You want to take advantage of the much-touted benefits of business intelligence software, but you have a problem—you don't know where to start.
You still have so many questions. How much do your employees know about data? What sort of data do you need to collect? Are you even ready to look at a BI software solution?
Fear not, there's a way to know where you stand.
It's called the business intelligence (BI) maturity model, and it'll tell you what level of BI maturity you're at. While it's not the be all and end all, it's a great point at which to start, or improve, your analytics strategy.
Once you know where you're starting at, you'll be one step closer to business intelligence maturity, and one step closer to being data-driven: that is, using the data you collect to make sound decisions. Increasing your business intelligence maturity will make your business more data-driven, and smarter and more profitable as a result.
Below, I'll talk about several ways your small business can increase your business intelligence maturity, and how business intelligence software can help.
What is the BI maturity model?
The business intelligence maturity model is a five-level scale that tells you how mature your data and analytics strategy is. There are actually multiple business intelligence maturity models (I count at least eight), but one of the top models is definitely Gartner's.
Gartner's business intelligence maturity model, from "How to Accelerate Analytics Adoption When Business Intelligence Maturity Is Low" (content available to Gartner clients)
The low end of the business intelligence maturity model looks like this: your data is scattered across different, disconnected spreadsheets and documents. Employees may want information, but they ask for it in haphazard, one-off fashion. Also, no one's in charge of data governance.
The high end of the BI maturity model looks like this: you have a CDO (chief data officer), or at least someone in charge of wrangling your data. Your data is organized and accessible because your data sources are connected to a business intelligence software program. Employees check the data when they want to make any decision, so much so that data drives decision-making.
3 steps to help you climb the BI maturity model ladder
The business intelligence maturity model is like training wheels on a bike: the training wheels help you balance, but eventually you need to learn to balance on your own.
Likewise, the business intelligence maturity model can give your business some initial balance, but your long-range strategy shouldn't depend on the maturity model. Once up and running, your data and analytics strategy should depend more on what your competitors are doing, and how you match (and outdo) them.
In other words, the business intelligence maturity model points you in the direction of the same solid business common sense you normally use. You need the business intelligence maturity model to understand how that general common sense applies to the specifics of data and analytics, but rest assured the model builds on mental muscle you've already got.
So how do you use the business intelligence maturity model, without letting it use you?
Gartner analyst Melody Chien has tackled this question, and her advice can help you navigate using the business intelligence maturity model (full research available to Gartner clients).
1. Set up a short-range strategy
Chien recommends that you start by setting up a short-range data and analytics strategy. In this case, short-range means one year. You should have definite milestones in mind for that first year, and set times at which you expect them to be finished.
Your strategy should focus on quick wins: manageable projects that can demonstrate to the entire company the value that business intelligence software can wrangle out of your data.
Quick wins like this fall under what Gartner calls a Mode 2 approach to data and analytics: a quick, agile approach to business intelligence— in other words, it's the way small businesses already work, and the way you should set up your BI program.
Chien, with another Gartner analyst, Nigel Shen, recommend this when they say "on the low-hanging fruit to get quick wins and build competency, get business buy-in, and gradually extend the scope for bigger business impact." (Full research available to Gartner clients.)
Where the training wheels come off: Don't let your short-range strategy become your sole focus. The quick wins you pursue should contribute to the long-term goal of data-driven employees.
Also, your strategy shouldn't just be tied to whether you've bought business intelligence software. It should be tied to whether your purchase has helped you reach the solid common sense business goals you had before you started considering a BI strategy. While you do need business intelligence software, know why you need it. If you buy the software without a clearly defined purpose in mind, you'll wind up with several thousand dollars wasted.
2. Build a virtual BI team
What's a virtual BI team? One that does work as needed. (In this case, at least—"virtual team" has other meanings elsewhere.)
A virtual team is organized around set goals, rather than set roles. Instead of a definite business intelligence department, which would take time and money to assemble, a virtual BI team is made up of stakeholders from across the company's pre-existing departments, on both the business and IT side.
Your virtual team exists to set up your BI strategy, then get it off the ground. Their purpose is to make sure your data and analytics program meets the needs of the company's departments, so that employees will be willing and able to act in a data-driven manner.
Where the training wheels come off: Your virtual team should not become a new center of power, or department. Instead, their goal should be to build a strategy that will encourage grass-roots interest and involvement in analytics.
To that end, when you go to shop for a business intelligence software program, make sure to look for one with self-service capabilities. Self-service means that any "self" in the company, regardless of technological knowledge, can use the program. Check YouTube, product forums, and customer reviews to find out if the program seems easy to use. If the software has a free trial version, download that and play around.
3. Set up a basic, scalable data governance framework
Setting up a governance framework begins with determining what data you have. Figure out what data you collect, and where it is. From there, setting up your governance strategy means you've got a plan to make sure your data is clean, accurate, usable, and secure.
If you don't have the governance framework established from the start, it's difficult to do in retrospect. This also may mean setting up your business intelligence software so that users have access to what they need, but not to all data.
Where the training wheels come off: No one likes being told what they can and can't do. Keep this in mind when constructing your data governance strategy.
Chien's recommendation is that "data governance should not be treated as restriction but more as agreement and influence."
If your governance strategy is developed in a collaborative fashion, employees are more likely to see governance as cooperation than coercion.
Gartner analyst Joao Tapadinhas echoes this advice. Governance frameworks should be set up "through collaborative work where business units share their best practices," and work with IT to make governance a shared enterprise. (Full research available to Gartner clients.)