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Monday 16 February 2009

Industry Specific BI – What's the common denominator?

My previous post on business process fundamentals concluded with a friendly exhortation to BI practitioners inciting them to view their craft from the point of optimizing business process.
So the next time you are involved in any BI endeavor, please ask this question to yourself and the people involved in the project – “So which business process is this BI project supposed to optimize, why and how?” I define ‘Optimization’ loosely as anything that leads to bottom-line or top-line benefits.
Business processes by its very definition belong to the industry domain. Companies have their own business processes – some of them are standard across firms in that particular domain and many of them are unique to specific companies. Efficiency of business processes is a source of competitive advantage and the fact that ERP vendors like SAP has special configurations for every industry illustrates this point. So by corollary, for BI to be effective in optimizing business processes, it has to be tied to specific industry needs creating what can be called as “Verticalized Business Intelligence”. (V-BI in short)
At Hexaware’s Business Intelligence & Analytics practice (the company and team that I belong to), we have taken the concept of V-BI pretty seriously and have built solutions aimed at industry verticals. You can view our vertical specific BI offering at this link and we definitely welcome your comments on that.
Though Verticalized BI is a powerful idea, companies typically need an “analytics anchor point” to establish a BI infrastructure before embarking on their domain specific BI initiatives. The analytics anchor point, mentioned above, should have the following characteristics:
  • All organizations across domains should have the necessity to implement it
  • Business process associated with these analytics needs to be fairly standardized and should be handled by experts
  • Should involve some of the most critical stakeholders within the organization as the success of this first initiative will lay the foundation for future work
Based on my experience in providing consulting services for organizations in laying down an Enterprise BI roadmap, I feel that “Financial Analytics” has all the right characteristics to become the analytics anchor point for companies. Financial Analytics, the common denominator, typically comprises of:
  • General Ledger Analysis – (also known as Financial Statements Analysis)
  • Profitability Analysis (Customer / Product Profitability etc.)
  • Budgeting, Planning & Forecasting
  • Monitoring & Controlling – The Dashboards & Scorecards
  • General Ledger Consolidation
The above mentioned areas are also classified as Enterprise Performance Management. The convergence of Performance Management and BI is another interesting topic (recent announcements of Microsoft have made this subject doubly interesting!) and I will write about it in my future posts.
In my humble opinion, the prescription for Enterprise BI is:
  • Select one or more areas of Financial Analytics (as mentioned above) as your first target for Enterprise BI.
  • During the process of completing step 1, establish the technology and process infrastructure for BI in the organization
  • Add your industry specific BI initiatives (Verticalized Business Intelligence) as you move up the curve
I, for one, truly believe in the power of Verticalized BI to develop solutions that provide the best fit between business and technology. That business and IT people can sit across the table and look at each other with mutual respect is another important non-trivial benefit.
Thanks for reading. Do you have any other analytics anchor points for organizations to jumpstart their BI initiatives? Please do share your thoughts.
Read More About  Industry Specific BI

Thursday 5 February 2009

Analytics, choosing it

We observe many BI Project Sponsors clearly asking for an Analytics Package implementation to meet business needs; the benefit is that it saves time. By deciding on an analytics package we can get the application up quickly and comes with all typical benefits of a ‘buy’ solution against a ‘build’ solution.
So what are the key parameters that we need to look for in choosing an Analytics Package. The following would be the points to consider in choosing an Analytics Package, in the order of importance.
1.The effort to arrive at the right data model for a BI system is huge and as well quite tedious, so a comprehensive ‘Data Model & Metrics, Calculations’ from the package is very important.
2.The flexibility and the openness in managing Data Model is also very critical, some of tools to manage the data model elements that can be looked for are
  • Ability to browse the data elements and its definitions
  • Support for customization of the data model without getting back to the database syntax
  • Auto Source System profiling and field mapping from the source systems to the data model
  • Enabling validation of data type, data length of the data model against the source system field definitions
  • Means to ensure that customization of the data model in terms of field addition doesn’t happen when a similar element exists
  • Availability of standard code data as applicable to the functional area
  • Supporting country specific needs in terms of data representation
3. ETL process for a BI system is also a major effort. Though the absolute effort of pulling the data and making it available for the package in the required format cannot be avoided, availability of plug-ins that can understand the data structure from typical systems like ERP would save good amount of effort.
4. Availability of ETL process for typical data validation as part of ETL is also a must; integration with any data quality product would be valuable
5. Ability to support audit and compliance requirements for data usage and reporting
6. Integration of the package with industry specific research data from vendors like D&B, IMS etc to enable benchmarking the performance metrics against industry peers/competitors
7. Customizable Security Framework
8. Semantic layer definition with formulas, hierarchies etc
9. Ready to use Score Cards and dashboard layouts
10. Pre built reports and portal
Often all the pre delivered reports under go changes and are almost completely customized when implemented. So availability of a larger list of reports itself doesn’t mean a lot since most of the reports would be minor variations from one other. Certain compliance reports would be useful when it comes along with the package; these would be published industry standard report formats.
Definitely an evaluation phase to test the Analytics products capability on a sample of the data before choosing it is a must, the above ten points would the evaluation criteria during this exercise.