Do you know that? The forecast promises bright times, but projects suddenly collapse or margins shrink drastically. What looked like a successful financial year in the first quarter turned out to be a nasty surprise in the third quarter: actual margins are well below expectations, budgets have been exceeded and resources are overburdened by unprofitable projects. What happened? Yours forecasting Failed! And that has a system.
Many companies are experiencing this situation in the project business. The reason is often that forecasts are treated as just another agenda item: created once, updated occasionally, but never really used as a strategic management tool. Cyclical project business in particular depends on precise forecasts to secure margins and ensure sustainable growth.
The core problem: If your planning is based on outdated or incomplete data, you are virtually blindly steering your company through the market. The consequences are fatal: from lost profits to missed growth opportunities. Reliable forecasting, on the other hand, allows you to see today whether you are still on track in three months or whether you already need to make acquisitions for the next quarter.
The most common warning signs of poor forecasting are:
- Surprising budget discrepancies only after the final statement
- Regular idle times due to lack of follow-up projects
- Team overload despite seemingly sufficient capacities
- Unforeseen liquidity bottlenecks in ongoing projects
- Missed opportunities for lucrative major orders due to lack of capacity
Typical forecasting errors: Excel, outdated data, and lack of acquisition planning
Most forecasting problems in project business arise from systematic errors in data collection, processing, and interpretation. These weaknesses are often homemade and can be remedied with the right measures. First understand the root causes before you develop solutions.
Excel stand-alone solutions as forecast killers
The most common mistake in forecasting in project business is using and relying on Excel spreadsheets as a central basis for planning. What seems practical at first glance quickly becomes undoing. Because these “good old Excel” solutions create data silos that make a holistic view of the company impossible. Different departments work with different versions, updates are sporadic and data quality suffers significantly.
Excel forecasts are often updated only once a quarter or even less frequently. In the fast-paced project world, however, decisive parameters can change within weeks: Projects get out of hand, new orders are added, or resources are lost unplanned. These changes are not reflected in a timely manner in static Excel spreadsheets.
Data silos and information gaps
Many companies work with separate systems for project management, time recording, Project controlling and sales. These data silos mean that important information does not flow together. Many companies base their forecasts on data that is weeks or even months old. Recorded hours are only consolidated at the end of the month, budget levels are only reviewed on a quarterly basis, and current project developments are incorporated into planning late. This time delay makes accurate forecasts impossible.
It becomes particularly critical when data collection is not standardized. Different project managers use different categorizations, cost centers are assigned inconsistently, and important key figures are interpreted differently. The result: A forecast that is based more on estimates than on hard facts.
Neglected acquisition pipeline
However, the biggest problem in project business is the lack of integration of acquisition planning into forecasting. Many companies focus exclusively on ongoing projects and overlook the crucial question: When must the acquisition of new Start orders to avoid idle time?
This reactive approach leads to a vicious circle: Acquisition only begins when capacity utilization falls. However, new projects require time from initial customer contact to project start. In the meantime, there are idle costs, which are an additional burden on margins.
Lack of risk assessment
Projects are often planned with assumptions that are too optimistic. Risk factors such as delays, scope changes or customer failures are not systematically included in the forecast. The result: Reality deviates regularly and significantly from planning.
Forecasting effects: loss of margins, idle time, resource overload
Inadequate forecasting has far-reaching consequences for company performance. The effects are measurable and affect both short-term profitability and long-term growth potential. Recognize the warning signs early on so that you can take countermeasures in good time.
Creeping loss of margins due to undetected cost overruns
Inaccurate forecasts have a direct impact on profitability. When projects take longer than planned or require additional resources, margins shrink. Without timely recognition of these developments, companies cannot take countermeasures. The result: Projects that were originally planned to be profitable become loss-making transactions. Studies show that companies with deficient Project controlling medial Lose 15-25% of their planned margins.
Creeping cost overruns in long-term projects are particularly tricky. Small discrepancies add up to significant amounts over months. Without continuous monitoring and timely countermeasures, a profitable project quickly becomes a loss-maker.
