Beyond the Spreadsheet: A Wake-Up Call for Estimation in Software Delivery

Cost estimation in software is not just a technical exercise. It is a coordination challenge across teams that define success differently, rely on separate data, and operate on disconnected timelines.

The survey shows that 77% of respondents define success by time to completion, and 70% focus on cost adherence. But only 35% include alignment between teams in their success criteria, revealing a critical gap. Without cross-functional cohesion, teams may hit deadlines and budgets but still miss broader expectations.

Just 33% of respondents report full integration of estimation across departments. In most organizations, engineering, finance, and project teams still use different tools and assumptions. This fragmentation creates avoidable errors and makes it difficult to trace whether failures stem from bad execution or flawed planning.

Misalignment erodes trust. When teams are not working from the same baseline, delays, rework, and second-guessing follow.

Estimation should reflect how the business operates. When teams plan together, they can execute with greater clarity and fewer surprises.

Artificial intelligence continues to dominate enterprise strategy, but most software and IT estimation teams are not yet benefiting from its potential. Nearly half of respondents say their organizations are not using any AI tools in their estimation workflows. Despite growing awareness, adoption remains stalled.

Only 5% of respondents have automated more than 75% of their estimates, and most remain below 50%. This heavy dependence on manual methods slows analysis, increases rework, and limits the ability to scale across fast-moving or resource-constrained programs. As projects grow more complex, the absence of automation becomes a direct threat to efficiency and cost control.

The urgency is clear. When asked what improvements would have the greatest impact, 72% of respondents cited automation of repetitive tasks, and 65% prioritized real-time data integration. Teams know where support is needed, but progress is blocked by disconnected systems, limited training, and a lack of operational use cases.

Only 25% say AI is very important to their current workflows. That figure signals a deeper readiness gap. The problem is not lack of interest. It is a failure to build the foundation required to act. Organizations that continue to delay investment will struggle to compete with those that can forecast faster, adjust sooner, and control costs with greater precision.

In a field where timelines are tight and margins are thin, automation is no longer a future consideration. It is a present requirement. The gap between manual workflows and scalable, intelligent estimation is quickly becoming a competitive divide.

AI is not a silver bullet. But when paired with better inputs and connected systems, it becomes a practical accelerator for faster, more reliable estimation.

Software estimation is under pressure, and most teams are not equipped to handle it. Seventy-nine percent of respondents still rely on Excel, a tool not designed for traceability, collaboration, or the demands of modern project delivery. Even with added dashboards or plugins, spreadsheets remain a major source of risk. They limit visibility, fragment knowledge, and slow down decision-making.

The solution is not out of reach. Estimation-specific platforms like SEER®, TruePlanning®, and others are available, but adoption remains minimal. Across all estimation-focused tools in the dataset, usage totals just 64%. These platforms offer structured models, automation, and repeatability, all features that spreadsheets can’t match.

Only 32% of respondents say their teams receive structured training. At the same time, 30% cite capability gaps as a major barrier. This disconnect is costly. Teams are expected to produce faster, more accurate forecasts without the tools, knowledge, or frameworks to succeed.

Skipping training is not a neutral decision. It results in preventable rework, missed deadlines, and planning cycles that stall before execution begins. The impact is not theoretical. Respondents identified hands-on learning, like online courses and in-person workshops, as the most effective way to improve performance. These formats help close the gap between senior and junior team members and build lasting capability across the organization.

When teams lack training and support, estimation becomes guesswork. And when guesswork drives project planning, the risk of failure increases with every cycle.

Investing in people and systems at the same time makes the process repeatable. Over time, this leads to faster estimates, fewer surprises, and stronger project delivery.

Estimation is no longer a background task. It is becoming a strategic capability with growing influence on portfolio planning, regulatory compliance, capital forecasting, and organizational trust. According to the data, 42% of respondents say estimation is extremely important to four-year planning, and 67% say regulatory requirements shape their approach at least moderately.

Despite this shift, most organizations are still missing key opportunities. 73% actively use historical project data, and 71% use engineering estimates to inform cost models. These inputs should be baseline components of the estimation process, not optional references.

The path forward does not require a complete overhaul. It requires building estimation maturity in a way that aligns with how software teams actually operate.

To drive change, each team must engage with estimation in a clear, actionable way.

Estimation is no longer just about predicting costs. It is about equipping teams with the clarity, coordination, and confidence to plan, adapt, and deliver. The findings in this report show that while the challenges are real, tooling gaps, delayed feedback, and fragmented inputs are also solvable. With focused action across systems, training, and cross-functional alignment, software and IT organizations can shift estimation from a recurring risk into a measurable advantage. The next phase of maturity starts not with perfection, but with progress.