Beyond the Numbers: Breaking the Monthly Forecasting Rollercoaster

Understanding the Monthly Forecasting Rollercoaster

A forecast for a month will be more accurate one day from the end of that month than it will be six weeks prior – this is the nature of forecasting, right? We aren't fortune tellers, and in trying to anticipate what revenue, cost, and resource needs our business will experience in an upcoming period, we're inevitably going to overlook some things that, as they come into clearer focus, will make our forecasts more accurate.

The challenge is that for many organizations without a disciplined approach to forecasting supported by the right technology, the forecasting journey for a period isn't a straight path from somewhat hazy to crystal clear. Instead, projected performance takes a wild and twisty path as updates across from teams pull the forecast up and down.

Here are the key inflection points on the monthly forecasting rollercoaster.

The Inflated Forecast: Optimism reigns at the start of the month, with forecasts that often overlook resource constraints, unassigned demand, or unresolved sales opportunities, resulting in overly bullish projections. The Surprise Dip: Mid-month, unexpected cancellations, lost deals, or project delays lead to sudden dips in forecast accuracy, leaving resources underutilized.

The Nice Surprise: When fixed-price projects wrap up early, projects get extended, or new urgent customer demands emerge, the revenue projections for the month take a positive turn, with resources pivoting to quick-to-close work.

The Delivery Shift: As the month-end approaches, delivery teams consolidate work, updating project statuses and chasing down timesheets and estimates to complete, finally giving an accurate picture of what actuals for the month are likely to be if nothing changes.

The Scramble: Finally, last-minute efforts to hit targets often result in reactive, short-term measures that may close the month on a high note but do little to address the underlying inconsistencies in forecasting.

Does any of this sound familiar? If it does, things don't need to stay this way. To break free from these cycles, businesses must understand the variables influencing forecast accuracy and strive to improve them. This includes recognizing patterns like inflated forecasts early in the cycle and adjusting for known behaviors, such as sellers' overestimation or delivery teams' under-reporting.

The Impact of Inconsistent Forecasts

Why does the consistency of forecasting behaviors matter? Inconsistent forecasts don't just leave decision-makers in the dark about what their business needs to do to maintain optimal performance. They also have a major influence on the confidence of owners, shareholders, boards, investors, and potential buyers. These stakeholders rely on forecasts to make informed decisions about resource allocation, investment strategies, and overall organizational health. A history of accurate forecasting builds trust and signifies maturity and stability in operations.

Accurate forecasts clarify expected financial performance for owners and shareholders, aiding in strategic planning and ensuring the organization is on track to meet its goals. Boards of directors use forecasts to assess risks and opportunities, making them crucial for governance and oversight. Investors view reliable forecasts as a sign of a company's financial health and operational efficiency, influencing their investment decisions. A track record of accurate forecasting for potential buyers can significantly increase the organization's perceived value, as it suggests a well-managed and predictable business.

Inconsistent forecasting introduces uncertainty, eroding confidence among stakeholders and making it challenging to secure investments or achieve strategic goals. The management team's credibility may also suffer, further complicating efforts to attract and retain top talent or partners. Therefore, overcoming the monthly forecasting rollercoaster is both an operational and strategic imperative.

Leveraging Technology to Diagnose Common Forecasting Traps

Considering the importance of a track record of forecast accuracy, our goal should be to identify and curtail behaviors destabilizing forecasts. This can't be done by looking at one period in isolation. Instead, it requires understanding how monthly forecasts in your business evolve and detecting patterns across periods.

No person can process the immense amount of information needed to analyze and diagnose forecasting behaviors effectively. This is where having the right technology at your disposal is crucial. Diagnostic analytics and machine learning have become key tools in the consulting leader's toolkit. These technologies can sift through vast amounts of data, identify trends and anomalies, and provide actionable insights that would be nearly impossible to discern manually.

