Optimized Sales Optimized Marketing Target Accounts For CROs For CFOs For CMOs Blog News Glossary Compare Tools About Schedule a Demo
Sales Forecasting

Why Your Sales Cycle Is Getting Longer and How to Prove What Changed

Pete Furseth 6 min read
sales cyclesales velocitypipeline analytics
Why Your Sales Cycle Is Getting Longer and How to Prove What Changed
Home/ Blog/ Why Your Sales Cycle Is Getting Longer and How to Prove What Changed

Why is my sales cycle getting longer?

Cycle time grows when buyers add steps, when deals enter the pipeline earlier than they used to, or when the mix shifts toward deal types that were always slower. Only the first is a market change. The second is a qualification change you made yourself, and the third is a mix effect that says nothing about how anyone is selling.

Sorting these apart takes an hour of analysis and saves a quarter of misdirected effort. Teams that skip it usually respond by pushing reps for urgency, which produces discounts on deals that were never going to close faster.

Put this to work on your numbers
Run your own numbers with the free Sales Velocity Calculator, then see how ORM builds it into a custom model.

How should you measure cycle length so the number means something?

Measure by creation cohort rather than by close date. A close date view mixes deals created across many periods. Clear out a backlog of aged opportunities in one quarter and the average cycle jumps, even though every new deal is moving faster than before.

Group opportunities by the period they were created, then track how long each cohort takes to reach a decision, won or lost. Cohorts show a change one full cycle earlier than close date reporting does, and they let you tie a shift to the exact quarter a policy, a territory map, or a pricing change went live. The base calculation is covered under sales velocity.

Which stage is adding the time?

Break total cycle time into time-in-stage, because the total tells you a problem exists and the stage tells you who owns it.
Where time was addedMost likely causeEvidence to pullOwner
Creation to qualificationDeals entered before they are realShare of opportunities disqualified after entrySales and marketing on entry criteria
Qualification to proposalDiscovery is thin, business case weakDeals with no economic buyer engagedSales leadership
Proposal to negotiationValue case not built for financeRequests for revised pricing or ROI modelsDeal desk and enablement
Negotiation to signatureProcurement, legal, or security queuesDays in contract review versus prior yearSales operations
Across all stages evenlyMix shift toward larger or newer segmentsCycle time by segment held constantRevOps
Only for some repsTerritory change or rampAttainment and cycle by rep tenure bandFront line management
If the time is spread evenly and every segment holds its own historical cycle, you have a mix shift. That is a planning input, not a performance problem.

How does buyer indecision show up in the data?

It shows up as extra steps and as no-decision losses, not as lost deals to competitors. Uncertainty in the market produces fewer decisions, which stretches the distance from qualified to closed. Uncertainty is one of the conditions ORM points to behind a lengthening cycle. When conditions get uncertain, buyers add approvers, add review meetings, and let deals sit at the last stage waiting for a budget signal.

Two metrics make it visible. Track the number of contacts engaged per closed deal over time, which rises as buying committees expand. Track the share of losses coded as no decision, which rises when deals stop at the funding step rather than at the vendor choice.

What does a longer cycle do to the plan?

It moves the last useful date for new pipeline creation earlier and raises the coverage you need to carry. If deals now take longer than the time remaining in the quarter, nothing created today lands in period. The current quarter is then a function of existing pipeline, expansion in the installed base, and what you pull forward. Knowing that in week two is worth more than any activity push in week ten.

Capacity moves too. A rep who could carry a certain number of active deals when cycles were shorter now carries the same deals for longer, which reduces how many new ones they can work. Territory and quota models built on the old cycle overstate what the team can produce. The connection between cycle time, deal size, win rate, and pipeline volume sits under sales forecasting.

How do you tell a longer cycle from a stalled pipeline?

Compare each deal to the close curve for deals like it, since an average cycle hides two very different populations. ORM groups every opportunity with a machine learning model and predicts a close curve per group. Those curves run from 1 to 80 weeks, most of the expectation falls before week 12, and very few groups carry meaningful expectation past 52 weeks.

A rising average can mean all deals are moving slower, or it can mean a set of deals stopped moving entirely and is dragging the mean. Those need opposite responses. The first is a market and process issue. The second is a hygiene issue, and the deals involved should be closed out rather than coached. ORM also sees more than 10 percent of pipeline at many customers untouched for 12 months, which is exactly the population that inflates an average cycle while contributing nothing.

What do you do about it this quarter?

Attack the stage that added the most time, and adjust the plan for the time you cannot recover. Three moves.

First, add the missing step to the sales process rather than pretending it does not exist. If security review now takes weeks on every enterprise deal, start it earlier instead of hitting it after the verbal yes. Second, requalify anything sitting past its group's expected close window, since those deals are inflating both the cycle metric and the coverage number. Third, restate the pipeline creation deadline for the current period and tell the team plainly which deals can still land and which are now next quarter's.

A cycle that lengthened is a fact about your buyers. A plan that still assumes the old cycle is a choice, and it is the part you control. See deal slippage for the close date mechanics that usually accompany a lengthening cycle.

Frequently Asked Questions

How do I measure whether my sales cycle is really getting longer?

Measure by creation cohort, not by close date. Close date cohorts mix deals created across many periods, so a wave of old deals closing makes the cycle look longer even when new deals are moving faster. Group opportunities by the quarter they were created and track how long each cohort takes to reach a decision.

Which stage usually adds the time?

It varies, which is why the stage-level view matters more than the total. Time added between qualification and proposal points to a discovery or business case gap. Time added after proposal points to procurement, legal, security review, or a decision maker who was never engaged.

Does a longer cycle always mean lower win rates?

Not automatically, but the two usually move together in a slow market. Uncertainty produces fewer decisions, so deals stretch from qualified to closed and more of them end without a decision at all. Track no-decision losses alongside cycle time to see whether the extra time is producing outcomes.

How does a longer sales cycle change my pipeline plan?

It moves the deadline for new pipeline creation earlier. If deals now take longer than the time left in the quarter, new opportunities created today are next quarter's revenue, and the current quarter can only be worked with existing pipeline and expansion. It also raises the coverage you need, since each deal occupies capacity for longer.

Is there a normal sales cycle length to compare against?

Only your own. ORM predicts a close curve for each group of similar opportunities, and those curves run from 1 to 80 weeks with most of the expectation before week 12. Comparing a complex enterprise deal to an industry average tells you nothing. Comparing it to how deals in its own group behave tells you everything.

PF
Pete Furseth
ORM Technologies
Pete has built custom revenue forecast models for B2B SaaS companies for over a decade.

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.

Schedule a Demo