We hear about Business intelligence (BI) all the time but the term itself is seldom explained. Simply put, business intelligence is the process of turning data into insights. Business Intelligence software provides users with the tools to access, visualize, and analyze data to identify trends and patterns. While BI has been around for decades, the advent of big data has put it on the forefront of corporate processes. In a world where companies are swimming in data, the ability to make sense of it all is critical to success. Let us explore what business intelligence is, and how it can be used to benefit your business.
A brief history of Business Intelligence
The term “business intelligence” (BI) was first used in the early 1900s by Richard Miller, who defined it as “the science of creating intelligent machines.” The concept of BI didn’t gain widespread attention until the 1960s, when IBM developed a system called Decision Support System (DSS), which was designed to help managers make better decisions by providing them with easy access to data and analytical tools.
In the 1970s, DSS evolved into what is now known as executive information systems (EIS), which were used to track key performance indicators (our most beloved KPIs) and help executives make strategic decisions. In the 1980s, personal computing gained in power and started becoming more accessible: spreadsheets became widely used for data analysis, giving rise to the first BI software applications such as Lotus 1-2-3 and Microsoft Excel.
During the 1990s, organizations began to realize that data could be used not just for making operational decisions, but also for gaining insights into customer behavior and trends. This led to the development of enterprise resource planning (ERP) and customer relationship management (CRM) systems, which generated large amounts of data that needed to be analyzed. To meet this need, BI vendors started offering more sophisticated software solutions such as OLAP (online analytical processing) servers and data mining tools.
from BI to Big Data
As businesses have increasingly turned to digital sources for information, the term “big data” has entered the BI lexicon. Big data refers to the massive amounts of data that can be generated by digital technologies – everything from social media posts to sensor readings from connected devices. Simply put, Big Data is Business Intelligence on a large scale, involving cross-applications, complex processes addressing the full range of a (usually) large company’s needs.
Today, most businesses are dealing with big data in some form or another because different tools became accessible – with custom-sized offers. And as the volume of data continues to grow, so does the need for effective business intelligence tools and techniques, making it fertile ground for the creativity and competitiveness of software companies. BI is still fully B2B, although individuals could benefit from tracking tools (like those very successful To-Do lists smartphone apps).
Finding a balance between time and space
Business intelligence is not just about having the right data; it’s also about being able to effectively analyze that data to find the insights that can help improve business performance. Because just like a stock of goods, Data requires space (on a server) and time (computation power, human time to make sense of it). Both of which are costly.
The main challenge of BI is finding the right balance between time and space. On one hand, you need to be able to store and access large amounts of data quickly and easily. On the other hand, you need to be able to analyze that data in a way that makes it easy to understand and draw actionable insights from it – which usually, in plain Pareto language, focusing on a few key metrics that are relevant to the problem at hand.
One way to find the right balance would be to invest in a BI platform that can scale easily as your data needs grow. Most BI platforms will offer data warehousing, which allows you to store large amounts of data in a centralized location.
Keep in mind that most operations require specific labor, for instance mining: a discipline about discerning patterns in raw data and extracting what you need. Oftentimes, data is compared to oil: it needs to be mined, refined and transformed before it can fuel a car which, in our case, would be equivalent to the reporting phase: creating reports that visualize your data in an easy-to-understand way, so you can make decisions. From SQL to the dashboard: the road can be long, complex and full of obstacles. Each step requires a different set of skills, a specific human talent.
Keeping the human factor in sight
When designing a BI system, it is important to keep the end users in mind. What do they need to know? How will they be using the information? What level of detail do they need? Answering these questions up front will help ensure that the final system meets the needs of those who will be using it.
It is also important to consider how people will interact with the system. Will they be using it on a daily basis? If so, then ease of use is critical. If not, then a more complex system may be acceptable. The key is to strike a balance between functionality and usability.
Finally, remember that people are fallible. They make mistakes and sometimes misinterpret data. As such, it is important to build in-checks and balances into any BI system. This could include things like alerts or notifications when certain conditions are met or incorporating some sort of approval process for certain actions. By taking the human factor into account, you can help ensure that your BI system is as effective as possible.
Keeping it low-tech (when possible)
If you’re not careful, business intelligence (BI) can quickly become an expensive endeavor. Not only do you need to buy BI software, but you also need to purchase hardware and services to support it. And if you want your BI system to be truly effective, you’ll need to invest in training for your employees so they know how to use it.
Fortunately, there are ways to keep your BI costs down. One is to use open-source BI software whenever possible. Open-source BI tools are typically free or very low cost, and they can be just as effective as their premium counterparts.
Another way to keep your BI costs down is to use existing infrastructure and applications whenever possible. For example, if you already have a database in place, see if you can use that for your BI data instead of buying a separate BI platform. Or if you have Excel spreadsheets that contain important data, consider using those as the basis for your reporting and analysis instead of purchasing a separate BI tool.
I remember the infamous example of a secretary who used to have to manually xerox tens of pages of reports daily that she then brought to her manager. One day, a brand-new auto-faxing machine got installed and she – along with her manager – thought that this would make them gain time for more productive endeavors. It turned out that the machine frequently failed and needed time-consuming assistance; they also got robbed from the habit of having coffee together when she was bringing them the files, an opportunity for discussing matters at hand live, in a friendly manner. This should have been kept “lower-tech”!
How to be user-friendly?
When it comes to creating a user-friendly interface for your business intelligence software, there are a few key things to keep in mind. First, your software should be designed with the user in mind. This means making sure that the interface is intuitive and easy to use. Secondly, you should provide users with the ability to customize their experience. This could include allowing them to set preferences or create their own dashboards. Finally, you should make sure that your software is always up-to-date with the latest trends and technologies. By following these tips, you can create a user-friendly interface that will help your business intelligence software be more successful.
This complex case is a job for a UX Design, part of a larger product Team. Testing is key, if possible, with the final user (if not, a carefully crafted avatar could help). In the end, especially in Business Intelligence, testing is key for a lot of issues. Halas, testing costs time, and space. My final advice would be to plan for testing in advance and including it in the overall balance for any BI solution.
I sincerely hope that you are now more familiar with BI and its key components. Or, if you already were an expert, that you spent the whole reading time nodding in pleasureful agreement
