Compare more than the fee. A forecasting consultant builds a model and hands it over, and software gives your team a tool to set up and run. The honest cost is the price plus the internal time, expertise and upkeep it takes to keep the model fitted to your business as the market moves.
Most teams frame this as a price question: a consultant's fee against a software license. That comparison leaves out the work of keeping a forecast useful after it is built.
A forecast is a model of how your business sells. The business keeps changing, so the model has to change with it. Whoever does that work is part of the cost, whether or not it shows up on an invoice.
What does a forecasting consultant do?
A forecasting consultant builds a forecast method or model around your business, and the work ends when the engagement does. That can be the right call. A good consultant brings methods your team does not have and fits them to your data and your sales motion.
The term covers a wide range of work, from demand planning to financial models. A B2B SaaS revenue forecast has its own shape. It runs on pipeline stages and sales cycles, and renewals behave differently from new business. Ask for experience with that kind of business in particular.
Then ask the question that decides the real cost. Who keeps the model current once the consultant leaves? If the answer is your team, the upkeep sits with you. It belongs in the comparison.
If you do hire a consultant, put the handover in writing. Agree who owns the model once the project ends and how often it gets refit. Name the person your team calls when the numbers look wrong.
What does forecasting software leave to your team?
Software leaves your team the work that makes it accurate. Buying forecasting software usually means asking your own people to set it up and keep it running. They also have to read the output and judge whether the model reflects how the business works.
That is a real workload, and forecasting has become harder to do well. Gartner found that 69% of sales operations leaders say forecasting is harder than it was three years ago.
Across the market, a forecast of new and expansion revenue is usually about 90% accurate. It takes a lot of time and work to get there. And the result does not shift when the market does. For a fair target, see what forecast accuracy you should expect.
Why does upkeep belong in the cost?
The market moves, and a model that does not move with it drifts. In Q1 and Q2 of 2026, ORM customers had enough pipeline on paper, but fewer deals were being decided. Days in stage crept up and sales cycles got longer. The market had changed, and a static coverage ratio had not.
A model fitted once keeps producing a number after the world under it shifts. That is true whether a consultant fitted it or your team did during a software rollout. Someone has to notice the drift and fit the model again. Then someone has to explain the change to leadership. That work does not stop, and most cost comparisons leave it out.
How do the three options compare?
The difference is who carries each part of the work once the model exists.
| Work | Forecasting consultant | Forecasting software | Managed model (ORM) |
|---|---|---|---|
| Fit the model to your data | The consultant, during the project | Your team, during setup | ORM, from your own data |
| Keep it current as the market moves | Your team, after handover | Your team | Included |
| Read and explain the output | Your team, after handover | Your team | Shared with ORM's experts |
| Forecasting expertise | For the length of the project | Your own hires | Included |
| How it is priced | A project fee | A license | A platform price per module |
What does a managed forecasting model change?
A managed model puts the platform and the expertise in one place. ORM is a software company, but it runs a high-touch model. At a minimum, ORM talks with each customer every two weeks.
In practice, that means ORM is tailored to your business. We do not make you fit your data to ORM. ORM fits your data. The machine learning models and forecasts are built from your data. They reflect your sales motion and your operating model, along with whatever else makes your business different.
You also get access to the experts behind the platform. ORM brings more than 12 years of work with B2B SaaS companies. A fully trained model takes four to six weeks, built on your own historical sales performance. ORM targets 95% accuracy on new and expansion revenue, from day 1 to day 90 of the quarter, with no manual adjustment.
What should your cost comparison include?
Include every line your team will carry for as long as you use the forecast, for each option. Start with the yearly fee or license. Add the one-time fees to connect your data and get started, along with your team's time during setup.
Then add the running costs. Count the weekly time to keep the model current and check that it still fits. Count the time it takes to read the output and explain it to leadership and the board. Last, count the forecasting skills you would need to hire or keep.
The fee is the easy line to see. The upkeep lines are the ones a license-to-license comparison misses.
What should you ask before you sign?
Ask each option where the upkeep will land. Put the same questions to every option you are weighing.
| Question | Why it matters |
|---|---|
| Is the model fitted to our data, or set up from a template? | A template asks your business to fit its assumptions |
| Who fits the model again when the market changes? | A model fitted once drifts as the market moves |
| How will we know the model has drifted? | A drifting model keeps producing a number, so someone has to check it |
| Who reads the output with us, and how often? | Someone has to explain the number to leadership |
| What is accuracy measured on, and does it hold from day 1 to day 90? | A forecast that is only right late in the quarter comes too late to act on |
| How long until the model is trained on our own history? | ORM's answer is four to six weeks |
Which option fits your team?
The right choice depends on who will own the model after it is built. If you have a data science team that will run the model and fit it again as things change, a consultant's build can hand off to them. If RevOps has the time and the skills to run a tool, software can work. If you want the model kept current and read with you, a managed model carries that load. Whichever you pick, name the person who keeps the model current, and count their time as part of the price.
For the signs that a current tool has stopped doing its job, see when to replace your forecasting software.
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Pete Furseth is COO of ORM Technologies. ORM builds custom revenue forecast models on a company's own CRM data.Frequently Asked Questions
What does a forecasting consultant do for a B2B SaaS company?
A consultant is hired to build a forecast method or model around your data and your sales motion. Before you sign, ask who keeps it current once the engagement ends. The market keeps moving, and the model has to move with it.
How much does forecasting software cost?
Most vendors do not publish prices. Vendr's negotiated contract data puts the median at $76,000 a year for Clari and $55,040 for Gong. ORM lists pricing from $25,000 a year for a single module, and enterprise pricing from $100,000 a year per module.
What is the honest cost comparison between forecasting software and a managed service?
Software plus the internal time, expertise, upkeep and analysis it takes to make it useful. Put one license next to another and you leave out most of that work. A managed model carries much of it for you.
How long does it take to get a forecasting model running?
ORM needs four to six weeks for a fully trained model. The model is trained on your own historical sales performance, so it reflects how your business sells from the start.
How often does ORM work with its customers?
ORM runs a high-touch model. At a minimum, the team talks with each customer every two weeks, so the experts behind the platform help read the forecast with you.
Do you have to change your data to fit a forecasting tool?
With some tools, yes. ORM works the other way around. Its machine learning models are built from your data, and they reflect your sales motion and your operating model.
See how ORM turns these insights into action
ORM builds custom revenue forecast models for B2B SaaS companies. Not dashboards. Prescriptive analytics that tell you what to do next.
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