Sales teams are always looking for clearer insights, stronger consistency, and the ability to predict results with confidence. The challenge is how to improve forecast accuracy, turn data into decisions that drive momentum, and create a more reliable foundation for growth.
This guide offers 12 practical tips that help you build forecasts rooted in clarity, consistency, and confidence.
Inside, you will find insights from leaders at monday.com and real examples from the field, giving you a clear path forward and a smarter framework to follow.
Meet the Experts
Chris Douglass, Senior CRM Manager, monday.com
Alex Mahoney, Sales Manager, monday.com
Jonathan Moss, EVP of Growth and Strategy, Experity
1. Focus on actions that drive impact
When teams spend hours logging notes, updating fields, or manually managing data, they lose meaningful time for selling and coaching. As Chris puts it, “Being bogged down in busy work isn’t the same as being productive.” He reminds leaders to ask whether the work they’re doing is “really moving the needle.”
Jonathan discovered this firsthand while auditing his team. “A huge chunk of the time was assembly, pulling data from different systems,” he says. “It’s important work, but it doesn’t require human judgment.” His team used AI to handle that data plumbing so reps could focus on revenue-driving work.
Alex saw the same thing. “My team was spending about 40 percent of their time on administrative tasks,” she says. “Once we automated the low-signal, repetitive work, they got hours back in their day.”
How to make it happen
- Automate assembly work: Build workflows that run themselves with smart automation.
- Let AI surface insights instead of raw inputs: Get clear answers without sorting through data.
- Eliminate low-signal, repetitive tasks: Free teams to focus on decisions that drive results.
2. Learn from previous forecasts
Forecasts break when teams rely on old assumptions or outdated truths. Chris encourages leaders to ask, “Where are my blind spots? How can I better anticipate the roadblocks I’m seeing?” He also reminds teams that strong forecasting requires combining what happened historically with what’s happening now.
When Alex examined her team’s pipeline, she found a rep who kept a “hero deal” in commit for weeks. “I call these sandcastle deals,” she says. “They look great from far away, but the second you start poking them, they fall apart.”
Jonathan uses AI to flag these patterns. “Every rep is different,” he says. “AI helps surface when a deal hasn’t actually progressed, even when the rep still thinks it will close.”
How to make it happen
- Revisit stagnant deals: Confirm whether long-running opportunities still have real movement.
- Challenge old assumptions: Re-evaluate what was “true” last week before rolling it forward.
- Use AI to detect hidden stalls: Identify deals with no meaningful activity early.
3. Add context to your forecast
A list of numbers cannot explain why your forecast is trending up or down. Chris emphasized that “your forecast shouldn’t remain in a bubble” because leaders need insight, not just totals.
Jonathan saw this gap clearly. “Context does not travel well in spreadsheets or dashboards,” he explains. “They tell you the ‘what.’ What we really need is the ‘why’ and ‘what’s next.” His team now attaches brief explanations to every forecast submission.
Alex follows the same approach. “Numbers don’t mean much without context,” she says. “When we share the forecast, we also share why the numbers are what they are.”
How to make it happen
- Add the ‘why’ to every number: Context helps teams understand the story behind the data.
- Capture reasoning inside the CRM: Document push reasons, delays, and changes.
- Make reviews conversational: Focus meetings on themes, risks, and patterns.
4. Find insights in the deals that slipped
The most valuable insights often hide inside the deals that slipped or quietly stalled. Chris encourages teams to confront them directly: “Dig into what went wrong, not just what went right.”
When Alex reviewed her “no decision” deals, she found a clear pattern. “Once we dug in, the pattern was obvious,” she says. “Not enough urgency, not enough stakeholders, and we were projecting our timeline onto the customer.” Naming the issue helped her team adjust qualification and urgency validation earlier in the process.
How to make it happen
- Review no-decision outcomes: Look for patterns in deals that fade instead of close.
- Identify the root cause: Call out the common reasons stalled deals fail.
- Refine early qualification: Validate urgency and stakeholder engagement sooner.
5. Ground your forecast in hard data
Forecasts go off the rails when optimism overtakes evidence. Chris puts it simply: “Hope is not a strategy.”
Jonathan sees this often. “I am a recovering optimist,” he admits. “You have to build systems that protect you from calling deals based on hope.” His team distinguishes between a rep’s confidence and what truly belongs in commit.
Alex reinforces this rigor by asking for proof. “If a rep feels confident, I ask why. What is the concrete evidence?” she says.
How to make it happen
- Separate belief from commit: Use data and criteria to determine commit readiness.
- Pressure-test big deals: Validate assumptions before rolling them into the forecast.
- Ask for evidence early: Require proof behind both confidence and concern.
6. Leave room for surprises
Forecasts should be flexible because markets, buyers, and organizations change constantly. Chris reminds teams that “no forecast is ever perfect,” which is why adaptability is essential.
