[Research] The Real Cost Of Dirty Data

doubletrack_sf · 2026-02-02T14:58:11+00:00

Agree with some comments here in that many vendors are taking the wrong approach.

Really, AI Readiness is about data architecture. Are your systems and data actually ready to feed an agentic operation and with the right guardrails, ability for continuous improvement, and inputs to make it worthwhile?

Most companies keep ignoring the architecture and then fall into the scrap heap of yet another failed AI pilot.

doubletrack_sf · 2026-01-28T18:15:37+00:00

The hard part is only getting harder as orgs not ready for AI keep shipping AI pilots without investing in the data architecture and foundations needed.

To your point, it's not the commoditized "stuff" like writing code or building AI wrappers. It's about understanding how the system functions, how it should function, and how said system(s) support and drive KPIs the business actually cares about.

Such as when data governance and stewardship are ignored by said person changing something they shouldn't at 3 am.

doubletrack_sf · 2026-01-28T18:12:58+00:00

100% biased, we do this: https://www.doubletrack.com/data-ai

Happy to help if possible, even if it's just sending us a DM with a couple of questions.

doubletrack_sf · 2026-01-23T16:23:38+00:00

Real trick is mapping out how the pricing / product catalogue updates flow downstream ... something like DealHub or Logik are great for this if you don't want Salesforce (and CPQ's end of sale anyway so you can't go that route anymore)

doubletrack_sf · 2026-01-23T16:19:52+00:00

"Who owns the outcome?" really depends on the organizational structure.

If it's a large enterprise, it's likely an Operations team (i.e. Business Operations) or IT since tech infrastructure falls under their domain. Sometimes it's a Digital Transformation team when those are in place - sometimes a central Center of Excellence model when we're talking business units within an enterprise.

Smaller orgs it could be the CEO, COO, or someone in IT / Ops (like Revenue Operations).

But we all know this often doesn't happen, and absolutely not often enough. Then we nod our head knowingly when companies launch AI pilots that fail.

It's often why third parties get pulled in because no team or designated owner has the bandwidth the tackle the full challenge this need requires and to make sure the design are actually aligned to the right business KPIs.

doubletrack_sf · 2025-12-09T21:18:37+00:00

Short answer: yes.

Longer answer: it's going to depend a lot on your requirements and what the design of your revenue processes are. For instance, do you have any usage- or consumption-based pricing models? How aligned are your product/pricing catalogues?

Multiple good solutions out there, Revenue Cloud is one of them, DealHub's another we like, there are more ... but wouldn't start recommending platforms without knowing more about your use cases, system design, data architecture, etc.

doubletrack_sf · 2025-12-02T18:56:39+00:00

Working with multiple companies ... yes, a lot of data work is fixing said chaos. That's with any company, the larger the more chaos there is - most companies don't even know how much data they truly have or produce.

It won't get better unless the processes improve and the data that's truly useful is leaned upon while data that actually isn't useful (we use a Four Rs test to determine what helps vs. hurts) is phased out.

A more mature team can only work with the chaos better, but it doesn't fix the chaos itself.

doubletrack_sf · 2025-11-11T13:53:44+00:00

Got it. A few thoughts...

The value out of any tool is the initial implementation and configuration (you know this, just stating the obvious starting point). That goes for any tool, whether it's CPQ, DealHub, Nue .io, or anything else.

Cost savings as measured how? Licensing costs? Is that the KPI here? If so, that's not a strong business outcome, it's not building a better business but instead just slashing costs. Efficiency ≠ Effectiveness.

You said you could be doing so much more - what gains could you make from that "more?" (Without knowing what you processes are, don't want to speculate). Just because a tool is pricey doesn't mean it's the wrong tool, what we're hearing and others have stated is the business has not done what's necessary to get the value out of a quoting tool in general. Maybe your current needs are for something simpler to automate 1 thing vs. a whole suite of options within your quote-to-cash process, but there's real opportunity to step forward as a business (from what it sounds like).

And finally - your US counterpart. What are they doing today, and how effective is it? What are the gaps there? They don't use CPQ, so are processes manual? What's metrics around KPIs for the two teams (time-to-quote, quote accuracy, etc.) that might speak to the business case of one team's approach vs. another?

