Origin & Destination optimization without investing in expensive systems


Maximizing the income of a company operating in its market, according to the precepts of yield management, can be summed up in a seemingly simple arithmetic formula: sell at the right price, at the right time, in the right place, to the best customer.

Solving the equations of the right price and the right time to sell is based on a set of skills that any organization that has survived in its competitive environment masters.

This is the function fulfilled by a set of processes piloted by the revenue management department (inventory and pricing managers), supported by an RMS (Revenue Management System). This essential technological component, when business volumes are counted in millions of dollars, allows efficient optimization – and therefore a maximization – of revenue, depending on the publisher of the software suite, the quality of data entry, and the training level of users.

When airlines realized the untapped revenue streams of the "good place" concept, it was natural that they expected their RMS vendors to push their models further, capitalizing on the demand differentials and selling prices within the large geographies covered by their networks.

O&D systems

The major changes consisted of:

- No longer forecasting demand at the level of each airline (“segment”), but at the level of each POS (Point Of Sale or point of commencement) – O&D (Origin and Destination) couple.

- Having the flexibility to sell a seat at very different prices depending on the passenger's itinerary.

So-called “O&D” solutions followed, which are elitist and costly. The performance of their revenue maximization model requires ingesting huge amounts of data and executing hundreds of business rules in record time.

So that consumers and sellers do not circumvent the system, income protection mechanism must be put in place simultaneously (married segments, control of the starting point, etc.).

O&D solutions also require the passenger and reservation management system to be compatible with advanced distribution standards so that the O&D offer is correctly distributed and connected to travel agencies and partner airlines, therefore excluding most low cost software publishers.

In addition to technological and distribution costs, the implementation and maintenance of O&D solutions require a dedicated and trained workforce.

Advanced O&D revenue management solutions are therefore beyond the reach of small and medium-sized companies as they are not large enough to make the implementation of such systems profitable.

However, even without having an inventory managed in O&D, proven models allow small structures to maximize their revenues according to the precepts of O&D without resorting to complex and costly RMS. These models are based on optimizing the other component of revenue management: pricing.

It is this O&D optimization model that this article proposes to explore. We will take the example of an airline, while keeping in mind that the solutions presented here can be applied to other modes of transport.

Understand the dynamics of demand on a transport network

Industries that apply yield management, and transportation networks in particular, offer capacity that is relatively stable over time. Meanwhile, customer demand is, in most cases, extremely seasonal.

For traditional business sectors, variations in demand are easily managed by storing production (material goods) or finely adjusting human resources (services).

However, for tourism and transport companies operating with high-capacity industrial assets (planes, trains, ships, hotels, amusement parks, car parks, etc.), reducing capacity, when possible, often means not operating (reducing the frequency of a line, removing timetables, closing the tourist site).

Increasing capacity to meet peaks in demand involves sizing the productive apparatus disproportionately (which only public service operators can afford).

This is why these sectors of activity apply the precepts of yield management to optimize their income during periods of very high demand during which the number of potential customers exceeds the maximum capacity that can be implemented (high season, holidays, certain days of the week, peak hours), and periods of low demand (low season) during which there are far too many seats available for sale.

In practice, the reality is much more subtle. For each day of operation, each time slot, for the same capacity implemented, the dynamics of demand are unique: consumers' willingness to pay is not the same, and the profiles of the load rise curves of reservations are different (anticipation of purchase, cancellations).

Multiple internal and external factors that cannot be modeled distort demand forecasting models and make the work of the revenue manager as exciting as it is essential.

Thus, the confrontation between supply and demand involves an infinity of nuances, represented by infinite variations in the stocks allocated to the tariff quotas in the inventory systems.

The optimization of a connected transport network

The relationship between supply and demand, as described above, is relatively easy to understand with an inventory system supported by an RMS.

Using a lot of algorithms, these systems forecast future demand for each product and date of operation, and calculate, at any time, the optimal sale price (in the form of a vector representing the number of seats available per tariff quota).

This price is more or less dynamically communicated to the distribution systems. This is how the hotel industry, the railway companies, some amusement parks, cruise companies, and low-cost charter airlines operate.

However, once airlines began to build their networks to facilitate connections, they faced more complex optimization challenges which, to put it simply, arbitrate, for each segment, between sales on direct flights and sales on connecting flights.

To address this issue, RMS O&D solutions that forecast demand and optimize sales at each POS–O&D have entered the market, along with more sophisticated inventory systems and new distribution standards.

Nevertheless, several decades after their implementation, these systems remain too expensive for small and medium-sized airlines.

However, there is a proven method to practice O&D revenue management with RMS that only optimizes at the segment level: the efficient allocation of prices in tariff quotas (booking classes).

The price benchmark

With or without an O&D system, the role of the pricing team is to maintain a competitive price offer on all market segments at a POS-O&D level.

A common impediment to revenue maximization that we observed is the excessive use of add-ons.

Competitive prices are established on direct flights, with a fare construction logic that sets the price of connecting flights independently of the dynamics of the market.

If this proves to be an effective way of protecting income in very high season or when managing interline, it becomes counterproductive in low season, especially with very competitive O&Ds and/or with high price elasticity.