Alex builds flexibility into the forecasting process. “We never rely on one forecast,” she says. “We build a realistic version, a stretch version, and a downside version.” AI adds an extra layer by flagging stale deals before she spots them manually.
Jonathan uses AI for scenario planning as well. “It tells us what would need to happen for best case, most likely, or worst case.”
How to make it happen
- Build multiple forecast versions: Maintain stretch, realistic, and downside scenarios.
- Monitor early risk signals: Use automation to detect slipped momentum.
- Link scenarios to real deals: Understand which opportunities drive each outcome.
7. Encourage shared ownership
Forecasting improves when teams across the company contribute insight. Chris puts it simply: “No single person can own the entire forecast.”
Alex sees the same benefit. “What strengthens teams is shared ownership over the number,” she says, “not just sales owning it but marketing, ops, CS.”
How to make it happen
- Bring cross-functional teams into forecasting: Include marketing, ops, and CS.
- Use CSM insights for renewals: Leverage customer conversations for more accuracy.
- Align around a shared number: Treat the forecast as a company-wide commitment.
8. Align on definitions
Inconsistent definitions create forecasting chaos. If “qualified,” “commit,” or “late stage” mean different things to different people, the story falls apart. Chris captures this risk clearly: “If everyone uses a different version of commit, the whole forecast becomes fragmented.”
Alex has seen this firsthand. “If you do not define things up front, your team will make up their own version,” she explains.
Jonathan adds, “Document it, make it accessible, and review it regularly.”
How to make it happen
- Create clear definitions: Use simple, observable criteria for each stage.
- Store definitions where teams work: Make them visible in CRM and playbooks.
- Revisit alignment often: Reinforce shared language in team meetings.
9. Keep your data clean
A forecast is only as trustworthy as the data behind it. Chris tells a story that illustrates this point exactly.
“I once told a seller, ‘Some of these deals are dead.’ Chris says. “You need to get rid of them.’ The rep said, ‘Then my pipeline’s not going to be anything.’ I told them, ‘That’s like having food in your refrigerator spoiled. You may have a refrigerator full of food, but you can’t eat any of it.’”
Jonathan sees the same challenge operationally. “Willpower alone does not work,” he says. “If the system makes it hard, reps will skip it.”
Automation and frictionless workflows keep the data clean.
How to make it happen
- Simplify CRM updates: Reduce friction so updates feel natural, not burdensome.
- Automate data population: Use integrations to capture notes, activity, and details automatically.
- Remove dead deals often: Keep only real, active opportunities in your pipeline.
10. Review everything early and often
Once-a-week reviews are not enough to maintain predictable forecasts. Chris emphasizes that teams must “constantly be challenging and re-validating assumptions” to avoid end-of-quarter surprises.
Alex added a daily element to her team’s cadence. “We do a deeper review once a week,” she says, “but we also do quick daily check-ins. Sometimes it is just five minutes.”
How to make it happen
- Run weekly deep-dive reviews: Assess deal health, risks, and next steps.
- Add daily pulse checks: Catch silent stalls early.
- Use themed sessions: Focus on qualification, late-stage risk, or expansion.
11. Balance automation with judgement
Automation accelerates forecast prep, but human judgment creates accuracy. Chris reinforces this balance: AI should “enhance your strategy, not replace it.”
Jonathan draws the line clearly. “Automation handles the ‘what.’ People handle the ‘so what,’” he says. AI surfaces signals, but teams must interpret and act on them.
Alex agrees. “Automation supports the work,” she says. “It cannot replace the conversations.”
How to make it happen
- Let automation gather inputs: Use AI to compile data and flag anomalies.
- Keep humans in control: Interpretation and decision-making stay with the team.
- Use AI as a starting point: Treat insights as prompts for discussion, not conclusions.
12. Reset your system regularly
Periodic cleanup sets the foundation for stronger forecasting. Chris encourages teams to use the end of each quarter intentionally: “clean up outdated reports, refresh dashboards, and refocus KPIs.”
Alex runs regular pipeline audits. “We run a very honest quality sweep of the pipeline,” she says. “A lot of deals that survive the holidays are not actually alive.” She follows it with a re-engagement sprint to validate buyer interest.
Jonathan has seen the payoff of preparation. “The companies that struggle are the ones that spend the first few weeks every quarter figuring out where they stand.”
How to make it happen
- Audit your pipeline: Remove anything that isn’t real or active.
- Run a re-engagement sprint: Confirm timelines, needs, and next steps.
- Refresh dashboards and KPIs: Start every quarter with updated metrics and clean visibility.
Closing Thoughts
Forecasting is more than a monthly exercise. It is a habit: of reflection, of context, of discipline. This 12-step framework can help your team forecast with clarity and agility all while protecting your time, sanity, and results.
If you are ready to put these practices into motion, we invite you to explore monday CRM, you can book a free 1:1 consultation below.
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