If you’re a SaaS provider, your end users are guaranteed to be great at three things: generating data, being curious about their data, and complaining loudly when they need reports on that data.
If up until now you’ve quelled the masses using a hodgepodge of spreadsheets, hard-coded reports, and duct tape, allow me to confirm your sneaking suspicion that this system will collapse into a fiery heap at the slightest provocation. Your IT team has better things to do than create data silos and one-off reports for curious customers. There’s a better way.
Business intelligence software is designed to make enterprise data more accessible to those who care about it most, and embedded business intelligence software integrates with the host application so that users can do their data entry and analysis all in one place. BI typically includes some combination of the following features:
- Canned reports: these are reports you build once so that your users can run them again and again
- Ad hoc reports: users build these from scratch per their own specifications
- Visualizations: charts, graphs, gauges, KPIs, maps, etc.
- Dashboards: lots of reports and visualizations all displayed at once
- Scheduling: a program that will run and/or email reports at specific times
The upfront investment in purchasing and deploying a BI solution will not only save you money in the long run, it will also improve customers’ product experience and give you a competitive edge, driving sales and generating new revenue.
But if you’re still not sure your application needs embedded BI, here are some surefire signs it does.
#1: You’re Building All Your Clients’ Reports Yourself
This method simply does not scale. Sooner or later, you will hit a critical mass of clients and be unable to keep up with the demand for reports. Unless you have employees whose sole responsibility is to respond to client reporting requests, these queries are likely taking your IT professionals away from the work they were hired to do.
Softerware, for example, discovered after implementing a BI solution that it had the resources to start data science projects aimed at optimizing their nonprofit fundraising platform, DonorPerfect. “The people doing data science were the ones that used to be writing reports,” explains lead developer Dave Killough. “So now that the ad hoc reporting puts more power into the users’ hands, we find we have more bandwidth to dive into some of these data science initiatives and bring greater results to the business.”
“So now that the ad hoc reporting puts more power into the users’ hands, we find we have more bandwidth to dive into some of these data science initiatives and bring greater results to the business.”
Without BI, report writing taxes your team and takes even longer than it needs to, which brings me to sign #2.
#2: Either You or Your Clients Rely on Spreadsheets
Spreadsheets are the flip phones of operational reporting: they’re unwieldy, they’re outdated, and you get strange looks when you whip one out during a board meeting. While spreadsheets might suffice in some situations, they don’t refresh dynamically as new data is generated, so different business users will have different data depending on which spreadsheet they’re referencing and when it was generated. Isolated sets of data like these, also known as data silos, can lead to conflicting reports and misinformation.
Spreadsheets also leave companies more vulnerable to human error and miscalculations. Data consultant Jen Stirrup once worked with an organization that stored its employees’ PTO data in a spreadsheet to disastrous effect. “The spreadsheet had two columns on it,” she recounts, “the name and the number of holidays that the person had taken that year. But they’d sorted one column of the two and not the other. So that mixed up everybody’s holidays. And honestly, if you’re going to mess up a spreadsheet, don’t let it be the one that’s got all of everyone’s holidays on it for the whole company.”
“If you’re going to mess up a spreadsheet, don’t let it be the one that’s got all of everyone’s holidays on it for the whole company.”
Stirrup also encountered companies who had so many spreadsheets that they needed a spreadsheet just to keep track of them. Maintaining a this kind of collection requires a great deal of time that could be better spent on other tasks.
#3 Joining Data from Different Sources is a Nightmare
It doesn’t have to be. A good BI application will make joining data from different sources easy and seamless. All you’d have to do is define how the two tables or datasets relate to each other. This could be something like using email addresses as the link between newsletter signup data and sales conversion data. Gone will be the days of manual data entry and thankless intern drudgery!
#4 Users are Agitating for More Control Over Their Data
Users don’t want to nag you for reports any more than you want to spend time building them. If your power users are coming up against technological impediments every time they try to answer business questions for themselves, that frustration is bound to snowball.
Instead of trying to divine your clients’ every reporting need, give them the tools they need to explore their own data. Marc Jorrens of Outbound Software discovered after introducing ad hoc BI to his attractions management software that his clients really wanted to know how many customers their zoo or museum was getting per hour. He says he wondered, “Customers per hour? Why would you want to think about that?” And then they explained: staffing. If you know you’ll be busier on rainy days, you can plan ahead and staff accordingly. Jorrens would never have thought to build a report around that metric on his own.
When a critical mass of product champions start clamoring for the same feature, there’s a good chance it’s time to give that feature serious consideration.
#5 The Joneses Have Adopted a BI Platform
Those of us who payed attention in kindergarten know it’s never a good idea to do something just because someone else did, but competitors help us keep track of the market. When other companies in your vertical start investing in a new technology, be it BI or something else, the trick is in choosing how to respond. You can:
- Do nothing. Maybe they’re moving in a direction that doesn’t fit your market niche, or perhaps you have reason to believe the move is a fad or anomaly that won’t impact the industry long-term. In any case, you feel safest not following the crowd.
- Adopt the same platform. Only do this if you think the move is crucial to the survival of your business and if you think not adopting the exact same technology will render you obsolete in short order.
- Adopt a similar technology. Maybe all your competitors are going with a particular vendor or feature set. Picking a different solution could help you stay with the pack while maintaining your brand identity. Finding a product closely aligned with your business objectives puts you at pace but also distinguishes your offerings from those of your competitors.
Regardless of which tactic you choose, it’s important to address the market problem the technology is designed to solve. Do your users have that problem? If not now, will they? Keeping up with the Joneses shouldn’t be your only reason for adopting BI, but it can absolutely be a reason, especially in conjunction with one of the other four above.
Of course, deciding you have an analytics problem is only the beginning. The next step is to begin a search for the solution that’s right for you. If that sounds overwhelming, know that there are resources out there to help you navigate the market as well as best practices for getting the most out of your product evaluations. Have questions? Feel free to leave them below.