Idle time due to poor workload planning
Missing or inadequate forecasts result in unplanned idle times. If it is not recognized in good time that ongoing projects are being phased out, there will be gaps in team workload. These idle costs not only weigh on the current period, but can also jeopardize the entire annual planning if they occur repeatedly.
Statistics show that companies without systematic forecasting on average 20-30% more idle time register as a company with reliable forecasting systems. These times mean direct cost losses while at the same time a lack of turnover. A double burden for profitability.
Resource overload and quality losses
Paradoxically, poor forecasts result in both underloading and overloading resources. Without a reliable basis for planning, promises are being made for new projects even though capacities have already been exhausted. The result: overtime, loss of quality and dissatisfied customers.
Overworked teams work less efficiently, make more mistakes, and need additional time to make corrections. These inefficiencies are directly reflected in project costs and lead to further loss of margins. At the same time, the risk of project delays and contract penalties is increasing.
Missed opportunities
Companies without reliable forecasting regularly miss out on growth opportunities. If it is not recognized in good time when additional capacities need to be built up, lucrative major projects cannot be accepted. The competition with better planning capacity is taking over these orders.
In the long term, this results in a loss of market position. Customers prefer service providers who can deliver reliably. Anyone who regularly has to reject projects or cannot meet deadlines loses trust and market share.
Strategic bad decisions
Based on unreliable forecasts, companies make wrong strategic decisions: Investments are postponed, employees are laid off or new teams are set up. And all of this is based on inadequate data. The long-term damage can be significant.
Forecasting with vs. without specialized software
Success factors for reliable forecasting: real-time data, KPIs, linked systems
Successful forecasting is based on four fundamental pillars: current data, meaningful KPIs, integrated systems and automated processes. These success factors are intertwined and form the basis for precise forecasts and proactive corporate management.
Current and complete project data as a basis
The first success factor for reliable forecasting is up-to-date and complete project data. This means: recorded Project hours, expenses and budget levels must be constantly updated, not just at the end of the quarter. Reliable forecasts can only be made with up-to-date data.
modernism Time recording systems enable automated data collection and consolidation. Employees record their working hours digitally, these are automatically included in the project evaluation and deviations are immediately visible. This transparency is the basis for proactive project management.
The most important data sources for successful forecasting include:
- Real time recording: Hourly or daily recording of all working times with direct project assignment
- Budget monitoring: Continuous monitoring of actual costs vs. planned budgets with automatic notifications
- Milestone tracking: Regular updates on project progress and goal achievement
- resource planning: Current availability and workload of all team members
- Pipeline data: CRM integration with probability assessment of new opportunities
Real-time KPIs for quick responses
The right key performance indicators (KPIs), which are available at the push of a button, are crucial. These include utilization levels, burn rates, deviations from the plan, and milestone achievement levels. These KPIs must be available in real time, not just after weeks of data preparation.
Key KPIs for successful forecasting include project profitability (actual vs. plan), resource utilization (current and planned), pipeline development (probability x volume), and cash flow forecasts. Corrective measures can only be initiated in good time if these indicators are available promptly.
Connected systems eliminate data silos
The third success factor is linked systems. time recording, Project controlling, CRM and reckoning must work on the same database. No silos, no stand-alone Excel solutions, no manual data transfers! This is the only way to create Single Source of Truth, which is required for reliable forecasts.
Integrated systems enable automatic data reconciliation and significantly reduce sources of error. Changes in one area (e.g. project budget) automatically affect all other areas (resource planning, cash flow forecast, utilization planning). This consistency is crucial for forecast quality.
Automation reduces human errors
Automated data collection and processing not only significantly reduces effort, but also the error rate. Manual entries are error-prone and time-consuming. Automated systems, on the other hand, collect data consistently and process it according to defined rules.
Modern project management software can identify trends, report discrepancies, and even make forecasts based on historical data. These data-driven approaches are significantly more reliable than intuitive estimates or Excel-based calculations.
Best practices in forecasting: defining scenario planning and responsibilities
Professional forecasting goes far beyond just collecting data. It requires structured processes, clear responsibilities and proven methods that have proven effective in practice. The following best practices will help you take your forecasting to the next level.
