If your company already has one system for sales, another for inventory, and a spreadsheet only you understand, you've probably heard the phrase “business intelligence” in a meeting or two. And you were probably left wondering what business intelligence is, exactly, beyond the acronym BI.

What is business intelligence, in simple terms

Business intelligence isn't a program you buy and install. It's a practice: organizing the data your company already generates every day—sales, inventory, collections, customer service—so you can look at it together and use it to make decisions.

A BI system (the software that helps you do this) is one piece of that practice, not the whole practice. You can have the best dashboard on the market and still not be doing business intelligence if nobody looks at it before deciding, or if the data feeding it is wrong.

What it's made of: data, reports, dashboards, and indicators

BI is built from four pieces, each resting on the others:

  • Data: what your systems already record (sales, inventory, cash, customer service).
  • Indicators: the specific numbers that matter for your business (average order value, inventory turnover, days to collect).
  • Reports: those indicators organized and explained, at the frequency each one needs.
  • Dashboards: a combined view of several indicators, so you can see the state of the business at a glance instead of report by report.

None of the four pieces is worth much on its own. A dashboard with poorly defined indicators only gives you the feeling of being informed.

What problem it solves: the difference between having data and having information

Having data isn't the same as having information. A company can have ten spreadsheets and five systems full of data and, at the same time, have no clear answer to a simple question like “Which product gives us the best margin?”

Information appears when that data is cross-referenced, cleaned up, and put into a format a person can look at and understand in minutes, not days. That's the problem business intelligence solves: the gap between what your company knows (because it's in some system) and what your company can actually see.

A hypothetical example, just to illustrate the idea: a distributor that sells through a catalog and over the counter. The data for both channels exists, but separately. Without BI, nobody knows whether the catalog is more profitable than the counter until someone cross-references the two spreadsheets by hand, a couple of times a year. With BI, that comparison is available every day, without anyone having to rebuild it each time.

Signs your company is ready to start

You don't need to be a big company to start with business intelligence. You need other things:

  • You have at least one system (ERP, CRM, a sales system) that already records information in a reasonably consistent way.
  • Someone on your team regularly spends time building reports by hand, cross-referencing spreadsheets.
  • You decide on prices, purchasing, or staffing more by gut feeling than by a number.
  • Different departments give different answers to the same business question.

If your data still lives in a mess, in scattered spreadsheets everyone builds their own way, it's worth fixing that first: we cover it in Moving off Excel in your company.

What business intelligence is NOT

Three clarifications so it doesn't get sold as magic:

  • It doesn't fix badly entered data. If the source is wrong, even the prettiest dashboard will show a wrong number—just faster.
  • It doesn't replace the decision. It brings the information closer; deciding with it is still human work.
  • It isn't, on its own, a complete digital transformation project. It's one piece of that process, usually added once there's consistent data to work with.

How to start without turning the whole company upside down

You don't need to tackle every indicator in the company at once. The order that works best:

  1. Pick a single business question that nobody can answer with certainty today (for example, which customer or product brings in the best margin).
  2. Identify where that data comes from today, even if it's messy.
  3. Build a small first dashboard around that specific question, before thinking about a complete system.
  4. Expand one indicator at a time, once the first one is actually being used to make decisions.

To see how this plays out day to day in a midsize company, with every stage of the process, read our article on data analytics for businesses. And if what you need is a strategic dashboard by department, the format is explained in balanced scorecard.

The next step

If, after reading this, you realize your company has data but no answers, the useful step isn't buying a dashboard: it's first understanding which business question you need to answer and where you'll get that data from.

That's what our assessment is for: we look at what data you already have, how consistent it is, and which indicators are worth watching first.

Book your assessment or, if you'd rather take the first step on your own, try the self-assessment.

Keep reading

  • Data analytics for businesses—dcisglobal.com/en/insights/data-analytics-for-businesses: the full process, across the different stages of a midsize company.
  • Balanced scorecard—dcisglobal.com/en/insights/balanced-scorecard: how to build and use a strategic dashboard by department.
  • Moving off Excel in your company—dcisglobal.com/en/insights/moving-off-excel: when the spreadsheet has become the bottleneck.
  • Data analytics and BI—dcisglobal.com/en/data-analytics-business-intelligence: the service, for when you've already identified what you want to measure.