The past week the team all came together for a few days - in person - to do some team bonding and align on the remainder of the year. It was a great opportunity for us that Doug and Jess talk about prior to the show. They also get deep into Disney’s movie on the Haunted Mansion ride. Doug made me crack up talking about Disney with Jess who is what I would call an expert on Disney.
If that isn’t your style, feel free to skip to time-mark 11:11 where the two get into our topic for today: source of truth versus system of record.
[RevOps Show] Episode 10: The Importance of Single Source of Truth (And How You Can Have More Than One)
[RevOps Show] Episode 14: Cracking the Code to Sales & Marketing Alignment
[Blog] Aligning Vectors & Structuring Your Team For Revenue Growth
[Blackline Podcast] Episode 4: What is Sales and Marketing Alignment?
Disclaimer: if you are a data scientist, please skip this episode because it’ll be painful for you.
What is a source of truth?
In talking about sources of truth, there is a labyrinth that exists as you start talking about sources of truth, the implication of sources of truth, data intelligence, etc.
A system of record is a source of truth. Source has some level of beginning where it starts and the reality is when most people are talking about a source of truth they’re needing a truth where they are.
Doug’s takeaway from this entire conversation is going to be: stop shooting bunny rabbits with shotguns. The conversation that exists in the mid-market around this concept is ponderous and doesn’t mean anything. It’s a distinction without a difference.
What is revenue truth? What we’re really talking about is direction. No rep needs to know the penny amount; no manager needs to know down to the penny what the revenue is. Doug isn’t saying that pennies don’t matter, but for how the sales organization uses the data, a penny amount isn’t relevant.
The primary place where source of truth comes into place is the underlying source of this as an issue is pre-cloud. The dominant way we would communicate data is with spreadsheets. While data may look to be the same, people were never truly looking at the same data for the same reasons. Single source of truth is the one place that has everything that is considered to be correct.
When we were in the big data world game, it was not about big data. It’s about small data. It’s about how you are applying the data. When we talk about source of truth we have to ask, what is truth? The answer to that question is needed for the rest of the conversation to be relevant. If you don’t have a fulcrum to manage the trade-off you can’t answer the question.
In doing research on this, Jess has seen a lot of people say it increases productivity to have a single source of truth because they aren’t having to go to multiple places for information. That’s not necessarily what it’s being hired for, but it becomes a juice for the squeeze question for Jess.
Here Doug makes a bold statement: The conversation around source of truth and single source of truth is small business to mid-market; 10,000 employees or less. Doug thinks it probably goes to more than that, but just to be conservative, what we’re talking about is data system alignment.
What is sales and marketing alignment?
Focusing on sales and marketing alignment is equal to rearranging the deck chairs on the Titanic. It might make you feel good for a minute, but the ship is sinking; it’s not going to help you. Alignment is a byproduct; it’s not the focus.
It all comes back to what are you doing with the data.
The productivity argument is that you’re increasing the productivity of your team by putting this single source of truth in place because you don’t have to go to multiple different places to find the data you’re looking for. To Doug and Jess, this seems like a consolidation of tools more than a single source of truth. Doug doesn’t think everyone needs all the data all the time. This argument is more about streamlining the process rather than having a single source of truth.
The point of source of truth is for the manipulation of data. It’s for the matching up of data. The whole point of the systems data warehousing is to be able to originate data at multiple points and bring it together into a single system. The level that you should do that is highly dependent upon the needs of the business.
What drives productivity when it comes to data?
Give me the precise piece of data that I want at the precise time that I want it in the precise place that I want without having to ask. That is what maximizes productivity.
Jess runs our migration team and there was a time when she did a mapping exercise with a client’s IT team and one with their sales team. They determined that if they have too much data, they were going to overwhelm the sales team because there was a lot of room for confusion and misunderstanding of things. There’s also a higher likelihood that when you migrate data, there will be more points of failure to manage. When she got on with the sales team they determined they didn’t need all the data that IT wanted to bring over. IT had the concern around “But what if we need that?”
There’s danger in source of truth where everyone’s so focused on different systems, meanwhile, the database has four variations of lead status or properties. So while people are worried about losing data, they still have the problem that the data isn’t all matching up.
What you can’t have is doubt that the data is accurate. You have to be able to count on your system rather than having to check 13 different places. It’s a backend RevOps job to make sure that data is aligned to the level that it needs to be aligned to.
Jess’s Takeaways:
Follow Jess, Doug & Imagine on socials for updates on the show or other insights:
Doug Davidoff: Twitter - @dougdavidoff | LinkedIn
Jess Cardenas: Twitter - @JessDCardenas | LinkedIn
Imagine Business Development: Twitter - @DemandCreator | LinkedIn
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Coming Soon: Episode 66!