How Kroll Built a Real-Time Business Intelligence Portal That Broke Booking Records and Exceeded Revenue Targets with Power BI

Client

Kroll is a global expert services and advisory firm providing risk assessment, governance, transactions, and valuation services across industries. In this engagement, Kroll required a business intelligence solution capable of consolidating travel partner performance data from multiple sources into a unified analytics platform — supporting the operational and financial oversight needed to manage a complex, multi-partner travel services business. The engagement required Ajackus to address both the technical challenge of data standardisation at scale and the operational challenge of maintaining uninterrupted data pipeline connectivity.

Challenge

Kroll’s travel data environment was characterised by fragmentation: multiple third-party partners submitting data in inconsistent Excel formats, each with different schemas, naming conventions, and levels of completeness. Before any analytics work could begin, significant data preparation was required — and that preparation was happening manually, creating a recurring bottleneck between data receipt and business insight.

Compounding this was a connectivity problem: the VPN connections used to access critical data streams were subject to frequent timeouts, requiring manual reconnection and creating gaps in what should have been continuous data pipelines. These interruptions affected the timeliness of the analytics output and, by extension, the speed at which Kroll could identify and respond to operational anomalies.

Non-Uniform Third-Party Data Schemas

Travel partner data arrived in Excel files with no standardised schema — different column names, date formats, currency representations, and data completeness across partners. Consolidating this data into a single analytical model required both a technical ETL solution and a data governance strategy capable of handling the variability that would continue with each new data submission.

Data Consolidation Complexity at Volume

The volume of incoming travel partner data meant that manual consolidation was not a viable long-term approach. Each data submission required evaluation for inconsistencies, cleansing to resolve formatting issues, enrichment with contextual information, and integration into the central repository — a multi-step process that accumulated significant time cost across a high-frequency data environment.

VPN Connectivity Disrupting Data Streams

Frequent VPN timeout events on critical data connections were causing interruptions to the data pipelines that fed the analytics system. Without automated reconnection handling, each timeout required manual intervention to restore connectivity — creating gaps in data continuity and reducing the reliability of real-time reporting at precisely the moments when uninterrupted visibility was most commercially valuable.

Absence of Real-Time Anomaly Visibility

Without a centralised, automated analytics layer, anomalies in booking data, revenue figures, and operator performance were identified reactively — often after they had already affected financial transactions or operational decisions. Kroll required a system capable of detecting and surfacing these anomalies in real time, enabling swift resolution before downstream consequences accumulated.

Goals

The platform needed to transform fragmented, non-uniform travel partner data into a single, reliable intelligence layer — with automated ETL, real-time anomaly detection, and secure interactive reporting as core deliverables.

Journey

The Ajackus team approached the Kroll engagement in three interconnected workstreams: data standardisation and governance, ETL pipeline automation, and Power BI portal development. Rather than building dashboards on top of the existing fragmented data environment, the Ajackus team first established the data foundation — clean, enriched, consistently structured data — before building any reporting layer on top of it.

Data Evaluation, Cleansing, and Standardisation

The Ajackus team began by conducting a systematic evaluation of all existing third-party data sources, documenting the schema inconsistencies, formatting variations, and data quality issues present across each partner’s submissions. Using Power Query, the Ajackus team implemented a data preparation and transformation layer that normalised incoming datasets to a consistent schema — standardising date formats, currency representations, field naming conventions, and handling missing or malformed values through defined cleansing rules. Each dataset was also enriched with contextual metadata to enable more granular downstream analysis.

Automated ETL Pipeline and Data Governance

The Ajackus team implemented an automated ETL process that replaced the manual data consolidation workflow. The pipeline extracts data from third-party partner sources, applies the Power Query transformation logic, and loads the cleaned, enriched output into the centralised data model — without requiring manual steps at any stage of the process. Alongside the automation, the Ajackus team developed a data governance strategy defining how incoming data should be evaluated, documented, and maintained over time, ensuring the platform remains reliable as partner data volumes and formats evolve.

Power BI Portal with Secure Access and Interactive Dashboards

The Ajackus team built a dedicated Power BI portal with authentication and authorisation controls that restrict access based on user role — ensuring that each Kroll stakeholder sees the data relevant to their function without exposing sensitive commercial information across the organisation. The portal’s interactive dashboards were designed for dynamic data exploration: users can filter by operator, route, time period, and booking category to drill into the metrics most relevant to their decisions. The dashboard architecture was tailored to support diverse data model requirements across the different travel partner sources, rather than applying a single generic view to all data types.

VPN Connectivity Management and Anomaly Detection

The Ajackus team implemented connection management logic to address the VPN timeout issues that had been disrupting data stream continuity. Alongside connectivity reliability improvements, the platform was configured to surface anomalies in booking data, financial transactions, and operator performance in real time — enabling Kroll’s operations team to identify and resolve issues before they propagated through downstream systems. The anomaly detection capability specifically enabled identification of loss-making operators whose route and schedule configurations were generating negative returns, providing the analytics foundation for targeted operational optimisation.

Results

The Kroll Power BI portal delivered measurable commercial outcomes — breaking booking records and exceeding revenue targets — whilst giving the operations team real-time visibility into anomalies and operator performance. Specific figures are held confidential per client agreement.

What went well:

Operational Improvements

• Manual data consolidation eliminated — the automated ETL pipeline processes all incoming travel partner data without human intervention at any stage
• Real-time anomaly detection enabled swift resolution of financial transaction irregularities before they affected downstream reporting or commercial relationships
• Loss-making operators identified through the analytics layer, providing the data foundation for route and schedule optimisation decisions
• VPN connection reliability improved, ensuring continuous data stream availability without manual reconnection overhead

Technical Achievements

• Power Query transformation layer normalises non-uniform third-party Excel datasets to a consistent schema, handling formatting variations and data quality issues automatically
• Centralised data model consolidates all travel partner sources into a single, queryable repository with enriched contextual metadata
• Secure Power BI portal with role-based authentication and authorisation controls appropriate to a risk advisory environment
• Interactive dashboard architecture supports dynamic filtering by operator, route, time period, and booking category across diverse data model types

Business Impact

• Booking volumes broke previous records — a direct commercial outcome enabled by the operational visibility the platform provides
• Revenue exceeded financial targets, with the platform’s anomaly detection and operator performance analytics contributing to optimised commercial decisions
• Security concerns identified and resolved through the platform’s access controls and data governance framework