The concept of self-service business intelligence has been around for some time. But in today’s business economy, providing consumers of information with direct access to data is essential. Even more important is doing so without IT assistance.
Like the rest of us, IT professionals are being asked to do more with the same or fewer resources. If they aren’t maintaining legacy applications, IT organizations typically are installing new systems to support various business operations – system implementations that consume huge amounts of their time.
Self-service BI is more than just providing a set of ‘tools’ to the end-user community so they can create, execute and maintain reports and queries on their own so IT while IT focuses on other core projects.
Providing access to and delivering data from a single repository or data ‘ecosystem’ is a key aspect, too (see Frank Bunker’s blog on Flexible Information Delivery). But that repository (or environment) also presents some challenges.
An analogy might help to illustrate. When I need to fill-up my fossil fuel consuming car at the local self-service gas station I have certain expectations:
- The station is open and the pump is working – I don’t know how the pump works and although I’m sure it’s fascinating and an amazing piece of machinery, now’s not the time – I’m on empty!
- Fuel is available – whether it was piped in, trucked in, etc., the important thing right now is it’s available.
- The fuel meets or exceeds certain quality standards – at a minimum, my car requires a certain octane level and purity as to not cause problems/damage to my car and provide an expected level of performance. Again, I’m not interested in the refining process, but it’s the end results that are important.
The BI self-service environment entails similar expectations:
- The infrastructure is working – Whatever device (PC / tablet, etc.) that’s used to access data is working and the network/servers required to access the data are operational. As with the gas pump, I’m not sure how the IT infrastructure works (just ask my IT guy!), but I rely on it 24/7.
- The data (fuel) required to make decisions and to provide reports is available. Data has been extracted, transformed and loaded to a single repository – one that everyone accesses. There are no ‘islands’ of data. Everyone is using the same data. And if needed, the data is based on established operational schedules.
- The data is of a known quality. This is key. When making tactical and strategic decisions based on operational data, it’s imperative that the data is of a known quality. All consumers of the data – both those that generate reports and those that use the reports must be confident of the quality of the data and have an understanding of what that data ‘represents’. Just as ‘bad’ fuel can cause hundreds, if not thousands, of dollars of damage to a car, ‘bad’ data can cause incorrect decisions and assumptions, which can cause damage to the organization. It’s essential that the consumers of the data understand exactly what the data represents.
Some things to consider when examining the quality of data:
- The consistency of items such as customer and product numbers. For example, when reviewing data by National Accounts – are all Sold-To’s correctly aggregating to the same National Account? Did one of your key customers acquire a competitor (which you sold to directly) and are you including those sales dollars? What business procedures need to be set-up so that this information is applied to the data?
- Does everyone understand the definition of ‘Net Sales?’ Again, this is where pumping from the same ‘tank’ of data is essential.
- When using POS data – are the product numbers used by your partners being correctly cross-referenced to your internal product / material numbers? Are transactions being rejected and not included in calculations?
Data quality is vital to making quality decisions. It’s an essential aspect that must be thoroughly reviewed when implementing a BI solution for the data consumers of your organization. However, it must also be an on-going process that’s regularly reviewed as your business changes – whether by acquisitions, product restructuring, etc. Business procedures and data transformation rules need to be established and strictly followed to help ensure the highest quality of data.
BI self-service is a necessity in today’s business environment. Providing quality data for the decision making end-user consumer is essential to its success.
Categorized in: Intelligent Analytics
This post was written by Paul Dorsett