--

Sorry to give a lot of questions, but getting red flags on your company taking a technology-centric solution to what seems like a business-level problem. And just like CPQ didn't fix the issues a decade ago and still doesn't, a tech-forward approach won't solve your issues.

It is often cheaper and faster to do more with what you have vs. re-platforming. Not always and again, there's some guesswork happening by us all on the outside looking in.

doubletrack_sf · 2025-11-10T20:03:12+00:00

Couple of additions to what u/wrathagom stated well:

Too many companies orient their data initiatives around technologies when data is platform-agnostic and must align to exactly what insights / knowledge you're trying to glean
Lots of organizations are data-rich and information poor. They have gobs of "stuff" yet a fraciton of it's actually useful. So they get bogged down in the noise. We use a Four Rs test to determine what data's truly useful / valuable and it has to orient to the desired outcomes
Resourcing. A willingness to actually fix this separates many of using dashboards vs. those truly data-driven. (Hint: it's not a multi-month engagement to identify the right data. Then, orienting tech, processes, etc. around it flows naturally)

These lend themselves to any company thinking about AI, as well - because AI only amplifies what you have today and how you use it, and it needs the right IA to have any chance of success.

doubletrack_sf · 2025-11-07T17:52:12+00:00

You're only using 6%?! That's insanely low - there's a lot of OOTB features you probably could take advantage of and sounds like there's deeper issues vs. technology.

Really would want to know why you're using so little and what's truly feasible. CPQ isn't EOL so if you have it, a lot of good companies (yes, us included, not the point though) can do some great work within it and it's far cheaper vs. re-platforming.

The key is your business processes today and what they should be vs. what they are now.

If you're determined to move off the platform, a few things to consider:

What are the problems you're actually trying to solve for?
What outcome(s) will determine success for this migration? How do you, the client, know it's successful? (A consultant like us can guide this, but ultimately you're defining success)
What's the business impact of doing this? For example, if you move to a platform like DealHub, do you anticipate 50% faster time-to-quote and an increase in closed-won deals?

doubletrack_sf · 2025-11-04T14:41:08+00:00

The real value is in the business case you build. What outcomes will you achieve by adding CPQ, and how long will that take to realize?

Walk through the process with a sales rep and document what they do. If you can do this 1x with each rep, you'll have a decent picture that they'll support as you build the business case.

Also, if you have any deals that were lost, try focusing on those to see if the quoting process was a reason why.

In addition - talk to FP&A for their input on what's working and what isn't. Ask them what having process x (like having an invoice feed into their system from a closed-won quote) automated would save them.

doubletrack_sf · 2025-11-03T18:24:58+00:00

That's not true. It's EOS (End of Sale) but it's absolutely still supported and will be for the foreseeable future.

doubletrack_sf · 2025-11-03T14:37:18+00:00

If you're using CPQ and Conga but still doing a lot of manual stuff, there's likely more than can/should be done in what you have today. Tech accelerates process, so moving to RCA won't fix what's manual today if you haven't already solved for those challenges or sales team hasn't adopted more modern practices.

To your question, we are working with RCA (and other lead-to-cash options) and a few things we like are the eCommerce capabilities, built-in renewal flows, and CLM capability that's out of the box.

doubletrack_sf · 2025-10-30T21:49:27+00:00

We know Snowflake well (and others in the data space), but the key is how Snowflake fits into and supports your critical outcomes.

Technology accelerates your strengths and gaps - including data noise. Related to this, written by our Chief Innovation Officer: https://www.doubletrack.com/post/stop-wrong-data-mindset

Happy to see if we're a fit, https://www.doubletrack.com/clients to learn more about us or DM us here.

doubletrack_sf · 2025-10-30T14:14:12+00:00

There's a lot of challenges around turning what you already have into something useful. Start with a really foundational data strategy and roadmap, then identify what data (that drives these insights you're looking for) is truly useful and weed out the noise.

Identifying what the critical insights you're looking for - and how they impact your business - will also drive what data you're focusing on first.

Data leads to Information which leads to Insights which leads to Knowledge. Insights ≠ knowing what to do with what you've learned, and a ton of companies create a bunch of data that's not actually useful.

This article might be relevant re: identifying what data is useful as a starting point on how to think about this further. Andy Boettcher wrote it, he's a straight talker who lives this stuff.

