Keep Up to Date with Pre-Trip Data

The Challenge

An intergovernmental organisation received data from their TMCs that covered all bookings made via those TMCs. However, this data was sent out on a monthly reporting cycle, meaning that the bookings displayed in it were frequently severed weeks out of date. This caused problems with both demand management and policy compliance. It meant that any discussions around non-compliant activity were had very much after the fact and could consist mainly of educating the traveller for next time. Moreover, demand management could only take place using a running measure of spend activity that was often a view of activity several weeks old. 

Additionally, the organisation used travel data to manage their cross-border tax and visa exposure. There had been several instances where trips had created taxable events or visa compliance issues due to overloading a quota.

The Solution

PredictX implemented their Pre-Trip module for the organisation. This linked to the several GDS systems being used and tapped them for the organisations’ bookings via their APIs instead. This meant that, for the first time, travel bookings could be seen intra-day, almost in real-time. 

This data was then passed through PredictX’s validation, mapping, cleansing and fusion processes before being integrated with the organisation’s policies, corporate structure and financial structure. This enabled the organisation to capture out of policy activity virtually instantly, well within the void windows and also within the period where an alert could be sent to policy managers, enabling them to rebook the transaction so that it was inside the policy. Furthermore, all bookings resulted in an alert being sent to cost controllers so that a conversation could be initiated with the booker about the necessity of the trip.

The Impact

Following implementation:

• Out of policy activity fell by 40%.
• Overall travel fell by over 15%, producing annualised estimated savings of over $20million. 
• Alerts now go to the traveller themselves for out of policy activity, informing them of the fact and enabling them to rebook themselves before workflow execution.
• This level of self-policing has enabled cost control to focus on yet more areas for savings.

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