Driving Change with Business Intelligence (BI)
What is Business Intelligence and What Does it Do?
by Crystal Lee, PMP, and Chris Patrick, PMP
Recently we’ve been hearing a lot about business intelligence (BI). In today’s challenging economy, many companies are turning to business intelligence to find ways to save money and identify new opportunities to make money. Do you know what BI is and what it can do for you?
More often than not BI discussions focus on the end result – visualize the image of the CEO poring over a report and making important decisions. However, business intelligence is much more than just a bunch of reports. BI refers to a wide range of applications and technologies aimed at collecting, storing,analyzing, and providing access to data to help people make better business decisions. In the end, to get the right report to the right person, every step of the BI cycle must function optimally.
There are business intelligence tools on the market that claim to provide exceptional reporting capability. The truth is that these data integration and business intelligence reporting tools are only part of the equation and provide little benefit without a scalable, accessible, and resilient data warehouse. The goal of this article is to discuss the critical components of a BI system and provide tips on choosing and implementing a winning BI system.
The BI Information Cycle
In a business intelligence system, information must pass through several transfer points. Data must be collected, sent to the data warehouse location (sometimes via intermediaries), transformed if required, and then stored in its original or transformed state in the data warehouse. The BI consumer then requests the information which is delivered in the requested format. During the reporting process, data may be transformed once more via various analytical techniques such as data mining, visualization, online analytical processing (OLAP), scorecards, drill-down, and modeling.
The following chart outlines what occurs in the BI cycle for three sample businesses: a bank, a restaurant, and a clothing store.
|Collect Data||Transfer Data||Transform and Store Data||Report Data to Management and Staff|
|Customer banking transactions, loan and credit services used||ATM and banking network||Data warehouse with financial analysis software and custom queries||Where do we open the new branch? What credit card enhancements can we offer to our customers? How can we make this data useful to our customers?|
|Dining purchases from food ordering system, in-store surveys, credit card data||Point-of-sale system (single store or at central HQ)||Spreadsheet or data warehouse, special analysis software for restaurants||Which menu items should we discontinue? Which items should waiters push more? Should we stay open later on weekends?|
|Clothing purchases from cash register receipts, in-store surveys, credit card data||Point-of-sale system (single store or at central HQ)||Spreadsheet or data warehouse, special analysis software for clothing stores||Should we spend more marketing dollars on babies or teens? Are there enough customers coming from the next city to open a new store there?|
There is an important feedback loop between the people who create the reports and those who use the reports. Keeping this feedback loop in continuous motion ensures that the reports being generated are providing useful data to the target users.
Choosing a BI Solution
Whether you’re choosing new BI software or upgrading an existing BI system, deciding which BI solution to go with is not a simple task. Ask anyone who supports or uses a business intelligence tool what you should purchase and you’ll get a different answer from each person. Their opinion will be influenced by how often they use the BI tool, how dense the BI user base is (sometimes referred to as “pervasive BI”), and how well the BI tools are working for them.
Use the decision points below to build a targeted requirements list:
- Analytics vs. Reporting Focus
- Licensing Model and Cost
- Availability of Third Party Tools
Of course, you may need to consider other factors depending on your industry and needs. You must also realize that these goals sometimes work at cross-purposes with each other, and stressing one quality may mean you get less of another. For instance, choosing a tool known for its reporting prowess like MicroStrategy, Cognos, or Hyperion may mean you sacrifice analytical power that you would get from tools such as SAP Business Objects, SAS, or Oracle “Siebel” Analytics (OBIEE).
In addition to looking at the factors outlined above, you should consider BI industry research from Gartner and other companies, and talk to people in BI organizations like TDWI or the Data Management Association. Doing your BI homework will help you to make an informed decision.
Implementing BI Successfully
After you have chosen your BI solution, the next step is implementation. Some companies will find it more effective to implement BI incrementally, by department or by function. Another best practice is to employ an iterative project implementation methodology like Agile/Scrum or Rational Unified Process. Both of these project approaches will give the BI user base early and frequent opportunities to examine the data and BI solutions, so that changes to the project scope can be made earlier on in the development phase, saving time and money.
Many companies have made the mistake of choosing the “big bang” solution, at a big cost. The unfortunate result can be a BI system that produces data that is not usable or is missing important chunks of data; the company then spends months or even years trying to make the BI solution work.
Know your user base. The goal of BI is to help people make better business decisions. This means disseminating information to people quickly – data that is not timely becomes stale and useless. Find out what delivery methods they prefer – it might turn out that they prefer an email or page, or they may want to see information on large screen displays on the wall. The level of analysis each user wants will also vary; higher-level management may want a canned report or dashboard, and more experienced analysts may want parameterized reporting or the ability to do ad hoc reports.
Architect the BI system. A data warehouse is a large project that needs to be engineered, architected, and managed. It is essential to follow an accepted system development life cycle from design to development to testing and validation, guided by standard project management processes.
Test the BI system. It is important to include an exhaustive testing phase, where multiple scenarios are tested during pre-implementation. Taking into account all possible scenarios requires a clear understanding of the business need and what the output should return to the end user. Neglecting the testing phase can result in poor performance and skewed data. During the test phase, don’t forget to add tasks to optimize and tune the system.
For a successful BI implementation, you’ll want to keep in mind these critical success factors:
- Find a sponsor with high reach in the corporate chain.
- Get good data – remember the old phrase “garbage in, garbage out.”
- Integrate BI with existing processes and tools.
- Get to know your users and customize BI services for each level of user.
- Enlist marketing to help you communicate information about BI initiatives to your users.
- Implement a feedback cycle to see how your BI data is being used and if you can deliver it better.
- Use Project Management to guide the project from start to finish.
The goal in any business intelligence effort is to win the confidence of the end user. Proper project management, comprehensive testing, and the timely delivery of information will determine the success or failure of any business intelligence effort.
Simply put, if your data is good, you will find that users will be more likely to adopt BI applications, and more applications will want to consume your BI data. Over time, BI data will become pervasive in the organization, and feed multiple departments, from marketing to finance to distribution. Ultimately, wise use of business intelligence will improve overall operational efficiency and decision making which will positively affect the company’s bottom line.
If you would like more information on business intelligence, send an email to [email protected]. We welcome your questions, comments and feedback.
Other Frequently Viewed Articles
Agile Software Development with Scrum FAQ: Learn about Agile Software Development, Scrum, Stories, Roles and More…
Agile, Waterfall and Uncertainty in Project Management: Agile Development vs. Waterfall
Introduction to Scrum: Benefits and Practices to Agile Software Development with Scrum.
Scrum as Project Management: Comparing and Contrasting Agile Development Scrum from Traditional Project Management Methodologies.
Agile Development & Scrum Meets the PMP: Agile Development and How it Compares and Contrasts to the PMI’s Methodology.
Daily Scrums in a Distributed World: Formal Collaboration to Reduce Overhead.
Integration of Waterfall and Agile Development: Tips for integrating Waterfall and Agile Development Methodologies.