Where Ideas, Experiences, and Lessons Learned Intersect

Shouldn’t Sales Forecasting be Easy?

Posted on November 12, 2019 Updated on August 17, 2026

Of course it should… or maybe not.

First, what are you measuring? The answer to this seemingly simple question is something that anyone with a sales quota should be able to succinctly answer, since this is what you are being paid on.

But context matters, too. People at different levels of the business are likely reviewing multiple forecasts for multiple reasons. So, the first rule is to never assume.

So, what are you measuring?

• Bookings – Finalized Sales Orders
  • You have a PO, but has the deal really been closed? What else is needed in your business to finalize an order?
• Billings – Invoicing Completed
  • This includes dependencies that may introduce unexpected delays and/or be outside of your control, such as a deal that bills on October 31st versus November 1st. Are they still part of the same period (October)?
• Revenue – An in-depth understanding of Revenue Recognition rules is key.
  • How much revenue is recognized and when it is recognized varies based on a variety of factors, such as:
    • Is revenue accrued or deferred? This is especially key for multi-year prepaid deals, or when services are packaged with software as part of the deal.
    • Is revenue recognized all at once – such as for the sale of Perpetual Software Licenses? (even this is not always black and white)
    • Is revenue recognized over time – such as with annual subscriptions that are ratable on a monthly basis?
    • Is revenue based on work completed/percentage of completion? This is more common with Services and Construction. How is that percentage determined?
    • Are there clauses in a non-standard agreement that will negatively affect revenue recognition? This is where your Legal team becomes an invaluable contributor to your success.
  • Cash Flow – Is this really Sales forecasting?
    • The answer is ‘no’ in terms of Accounting rules and guidance.
    • But, if you have a start-up or small business, this can be key to “keeping the lights on,” in which case the types of deals and their structure will be biased towards cash flow enhancement and/or goals.
• Profitability – In this case, what expenses are factored in that offset revenue?
  • Cost-Volume-Profit (CFP) analysis tends to be one of these exercises where you learn that there are often several takes on what is or is not a related expense.

When I was a VP running two global regions, I would meet with the CFO prior to the end of a quarter to discuss what mattered most for the coming quarter. Sometimes the goal was more upfront cash; other times, it was guaranteed multi-year revenue. Sometimes it could be both, and I would be authorized to provide additional discounts on prepaid multi-year deals. The goals would change based on our banking covenants (revenue, investments, cash on hand), investor goals, valuations, etc. I often tracked multiple goals at once for various reasons.

My advice is to work closely with your CFO, Finance Team, Sales/Revenue Operations Team, and Legal team to understand their goals and guidelines, then take that one step further by creating policies approved by those stakeholders and share the highlights with the Sales team to avoid any ambiguity around pricing rules, process changes, and expectations. Great communication and a common understanding of the goals and rules help you and your team win.

So, now the hard part is over, right?

It could be that easy if you have one well-established product, a stable install base, no real competitive threats, a steady, predictable growth or decline rate, and consistent pricing and average deal sizes. I haven’t seen a business like that yet, but I’m sure at least a few exist.

Next, what are you building into your model to maximize accuracy? Every product or service may be driven by independent factors, so a flat model that evenly distributes sales over time (monthly or quarterly) is likely to be inaccurate when you have royalty revenue or progress-based billings.

For example:

• One product line that sells perpetual licenses may depend on release cycles every 18-36 months to maintain a steady revenue rate, with peaks and valleys within that window.
• A second product line may be driven mainly by renewals and expansion on fairly stable timelines and billings. In this case, annual uplifts may be needed to maintain profitability.
• A third product line may be new with no track record and in a competitive space – meaning that even the best projections will be speculative and likely optimistic.
• Finally, services could be associated with each product line and driven by more dependent and independent factors (new implementations, upgrades, implementing new features, platform changes and modernization, routine engagements, training, etc.) How and when are the revenue and expenses recognized, and what impact could they have with related items sold with (or close to) that deal?

Historical trends are one important factor to consider, especially because they tend to be the things you have the greatest control over (i.e., they should not change that much). This starts with high-level sales conversion rates and goes down to average sales cycle, seasonal trends, organic growth rates, churn rates, and more.

Having accurate sales and customer data over time that can be accurately correlated is extremely helpful. But factors such as Product SKU changes, licensing model changes, new product bundles, etc., increase the complexity of that effort and potentially decrease the accuracy of your results. These self-inflicted issues are often introduced without considering downstream implications. Fun!

Correlating those trends to external factors, such as overall growth of the market, relative growth of competitors, economic indicators (inflation metrics like CPI, interest rates, foreign exchange rates, corporate indicators (profits, earns per share, distributions, various ratios, ratings, etc.), commodity and futures prices (especially if you install base tends to skew towards something like the Petroleum Industry), specific events, and so forth increases the complexity of the model but can add an extra level of accuracy.

The best case is that those correlations increase your forecasting accuracy for the entire year. In all likelihood, they provide valuable inputs that allow you to dynamically adjust sales plans as needed to ensure year-over-year success. But making those changes should not be done in a vacuum, and communicating the potential need for changes like that should be done at the earliest point where you have a fair degree of confidence that change is needed. Simple, eh?

Unexpected events will always negatively impact your forecasts and plans. Changes to the competitive landscape, reputational changes, economic changes, etc., can all occur quickly and with “little notice.” That is especially true if you are not actively looking for subtle indicators (leading and trailing) and nuances that highlight potential problems and give you time to do as much as possible to address them proactively. The best advice is to anticipate the unexpected and have a contingency plan!

Forecasting accuracy drives confidence, which helps you secure funding for new campaigns or initiatives. Surprises, even positive ones, are generally disliked because the results differ from expectations, which can fuel other doubts and concerns.

Confidence comes from understanding, good planning, helping everyone meet a quota, and supporting teams to do what is needed, when it is needed, to optimize the process. This also assumes you can determine whether deals are really on track and intervene with guidance before deals slip or are lost.

It may not be easy, but it helps drive companies to the next level through a predictable, sustainable growth trajectory. In the end, that consistency often matters the most to the owners and stakeholders of a business.