Business Intelligence

What Is Business Intelligence?

Business intelligence refers to the process of taking data points and converting them into resources that can be used to make intelligent business decisions. Processes that are part of business intelligence can include collecting, storing, and retrieving data; creating reports based on that data; and making decisions backed by data.

What Is the Difference Between Business Intelligence and Business Analytics?

Some companies use terms such as business intelligence and business analytics interchangeably, but technically these are two different things. At the very least, they’re two sides of the same coin.

Business intelligence is the act of gathering, reporting on, and understanding existing data. It’s descriptive in nature, which means it tells you to want has already happened or what is currently happening. Examples of data or reports related to business intelligence include:

At first, business analytics look like the same thing, but where BI seeks to ask and answer questions about what is, why it is, and what that means for the company, business analytics takes what is and forecasts what might be. BI is descriptive, but BA is predictive. Examples of data or reports related to business analytics include:

In many cases, business intelligence is used as a catch all term that includes business analytics. When this is the case, all of the above data and reports may be the purview of the business intelligence team.

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Who Needs Business Intelligence?

Smaller companies tend to overlook business intelligence as something only large corporations require. But the truth is that every endeavor that seeks to serve people or make a profit can use business intelligence to make decisions that better support short and long-term goals.

Not everyone needs to do business intelligence the same way, of course. It would be overkill for a small local bakery to invest in robust reporting and analytics software that a corporate manufacturer or bank might use. But that doesn’t mean that the baker shouldn’t base their decisions on real data.

Consider this example. The baker arrives at the shop on a Monday morning. It’s time to prepare ingredients and dough ahead of time for the items that will be baked and sold that day or week. Does the baker randomly guess how many cakes, cupcakes, or other items to make? No, they make products based on how many orders are already in and how many orders might be expected to come in, given past experience.

Whether the data is held in the baker’s mind, written in a notebook, or housed in a computer database, this is still business intelligence in action. The more information the baker has — and the more accurate it is — the better. So digital data, which can exist in large amounts and is easier to work with than hard-copy or “memorized” data, is typically the best practice.

What Are the Benefits of Business Intelligence?

The benefit of strong business intelligence processes is that you’re able to make smarter decisions about every facet of your company. Experience is still important, but most people can’t remain competitive in the fast-paced, thin-margin markets of today without combining experience with data when making decisions. Some things business intelligence can help you with include:

  • Identifying areas where costs can be decreased to enhance profits
  • Understanding patterns of customer behavior so you can use them to your advantage in sales, marketing, and product development
  • Tracking the performance of employees for the purpose of rewards and to inform coaching and HR decisions
  • Tracking the performance of processes and machines so you know where bottlenecks and other issues exist for optimization purposes
  • Comparing your performance to that of competitors so you can find ways to improve your share of the market

Tools and Applications Used in Business Analytics

Historically, business analytics were conducted with tools that required very specific skill sets. Statistical analysis might be completed in software such as MiniTab or even Excel, for example, and report writing was done via coding and query languages such as SQL. These tools and skills are all still required and evident today, but business analytics tools have also stepped in to make the day-to-day work of understanding critical data easier.

Today, common applications and tools used by organizations engaging in business analytics can include:

  • Business intelligence reporting software, which gathers information and presents it in ways that are easy to view, sort, and understand. Often, these software programs come with dashboards companies can customize to meet their needs. Someone managing a call center, for example, might be able to quickly see on their computer or mobile device all critical metrics, including current average speed of answer, call volumes throughout the day, and how many calls are in the queue.
  • Data visualization tools, including the aforementioned dashboards. These tools convert raw data and some analysis into charts and graphs. This is the easiest way for most people to quickly understand what the data is saying. A bar graph or line chart communicates in seconds whether a metric is trending up or down. It also lets someone know whether a number has fallen above or below a required range. Visualization helps drive immediate decision-making, but it also helps create a narrative when presenting complex data to stakeholders.
  • Statistical analysis tools, including spreadsheets, MiniTab, and other tools that help you crunch numbers. Many software solutions include built-in analysis tools that address common questions and queries.
  • Data platforms and warehouses. If you’re going to draw from and report on data, you need somewhere to store it securely. You also need methods for organizing, querying, and translating the data, as raw data is not all the same and isn’t always in a format that’s immediately useable.

