Friday, 22 January 2010

The Great Expectations of BI

I recently read a fantastic article by Jim Harris - "A Tale of Two Q's" on DQ Theory Vs Practice. The article quotes Charles Dickens, which led to my mind wandering off to one of my favourite Charles Dickens books, "Great Expectations". This in turn got me thinking about how the business often have great expectations of BI.

"Now, I return to this young fellow. And the communication I have got to make is, that he has great expectations."

My question is, Why doesn't BI, in many organisations, live up to these expectations?

1. It was oversold

"I had come into great expectations from a mysterious patron."

Often, BI is simply oversold within an organisation. It markets itself as the cure to all business problems. It will allow the business to quickly self-serve and extract good quality information. It will have efficient management of reports and will act as a 'one stop shop' for all information requirements.

However, it often manifests as quite the opposite.

The aim here is to manage expectations. Build steadily, and show how BI can add value within a particular function or process. Once we have success here, build upon progress made, and lessons learnt, into other areas of the business. Too many organisations over-sell what their BI implementation will actually deliver - perhaps to justify the budget spent on technology - and the business naturally get excited by the prospect it promises.

2. Tools don't do what the business want

"He says, no varnish can hide the grain of the wood; and that the more varnish you put on, the more the grain will express itself."

Although the marketing literature may demonstrate the flexibility and functionality of the tool, this may not always align with the practicalities. The business may not be able to use the tools in the way they wish, or may not even understand how to utilise the tools correctly.

Only by understanding what the business want from a BI tool, prior to it's selection, will we ensure that expectations have been both considered, and managed.

3. Data Quality issues

"Take nothing on its looks; take everything on evidence. There's no better rule."

No matter how much effort has gone into the presentational side of data, the simple rule is that if you put bad data into your data warehouse, you are going to get bad data out. BI is not going to magically solve data quality issues without serious effort put into quality control and governance.

4. Lack of Governance

"Mrs. Joe was a very clean housekeeper, but had an exquisite art of making her cleanliness more uncomfortable and unacceptable than dirt itself."

BI implementations should result in a centralised store of information - be it OLAP type environments, or reporting portals.

However, no matter how centralised this store of information is, if it's not being used, governed, and managed efficiently it is going to cause confusion. Although it may look clean to the untrained eye, the truth may actually be the opposite.

5. Slow turnaround on Information Demand / Supply

""So!" she said, without being startled or surprised; "the days have worn away, have they?""

BI should result in the ability for the business to self-serve information. However, OLAP cubes, complex reports & dashboards will need to be designed/built by skilled technical developers.

The expectation that BI will allow quick access to information can be hampered by poor turnaround in Information Demand & Supply. Do you have communicated SLAs in place within your Demand/Supply team, so that the business users have an idea of the timescales involved between requirements gathering, translation, build, testing, and go-live?

6. Poor Performance

"For an hour or more, I remained too stunned to think; and it was not until I began to think, that I began fully to know how wrecked I was, and how the ship in which I had sailed was gone to pieces."

If a business user suggests that it takes too long for a report to run, or query times to an OLAP cube are slow, they will often look for other ways to source the data they require. What performance testing and tuning has been conducted to ensure that the performance expectations of the business have been managed?


All quotes are from the Charles Dickens book "
Great Expectations"


Pedro said...

Very interesting point of view!

Anonymous said...

All these factors play a part but in my experience, claims of 'ease of implementation' and 'ease of use' are two of the biggest culprits when BI efforts don't match expectations. There are wonderful BI products out there but the vendors always oversell capabilities and undersell the effort that end users need to put into defining their vision for their use of that product. If more stakeholders came into a BI implementation with eyes wide open and ready to work as hard to define their requirements for a BI tool as they do on their operational tasks there would be a lot more success stories. You get out of an undertaking the effort that you put into it and having IT do it all is a recipe for disappointment.

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