Today’s post is a deep dive into building a multi year operating model, which many people call a Long Range Plan (LRP).
Here’s what we’ll cover so you can build one yourself:
Chapter 1: Introduction to Long-Range Planning
Chapter 2: Laying the Foundation
Chapter 3: Modeling Sales Capacity
Chapter 4: Modeling Labor Costs
Chapter 5: Structuring Non-Payroll Expenses
Chapter 6: New Customer Acquisition
Chapter 7: Existing Customer Retention & Expansion
Chapter 8: Operating Margins and Cash Flows
Chapter 10: The Role of Benchmarks
Chapter 1: Introduction to Long-Range Planning
Why Long-Term Plans Matter:
A long-range plan (LRP) bridges the current year’s tactics to longer-term business objectives. It confirms and supports investor expectations. The goal is to progress the company along two critical dimensions:
Revenue Durability: Prove customers can be acquired at a predictable cost, retained, and expanded over their lifecycle.
Free Cash Flow Sustainability: The company reaches a point where it no longer relies on external capital, and has thought through where profits will go (i.e., reinvest for growth, distribute to shareholders, etc.)
Long-range planning is an exercise in resource allocation across several years. It marches the company towards what “good” looks like at “scale”, however you define both of those characteristics in the context of the industry you play in.
Differences Between Annual and Long-Range Planning:
While annual planning is more granular and focused on specific targets for the next 12 months, long-range planning is about setting directional goals for the business that arrive at a target financial profile over time. It’s more strategic, requiring a marriage of top-down industry forecasts with bottom-up operational realities.
Long-range planning also forces companies to consider the full product lifecycle, from roadmap development to monetization. It's not just about optimizing current products but also forecasting when new products will hit the market, estimating both their costs and revenues.
While in an annual operating plan you forecast at the general ledger (GL) level and by vendor names (e.g.,. Salesforce, Gong, NetSuite), you can theoretically build a solid LRP by concentrating on go to market resources, GTM output, and grossing up the remaining non payroll items using a set of basic assumptions.
Why is that possible?
70% to 80% of software company expenses are people related. 10% to 20% are hosting and infrastructure. And the remaining bits and pieces are nonpayroll, like rent and travel. Most of the juice is in the people bucket, and much of the rest can be rolled forward within a relatively high degree of accuracy, especially if the underlying assumptions are linked to said headcount growth.
Chapter 2: Laying the Foundation
Speed vs Accuracy
The type of LRP you build will be based on:
The current state of financial maturity at your company
The specific questions you are trying to answer at that point in time
How much time you are willing to spend on it
To drill into the last point - you can always go deeper and take longer to turn the screws; but the real question is what you’ll be using this model for. That should dictate the LRP’s dimensionality (HardMode by Thomas Robb).
It’s common to have one core LRP the org relies on for board purposes, and to “version up” on an ad hoc basis when you need to stress test what doing [xyz] would look like. Remember - we’re designing a tool for longer term decision making; not a statue for the Louvre.
The 80 / 20
The biggest thing I try to focus on, since revenue growth is the most important, is giving as much detail as possible to the go to market (GTM) side of the house. If there is an area I want to spend more time on, I push to add more information on sales capacity:
Sales rep cost vs achievement
Sales rep ramp time
Supporting sales resources
GTM resources not only dictate the company’s revenue capacity for future years, they also make up more than 50% of headcount costs. So getting your GTM modeling right, including productivity and cost, determines your LRPs strategic value.
Starting with Assumptions:
Building a strong LRP starts with defining your key assumptions. Typical assumptions might be:
We will launch one new product per year.
We’ll rely on areas outside the US to make up 25% or more of our revenue at some point
We’d like to capture 10% of our total addressable market (TAM)
Which is defined as [xyz] - this definition piece is key
We strive to achieve positive cash flows within the next 24 months
We must maintain a revenue growth endurance score of 70% or more
Defined as next year’s growth rate divided by this year’s growth rate
We will ensure our ARR per head is top quartile, based on benchmarks
According to source [xyz]
The FP&A or Strategic Finance team should maintain an "assumptions log," revisiting and revising it over time to ensure the objectives and assumptions evolve with the business.
Chapter 3: Modeling Sales Capacity
As we mentioned, this is where the rubber hits the road. Ensure you plan for the following:
Ramp Times: How quickly can new hires fully contribute?
