You Have Too Much Unhelpful Data.
And most firms start with the tool built on top of it - not the architecture its built on.
Our approach starts where the problem actually lives.
The Data Pyramid
Far too many companies are stuck in "reporting mode" where they've looking at reports ... and not much else.
We denote this in four tiers with a question on each:
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Data: "What do we have?"
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Information: "What do I know?"
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Insights: "What do I NOT know?"
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Knowledge: What can we learn?"
Focus varies on each stage, from your records and fields in Data to the patterns and trends shown in Insights that lead to powerful decision-making in the Knowledge stage.
With Data, Remember 8->4->4
Eight Domains
First, we categorize all of your data into eight domains. Across hundreds of engagements, these eight hold up.
Now, we know what data you have. But what's helpful?
Four Rs
Now, we check your data vs. the four Rs to learn what actually drives progress ... and what's friction that's slowing you down.
And then, we keep momentum with an eye towards AI readiness
Four Ps
The four Ps of AI readiness check to see if your purpose, pipeline, people, and processes can actually support strong AI.
Otherwise, you're racing towards a bad outcome.
The Four Rs of Data
Does your data stack up? Most doesn't. Try this quick test, or assess your data now:
Look at an opportunity in your CRM and ask these questions of each field you see.
Relevant
Does your data meet your team's needs today? Is it easy to use?
Reliable
Is it complete, consistent, and can be trusted now and next year?
Revealing
Do you learn about new trends, patterns, or insights from your data?
Reusable
Can data be activated and used across multiple systems and processes?
How many fields pass at least three of these Rs?
Those are worth keeping. The rest is noise. And this is one of three critical steps in evaluating your architecture, data, and AI readiness.
"I typically see about 50% of data passing the four Rs, but it's often much, much lower."
For those that don't, small fixes to process or integration frequency often get them there - or, conversely, it's easy to eliminate them entirely.
This doesn't take months. It's meant to move quickly.
Andy Boettcher
Chief Innovation Officer
Salesforce MVP Hall of Fame inductee
Data is platform-agnostic. Your approach should be.
Data isn't a Salesforce, NetSuite, Azure, CPQ, SharePoint, or Dynamics problem.
The problem is you're likely approaching it this way: by bucketing it on a per-platform basis.
Instead, you need information architecture.
It has to be correctly architected to have any chance of driving something useful. Start with outcomes, not tools.
And pursue good enough data today vs. having "perfect" MDM projects that take three years to show value.
Don't fall into the trap of treating data and revenue operations separately.
You'll hire one firm for data, another for AI, and a third for CRM and sales ops.
Who's working on the layer where they all connect?
Data Chaos Equals
Revenue Chaos
Friction is everywhere, even if it's hard to find.
The manual checkbox on a quote. A quick copy / paste from a spreadsheet. The invoice adjustment before the customer ever sees it.
You have it. It's a matter of how much - and the four Rs test is your first step to finding out.
See How Your Data Stacks Up
Based on our proprietary Four Rs test and Data-First Pyramid methodology.
Take the first step to see if you're at risk and what steps to start with.
Curious how costly bad data truly is? Read our dirty data research.
Let's Talk
On Your Schedule
Schedule a time that works best for you, and we look forward to learning how we can help - and adding value right away.
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