Business Intelligence Should Be About Business Results.
It’s nearly impossible to go through a full week without stumbling upon an article about the boom of business intelligence reporting. Billions of dollars are being spent on technology stacks to make business data available to employees in the cleanest and most efficient way.
When we go into the market to sell Quill, the analytics function is either the direct buyer or at least a key stakeholder in the buying process.
We have tons of meeting with prospects every week and every time I ask our Account Execs the same question: “Was [insert prospect] able to articulate why they even purchased a BI tool in the first place?”
I know this sounds a bit silly, but it would probably astound you how many times we hear Enterprise organizations fail to clearly communicate the business return on investment they are seeing or want to see as a result of deploying a business intelligence tool.
“We want to deploy and maintain a business intelligence tool because we believe that giving data and reports to our users will help make an impact. We want to be a data-driven organization.”
I’m paraphrasing, but this is the gist of what I’m hearing from organizations that haven’t spent enough time thinking about business results.
Now, would that answer suffice to your CFO? Probably not. He/She needs to know why – particularly from a financial perspective.
On the flip side, we have a ton of incredible customers that have an acute eye for measuring a business impact as a result of deploying a solution.
Here are three metrics I’ve seen our most successful customers use to measure the effectiveness of their BI investment.
(1) Time Saved
This one most often falls under the category of “hard dollar savings” as they say. I have great respect for analyst teams for the amount of annoying time-consuming requests they have to endure from the business.
Let’s consider time-to-value (TTV). Think of TTV as the time difference from when the initial ping, Slack or email comes in from the business with a request to the time that the answer is provided back to them. Business intelligence tools help to dramatically shorten that time by providing business users real-time dashboards so an analyst can say – “look at the data yourself!”
It’s not terribly easy to do, but if you make some assumptions:
How many requests are coming in [times] the average time-to-value [times] an average FTE costs [equals] a good estimate of hard dollars saved as a result of deploying a BI tool.
Ok, now our business case is starting to look a little more…financial.
(2) User Adoption & User Engagement
I’ll first caveat this section by saying that not all Business Intelligence tools are created the same. Each has their own respective tooling to measure adoption & engagement, so I encourage you to understand the functionality of the tool you’re using.
Let’s define User Adoption as # of daily active users (DAU) or weekly active users (WAU).
And for User Engagement, this is most often measured as average session length. Or in other words – on average, how long are users logged in and looking at dashboards for? This, to me, indicates that they are engaging with the platform. Analyzing, filtering the data, clicking on things, you get it.
Nonetheless, this is where we start to measure if your users are starting to see value. Things like:
- Do they know where to log in to the tool? Is it accessible?
- Do they remember their login information?
- Is the chart designed in a visually aesthetic way? Does it look nice?
- Is it organized intuitively?
- Is the data accurate?
- Is the data useful?
- Is the data real-time? Does it change frequently?
- And so on
It’s no perfect science, but we’ve all seen a great dashboard and we’ve all seen a terrible one. If your users are logging in and engaging with the platform, that means you are probably on the right track.
(3) Lift in Business Performance
I’m not going to lie, this one is tricky. But it’s crazy powerful if you can do it. This is measuring the impact on the business performance of your organization AS A RESULT of your business intelligence investment.
A simple example – a company deploys a business intelligence tool and publishes dashboards so their sales team can be more “data-driven”. I would encourage the IT & Analyst teams to measure and feel some sense of accountability on the impact the investment has on sales performance metrics (new pipeline added, new bookings, etc). These are undeniable inputs to revenue growth which is what most executives care about at the end of the day.
Even if it’s as simple as sending out a survey to the end users before & after a dashboard is published, you can start to get a sense on what type of impact your investment is making on business performance.
With any investment, it’s important to take a step back and zoom out by better understanding how your investment is expected to see a financial return for the business.
Agree/disagree? Drop me a note and let’s have a conversation – email@example.com