SAP Concur: Using Data Analytics to Improve Corporate Travel Programs
A SAP Concur blog post describes four types of travel analytics—descriptive, diagnostic, predictive and prescriptive—and how they help optimize costs, enforce policy, reduce risk and improve traveler experience. It recommends tracking KPIs such as total spend, cost per trip, booking rates, preferred vendor compliance and travel policy compliance rate. It also says analytics can support vendor sourcing and negotiation, policy optimization, demand management, experience enhancement and benchmarking.
Impact and considerations
The post provides a classification framework and KPI list for travel managers, helping turn spend data into concrete actions for cost control, compliance and experience improvement.
Key points
- Travel analytics fall into four types: descriptive (what happened), diagnostic (why it happened), predictive (what is likely to happen) and prescriptive (what should be done).
- Recommended KPIs include total spend, cost per trip, booking rates, preferred vendor compliance and travel policy compliance rate.
- Analytics can support vendor sourcing and negotiation, for example securing corporate rates based on hotel booking volume.
- Analyzing traveler behavior can reveal non-compliance patterns, such as booking business class for domestic flights or last-minute high-cost bookings, guiding training or policy changes.
- Analytics can also support demand forecasting, traveler experience enhancement and benchmarking against industry standards.
Sources and time
- Primary source
- SAP Concur
- Other sources
- 0
- First source publication
- 7 Jun 2024, 20:36
- Page published
- 14 Aug 2026, 08:14
- Last updated
- 7 Jun 2024, 20:36
- Original links
- SAP Concur Blog：How to Use Data Analytics to Improve Your Travel Programs (opens in a new tab)Primary source · en · Published 7 Jun 2024, 20:36