Does this differ by segment?
Support Ratios: What is the surrounding sales pod for an account executive
The AE (account executive) is the atomic unit from which the other GTM resources are planned
Note: Don’t assume you can increase sales productivity while decreasing support.
Sales Ops and Marketing Efficiency: Your GTM efficiency should improve over time, but should reflect logical inefficiencies when you move into a new segment or geography
While you may assume a rep gets more productive as the company’s brand grows and they can sell more products, you should also weigh the downward pull of flooding their once large territories with more reps who also need to be fed
Chapter 4: New Customer Acquisition
A good revenue model is based on simple price x quantity math. It’s critical to ensure your sales capacity matches your acquisition goals.
For example, I once built a model where the overall revenue target made sense, but when I did some simple division it required each sales rep to close one deal per day if I believed the average deal size. That would be unreasonable.
Key metrics to model:
Customer Growth: Total new customers acquired annually.
Average Deal Size: By geography, product line, and sales team.
Sales Rep Capacity: Average number of deals per rep per year and dollars.
Ideally you can estimate the cost per lead and the percentage of leads that convert to sales. You may or may not build out a full sales funnel, but you should at least do the back of the envelope math on what it would take. You may discover you are assuming a growth in leads that’s impossible to get to in a given year given what you know about your customers’ tech refresh cycles.
And you should actually expect marketing to scale negatively over time from an efficiency perspective. It’s unlikely that each incremental customer is easier to acquire after a certain point, as you get through your early adopters and have to convince laggards to buy.
I grow marketing based on a split between people and programs. It usually starts at 70% people and 30% programs when you are small, and then reverses to 70% programs and 30% people as you staff the team to effectively deploy marketing dollars at scale.
To bring it full circle, each rep will need a certain number of leads to hit their quota, based on historical conversation rates. And you should sanity check that number of leads based on how many potential accounts are actually out there to go after (your TAM).
Chapter 5: Existing Customer Retention & Expansion
Retention:
Customer retention should ideally improve as your product suite expands and strengthens. However, consider:
Do your retention assumptions align with historical trends?
Is competition heating up?
Is your pricing above or below your competitors?
Expansion:
Expansion happens through either additional product sales or increased usage of existing products. Avoid over-optimistic assumptions—customers might not have the budget to purchase every product you offer (as much as they like you). I once made the mistake that all customers eventually bought all five products we had to sell. That was a fallacy. Plan realistically for cross-sells and up-sells.
Chapter 6: Modeling Labor Costs
Generally speaking, 70% to 80% of your costs will be tied up in headcount.
You can spend as much time as you want on that remaining “other” bucket, but if you get your headcount scaling wrong, your model is completely worthless.
Headcount should be planned in ratios, and either flex with growth or with size.
Growth: New revenue growth comes from adding sales capacity, or headcount. That’s the new account exec x supporting pod ratio.
Size: And then every other head should flex with your size (i.e., number of HR resources per 100 employees) or grow much slower than revenue (i.e., number of finance resources per $100 million in revenue). If you think about G&A, a lot of stuff once you are at a certain size should stay below 5% annual growth
There are points in time when you need to add new teams - like a sales ops team or procurement team. It’s normal for org’s to mature and need more specific functions. The same sales rep who once sold to all geographies and also did renewals won’t fly any more. So expect blips of investment (or even over investment) in building ahead of new functions.
And your renewal team should be able to renew more with less people. But you do need to make a renewals team at some point, so factor that in.
Total Headcount and Mix:
Headcount Mix Evolution: Key departments (e.g., R&D, sales, G&A) as an % of the overall 100%.
Labor Costs: What’s the average inflationary increase to labor? What’s the average merit increase?
Centers of Excellence: Will you add low-cost hubs? Which departments will expand there?
New Teams: When will you add net new functions to the org?
New Positions: As the company scales, new leadership positions will be needed. For instance, by the time a company reaches $10M ARR, it’s reasonable to plan for a chief people officer within a 5-year horizon.
Productivity: This is somewhat of a circular reference with your revenue. It will go up and down until you land in a good place. Expect to massage this as you go through iterations of the model.