Before even looking to achieve complex revenue optimizations, we recommend ensuring that pricing processes are robust. This means that each POS–O&D–Cabin must feature:

- a consistent and documented identification of direct competitors, according to their respective market shares

- a detailed knowledge of the strengths and weaknesses of the product (frequencies, times, connection time)

- a coherent pricing strategy vis-à-vis each competitor (match undercut, charge a premium) and shared internally (revenue management and sales teams)

- a floor price procedure below which analysts and managers cannot go without hierarchical authorization (psychological price, according to variable costs, or minimum price per kilometer)

Market segmentation

In addition to the benchmark, the pricing teams must strategically analyze each market and adopt a position adapted to their competitive situation and their market share ambitions.

Segmenting a market is an excellent way to differentiate yourself from the competition. Also desirable are a range of action levers to rely on when responding to the multiple nuances resulting from the confrontation between supply, demand, and the competitive landscape. The most common dimensions are:

- the type of passenger (adult, child, youth, student, senior, couple, military, sailor, etc.)

- the purpose of the trip (business, leisure, etc.)

- the distribution channel (Travel Management Companies, independent, online, specialized agencies, tour operators, group operators, etc.)

- the product characteristics (with or without baggage, ticket exchange and refund conditions, exclusive services, etc.)

In addition to these dimensions, there is the management of products in fare families (for airlines, based on the distribution standards “branded fares” and “rich content”) which increase the average income by a small percent, but also come with strong constraints.

The implementation of the segmentation of a market requires relying on expert human resources and technical capacities framed by effective internal policies.

The challenges of O&D revenue management

airlines are trying to solve, let's take the example of a Geneva–New York flight on which there is only one seat left to sell in a tariff quota. To which passenger is it financially most beneficial to sell this seat?

The most obvious answer is to sell to the highest paying passenger. However, depending on the circumstances, more subtle network-level optimization solutions may perform better (direct flights priority, revenue-mile priority, revenue-network priority).

Nevertheless, the reality is contradictory because there are thousands of fares in this tariff quota (dozens of different O&Ds, available in many market segments).

The fastest passenger to reserve a place in this tariff quota will be on board the plane, not the one who is the most financially attractive.

An RMS O&D allows you to impose order by isolating the demand of each POS-O&D, and then open or close access to the tariff quotas according to the expected average price.

Complex optimization formulas aggregate and weigh the multiple fares available for sale in reference segments.

But as we said in the introduction to this article, small and medium airlines cannot afford these systems.

The optimal allocation of fares in the tariff quotas

The solution for small and medium-sized airlines is a rigorous allocation of fares within tariff quotas.

The first step is to define for each segment, and each period of the year, the optimal solution to maximize total revenue:

- priority to direct flights: recommended for airlines with undercapacity and/or disconnected from the connecting hub

- revenue-mile priority: perfect for periods of high demand and tariff quotas at the top of the hierarchy.

- revenue-network priority: ideal for periods of low demand and new lines that lack traction.

The second step is to define fares assignment rules in tariff quotas that work for all market segments, while integrating or anticipating branded fare constraints.

The third step is to reassign the fares of the entire network within their optimal tariff quota.

At the same time, the inventory system must be recalibrated, part of the RMS input data reprocessed, and sometimes certain expected prices manually configured while waiting for a new demand history to be formed.

The fourth step is the coordinated launch of the new tariff schedules with the recalibrated RMS and performance measurement.


After an implementation period of between 3 and 9 months, the minimum gain that an airline can achieve corresponds to 1% of passenger turnover. Without technological expenses, it is a project with a strong return on investment.

The main vectors of this gain in income are linked to the reduction in the dispersion of the fares assigned in the tariff quotas, which allows:

- the RMS to work with a more precise valuation of demand

- no longer missing the opportunities of connected traffic closed for sale when their prorated income is higher than direct flight sales

- artificially promoting connecting traffic in periods of low demand without diluting the yield of direct flights.

To go further

With or without an O&D system, the proliferation of fares poses many challenges to maximizing revenue. While advanced O&D systems manage to optimize revenue, even when the allocation of fares within quotas lacks consistency, airlines without such a system have no other solution than to work with the constraints of a segment-wide demand-optimizing RMS.

As soon as the demand for point-to-point traffic declines (economic situation, new competitor), the development of O&D sales becomes a major issue that most companies take up by injecting skills into their organization.

Support from a team of Airline Tactics senior consultants is strongly recommended. This will allow you to capitalize on our experience with many airlines, temporarily strengthen your teams for the duration of the project, and above all, utilize the optimized tariff quota allocation solution for your network.

Without additional technological investment, we have a powerful model. In less than a year we can:

- increase your turnover

- increase your yield in high season by only accepting connection traffic with high added value

- increase your occupancy rate in low season by being more efficient in developing O&D traffic.

- differentiate you from the competition with a relevant breakdown of prices on many market segments

We have the operational capacity for:

- reviewing all your price lists, public and private

- automating the loading of new grids into the ATPCO system

- collaborating with your RMS editor to recalibrate historical data and settings

- taking into account your branded fares and structure fares, or seizing the opportunity of the tariff review to implement a more efficient one.

Models to maximize revenue

The most successful solution is usually to combine revenue-mile and revenue-network approaches, with possibly a few exceptions where prioritizing direct flights makes sense.

Priority to direct flights
Priority to Revenue-Mile
Priority to Revenue-Network

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