Review Metrics

Packaged Analytic Applications

1. Domain Automation. Does the analytic application focus on a specific business function, with reports and workflows that automate the specific recurring tasks of that domain? If the analytic application is a suite covering multiple business domains, is the analytic view integrated across domains? Without these, end-users will have to spend a lot of time transferring their knowledge to IT personnel or consultants, who then build domain-specific functions.

2. Business Methodology. Does the analytic application apply business performance management, balanced scorecard, dashboard approaches, or other established business management methods? If so, how deeply and how creatively? Without a well-defined method, multiple end-users will make multiple interpretations of metrics, reports, and analyses, instead of understanding the appropriate action immediately.

3. Analytic Methodology. Does the analytic application apply the current best practices for OLAP, data mining, ad hoc query, reporting? If so, how deeply and how creatively?

4. Ease of Integration. Does the analytic application include packaged "connectors" for data integration with packaged applications and other sources, as well as support for Web standards, etc., so the analytic application can be presented in a portal? Without these, users should anticipate the need for an expensive and time-consuming integration process.

5. Ease of Customization. How easy is it to alter the data model included to match the customer's business and to tweak canned reports/analyses to match end-user requirements? Without these, users should anticipate the need for an expensive and time-consuming customization process.

Business Performance Management

1. Installation, scalability, reach: Ease of distribution of the software and its capabilities to those who will need it.

2. Learnability, usability, usefulness: The quality of the end-user experience with the tool.

3. Reporting & analysis: The variety and quality of methods the tool incorporates.

4. Granularity & analytical depth: To what level of detail can a user explore the source data underlying performance measures?

5. Data access & application integration: How easy is it to incorporate data or integrate with other systems?)

6. Flexibility, configurability, extensibility: How much latitude is the business user given to accurately model the business, its workflows, relationships, objectives, and so on?

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