Quick: which company do you like better?
Yes, assume they’re similar size, growing at similar rates, and both at scale. Pick A or B. Thelonious can’t help because there’s no third option.
C’mon. You know you want to pick A.
- Company A has a leaner services business at 10% of revenue, where company B’s is kind of hefty at 25%.
- Both companies have barely profitable services businesses (2% gross margin), but at least company A’s is relatively smaller so that services boat anchor does relatively less damage.
- Company A has much higher gross margins – by 13 percentage points – at 81% vs. 68%. Additionally, that 81% is above the public company median of 76%.
- Company A has somewhat higher operating expenses, but in the end they both produce the same 3% operating margin.
It seems clear that Company A is superior. And not just by a little — look at the gross margins. Think of the impact on CAC Payback Period.
Here’s the trick, though. Company B is company A with one, single difference: $100M additional services revenue. Here’s a deeper look showing both dollars and percentages.
Company B has $100M more in total revenue, $2M more in gross profit, and $2M more in operating profit. Every other figure (not derived from those differences) is the same. For example:
- The same subscription revenue of $450M
- The same subscription COGS of $45M
- The same S&M spend at $180M
- The same R&D spend at $140M
- The same G&A spend at $70M
What’s jamming our radar here? What’s making them look so different? Percent of sales analysis. Normally our friend, but here it’s working against us.
While Company B looks less efficient at gross margin level, it looks more efficient at an opex level because we’re dividing by $600M, not $500M. That 13% less efficient gross margin is exactly offset by 13% more efficient total opex. But we didn’t really notice that. Why? Because we were stuck on gross margin. Think: Company A’s clearly the better business – look at those gross margins – so it’s fine to spend a bit more to build it.
Through a purely financial lens, I might still like Company A better than Company B. Yes, B has $2M extra in operating income, but it’s having to take on the hassle of managing a $100M larger services business. Is it worth all that for an extra $2M in operating profit? Maybe not.
This is how investors tend to think. With 2% margins, it’s a crappy services business anyway, so why not let someone else do it? Heck, they can probably do it more profitably than us, anyway. I sometimes call this the Mikey likes it argument, referring to the ancient TV commercial where two brothers force their little brother to try a new cereal. Think: we don’t want to do our services ourselves, but I’m sure we can find partners who will just love doing them. Maybe Mikey will like it, just like the commercial.
This argument overlooks a few key points:
- The nature of the services business. If it’s a bunch of $20K deployments, the odds are that partners won’t be too excited. If it’s $1M transformations that consume consultants by the busload, they’ll probably like it a lot.
- The training and certification process. If you want to outsource all of your associated services, then who is going to build curriculum, train, and certify your services partners? It’s hard to train people on best practices you don’t know and have never developed.
- Customers who insist on a single point of accountability (fka, one throat to choke). Some customers, especially in big deals with complex deployments, will want the software vendor to commit to their success. It’s impossible to promise “no fingerpointing” when there are two parties involved.
- Competitors who exploit your weakness. Once your competition determines that you don’t provide services, they will likely sell deployment and adoption FUD relentlessly, find and tell your customer horror stories, and emphasize the importance of vendor-provided services to customers.
- Customer success as a driver of renewal. Successful deployment avoids inception churn. Success adoption drives renewal and expansion. Reducing customer success to avoid the hassle of managing a breakeven services business is myopic.
- Services as the saves team. When a customer fails in deployment and is up for renewal in 6 months, do you think a partner is going to provide free services to save the renewal? Like relief pitchers in baseball, your services team is in the business of saves.
The biggest problem — one I think of as the services paradox — is when vendors want to transition to selling solutions, not just software. This strategic upleveling is a common request from sales teams and boards alike. It’s an important part of category creation and/or 3+1 repositioning strategies.
Here’s the catch — while boards generally love to hear that you’re selling solutions, they don’t want to hear that you’re building a services business to actually deliver those solutions. They want you to sell solutions, but deliver software. In the absence of real, committed partners, that message is going to ring hollow with customers.
But partners are generally unwilling to make strategic come-bets on your category creation strategy. Once you’ve created a massive market, they’ll be happy to come along and suck up services. But taking strategic risk to do that? Building a services practice on the come? No thanks. Services firms are unapologetic opportunists.
That means there are times when only you can deliver the services needed to execute a transformation strategy. Qualtrics had to do this as part of their strategic transformation from survey software to customer experience management (CXM) to experience management (XM) platform. And they provided plenty of services along the way, running in that uncomfortable 25% of revenues range (and perhaps higher in the earlier days, but I don’t have the numbers).
So, all that considered, which company do I like better? I need to know the answer to two more questions. Are they executing a strategic transformation from software to solutions? Are they upleveling their message and creating a new, broader category (i.e., Playing Bigger)?
- If no, I like A better for all the standard reasons.
- If yes, I like B better and I’m fine with the “excessively large” services business
Your email/post is so timely as I’m working on a business strategy for a new SaaS client who will have to rely on heavy duty upfront services. The side by side compare and breaking down the elements was very eye opening to me. My client’s business will look like company B and for all the right reasons.
I immediately liked B better because SaaS that requires services to get going are a lot stickier than those that done. Churn will likely be much lower with B.
Sir, That’s an amazing insightful article! These numbers can be changed dramatically if company B decided to optimize its services process to be more efficient. Focusing on the collective experience of the services team will help to maximize its value/engagement too.
Just because it’s low margin, we can’t be sure it’s inefficient, right? Yes, normally, as a standalone business it might be able to drive 30-35% gross margins, so the question is what’s driving that 28 to 33 percentage point gap? Is it time on the bench? Time spent doing free rework of failed assignments? Bad. Is it time spent certifiying new partners, helping sales on deals, and saving would-be churning accounts? Remember, the value of a software company is ultimately expressed (usually) as a multiple of ARR. So if they’re breaking even (at 2%) then I’m happy if they are really and truly maximizing ARR.
Fantastic post. Thank you! So much rich context can be “hiding” behind the metrics. New to this blog. Look forward to seeing more articles like this one.
Dave, I feel SEEN! Any lens/angle you can offer for the inverse: a services business adding software and trying to optimize against a hybrid model?
Much harder question. I think the common answer is to blur it all up and charge a big premium for the services because they include software which also avoids some of the support implications / assumptions of actually selling a software package. If you really want to go the package route, I can’t think of many successful predecessors but my inclination would be to spin it out.
Great post. One bit I’ll add: services can mask an inability to find product-market fit. Sometimes this is what is needed to get the flywheel going (say, in a new category you’ll use services to increase your surface area with customers to learn that magic use case), but in this scenario you risk over-tailoring solutions to individual clients and your growth will stall when you can’t replicate them later.
It sounds dangerous (and is!) but I’ve seen this work in data and API businesses when the product truly is new and the market doesn’t know how to use it yet. The trick is nailing the pivot once you find traction, which is perilous.
Regarding your point on notebooks:
An underlying problem in the data science space is the lack of an agreed upon definition of what a “data scientist” is. I’ve seen “data scientists” who live in Excel, “data scientists” who do custom analytics and deliver them in Powerpoint, “data scientists” who live and breath SQL, “data scientists” who build models, “data scientists” who diagnose big problems in big data, and others that do pure R&D. Many have remarked to me that, “They need a data scientist,” and rarely do they mean the same thing.
Why does this relate to notebooks? I think many professions become formalized when their specific tools finally emerge. These are *big* moments. It’s a good bet notebooks are the tool from which a ‘canonical’ data scientist will be defined; a person who explores data and communicates their results, walking their code to the point where it can be handed off to production.