Scenario planning for various developments
Professional forecasting works with various scenarios: Best Case, Worst Case and Most Likely Case. This combination of three makes it possible to anticipate various developments and prepare appropriate measures. Each scenario should include well-defined assumptions and probabilities.
Best-case scenarios take into account optimal project processes, additional orders and perfect resource utilization. Worst-case scenarios include project delays, budget overruns and order failures. The most-likely scenario is based on realistic assumptions and historical experience.
The three forecast scenarios in detail:
- Best case (20% probability): All projects are running optimally, new orders arrive earlier than planned, no unplanned outages
- Most Likely (60% probability): Realistic assessment based on historical data and current trends
- Worst case (20% probability): Delays, budget overruns, order postponements taken into account
Plan buffers and reserves consciously
Successful companies deliberately include buffers and reserves in their forecasts. These safety margins are not chosen arbitrarily, but are based on historical deviations and risk analyses. Typical buffer sizes are between 5-15% depending on project type and complexity.
Reserves should be planned both temporally and financially. Time reserves take into account possible delays in critical milestones. Financial reserves cover unforeseen costs or market changes. These buffers must be actively managed and adjusted as needed.
Define clear responsibilities
A critical success factor is the clear definition of responsibilities. Everyone must know who provides which data and by when it must be available. Project manager are responsible for their project data, Controlling consolidates the overall view, and management makes strategic decisions based on this.
Regular forecast meetings with regular participants and standardized agendas ensure commitment. These meetings should last no longer than an hour and focus on discrepancies and necessary measures. Routine updates can be carried out automatically via dashboards.
Proven roles in the forecasting process:
- Project manager: Weekly update of project data, milestone updates, risk assessment
- controlling: Consolidation of the overall view, KPI monitoring, variance analyses
- Sales: pipeline updates, probability assessments, timing of new projects
- Management: Strategic decisions, resource allocation, investment planning
Continuous improvement of the forecast process
Forecasting is not a static process, but must be continuously improved. Regular forecast quality analyses show where the biggest deviations occur and which improvements are possible. These learnings will be incorporated into the next round of forecasts.
Successful companies carry out forecast post-mortems: What has happened, what hasn't and why? These analyses help to continuously improve forecasting quality and eliminate typical sources of error. The KPIs and processes used should also be regularly scrutinized and adjusted.
Integration into corporate management
Forecasting must not be viewed in isolation, but must be an integral part of corporate management. The findings from forecasting must be incorporated into strategic decisions: personnel planning, investment decisions, market processing and customer acquisition.
Managers must learn to interpret forecast data and derive appropriate measures. This requires not only technical tools, but also appropriate training and change management processes. Only when forecasting becomes a management culture will it be fully effective.
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Practical example: Forecast errors and loss of margins in management consulting
Starting position:
A growth-oriented business consulting manages between 8 and 12 parallel customer projects per quarter (fixed price, retainer and daily rate events). Project managers often keep status reports in individual Excel sheets, and central management is carried out monthly.
Typical forecast errors:
- Several project managers underestimate the remaining expenses because change requests and scope changes are not reflected promptly.
- A consulting mandate with a high turnover volume is postponed at short notice, but the information is delayed from account management to controlling.
- Data from sales (acquisition) and ongoing consulting projects is inconsistently incorporated into capacity planning.
Consequences:
- Resources are blocked for a project that has actually been postponed. New, lucrative mandates cannot be accepted.
- The margin is falling: Consultants are working on projects that contribute less than planned, or are temporarily out of capacity.
- Lack of real-time data leads to hasty adjustments or unplanned overtime.
- Management makes false assumptions, which result in investments being postponed or made hastily.
- There is a lack of precise KPIs to systematically identify the forecast error.
Optimization with forecasting software:
- An integrated forecast solution (such as ZEP) bundles data from sales, project management and time recording on one platform.
- Any status change (such as delays, consultant changes, customer feedback) is immediately adopted for capacity planning and margin forecasting.
