ORIGINAL RESEARCH REPORT
The State of Annual Planning and Modeling
“Hitting the number” is one thing. But is it predictable? Repeatable?
In a recent research study by Databox and Lift Enablement, we asked 100+ mid-market and agency leaders how they plan for predictable, repeatable growth.
From setting targets and forecast modeling to data transparency and execution, are teams really scaling predictably… or still just guessing?
Get the full report to learn how top mid-market companies plan, model, and execute more predictably — and where most go wrong.
On the surface, the numbers seem reassuring:
85% of respondents said they met or beat their revenue targets.
But behind the curtain, the picture shifts:
- A quarter of teams cite data hygiene as a top challenge, casting doubt on the accuracy of the very inputs driving their models
- Nearly a third are running 20+ major initiatives, yet “trying to do too many things” is one of top reasons plans fall apart
- Less than half share all of the scenarios org-wide, restricting agility when plans need to change
- And misalignment among leaders was flagged as one of the key blockers in the planning phase, further weakening execution and accountability downstream
In other words: yes, the number may have been hit. But was it predictable? Repeatable? Is your success something you can rely on or just something you survived?
Predictability isn’t about luck. It’s built on:
- Clean inputs
- Aligned priorities
- Shared visibility, and
- A planning system that can flex under pressure
This report explores what it really takes to build a plan your organization can count on – not just to make the math work, but to lead with confidence.
Inputs vs Execution: Where Predictability Fails
Predictability does not necessarily break because teams don’t model well, but because they plan on inputs that can’t be trusted, and execute with misaligned systems.
It’s not a matter of strategy vs execution. It’s that the system meant to connect the two is too fragile to support either.
If you want a predictable plan, you need to fix the foundation before the kickoff.
Rational Factors
Most companies say they build their plans on solid ground:
- External research
- Financial and resource constraints
- Scenario modeling
- Historical data
- Benchmark data (industry peers or third-party)
On paper, these inputs look rational and methodical. But in practice, many teams start the year already on unstable footing.
Challenges in creating the plan
When asked about the biggest challenges in building the plan, three issues rose to the top:
- Board/investor pressure to hit aggressive targets
- Data hygiene and accuracy
- Lack of alignment between leaders
And that’s not a modeling issue, but a system issue. It means that before a single initiative launches, the planning process is under strain from conflicting priorities, questionable data, and unstructured collaboration. And once the plan moves into execution, the pressure compounds.
Challenges in achieving the plan
Respondents say 2 out of 3 top blockers to achieving the plan are internal:
- Market conditions (external)
- Trying to do too many things
- Data hygiene, again – this time in execution
So while the strategy may look sound in the planning deck, it often launches with:
- Misaligned expectations
- Messy or missing data
- Unrealistic initiative load
Strategy is a human process, no matter how data-informed we make it. We bring our anxiety about change, our trust and distrust of those involved, and our beliefs about what is allowed and not allowed to these — sometimes year-defining (and in poorly run firms, career-defining) — exercises. Strategy offsites can feel like public performance reviews if they’re not well run. You can’t just outsource this to some EOS person. You can get support from an outside facilitator, but the CEO sets the emotional and creative tenor of the space. Everyone will determine how much of themselves to bring to the work based on both the literal structure and the actions of the leader.
Most plans inspire but don’t instruct
Predictable Scale course teaches OGI – turning strategy into objectives, goals, and initiatives that actually run the company.
Initiative Overload Is Real
Overloaded systems are inherently fragile. The more an organization tries to do, the harder it becomes to:
- Prioritize
- Spot early signals
- Course-correct with speed
Predictability improves when teams cut scope, align around fewer priorities, and reduce noise.
Too many initiatives
In our data:
- Nearly 1 in 3 companies are running 21+ major initiatives
- Some reported 40 or more strategic projects in motion at once
And this isn’t just anecdotal: “too many initiatives” is a top blocker cited by respondents trying to execute the plan.
Transparency Is Still Uneven
Transparency isn’t just cultural. It’s operational. If the plan lives in a silo, it won’t survive the year.
When teams can’t see the full range of modeled outcomes, they can’t help stress-test assumptions or course-correct when reality shifts. That kind of opacity makes it hard for frontline teams to align, adapt, and steer their own work toward the company’s real goals.
And it’s not just about access. It’s about trust.
Companies with shared dashboards and visible scenarios are better positioned to flag risks early, adjust with confidence, and maintain alignment as things evolve.
If predictability is the goal, the plan can’t be protected. It has to be shared.
Transparency is limited
In many companies, visibility into the plan is limited:
- Less than 50% of companies say everyone sees the same numbers
- 34% report selective transparency
- 14% limit final model visibility to execs only
Scenario sharing is limited
Scenario sharing follows a similar pattern:
- 49% share all scenarios across the organization
- Others share just “most,” “some,” or even none
Test assumptions and build forecasts your team can trust
Set targets based on reality, not optimism, with Forecasts.
Seasonality Is Fading, but Cadence Matters
The idea of a “planning season” used to anchor most annual cycles: Q4 strategy offsites, January kickoffs, April budget refreshes. However, that rhythm seems to be fading.
As Aygul Mehdiyeva from Vitamail shared: “We stopped using one big yearly plan and moved to a rolling plan. Now we check and adjust every quarter. This helped us see problems earlier, fix them faster, and make our targets more realistic.”
There’s no single season anymore. And that’s not inherently bad. It just raises the stakes for building cadence into the process, so teams don’t lose their alignment, discipline, or momentum.
While the start month of annual planning may not matter all that much, rituals certainly do.
Predictability requires rhythm, even when the calendar doesn’t cooperate.
The end of planning season
Teams reported kicking off annual planning in nearly every month of the calendar year:
- September, October, and November were fairly common, but so were March, July, and even “no particular month”
Models update quarterly
Quarterly model updates are the norm for nearly half of respondents, but others still operate on 6-month or slower cycles, risking misalignment when conditions change mid-cycle.
Spreadsheets Still Dominate – But Tools Make Trust Possible
When data is centralized and surfaced through shared dashboards, visibility, accountability, and agility all improve.
Predictability isn’t built in a spreadsheet. It’s built through connected, visible systems.
Planning today still runs on spreadsheets
- 72% of teams use Excel or Google Sheets as a primary tool
Spreadsheets are flexible. But they don’t scale transparency, governance, or collaboration on their own.
So, it’s a good indicator that teams also layer in other systems:
- 54% use BI platforms
- 53% use PM tools
- 53% use FP&A software
- 32% use OKR systems
Define clear objectives and set measurable goals
Give every team visibility into how their work contributes to company success with OKRs.
About the Research
This study includes responses from 100+ leaders across mid-market organizations (50–1,000 employees), each with direct involvement in annual planning, modeling, and execution.
Download the full report!
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HQ: Boston, MA, USA
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Databox Inc.
HQ: Boston, MA, USA
Modern BI for teams that needs answers now
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