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BASICS: Streamlining the Information Supply Chain > The Distribution Channel
The VDDW significantly streamlines the content distribution channel, but it doesn’t do so by touching it directly in any particular way. Rather, it changes it as a matter of consequence by virtue of the quality and depth of content it makes available for distribution via the channel.
The diagram to the right depicts the path to value capture in a traditional DW / BI info supply chain versus a VDDW. The top diagram depicts what’s typical in many enterprises. There are a host of datamarts, cubes, and various reporting repositories fed from the data warehouse that often re-integrate or transform data from the DW somehow so as to make it useful for that particular line of analysis. Furthermore, the secondary systems may be interwoven with each other and even with end-user desktop databases and spreadsheets in a complicated web of downstream integration. From this morass of systems, users run reports which they typically dump into Excel for further analysis.
Much of the work of pinpointing value actually happens by users spending long hours with multiple spreadsheets culled from all these different systems. This whole layer of spreadsheet jockeying may even be classified as another tier of data integration, “swivel-chair” integration, so named because it may even involve users literally sitting on a swivel chair with two computers keying in data from one to the other! (Though most of the time data is copied and pasted nowadays, the imagery of the swivel-chair is rich, and captures the often mind-numbing, unproductive tedium that all this spreadsheet jockeying entails.)
There are numerous inefficiencies and costs in this approach to DW / BI value capture:
1. All of the human effort required. This approach plainly consumes a lot of human capacity that could often be directed elsewhere to higher, more productive ends. 2. Infrastructure costs. Where there are additional layers of integration coming out of the DW, there are additional storage costs, processing cycles, and points for failure. This costs money both in terms of hardware and human administrative attention. 3. Lost Opportunities. The traditional approach is a long and complicated one. It may take so long to pinpoint a piece of insight that is actionable with return, that the opportunity to seize that value is missed or the value has diminished. More importantly, many valuable insights may never be identified to begin with because the time-consuming complexity of the traditional approach does not lend itself to the speedy, heuristic analysis that enables value discovery. You can’t navigate and slice the data thru to an insightful conclusion when you’re busy trying to piece it all together. 4. Questions of Accuracy. One of the big downfalls of the traditional approach is that it typically introduces doubts and questions as to the accuracy of the results found. All of the various systems downstream of the DW may and typically will define the same or similar metrics in slightly different ways, such that numbers don’t match as expected. Many of the downstream analysis systems and user spreadsheets are not likely to capture data at the transaction level, or enable drill-back to that level, to audit and ensure numbers are accurate. All of the hand-offs between systems and users and spreadsheets makes it difficult to track which data comes from where, how it’s defined, and which sources are authoritative and for what purposes. The end product of all the effort? A lot of questions… that compound the issue by necessitating more trips back and forth through the jungle so as to answer them!
To be sure, enterprises do find points of value from following this path, but they are not as large as they could be, and they pay a high price to get there, often with nagging questions about the accuracy of the data upon which they are acting.
The VDDW approach overcomes these issues by dealing with the root cause head on at its source. In short, that root cause is a content deficiency in the traditional DW, a product of poorly integrated data that hasn’t been properly enriched and connected so that what the user needs is simply “right there.” VDDW is an approach born of integrated methodologies (a hybrid of dimensional modeling and activity-based costing design) that combine to produce integrated data yielding integrated insight for integrated organizational action.
The path to value capture coming out of the VDDW is much simpler, faster, and with greater value captured, and without the nagging questions of the traditional approach. Generally all that’s required to pinpoint value under the VDDW approach, as far as the Content Distribution Channel is concerned, is a good cube viewer. Certainly, spreadsheets and ancillary reporting repositories will never go away, nor will a system, by itself, ever magically make everyone agree on the numbers, and those are not the claims being made, nor even a sought-after outcome of the VDDW approach.
Rather, under the VDDW approach, these are simply not critical impediments on the path to value, like they are under the traditional approach. With the VDDW approach, what the enterprise needs so as to fully understand Net Operating Performance is simply “right there” in the system. Business Processes, Operational Data, and financials are all deeply and schematically wed at the transaction level, along with the drivers of those numbers. The results, the explanation, the audit trail, it’s simply all “right there.”
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