I saw an interesting article in DM Review this week - Ability to Mine Data Major Major Roadblock. This reported on a PricewaterhouseCoopers survey and essentially said that companies thought their data should give them a real competitive edge but actually did not. The prime reason for this was an inability to mine the data. This came ahead of consistency, accessibility, timeliness and accuracy even though, if you read the BI press, you might think that issues of consistency (single version of the truth) or accessibility (buy everyone a reporting tool) were critical! What was even more enlightening, however, was that deriving value required four key components:
- Mining data, to produce insight presumably
- Delivering data assets, or insight based on these data assets (given 1 above)
- Integration with business processes
- Real-time information
Companies have the data they need, they understand that it could be immensely valuable to them, they can't deliver it. The ROI of traditional BI is flakey at best. This accords well with a survey Opinion Research did some time ago. Opinion Research took a sample of 200 IT professionals at companies over $100 million in revenue. More than half were VPs or better and the sample included 40 CIOs/CTOs. The results are in the table below but essentially ORC got the same results in that executives did not think they were getting value out of their data and that the inability to merge this information with their business rules was one of the primary drivers.
So what does it take to get data insights integrated with business rules? Well you have to mine the data for rules or turn it into predictive models that can be executed by rules (barrier #1 above), deliver this in operational systems (#2), probably in real time (#4). In addition, you probably need to deliver decisions based on these rules and this data into your business processes (#3). This approach is the essence of Enterprise Decision Management or EDM. The use of a business rules platform let's you deliver insight from your data into operational processes. Closing the gap between having the data and making better decisions with it is what counts so you can move to transaction-centric processing or analytically controlled processes.
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