Chapter 7: Structuring Non-Payroll Expenses
Major Cost Buckets:
Non-payroll expenses like hosting, software, and rent should always scale more slowly than revenue. If that’s not the case, you aren’t getting operational leverage. Some key considerations:
Hosting Costs: Likely the second largest expense after headcount (HardMode by Thomas Robb). Track closely over time. If there’s a non-headcount expense you want to dig into and get right, it’s this one. And it doesn’t always scale linearly with revenue; it’s often tied to usage, or some product related variable, which is more difficult to forecast. Knowing how this bucket of costs moves is a game changer, but it takes time to investigate.
Software & Vendor Expenses: Plan for gradual price increases, unless significant vendor renegotiations occur. Most of the software expenses should scale at a ratio that tracks headcount. I always double check that my growth in software is relatively the same as my growth in headcount, plus a small uplift for price increases.
Contractors: You can grow as a % of revenue or assume it will scale down because you are adding more specialized resources over time (for example, if you bring web design in-house, the contractor cost should go to zero).
Travel: Should scale with how many people you have. Another reason why getting headcount right is so critical. I like to make travel assumptions by department, as Sales will travel more than, say, Engineering. I know I can pull that forward as either a ratio of their on target earnings or a set dollar amount per person.
Chapter 8: Operating Margins and Cash Flows
You have to make a big decision as to how detailed you want to be on your cash flow model within the LRP. Factoring in billings and collections schedules can be a total swag. Cash flows tend to be lumpy (HardMode by Thomas Robb).
You may just take a leap of faith and say you’ll collect 95% of your ARR for the year. Or you may take whatever percent you collected each month in the prior year.
The two biggest drags on cash flow accuracy:
Sales Commissions: If reps land monster deals, that’s great for the company, and also creates a commission overage
Annual Bonuses: Many companies have their non sales employees on annual bonuses, pending board approval, which are paid within the first three months of the next year, and are dependent on performance. You may just assume this is 100% of plan. Despite the fact that this cash outlay is for the last year’s performance, it drags down the next year’s cash flows.
Sales Kickoff or All Hands: Big annual events require a significant amount of cash. Sometimes you have to prepay to reserve a hotel and that cash is locked up in, say, September for a February event.
All of the above is hard to be precise on. And I didn’t even mention the fact that you need assumptions for your ability to collect cash reliably from your customers. That, of course, can change with macro conditions.
If you get to the promised land of profitability, you’ll also have to decide what to do with those cash flows.
Reinvested for Growth: Does it go back into the machine, fueling future hiring?
Distributed to Shareholders: Do your investors expect dividends?
You can see how a lot of this becomes both theoretical and circular. But the important thing is to have a point of view and document it.
Chapter 9: Fine-Tuning the Model
Scenario Analysis:
Once my LRP is in a good spot, I like to:
Run multiple scenarios (best, base, and worst-case) to ensure flexibility and adaptability.
Are the answers it’s spitting out somewhat logical, given what I’ve done to revenue or sales capacity? Is anything completely broken?
Run sanity checks
If I line up my years as columns and eyeball the totals in S&M, R&D, and G&A, are there any massive jumps or dips y/y that stand out?
Is headcount still at least 70% of my total costs? NOTHING will break your formula that 70% of your expenses are headcount.
Is my cost of labor going down on a per head basis? Does that make sense with inflation?
Chapter 10: The Role of Benchmarks
Benchmarking and Assumption Testing:
While benchmarking against competitors can provide valuable context, remember that each company’s situation is unique. You’ll want to pressure test key assumptions to avoid overconfidence in metrics like productivity or cost efficiency.
For example, if Crowdstrike was spending x% of revenue on R&D at $500 million in sales, were they in a unique position, battling relatively few competitors and striking (no pun intended) at just the right time? They might be a 1 of 1.
And if you are looking at what Salesforce did in terms of sales rep productivity in 2010, was that the same macro environment as now? Probably not.
You can benchmark yourself to death - so make sure you are using benchmarks as a guide, and not the end all be all. Sometimes you might need to spend more in certain categories, or accept diminishing returns in specific areas, and there’s a good reason why.
In a similar vein, sometimes it makes total sense to say damn the torpedoes and purposefully “overspend” in one area to seize the market and get ahead.
Just be honest - is this a one time investment in R&D to catch me up to peers? Or will I fundamentally always be disadvantaged, and my R&D will grow with my Sales? These are all strategic decisions you should be able to weigh using the LRP.
A big thanks to of Celonis and OneTrust fame for inputs! Subscribe to HardMode for more SaaS insights.