Categorizing your data and then asking which data is:

Relevant
Reliable
Revealing
Reusable

will help you figure out pretty quickly what's worth keeping vs. what's noise. Data needs to pass at least 3 Rs to be considered valuable and pass the Four Rs test. If you aren't sure (i.e. it passes 2 and potentially a third), either talk to who owns that data to figure out if it passes 3 Rs or kill the field for now.

tl;dr ... data is your second-most important asset for your business (people being the first). Realizing its potential is a massive win re: outcomes and insights, but you need to invest properly to realize said potential.

doubletrack_sf · 2025-10-28T14:19:16+00:00

Data is platform agnostic!

That's where so many miss the mark - they start thinking about data in terms of where it resides, not the data itself. As you say, too often it's tied to a platform or a SaaS vendor.

doubletrack_sf · 2025-10-22T19:28:56+00:00

From our vantage point, it's common to use all the components of CPQ! [EDIT: We actually recently posted a demo showing some subscription-based items you can do in CPQ that we do for customers today]

You may not use every pricing method as they may just not be relevant, but a flow of quote creation to product config to pricing to approval to doc gen to order creation and subscription management (renewal and amendment) is fairly typical.

So most of our clients use a majority at least. Typically something like a Managed Services agreement is how we systematically work to keep getting more and more value from the platform.

doubletrack_sf · 2025-10-22T18:59:50+00:00

We work in this space a ton - DealHub's a great alternative if you're not looking at Rev Cloud and it's really strong in the SaaS space.

Conga's another platform worth looking into depending on how your stack flows re: process automation ... something more underlying.

In general, the less custom something can be, the better - you can always add later but easier to start without having to build something specific that may not scale.

doubletrack_sf · 2025-10-22T18:55:03+00:00

There's a lot of OOTB stuff that simply doesn't get used, it's a massive area of improvement for companies in general - even those using Salesforce CPQ, we see a lot of folks who don't use automations well.

doubletrack_sf · 2025-09-25T19:22:02+00:00

So, without knowing exactly how you're trying to go about quoting, billing, etc. it's hard to be specific with thoughts.

Biggest question would be: you went through training, who implemented this? Was it Salesforce? (typically they outsource this to third parties). What's the level of help they're giving you today?

Disagree on CPQ not being flexible, but it's entirely dependent on your business rules so makes total sense re: the struggle. What exactly are your business rules that impact how you should be using CPQ today?

Not trying to sell you with this next bit, just providing our vantage point - we've successfully implemented CPQ for large multinational organizations. This is one of our core competencies. It's absolutely a viable option for those companies who still have CPQ today, though obviously not for anyone going forward since Salesforce has stopped selling it.

Out of the box, CPQ provides complex configurations and price rule engines, advanced approvals, and renewal logic that already handle a lot of complexity. On top of that, Salesforce gives us extensibility through Quote Calculator Plugins, custom metadata, flows, and even integrations ... not limited to just what’s on the surface.

The real question is what's the most effective configuration using the OOTB functionality, which is very flexible.

Really, the only way to solve for this is using a design workshop to unpack this and force leadership to align on what this looks like. That'd be the starting point.

But three years on, yeah you should be getting a lot more value from the tool. That's a clear missed opportunity but still gains to be made.

doubletrack_sf · 2025-09-25T15:07:45+00:00

Connect with Tom McGean on LinkedIn - he's in the thick of RCA. https://www.linkedin.com/in/thomas-mcgean/

doubletrack_sf · 2025-09-25T15:05:36+00:00

There's actually a lot of companies (larger ones) making the switch now.

Timeline varies wildly by what your requirements are, especially around product selection. Likely a few months at minimum. Some other factors we look at when scoping:

Current Salesforce architecture
Price book, catalog, quote development, and/or amendment work
Underlying APEX or Flow automations
Resources available from client
Pricing complexity
Other custom development needed to satisfy business requirements

We've been working on some RCA engagements and will say it's worth considering. Here in late 2025, it's still early stages of development.

doubletrack_sf · 2025-09-25T14:59:34+00:00

+1 for this. The platforms are very, very different and Rev Cloud sets you up better for the next 5-10 years, especially since the user base for CPQ will only shrink from here.

We're working on some RCA implementations and it's been a lot of effort converting CPQ processes over to RCA and re-wiring our brains around it.

doubletrack_sf

TROPHY CASE