Journey from Decision Support to Decision Automation - 1

BI Applications sit a top the information value chain that originates in operational systems such as Core Systems, and other transaction processing systems, providing insights into issues such as customer profitability, corporate performance, risk and anything that is based on the collection and analysis of large amounts of data.

Though this is a critical tool from an organization / managements perspective, till very recently the power of this tool was left in the hands of only a few specialists. As the process of accessing the information in this system was quasi technical and needed more knowledge/training then an end user to be able to access the information. These specialists would act as information brokers and field all requests raised by the business and be responsible for generating the required information. This information would then need to be interpreted "manually".

In this process there were two types of information requests the regular and the adhoc. The regular reports which are institutionalized - they are fixed data set and fixed points of view and they are communicated to the team. This is the low hanging fruit of getting a BI system in place.

But the true value comes in the adhoc or on need analysis, When deep diving into a certain issue / problem the information worker or knowledge worker needs the relevant information / data that can assist him in getting insights into the problem at hand and also help in framing a solution for the same. But these kinds of requirements are not catered to sufficiently currently. In most cases when such requests go to the IT departments the elapsed time taken to be able to create information chain is so long that the time context is lost on the same.

Primarily in BI systems there are two models, One which sits directly on top of the ERP or transaction processing system and accessing the same in real time to serve the information requests. The second model is where this information is extracted transformed and loaded into Data warehouses and those warehouses then power information cubes/ OLAP engines which then serve the information worker.

Both these models have their relevant pros & cons the data warehouse based model - provides consistent, reliable data plus the benefits of database server technology designed to handle large sets of summary and detail-level data. However they take a long time to build and as far as BI systems are concerned, the value they provide diminishes rapidly the longer you take to deliver them. A warehouse project might get signed off based on some immediate market opportunities your company has spotted, but if you take a year to deliver the system, by then the opportunity may well have gone.

In the other model that directly sits atop the transaction system , they work by mapping their metadata layer directly against the underlying source data, applying aggregates and caches to try and speed up query performance. In some cases, these tools actually allow you to integrate data across multiple systems, though this will never be as fast to query as data that actually resides in just one database. Over time, systems built like this get harder and harder to manage, but at least you get reports and analysis in people’s hands fast and the business aren’t usually interested in arcane technical discussions about the merits of a properly architected data warehouse.

As indicated in the Rittman Mead blog, The possible solution to this is a hybrid between both these routes where the systems that directly sit atop the transaction system , are used for the immediate data access and over a period of time they be moved into a data warehouse and the BI application run from that as a data source. - Sounds quite promising.

But given this background it is important not to restrict our thinking at this point, what does the future hold for BI environments. "Decision Automation"

Decision Automation has been the holy grail of Enterprise Software for a very long time now. So are we any closer to this vision today ? (To be continued)

Tags: business+intelligence - DSS - bi - information - oracle - hyperion - sap

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Prashanth Rai