Thursday, July 18, 2013

Principles of Dashboard Design

I was thinking about the ideal strategy for designing dashboards, till I came across a couple of blog entries by the master himself - Ralph Kimball. In these blog posts, titled "Drill Down to Ask Why" (first and second) the master gives the mantras of good dashboard design.

Here they are, in the order explained by the Master (and mentioned to him by his colleague):

1. Publish reports. Provide standard operational and managerial “report cards” on the current state of a business.

2. Identify exceptions. Reveal the exceptional performance situations to focus attention

3. Determine causal factors. Seek to understand the “why” or root causes behind the identified exceptions.

4. Model alternatives. Provide a backdrop to evaluate different decision alternatives.

5. Track actions. Evaluate the effectiveness of the recommended actions and feed the decisions back to both the operational systems and DW, against which stage one reporting will be conducted, thereby closing the loop.

More on Asking Why?
Giving the example of an air fare planner looking for reasons for poor performance of their data, Ralph provides the following illustrations:

1. Give me more detail. Run the same yield report, but break down the high-level routes by dates, time of day, aircraft type, fare class and other attributes of the original yield calculation.

2. Give me a comparison. Run the same yield report, but this time compare to a previous time period or to competitive yield data if it is available.

3. Let me search for other factors. Jump to nonyield databases, such as a weather database, a holiday/special events database, a marketing promotions database or a competitive pricing database to see if any of these exogenous factors could have played a role.

4. Tell me what explains the variance. Perform a data mining analysis, perhaps using decision trees, examining hundreds of marketplace conditions to see which of these conditions correlates most strongly with the drop in yield (explaining the variance in data mining terminology).

5. Search the Web for information about the problem. Google or Yahoo! the Web for “airline yield 2008 versus 2007.”

I think the above provides a great structure for a real enterprise level executive dashboard.

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