“The only real valuable thing is intuition,” Albert Einstein once said.

I’m willing to bet today’s data-driven business executives would disagree with Einstein on account of the development of Business Intelligence (BI) software.

BI software allows management to utilize data and guide their companies with data-driven decisions rather than intuition, opinions or ideas.

What is Business Intelligence?

According to Gartner, BI is an umbrella term that includes the applications, infrastructure and tools and best practices that enable access to and analysis of information to improve and optimize decisions and performance.

Companies use BI to enhance decision-making processes, trim costs and identify new business opportunities.

Terminology

Just like with any new subject, before you get started utilizing BI, you need understand the common terminology, which is divided into four categories: reporting, analysis, monitoring and prediction.

Reporting

Reporting answers the question: What happened. This category only includes one term and that is standard reports, which are records of past data.

Analysis

Analysis tells us why this happened, and the category includes three definitions.

  • Spreadsheet analysis: The analysis of data using standard productivity software to evaluate or anticipate business performance under a given set of circumstances. (Technology: Microsoft Excel)
  • Ad-hoc query: Software that enables the users themselves to create specific, customized data queries. (Technology: MySQL database)

Monitoring

Monitoring allows companies to know what’s happening in real-time. There are three key terms in this section.

  • Dashboard: a graphical summary of various pieces of important information, typically used to give an overview of a business. (Technology: geckoboard.com, Birst.com)
  • Key Performance Indicators (KPIs): A set of quantifiable measures that a company or industry uses to gauge or compare performance in terms of meeting their strategic and operational goals. KPIs vary between companies and industries, depending on their priorities or performance criteria.
  • Performance Management: A system that ensures all KPIs are being met efficiently.

Prediction

The prediction phase allows businesses to hypothesize what might happen. There are only two definitions for this phase.

  • Predictive modeling: Any model that attempts to predict the probability of an outcome.
  • Data mining: A way of extracting patterns and correlations from large amounts of data.

Why is BI becoming so popular?

BI is far from new. In fact, BI tools have been around for more than 20 years. The reason you are probably just learning about it is because there’s been a recent influx of interest due to the significant amount of data that is available to businesses today.

Which types of companies use BI?

All different types of companies use BI tools to help them make big decisions in real-time.

Restaurant chains, in particular, are a big utilizer of BI software because it helps them make strategic decisions, such as:

  • Which items to add to their menus
  • Which dishes to remove
  • And which underperforming locations to close.

They also use BI for tactical matters, such as when they’re renegotiating contracts with food suppliers and identifying opportunities to improve insufficient processes.

Since restaurants are so operations-driven and because BI is so central to running their companies, they are among a small few that are extracting significant value from BI systems.

Restaurants are far from the only one getting use out of BI though. Here are a few big-name chains that utilize BI.

  • Walmart: Walmart uses a lot of data and category analysis
  • Harrahs: Harrah’s has changed the basis of competition in gaming from building megacasinos to analytics around customer loyalty and service.
  • Amazon: A multitude of ecommerce sites now recommend products based on your recent searches and purchase history.
  • Capital One: Capital One runs more than 30,000 experiments a year to identify desirable customers and price credit card offers.

Three success factors of BI implementation

According to Ralph Kimball, author of the The Data warehouse Lifecycle Toolkit, three things  must be in place to successfully implement BI. Here are the three success factors.

1. Sponsorship and adoption

Everyone, from senior level management down to the sales team, need to be on board with using BI. According to Kimball, even the most elegantly designed BI system cannot overcome a lack of business sponsorship.

The consensus is that BI project adoption should begin with high-level executives, but who should the next group of adopters be? The sales team.

Since their jobs revolve around their ability to, well, sell, they will be more likely to test out the new tools, if they are user friendly and trustworthy to them.

Once the sales team is all for it, then they can sell it to the other people in your company.

2. Demand

What’s the level of need for BI in your organization?

This the second most important factor when deciding whether or not to implement BI in your company, according to Kimball.

Aside from a business need, is there a transparent benefit to the company by implementing BI?

A few needs and benefits for implementation include:

  • The need to gain a competitive advantage
  • The acquisition of other organizations
  • The need for a well-consolidated view of lots of data

3. The data

Do you have a lot of QUALITY data that’s going unused?

The amount and quality of your data is the remaining success factor to BI, according to Kimball.

No matter how good you do on the first two factors, doesn’t matter, if you do not have the right data or too little clean data.

Executives have to ensure that the data feeding BI applications is clean and consistent so that users trust it.

For more on this section, read this.

Seven steps to implementation

Once you have determined that all three success factors are in place then it is time to actually implement BI in your organization. According to CIO, there are seven steps to implementation.

  1. Ensure you have “clean” data, as discussed in the above section.
  2. Train your staff.
  3. Execute rapidly, but use a “test and learn” approach. Do not spend a ton of time developing the perfect reports because the reports will evolve as the business does. You want to settle on reports that provide the most value with the least effort and then adjust them.
  4. Use an integrated method to building your data warehouse, which will keep you from locking yourself into an impractical data strategy in the future.
  5. Clearly define your goals before beginning. How will you measure ROI? Specifically detail your expectations of BI then, every quarter or mid-way through the year, check if this is happening.
  6. Focus on business objectives.
  7. Only purchase BI software if you have the data, but cannot find the numbers that you need currently. Do not buy it simply because you think you need it.

Conclusion

BI is more than decision support. If used correctly, BI has the potential to transform organizations.

Make sure to bookmark this guide to revisit when you begin the process of implementing BI for your organization.

Do you have any lingering questions? We’d be happy to answer them in the comments below.

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