I remember one of the first times I was allowed to present data to a bunch of executives like it was yesterday. I put a slide covered in charts from my deck up on the wall and sat in silence. Instead of staring at the slide and absorbing the data, everyone but the CFO stared back at me, waiting.
My boss at the time liked to teach me by throwing me in the deep end, but a heads up would have been helpful.
The big piece of advice I was missing?
The executive team didn’t have time to tease out what the patterns from the charts told them on the screen. They wanted the highlight reel, not the full game tape played back in real time. And not only did they want the highlight reel, they wanted the color commentary that goes along with it.
It wasn’t enough to show them patterns and proof that there was an issue. They weren’t familiar enough with the day-to-day stats I watched like a hawk to know why the charts on the screen should matter to them.
After some stammering, I caught onto the problem and ran ahead with the presentation, standing up and pointing to the data points that mattered, listing off the factors that fed into the trends, and where I thought we should dig deeper.
The experience wasn’t great. But I learned that one of the reasons things weren’t changing was because I wasn’t adequately communicating with my leadership team. I would send them a deck, and unless they had follow up questions, that was it.
After that day, I started writing up my findings. Then I learned that executives don’t read novels and bullet points are best. The emails helped, but I got better results once I started pulling together leadership team meetings and walking through a narrative.
It turns out that even data is absorbed better with an interesting backstory. But there’s groundwork that needs to happen first.
You can’t tell a story without the proper tools.
Even the most talented analysts can’t dig up cause and effect if they’re spending all of their time trying to merge data sources and fix a data hygiene problem.
Invest in CRM deduplication and merging tools. Enrich the data you can passively to eliminate human error. Buy tools that make data entry as simple as possible for salespeople and advocate for simple processes with the minimum required fields possible.
Recognize Salesforce’s (or any CRM’s) reporting limitations. In order to answer difficult questions, you will need to have a data warehouse or analytics tool that can merge your data sources and allow for ad hoc analysis.
I know people who have avoided learning T-SQL, and this is a big mistake. We have an excess of data available to us, and analysis isn’t getting any easier. Understanding data structure and logic will only become more desirable in the future.
Get the right tools, invest in education, and embrace a thorough understanding of how the data flows from one system to the next, and you’ll have the information necessary for a good narrative.
Put a chart in front of five different people, and you’ll get five different interpretations. Some will pick up on some patterns but not know the business context. Others will shove the chart away because it’s just a jumble of numbers and shapes.
A good analyst will spot problems.
An excellent analyst will try to understand where the data is coming from, who or what populates it, and the factors that drive success and failure.
For example, we know that opportunities have stages with correlating percentages that are supposed to reflect the probability of a deal closing. And there’s a close date and an amount associated with products. For short-cycle sales, a seller will have an idea of how many deals they can close in a given time period, but they don’t know the exact mix of accounts that will make up that number.
For longer-cycle sales, the salesperson will know that some deals are shaky and some will definitely close, and it’s their job to figure out how to close enough to make up the gap.
Sales managers understand that their team members will each favor a forecasting strategy. Some like to under promise and over deliver (the “sandbaggers”), some are wildly optimistic, and a few are spot on target nearly every month. A manager sees the amount each sales rep is projecting and uses their gut to temper that number when it gets to their manager, and their manager does the same.
When analyzing forecasts, analysts can draw some conclusions about how accurate a salesperson’s forecast will be based on prior performance. They will also see how much they tend to push their close dates and how many deals they refuse to close that clearly aren’t going to close. An excellent analyst will also look at leading indicators and be able to flag that a lack of SFDC logins, pipeline build, and activities is a strong predictor of attrition.
Once an analyst learns to look at leading and lagging indicators, they’re on their way to telling a story instead of flagging outliers.
Let’s say your sales VP has let the executive team know that he doesn’t see a clear path to reaching their number for the quarter. With fifteen days left, it looks like his team will only produce 80% of goal.
The executive team wants to know what went wrong (and is on call to leverage any connections in order to close deals).
A good analyst will point out that bookings aren’t on track. A great analyst will work backwards to figure out the backstory.
Start at the point sale and look for points of failure:
Sometimes it takes a few salespeople to trust you to figure out what’s wrong. At one company, a few phone calls uncovered that we had made a key competitor’s radar and they had an initiative to price us out of any deal where we went head-to-head. At other times the feedback was that the product had a key shortcoming that sabotaged a proof of concept or contract terms were causing larger corporations to balk and redline.
If the issue appears to stem from a department not supported by your organization, we would advise working with their analysts instead of escalating directly to the executive team. It will give them an opportunity to figure out their own narrative and encourage an open line of communication. Unfortunately, finger pointing is a common symptom of a bad quarter. It’s best to let teams know they’ll be under scrutiny before it’s too late.
We are so fixated on making the traditional demand generation metrics work for us because our systems aren't developed for B2B buyer cycles. Our technology has been limited because our systems think of buyers exclusively as people--which is fine for B2C. But it doesn’t have to be this way, and frankly, it shouldn’t be.
WIth the help of some industry leaders, we look at fixing your sales data problems before they start...or at least turn them around once your CRM has fallen off the rails. We’ll look at some of the latest tools that make your end-users’ lives easier while improving your data quality, methods for improving what you have without buying something new, and automation that actually works.