Whether you’re still ironing out the details or you’ve wrapped up your numbers, budget season is drawing to a close. And that means forecast season is getting started. Whether you’re a TMC, OTA, or corporate travel buyer, the stakes are high: forecasting helps you anticipate trends, optimize resources, and make smarter decisions.
In the travel industry, where every dollar spent, every ticket booked, and every mile traveled matters, your ability to forecast accurately can make or break your success. Can your data withstand the turbulence of system disruptions, fluctuating demand, new or churned clients, and shifting travel policies driven by corporate priorities or industry dynamics?
This isn’t another generic guide. It’s your ticket to mastering the art and science of forecasting.
In this blog, we’ll go beyond the basics, diving into actionable insights and real-world examples to show you how to fine-tune your forecasts. It’s time to move from reactive to proactive, harnessing data to predict—and even shape—the future of travel. Ready to take off? Let’s explore.
Why Forecasting Matter
Forecasting isn’t just about projecting numbers; it’s about aligning resources and planning for the future. If done incorrectly, it can mislead decision-makers and hinder growth opportunities. For instance, deciding whether to hire a new team member often depends not just on current performance but also on anticipated future performance.
This is where forecasting becomes a mix of art, science, and, maybe a little magic. While actuals—the data already realized—are firmly in the realm of science, forecasting involves nuanced adjustments and subjective interpretations to predict what’s ahead.
The Monthly Cadence 1+11 and Beyond
Many organizations operate on a monthly cadence, using a system like “1+11” or “2+10.” In the case of 1+11, at the end of January, you have one month of actuals and 11 months of forecast. By the end of February, it becomes 2+10, and so on. This approach ensures regular updates and adjustments to align projections with the latest data.
The secret sauce of successful forecasting lies in continually refining the process as more actuals are reported. The ability to course-correct and improve forecasts is key to maintaining relevance and accuracy.
Balancing Historical Trends and Future Adjustments
A strong forecast starts with historical trends, adjusted for seasonality and other known factors. However, looking backward alone isn’t enough. Businesses should incorporate adjustment factors to account for changing conditions, such as shifts in customer demographics, new product launches, or fluctuations in market demand. Below are examples from the corporate travel and leisure travel ecosystem:
Example 1: A TMC Adapting to a Changing Client Mix
If a TMC traditionally catered to large enterprises but recently experienced a significant influx of mid-market clients, its forecasting methodology should reflect this shift.
Instead of relying solely on historical averages, the TMC could:
- Segment client data by enterprise and mid-market categories.
- Calculate separate growth rates for each segment, factoring in differences in travel patterns and spending.
- Apply a weighted approach to forecasts, ensuring projections better capture the evolving client mix.
For instance, if large enterprises previously accounted for 70% of the TMC’s revenue but now contribute only 50%, continuing to use outdated averages would lead to inaccurate demand predictions and misaligned resource allocation. By rebalancing forecasts, the TMC ensures it meets the unique needs of its diverse client base.
Example 2: An OTA Responding to Market Fluctuations
Last summer saw record-breaking travel to Europe, with many popular destinations struggling to manage overcrowding. While international travel surged, the experience left many travelers reconsidering their next trips—some opting for less crowded destinations or domestic travel. How can an OTA prepare for these shifts and maintain a competitive edge?
To stay relevant, the OTA must forecast changing demand and adjust strategies to match traveler preferences as they evolve.
Steps the OTA could take:
- Analyze regional travel trends to identify areas where overcrowding has dampened demand and explore emerging destinations that travelers are gravitating toward.
- Examine changes in booking behavior, such as preferences for lesser-known international locations or an increase in domestic trips as travelers seek quieter, more accessible options.
- Use historical data from similar situations (e.g., post-peak periods of international travel) to predict how these shifts will affect the mix of domestic and international bookings.
For instance, if data shows international bookings accounted for 20% of trips last summer but travelers are now shifting to 15%, with domestic bookings rising, the OTA can adjust its marketing efforts. Targeted campaigns can promote hidden gems in domestic markets or highlight quieter international destinations, ensuring the OTA stays ahead of demand patterns. Ignoring these changes could result in misaligned promotions and lost revenue opportunities.
By anticipating traveler preferences and proactively adapting to these shifts, the OTA not only mitigates risks but positions itself as a trusted partner in delivering stress-free, meaningful travel experiences.
Example 3: A Corporate Direct Travel Program Optimizing Policies
A large corporation observes a shift in employee travel behavior, with more frequent virtual meetings reducing the need for overnight trips but increasing demand for longer, less frequent trips.
Key adjustments for the corporate travel manager:
- Analyze employee booking data to identify shifts in trip length, frequency, purpose and destinations.
- Incorporate department-specific needs (e.g., sales teams may still require frequent travel, while other teams may not).
- Use historical data to adjust expense allocation policies and negotiate more targeted contracts with airlines and hotels.
For instance, hybrid work may increase the number of team meetings at headquarters and see a higher percentage of long trips to key client locations. The corporation might re-negotiate hotel contracts at headquarters while increasing discounts on long-haul routes. Ignoring these changes would lead to underutilized contracts and higher costs.
Key Considerations for Effective Forecasting
- Segment Your Data: Don’t rely solely on overarching averages. Break your data into meaningful segments, such as customer types, geographic regions, or product lines, to capture more nuanced trends.
- Adjust for Business Mix Changes: A shift in your customer or product mix can make historical data less reliable. Rebalancing forecasts based on current business dynamics ensures greater accuracy.
- Account for External Factors: Seasonal trends, economic shifts, and industry-specific changes can all impact your forecasts. Use external data sources to supplement your analysis.
- Leverage Technology and AI: While forecasting has traditionally relied on manual processes, advancements in AI and predictive analytics can enhance precision. Machine learning models, for instance, can identify patterns in data that might otherwise go unnoticed.
- Focus on Baseline Accuracy: The first step to any effective forecast is ensuring your baseline data is accurate. This includes reconciling historical data and ensuring all relevant factors are accounted for.
Forecasting in the Travel Industry: A Unique Perspective
While many principles of forecasting apply universally, industry-specific nuances should be considered. For example, in travel, shifts in customer behavior—such as the rise of alternative accommodations or increased ride-share and commuter rail—require careful attention. Additionally, staffing changes in travel-heavy organizations can impact spending patterns, making accurate forecasting essential for managing supplier contracts.
Whether you’re a TMC, OTA, or corporate buyer, forecasting plays a central role in managing volumes and optimizing vendor relationships. Patterns, demographics, and travel habits must all be factored into projections to ensure contracts and resources are aligned with expected demand.
The Role of Data Platforms
In today’s data-driven world, forecasting is increasingly tied to robust datasets. These establish a strong baseline, and the volume of data is essential for more accurate projections. Predictive analytics can then layer in future insights, allowing businesses to transition from basic forecasts to advanced, actionable strategies.
While predictive analytics offers exciting possibilities for the future, organizations must first focus on mastering their current forecasting processes. By applying adjustments to a solid baseline, businesses can create more reliable forecasts that support smarter decision-making.
Conclusion
Forecasting is both an art and a science, requiring a delicate balance of data analysis, strategic adjustments, and forward-thinking. By following best practices—segmenting data, adjusting for business mix changes, leveraging AI, and ensuring baseline accuracy—you can create more accurate forecasts that guide your business toward success.
As we head into a new year, it’s the perfect time to refine your forecasting process. Remember, it’s not just about predicting the future; it’s about preparing for it
