BASICS: VDDW Architecture   >   OLAP Hyper Cube

• Enlarge VDDW Architecture VDDW Components: Overview Common Dimensions Common Schemas ABC Allocation Activity Dimension Contribution & Consumption OLAP HyperCube What's Left Out

  The final core piece of the VDDW is an OLAP hypercube that provides one-stop integrated analysis for all traditional DW schemas (ABC drivers) as well as all ABC contribution and consumption metrics. This hypercube or virtual cube enwraps a collection of physical cubes (or "measure groups") and expresses the full dimensionality of all the cubes it includes.

• Each underlying physical cube corresponds one-to-one to the star schemas depicted above. That is to say, based on the above diagram the VDDW Hypercube would include 8 cubes: GL, HR, Sales, Inventory, GL-Activity Contribution, Resource Driver-Activity Contribution, Inventory Performance (Consumption), and Sales Performance (Consumption).

• The distinguishing strength of this approach is the way it tightly and schematically pulls together all of the critical elements of data, in user-friendly fashion, so that virtually everything a manager or analyst would need to know about the controllable factors driving corporate performance is simply "right there", with instantaneous or near instantaneous speed, and at whatever grain of analysis is desired. Operational data, financials, and process / activity are all deeply linked in the schema at the transactional level, which is what makes it all possible. And the drill-across capabilities enabled by a common dimension bus in conjunction with the richness of the MDX language enable the construction of a new family of ratios / metrics within the cube that are quite powerful, and again, analyzable in ad hoc fashion instantaneously along any dimension or combination of dimensions desired. Some of those ratios include:

• Activity-expense-as-a-percentage-of-sales. Anyone with some background knowledge in financial analysis is familiar with the idea of margin-percentage. Typically similar companies are compared on the basis of their gross-margin or operating margin percentages to see who is more efficient and in what respects. The VDDW hypercube extends this useful ratio deeper down to the root of the activity hierarchy, where every product, every supplier, and every customer, and every mix of the three, can be benchmarked and compared on how expensive they are as a percentage of the sales dollars involved, activity-by-activity.

• Capacity / Resource Utilization.This is the division of allocation units from the activity consumption schemas into the Resource driver values from the contribution schemas. This is described further under the section for Activity Contribution and Consumption Schemas.

• NOP Resource Leverage. Most companies have some pool of dollars and resources who's intended purpose is revenue generation, typically the spend involved for sales and marketing / advertising. Leverage analysis, that is, the mathematical division of net margin by the amount of money and resource time spent engaged in revenue-generating activity, shows how much bottom-line bang the company is getting for the dollars and resource capacity spent on those revenue generating activities, vis-à-vis every corporate resource and every product and customer or supplier involved, dynamically analyzable by any combination of the aforementioned entities.

• Fixed / Variable Analysis.Many companies make some level of high-dollar upfront investment in fixed cost assets without which they simply can’t run their business. It is important in performing profit analysis to understand how much of a drag the allocated portion of a company's fixed costs has upon a particular product, customer, or supplier's performance, versus its variable costs. Drag in fixed costs versus variable costs will typically call for different types of tactical or strategic maneuvers on the part of the business, and over different time horizons, in order to address the performance issues seen with particular products, customers, or suppliers. The fixed / variable designation typically comes down to a categorization of the GL accounts from which the ABC system begins its allocation process, and MDX provides the ability to dynamically marshal the contribution percentages of various fixed and variable accounts to the activities they pay for and then finally to the products and partners which consume those activities.

• The speedy, ad hoc capabilities of this hyper-cube approach have several benefits that may or may not be immediately obvious.  First and foremost, the VDDW hypercube enables users to engage in heuristic rather than structured analysis of the data. Being able to slice-and-dice performance six ways to Sunday in lightening-quick fashion means users can discover and pinpoint root cause performance issues and opportunities much faster than they ever could before, if they even could at all, under a canned, poorly integrated performance reporting approach.

• Second, the speed and comprehensive analysis capabilities of the VDDW hyper-cube dramatically expedite ABC model validation and refinement, which can otherwise be a very time-consuming process.

• Third, if modeled properly in the ABC engine, and with some creative MDX coding, the VDDW Hyper-Cube can be used to defer certain steps of the ABC allocation process until end user query time, with the beneficial effect of dramatically reducing storage requirements for the ABC output as well as cube processing time, without sacrificing any data availability in the cube or introducing any end-user performance degradation whatsoever.
  

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• Learn More: Information Supply Chain Basics How VDDW Streamlines the ISC VDDW and Corporate Performance Management How VDDW Delivers Results VDDW Distinctives