IBM Quest for Analytics Dominance

IBM has the capabilities in data mining, analytics software, ETL/BI, and the advanced purpose build hardware in SPSS, Cognos, and Netezza, and it should make a handsome profit with all those capabilities. Nevertheless, the companies that use these tools need to effectively utilize them to give them an edge in their respective markets. Just buying these analytics tools is not enough to build an analytics system. For example, I may own all the best power tools but that does not mean that I can build a house.



Companies that use business analytics are somehow like restaurants. They may have a beautiful site and a great location, but customers go to a restaurant because of the food. People go to fast food restaurants because it is simple and convenient. Fast food restaurants do not have do not have the ability and flexibility to change their menus to adapt to market conditions. Companies that want simple and convenient analytics solutions will find themselves with making substantial investments, but not getting any substantial ROI.



The way that companies can differentiate in the analytics market place is by adhering to these principles:

1. Time-to-market - The ability to turn complex analytics projects in no more than 30-90 days is essential. Companies have a need for speed, and are driven by quarterly earnings reports.


2. Low cost business model - Offshore/onsite models, and revenue sharing business models are essential in today's economic environment.


3. Technology neutral - The understanding that most advanced analytics tools in the market place are based in the same mathematics at the back end is extremely important.


4. Visualization and easy to use - End users, from field personnel to executive management, should be able to "see" and take action on relevant and pertinent information is a keystone of transforming data into actionable information.


5. Industry specific knowledge - The knowledge of the industry issues and specific data elements is something that cannot be ignored for a successful analytics project.

In the next 3-6 months we will see that the quest for analytics dominance will shift from software and hardware, to the effective application of those products to solve business problem.