What Processes Are Part of Business Intelligence?

The processes included in business intelligence vary by company, especially since some businesses use the term to cover all data gathering, warehousing, and analytical work while others use it only to refer to descriptive data work. Typically, though, anytime you’re dealing with data for the purpose of making business decisions, some or all of the following processes are at play:

  • Collecting the data. This involves setting up procedures to gather information and usually relies on both automated and people-powered tools. For example, a company that takes orders on the web can automatically capture all information related to orders as well as the data related to site visits, link performance, and shopping cart abandonment. In a retail setting, however, the cashier may have to ask someone for data, such as a zip code or phone number.
  • Storing the data. Data must be stored and kept safe until it’s required for business intelligence or analysis purposes. The primary options include storage on in-house servers or computers and cloud storage. Many companies are opting for cloud storage now, as it reduces the expense of buying and maintaining hardware, allows for easy redundancy to ensure data is almost always available, and makes it possible to work with expert vendors who can ensure speed of data access and security of information.
  • Retrieving the data. This may be as simple as opening up a spreadsheet containing your customer list in a small business. However, if you have large data sets, you may need to query databases with a special reporting language, such as SQL. Many software vendors provide out-of-box data programs for small and mid-size businesses with prebuilt queries, which reduces reliance on analytical and technical personnel to pull regular data and reports.
  • Analyzing the data. Again, software tools can help with this process, allowing anyone to quickly pull reports that let them analyze information and make decisions. For example, the software may let you see a trend over time on how many customers you have each day. It may also be able to extrapolate forecasts for how many customers you might have today. Larger organizations, however, can’t always rely on precoded reports and analytics. The more complex the data sets and questions, the more difficult the analysis may be, which is why certain businesses hire data scientists and analysts who can apply unique statistical solutions to tell stories and make predictions with data.
  • Presenting the conclusions. Often, the people who retrieve and analyze the data are not the ultimate decision-makers. Someone must be able to take the raw data and the analysis of it and convert that information into a story that supports a conclusion. Stakeholders — department heads, executives, or even shareholders — can accept or reject the conclusion based on the information and story being presented. Often, one of the best ways to handle this part of the business intelligence process is to convert the numbers and facts into a narrative that’s supported by pictures. It’s often easier to understand a chart than the raw data behind it. BI dashboards can actually do a lot of this data visualization storytelling work for you.
  • Making data-backed decisions. Finally, someone must make a decision after taking all the relevant information into account. It’s important to note that business intelligence doesn’t automatically ensure you’ll make the right decision. Accurate, properly analyzed data supports a stronger conclusion, but teams and business owners still have to apply experience, logic, and their own knowledge.

Common tools for Business Intelligence

Regardless of organization size and the intent behind your data storage and analysis processes, business intelligence usually relies on common types of tools:

  • Data warehouse or storage. You need somewhere to keep the information you’re collecting. This can be the hard drive of a computer (very limited in scope), an on-site physical server (somewhat limited and potentially expensive to keep up), or a cloud solution.
  • Analytics software. While individuals trained in statistical analysis can use tools such as Excel and MiniTab to conduct a wide range of analysis, that takes time and expertise to handle the job. Most companies invest in embedded analytics software, for example, to handle some of the most common or difficult tasks while reserving manual manipulation of data for times when out-of-the-box solutions don’t meet the need.
  • Reporting dashboards. One perk of analysis software is that it typically comes with business intelligence dashboards that let managers and decision-makers get fast access to the most important reports, analysis, and numbers. Often, dashboards work in real-time to inform decisions throughout the day.

Other business intelligence tools include technology to normalize data and move it across storage and reporting platforms; tools to turn data into visual representations such as charts and graphs; and data-entry interfaces.