The starting point of business intelligence (BI) is data and lots of it. Our modern business systems are good about creating huge amounts of raw data that people store “for future use”. The drop in storage costs means people don’t have to prioritize the data they keep. They can just keep all of it.
This means the work gets shifted from putting clean, useful data into the BI database to the tools that extract and process it to make decisions later.
The Raw Data That Feeds Business Intelligence
A database full of raw data has within it, somewhere, the information needed to make key business decisions. To make it really helpful, people work with database cleanup applications to reduce the amount of useless information and from that create the BI database. The BI database is where most of the analysis and reporting will get done.
Programs will be run against the raw data to accomplish several functions:
- Check for duplicate information
- Check for missing information
- Check for invalid information
- Check for corrupted information
Examples of the types of information the cleanup program will uncover include:
- Duplicate order numbers for a single customer order
- Zipcodes that are four digits instead of five or nine digits
- Product SKUs that don’t exist in the company product list
The output from this cleanup step is a set of data that the business intelligence tools can use. If the BI tools were required to sort through all of these “bad data” conditions, they would take forever to run and could give unpredictable results.
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Data for Intelligent Decisions
The cleaned-up business intelligence database is used for four primary purposes. The goal of any BI effort is to get the right information into the hands of the decision-makers when they most need it. The decisions might be critical for short-term objectives and minor changes in direction, such as developing cash flow forecasting. Or they might be necessary for long-term goals, such as long term investment strategies. The information might even indicate that no decisions are needed — everything is proceeding as desired.
Each of the four primary uses of BI data uses a different set of tools. Some are easy and intuitive to use. Others require special training to even begin using them.
Dashboards
A dashboard is a single place where people can see information presented in several ways. Think of the dashboard of a car. A person scans the dashboard in the car to make sure there are no problems and that things are running smoothly. The business dashboard is used in the same way. It is scanned to make sure the company is moving in the right direction.
Executive dashboards will present very high-level information about the company. However a shop floor manager dashboard may show individual manufacturing line status and output. Dashboards are customized for each role that will use them, such as project management.
Dashboards tend to be very simplistic ways of displaying complex data. Behind the dashboard is a lot of configuration and programming. These programs are the tools that provide the data displayed on the dashboard. What the user sees on their dashboard will only be as accurate as the programs running beneath the surface. Dashboards are usually set up by people experienced with the BI tools that support the dashboard.
Dashboards usually display a mixture of charts and graphs, gauges, and animations. These can be quickly scanned for key information. There will be some capability to drill-down through the information presented on the dashboard. A plant manager could see overall logistics planning such as expenses and with a mouse click see the expenses broken down by department.
Analysis
This is where the real “number-crunching” begins. Business intelligence analysis displays the trends that a company may be experiencing. Based on how the company has performed, analysis can give some indication of where it might be beheaded. This forecasting capability is used by companies for many purposes: how many people to hire, when to order raw materials, what marketing campaigns to prepare for.
Analysis can be complicated however can be performed with spreadsheets and patience. Reporting/analysis tools are available to do some of the tedious work. There are limitations, however, as analysis views the future as a repeat of the past. Analysis alone can’t predict what will happen when the unpredictable happens. That’s where business intelligence analytics comes in.
Reporting
This is the simplest use of BI data. Reporting filters out the desired data and presents it in a formatted view, either printed or on the screen. An example of this would be a customer list. There is little processing of the data before it’s used in the report. If there is, it is minimal such as a list of customers who made a purchase within the last 12 months.
There are many reporting tools available, from ad hoc tools that anyone can use to ones that do more sophisticated formatting. On-screen query tools are available for people to do a quick check of information. In a way, the reports can be treated as a risk management activity, ensuring the business stays safe from unexpected issues in the future.
Standard reports can be created and refreshed on a regular basis (e.g., hourly or daily). People can look at these reports or push a button and create a current one for their review.
Analytics
These tools take the analysis one step further by adding the “what-if” and simulation capabilities. This is what makes business intelligence so powerful. The analytic tools help executives make critical direction-setting decisions.
These tools can be very complex to use and configure. There may need to be several databases set up to feed into the tools. The more complicated the question, the longer the process will take. Simulations, such as breaking into a new, unrelated market may require a project and a team of people to get good information.
Summary: Business Intelligence
With the tools available now, even small businesses can make use of business intelligence. Spending the time to understand the data and the output from a BI effort can help any business make better decisions about its growth and expansion.