By analyzing the trajectory of your forecasts over time, you can better understand what is explicitly leading to variance across forecasts. Maybe drilling down into forecasts by business unit reveals that a certain practice is overestimating margins across proposals. Or that the delivery teams in a certain geography are not consistently following prescribed processes for updating estimates at completion (EAC) for their projects. The analysis could show that a certain type of project is consistently delayed because it requires a lot of time from someone with a skill that's in high demand. The key is having the right tools to find root causes and refining processes to drive systematic improvements that flatten out peaks and troughs in the monthly forecasting rollercoaster.

Here are some common pitfalls I see when working with consulting firms that you may uncover as you analyze your forecasts:

Unrealistic estimates and timelines: A lack of alignment between sellers and delivery experts can often lead to doomed estimates. Sales teams may promise aggressive timelines and budgets to close deals without thoroughly understanding the delivery team's capacity or potential challenges. Additionally, ever-shifting close dates make forecasts a moving target, leading to a cascade of inaccuracies down the line.

Resourcing blind spots lead to suboptimal staffing decisions: When planned resources are unavailable, more expensive substitutes must be selected, causing project costs to balloon. Businesses often find that there can be a major discrepancy between their as-sold and as-resourced margins, and margin erosion that might be easy to blame on project managers actually stems from a lack of cost discipline in the resourcing phase. Additionally, delays in staffing can have a domino effect, pushing back timelines and impacting future forecasts.

Lack of Accountability and Delivery Governance: Poor visibility into the financial implications of decisions leads to suboptimal choices by project managers, particularly when projects veer off plan or scope creep emerges. Both lack of bandwidth and fear of being blamed for project issues drive projects to report green statuses that suddenly turn red when risks reach critical mass. This green-green-green-red pattern often masks underlying issues until they become too large to ignore. Additionally, billing errors such as miscategorized time and expenses can drive revenue leakage.

A Flurry of Reconciliations Post Month-End: Many organizations fall into a reconciliation frenzy at the end of each month. This culture of chasing and compiling data across silos for multiple weeks at the end of every month creates significant swings in subsequent forecasts as pipelines and projects are updated as the books are closed. Encouraging team members to make these updates in the moment rather than waiting to be chased by the finance team at the end of the month would flatten out the impact of updates on forecasts.

Professional services firms face an ever-evolving landscape with fierce competition and swiftly changing market dynamics. Firms that continually identify and circumvent challenges like these will be in a position to optimally adapt their strategies and processes to keep pace with industry shifts, customer expectations, and emerging technologies.

Cultivating a Culture of Transparency and Continuous Improvement

What all of these potential areas of opportunity for improvement make clear is that the act of driving accurate forecasts is as much about culture and change as it is about calculation. Calculating forecasts is relatively easy; navigating the change required to optimize forecasts can be hard. Achieving forecasting confidence requires a cultural shift towards transparency and continuous improvement. Engage stakeholders across the organization in forecasting, ensuring they understand the assumptions and methodologies behind the numbers. Organizations can reduce biases and build trust in their forecasts by fostering open communication and involving diverse perspectives.

Organizations can ensure their forecasting models evolve with changing market conditions and business needs by encouraging a mindset of ongoing learning and adaptation. Continuous improvement also includes investing in training and development programs to enhance the forecasting skills of employees across all relevant departments. This commitment to growth and development helps maintain high forecasting standards and supports the organization's strategic goals.

Conclusion

To break free from the monthly forecasting rollercoaster, consulting firms must adopt a holistic approach that considers the entire professional services lifecycle—from sales to resourcing to delivery. Achieving forward-looking forecasting confidence is about more than just numbers—it's about understanding the cyclical patterns that influence forecasts, leveraging advanced technologies to adjust for these biases, and cultivating a culture of trust and continuous improvement.

As Kantata's Chief Product Officer, Sarah Edwards leverages over 27 years of global experience in consulting, project management, and business leadership to drive innovation, enhance product capabilities, and help customers achieve service success.