How to Use Data Analytics to Improve Your Travel Programs
This SAP Concur blog post outlines the four main types of travel analytics: descriptive, diagnostic, predictive, and prescriptive. It explains how these analytics can help organizations control costs, enforce policy compliance, reduce risk, and improve traveler experience. The article also highlights key metrics such as total spend, cost per trip, booking rates, preferred vendor compliance, and policy compliance rate, and provides actionable strategies for leveraging data to optimize corporate travel programs.
Impact and considerations
Provides a data-driven framework for travel managers to optimize costs and ensure compliance.
Key points
- Travel analytics are categorized into descriptive, diagnostic, predictive, and prescriptive types.
- Data analytics help identify cost-saving opportunities, enforce policy compliance, and reduce risk.
- Key metrics include total spend, cost per trip, booking rates, preferred vendor compliance, and policy compliance rate.
- Analyzing employee behavior can optimize travel policies and improve compliance.
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