Security                                                                                                                                         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: 8/18/2011

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: 8/18/2011

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




      2b92c43b-e6c6-46cf-822c-abd2b9bcf387.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 delivery
     Acquisition          acquiring new             customer acquisition     - Customer data quality               and on-boarding           customer data with       changes, e.g.                valuable customer          access to third party of sales lead data to
                          customers                 - cost per lead          improvement                           based on accurate         sales and third party    switching credit             lead, financial and        customer data e.g.    appropriate channels
                                                    - # new customers        - Integration of 3rd party data       customer/prospect/        channels to reduce       bureaus or                   other information          credit bureaus,
                                                    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 across      Accurate, complete,       Single view of           Improve governance           Customer data              Opportunity              Real-time customer
                          and sales within          - # products/customer    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      customer data to          differences in           data by maintaining          assurance to protect       integrated access to     tailored cross-selling
                                                    - customer lifetime      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 to   revenue data,            availability of lead,
                          improve visibility into   - close rate             - Sales & demand analytics            activity, pipeline and    incentives based on      revenue reports              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 both   Distributed, round-
    Service Delivery      product/service           launched/year            development, production and           duplicated product        application of           with product                 collaboration on           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 data
                         promotions to              - profitability per      channel pricing visibility            product pricing and       functional               pricing and improved         differential pricing and   management based         to enable constant
                         stimulate demand           segment                  - Differential pricing analysis and   discount/ profitability   reconciliation of        record keeping for           promotions data for        on data from             monitoring & on-the-
                         while improving            - cost-per-impression,   tracking                              data                      pricing and              price changes                different customers,       applications,            fly pricing adjustments
                         margins                    cost-per-action          - Promotions effectiveness                                      promotions data                                       channels, etc.             including pricing        based on demand
                                                                             analysis                                                                                                                                         spreadsheets




       2b92c43b-e6c6-46cf-822c-abd2b9bcf387.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 chain
   Management        costs, increase supply      - inventory turns             integration                    complete view of    purchases across all           of product master data      exchange with            unstructured data          management, aligned
                     chain visibility, and       - quote-to-cash cycle         - demand analysis              products and materials
                                                                                                                                  suppliers to improve           by maintaining visibility   extended network of      (typically in              with just-in-time
                     improve inventory           time                          - cross-supplier purchasing    data to improve supply
                                                                                                                                  purchasing                     into definition of and      suppliers/distributors   Excel/Word) from           production models
                     management                  - demand forecast             history                        chain efficiency    effectiveness &                changes to data                                      suppliers/distributors
                                                 accuracy                                                                         negotiation stance
7 Production &       Lower the costs to          - production cycle times      - cross-enterprise inventory Improved planning and Reconciled product             Ensure compliance           Role-based access to Integrated access to           Near real-time
  Service Delivery   manufacture products        - cost per unit (product)     rollup                       product management and materials master              with production             critical operational EDI, MRP, SCM and              production and
                     and/or deliver services - cost per transaction            - scheduling and production based on accurate      data to ensure                 regulations through         data, bsaed on       other data                     transaction data to
                                                 (service)                     synchronization              materials, inventory  accurate inventory and         version control and         business need                                       streamline operations
                                                 - straight-through-                                        and order data        production planning            view of lineage
                                                 processing rate
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 into unit                          logistics management and       and distribution errors   across extended          changes, e.g. flagging  exchange with                integration of data with   status and delivery
                     distribution chain          - average delivery times      distribution partners          with accurate,            ecosystem of key data    dependencies on a 3rd   extended network of          3rd party logistics and    data on a real-time, as-
                                                 - delivery date reliability                                  validated data            such as ship-to,         party provider's data   logistics partners,          distribution partners      needed basis
                                                                                                                                        delivery information                             distributors and
                                                                                                                                                                                         customers
9 Invoicing,         Improve invoicing and - # invoicing errors                - invoicing/collections        Reduced errors in      Reconciliation of           Detection/prevention of Secure customer              Integration of             Hourly or daily
  Collections and    collections efficiency,and - DSO (days sales              reconciliation                 invoicing/billing to   purchase orders to          inefficiencies or fraud access to billing and        historical customer        availability of
  Fraud Prevention   detect/prevent fraud       outstanding)                   - fraud detection              accelerate collections invoices to payments        though dashboard        payment data                 data with third party      reconciled invoicing
                                                - % uncollectable                                                                    across geographies,         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 data access to sensitive         spreadsheet data with      availability of financial
                     reporting                  - Financial reporting          - Financial reconciliation     with accurate,         of accounts across all      to ensure                financial data              data from financial        management data to
                                                efficiency                     - Asset                        complete financial     functions and               transparency and                                     management and             business users
                                                - Asset utlization rates       management/tracking            data                   geographies                 regulatory compliance                                reporting systems




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                                                                                                                                                                 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 of       Reconcile data            Ensuring compliance     Secured, encrypted     Leverage compliance       On-demand,
   SEC/SOX/Basel II/    outages to avoid             findings                        - Compliance monitoring & data conformity and          being reported across     on data integrity       reporting data         metrics tracked in        continuous availability
   PCI) Risk            investigations, penalties,   - probability of compliance     reporting                 accuracy issues              groups, functions to      through version         available to           spreadsheets, along       to reporting and
                        and negative impact on       lapse                                                     through scoring and          ensure consistency        control and data        authorized,            with system-based         monitoring systems
                        brand                        - cost of compliance lapses                               monitoring                                             lineage                 designated personnel   data
                                                     - audit/oversight costs


12 Financial/Asset      Improve risk                 - errors & omissions            - Risk management data         Continuous data         Validation of             Visualize data          Ease management        Integrate financial and   Real-time availability
   Risk Management      management of key            - probability of loss           warehouse                      quality monitoring to   correlated data for       relationships and       oversight through      risk management           of key financial and
                        assets, including            - expected loss                 - Reference data integration   maintain fidelity on    financial reporting and   dependencies at         access records and     systems data with         risk indicators for
                        financial, commodity,        - safeguard and control costs   - Scenario analysis            financial data          risk management           both business and IT    granular privilege     spreadsheet-based         ongoing monitoring &
                        energy or capital assets                                     - Corporate performance                                                          level                   management             data                      prevention
                                                                                     management

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/ Disaster lost business, prevent       (MTBF)                          failover/recovery for all data duplicated data         across primary and        dependency              firewall access for    premise data to           automatic
   Recovery Risk        loss of key data, and        - mean time to recover          integration processes          reduces and             backup systems            analysis across         operations from        support                   failover/recovery to
                        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)




       2b92c43b-e6c6-46cf-822c-abd2b9bcf387.xls                                                                           Value- Risk                                                                                                                 Page 12

				
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