BI (kinda) sucks
đ Hey, Toni from Growblocks here! Welcome to another Revenue Letter! Every week, I share cases, personal stories and frameworks for GTM leaders and RevOps.
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Since starting Growblocks, Iâve had so many conversations with CROs about their data problems.
Everything from their data being everywhere, being ashamed of it, or simply not trusting it. At the end of the day, theyâre all having trouble using data to solve GTM problems.
(By the way, we just recorded a great podcast on the topic with Lindsay Cordell. Look for that in the next few weeks)
With how many times itâs come up, you would think itâs an epidemic in SaaS.
So, how are most companies trying to solve it?
They build out Business Intelligence.
The bad news? It kinda sucksâŠ
But as your GTM becomes more and more complex, youâll inevitably be tempted to invest in it (or at least be told by your board to âjust get a BI toolâ).
Before you do, I wanted to take some time to tell you what you should expect.
The true setup cost
The promise of BI is compelling.Â
You need an understanding of your overall business performance, and having one central dashboard to see everything across your GTM is compelling. Especially the more complex you become.
But the realities of BI arenât as nice.
First of all, it comes with a huge cost. Youâll basically need:
To buy the BI tool (which isnât cheap to begin with)
A data warehouse and pipeline tool (canât get rid of those!)
Hire a full-time data engineer to work it
And hire consultants to get the project running faster
And with all of that, according to Gartner, up to 80% of BI implementations still fail.Â
To put it another way, if I pitched you a product that only works 2/10 times, would you still be interested?
So why do these rollouts fail?
Itâs not because BI vendors suck. There are some great ones out there.
The problem is always that you fail to get a consensus on what metrics mean in your business.
Sure, you can pull data from Salesforce, Hubspot, Netsuite, your Product, etc. But for it to be usable by your GTM leaders, you need to make sure they agree on:
What is an âactive customerâ?
How is churn calculated for finance and for operations?
What goes into CAC?
Which (of the 11) MQL definitions in your busines are you going to use?
And sure, you may be able to get your company on board with these definitions (believe me, itâs not an easy thing to do but itâs possible).
But if youâre a $100M+ company? All of a sudden, youâre also dealing with so many little kingdoms and fiefdoms across your GTM. And they all have their own special way of tracking and calculating metrics.
Because in those cases? Changing metric definitions might mean:
Changing commission plans
Changing targets
Changing processes and tooling
Again, not impossible. But much, much harder.
Gatekeepers of data
I once read a great analogy in the book Winning with Data by Tom Tunguz and Frank Bien, about the traditional way we deal with data requests.
They said employees who need data are like people standing in a breadline.Â
The promise of BI was to get rid of that line and everyone can help themselves. Thatâs not the case though in the majority of companies out there.
You see, I think what many people forget is that BI tools are built for data people⊠because theyâre the ones that actually make the purchasing decision.
But the majority of users (like your GTM leaders) arenât those analytic types.
So we start running into frictionâŠ
This is where tailored analytic tools start to come up.
Instead of relying on one BI dashboard?
Marketing, Sales and CS all now run their own dashboards.Â
Now they have the monitoring they need, and without bothering their data team.
Until they start to bring it all together and realize that none of their numbers match.
The answer really relies somewhere in between.
BI is stuck in the past (literally)
If youâre using it right, I think BI is great.
Especially when it comes to analyzing historical data and trends.
But thatâs where it stays.
BI solutions wonât predict whatâs going to happen in the future.Â
It canât account for future variables or inputs not already accounted for.
Whatâll happen if we add 10 more reps in EMEA?Â
Whatâll happen if we close deals 3 days faster?
Whatâll happen if we decrease CAC next year?
That what/if piece? Itâs super important to predicting your revenue.
And thatâs something that BI alone canât do.Â
On the Podcast this week
