If you ask three different people how to define business intelligence today, you will likely hear three drastically different answers.
There seems to be little consensus on how to define business intelligence in part because we are in the era of data. In fact, data is growing at such a rapid rate that we would have considered unfathomable a decade ago. We have yet to agree on what business intelligence is and how it’s defined.
We’re not going to pretend we have all the answers, but we do hope to make it clearer. We’re willing to throw a stake in the ground on this one with the forthcoming argument and if you disagree or you think you can help improve our definition of the verbiage, do comment below!
What is Business Intelligence?
Although the term “business intelligence” was coined as far back as the late 1950s by IBM researcher Hans Luhn, the term has undoubtedly boomed in popularity in the last decade and especially in the last three years.
The term “business intelligence” truly gained momentum when Gartner analyst Howard Dresner used the phrase to describe “concepts and methods to improve business decision making by using fact-based support systems” back in 1989. This definition really made sense at the time.
It’s no coincidence that Salesforce, now one of the world’s most popular cloud-based applications, was founded in February of 1999. Since then, the number of SaaS applications used per company is showing no signs of slowing down at all.
Back in 1989, at attempt at gathering business intelligence might take an entire quarter, not including the time needed for executives to review it and take action upon it. It was, and will continue to be, a process that includes the integration of people, data and commitment to ongoing improvement.
Acquiring the data needed to extract business intelligence insights, there isn’t a button you can push. There needs to be company-wide consensus to accept the data, how to interpret it and how to act upon it. It is a process, not a strategic goal you check off your list every quarter.
Business intelligence today has changed a great deal since the term became more widely known in 1989. Cloud-based SaaS applications have begun weaving reporting and business analytics software into their product by allowing users to build customized reports and dashboards.
This has helped more companies track their KPIs (Key Performance Indicators), which is a category, if you will, of business intelligence that companies should review quarterly, as early as possible.
Typically, executive leadership or founding CEOs will meet with respective sales, marketing or operations teams to make adjustments to their plans in order to correct a problem area or better yet, spur growth. By far, this is toughest part of the business intelligence process; deciding how to interpret the data should impact the business.
What is Needed to Generate Business Intelligence?
For the sake of simplicity, consider data to be the concrete, immutable foundation and most important element needed to gather business intelligence. The obvious, inherent side effect of capturing and maintaining good data is that it has far reaching, positive effects beyond business intelligence, like happier customers and employees.
If you’re not using at least one cloud-based application, or single source of truth, to help you capture and maintain accurate customer and prospect data, such as a CRM or an industry-focused platform that includes one, you undoubtedly ought to be.
Without data as the foundation, business intelligence is impossible. In today’s fast-moving, digital economy, making data capture and maintenance a priority points to your long-term success. If this philosophy and the need to modernize, with technology is ignored, such companies typically have a higher failure rate.
Now that you know data is key to business intelligence, you’ll want abandon any legacy applications that don’t help you capture and analyze data. If you’re a growing SMB, you may not have all your key business functions in the cloud and it doesn’t always make sense to do that right away.
The best approach to take here is to extract data from the cloud-based apps you do have so that you can take a closer look—in this case we’re talking pivot tables and combining with other key data from finance as an example—or better yet, many SaaS applications have business intelligence built into their platforms today.
How to Act Upon the Business Intelligence Gathered
Some leading market SaaS applications are using artificial intelligence to help automate the business intelligence function of providing predictive analytics, but at the end of the day, your team still needs to examine the data, test theories to improve your business and a consensus on which ones to attack.
In any case, department leads should agree upon KPIs to track, the ideal metric goal for each and team recommendations to improve their respective departmental functions, which should be carried forward and presented in an executive leadership two weeks after each quarter ends.
The two-week period should be ample time for each team to gather the previous quarter results, discuss the results with your team and put together a plan to move forward. If you walk into you executive leadership meeting with the results and a solid plan to move forward, you’ll have fewer questions.
Then, comes the hard work with your functional team. You’ll need to spend time determining how to make the adjustment improvements or adjustments, which may take cross-departmental collaboration, new software or headcount, which may take 90 days to implement. Regardless, getting the hire in is part of your implementation plan.
You’re basically cycling through quarterly reviews, continual improvement and keeping up with the day to day of your job. Appoint a subordinate on your team as your lead to keep things moving without your help or presence and your on your way.
Business intelligence is not a strategic goal that you cross off your list every quarter, it requires a team to move it forward, data, people, processes and a team to keep it on track.