Analytical Packs For Your BI Environment
In one of my earlier posts,I had written about the availability of packaged BI applications as an alternative to custom built BI solutions. Packaged BI applications from major product vendors, as enticing as it sounds, are not applicable in all kinds of business scenarios. In this blog, let me strike the middle ground and provide the 3rd option – “Analytical Packs”. So, in reality, we are looking at 3 options for creating analytical applications:
1) Custom-built BI applications from scratch
2) Implement & Customize Packaged BI Apps
3) Implement “Analytical Packs” – Build connectors and Improve on business functionality based on specific needs
Analytical Packs, as conceived by Hexaware, are developed for a specific functional purpose. This purpose can be completely domain focused (Insurance Analytics) or can be applicable across multiple industries (Human Resource, CRM analytics etc.). The Analytical Packs provide the flexibility of a custom built solution and also the benefit of faster turn-around time as provided by packaged BI apps. Also, the analytical packs can be used by organizations to understand their analytical needs better before embarking on bigger BI initiatives.
The following are the pre-built components of an Analytical pack:
1. List of Subject Areas that make up a functional domain
(Example – HR Analytics will cover the subject areas of Staffing, Retention, Workforce, Organization Effectiveness, Compensation & Benefits, Environment etc.)
2. Set of Business Questions for each subject area
3. Data Model for the functional domain / specific subject areas
4. Semantic Layer for ad-hoc analysis
5. Canned Reports
6. Pre-defined Metrics / KPI’s
7. Executive Level Dashboards (based on roles)
8. Predictive Analytics Scenarios and Mining models
9. Connectors to source systems (if feasible)
At Hexaware, we have close to around 25 analytical packs for multiple industry domains and these are constantly being improved upon. Many more packs around Leasing, Credit-risk, Collections, Accounts Receivables etc. are in progress.
How does an Analytical Pack get built? – The steps at a high level are given below:
1) Identify the business process associated with the functional domain
2) Identify the data elements / entities generated by the business processes
3) Identify the analytical scope by listing out the scope of analysis / KPI’s etc
4) Organize the data generated by business process in a meaningful way (cut out the operational noise and focus on analysis) – Create the data model
5) Identify meaningful ways to analyze the data – Reports, Graphs, Dashboards etc.
6) Identify scenarios for predictive analytics and build mining models
I will explain specific analytical packs in more detail in subsequent blogs. Thanks for reading. Please do share your thoughts.