- Early warning systems show resource bottlenecks and margin risks on a daily basis so that measures can be initiated in a targeted and proactive manner.
- Reports and meetings are now based on uniform, reliable figures — no more wrangling over “whose” Excel is right.
Outcome:
- The margin remains stable, capacities are planned realistically, customer projects are carried out in a planned manner and without unpleasant surprises.
- Acceptance of forecasts and KPIs is increasing significantly, as planning security and transparency are provided for all roles.
How ZEP helps you with professional forecasting
With its integrated modules, ZEP offers exactly the functions required for reliable forecasting in project business. The module resource planning enables precise sales forecasts based on current planning. The system automatically calculates the expected turnover within the desired time frame based on current project planning. This regular distribution of working hours provides realistic planning principles over defined periods of time.
The project approval function is particularly valuable, which acts as an additional verification mechanism and ensures that only approved times are included in invoicing and thus in the forecast. In combination with the integrated time recording and the Project controlling This creates a continuous database without the dangerous stand-alone Excel solutions. Thanks to the direct connection of all modules — from project planning to time recording to accounting with DATEV Online interface — Always work with up-to-date, consistent data for accurate forecasts.
Fazit: competitive advantage through reliable forecasting
In project business, precise forecasting is not a nice-to-have, but a decisive competitive advantage. Companies that can reliably predict their future act proactively rather than reactively. They identify opportunities earlier, minimize risks and continuously optimize their profitability.
The path to better forecasts is three key success factors:
- Integration of the system landscape for current, consistent data bases
- Definition and use of meaningful KPIs
- Establishing clear processes and responsibilities
Investing in professional forecasting pays off in several ways: through more stable margins, better resource planning and well-founded strategic decisions.
Modern companies in the project business cannot afford to rely on stand-alone Excel solutions and outdated data. The technology for integrated, real-time forecasting is available and proven.
The measurable benefits of professional forecasting:
- 25-40% higher margin quality by identifying problems at an early stage
- 30-50% less idle time through predictive acquisition planning
- 20-35% more efficient use of resources through optimized capacity planning
- 15-25% faster decision making through automated KPI dashboards
The question is not Whether You should improve your forecasting. but When They start with that. Because while you're still hesitating, your competitors are already gaining a decisive advantage in terms of information.
FAQs
How often should the forecast be updated?
In Project Business, a Rolling Forecast with Monthly Updates is recommended. Critical projects or major orders should be reviewed weekly. However, it is more important than frequency that changes are recorded immediately, for example when project runtimes are postponed or new mandates are won.
Which KPIs are essential for a reliable project forecast?
Key KPIs include: Project progress (Earned Value), budget consumption vs. progress, resource utilization per field of expertise, pipeline volume by probability classes and the win rate of historic projects. These key figures should be available in real time, not just in the monthly financial statements.
Why do Excel-based forecasts regularly fail?
Excel forecasts suffer from three systemic problems: First, they are not linked to other business systems, meaning that data is transferred manually and prone to errors. Second, data silos arise when different departments keep their own tables. Thirdly, there are no automatic warning mechanisms for critical developments, i.e. problems are only identified when it is too late.
How do I identify margin risks for ongoing projects at an early stage?
Continuous monitoring of budget consumption in relation to project progress and automatic alerts in the event of deviations of more than 10%, for example, are decisive. In addition, qualitative indicators should be observed: frequent scope changes, communication problems with the customer or resource bottlenecks among key people. An integrated system proactively reports such risks.
What role does pipeline planning play in project forecasting?
The acquisition pipeline is essential for medium-term forecasts. Without a realistic assessment of sales opportunities, dangerous planning gaps arise. Successful companies rate their pipeline according to probability classes (hot: 80%, warm: 50%, cold: 20%) and take into account historical conversion rates and average sales cycle times in their industry.
How do I convince my team of a new forecasting system?
Focus on transparency and show specific benefits: Project Managers benefit from automatic reports instead of manual data collection, sales receive better capacity information for customer inquiries, and controlling can proactively control instead of just reacting. Start with a pilot project and let the successes speak for themselves. Acceptance results from noticeable improvements in everyday working life.
