I’m taking a Business Intelligence class this semester at UCF and decided to share some of what I’ve learned thus far about this important segment of the Decision Support Systems world.
Who uses BI successfully?
- Western Digital uses BI to better manage its inventory, supply chains, product lifecycles, and customer relationships. BI has enabled the company to reduce operating costs by 50%.
- Capital One uses BI to analyze and improve profitability of its product lines as well as effectiveness of its business processes and marketing programs.
- Continental Airlines invested $30 million in BI to improve its business processes and customer service. Continental says it has reaped a $500 million return.
- A Recent Accenture study that found that nine in 10 senior executives at Fortune 1000 companies place strong analytical and business intelligence capabilities at the top of their list in preparing them for their biggest challenge ahead.
So, what is Business Intelligence?
Well, it’s a collection of tools. More like a sub-layer, actually. A sub-layer that is part of a major layer of Decision Support Systems (see diagram below). Business Intelligence sits on top of an organization’s data layer and tries to manipulate and transform that data into information. What’s the difference? Information is valuable, data is not (read more…). The Business Intelligence layer’s purpose is to squeeze out has much value as possible from your static and boring data layer, and use this valuable information to accomplish three goals:
- Increase the organization’s profit
- Reduce the organization’s costs
- Improve business processes
Let’s consider the evolution of data systems, just to put things in perspective.
- Transaction Systems
- Management Information Systems
- Decision Support Systems
If you’d like more detail about this, read my previous post about storage systems.
Anyhow, we started out by static/boring transactional data systems that held basic information, like: Customer A bought product B for ABC cost. Boring, huh? A couple of years later, someone had a the great idea of creating reports from that data, and hence the MIS era was underway. The reports were great, but managers wanted more value added to their information. That’s when Business Intelligence came along. Managers wanted more information to compete better and cheaper.
The questions being asked now (and we’re talking about the 1970’s or something) were: What happens to product sales if we decrease price? What happens to our performance levels if we layoff 5 employees? What if he hire 2? How can I produce more? How can I produce faster? How can I maximize profits?
That’s the whole purpose of Decision Support Systems. It puts your business processes on rails. You have a question, a well built business intelligence layer will most likely provide you some sort of answer to make a good solid decision!
What does BI include?
- Data Warehouses, data marts
- Reporting, querying
- Forecasting, statistical analysis
- Simulation, optimization models
- Business Process Management (BPM, YAWL, etc)
- Process re engineering
Anything from ERP systems to web technologies, analytical software, network infrastructure and mature data warehouse technologies.
Many BI initiatives have failed to live up to their hype. A recent survey in the UK found that 87% of BI projects don’t live up to expectations. Nearly a quarter of BI projects intended to improve management decision making are going over budget. A fifth found that data failed to reveal important information, and only half said that end-users were satisfied with the system.
Reasons of Failures
Failure doesn’t happen because of technical issues, altough data quality and integration need often more attention. In general, failure happens because the business value aspect is not built into the project from the beggining and many projects aren’t “smoothly” shown to users, hence making them quit when first obstacle is found.