Marc-Olivier Simard first operates as a fleet owner for his own equipment, then as a distributor through his digital consulting services: transforming machine data into decision-support tools for the forestry industry, multi-source data consolidation, Power BI dashboards, and support for forestry operators.
The key metrics he monitors are fuel consumption and machine anomalies, which are at the core of forestry fleet management.
Before Hiboo, this data was scattered across multiple OEM portals, making it difficult to consolidate. Standardizing a reusable reporting model from one client to another required significant adaptation work, with numerous technical back-and-forths to reconcile differences in dates, time zones, and cumulative values. The result: valuable time lost on data consolidation.
As the forestry industry continues to modernize rapidly, the need for simple and reliable tools has become essential.
To address these challenges, Marc-Olivier Simard Consultant relies on Hiboo to:
A closer look at the Hiboo API powering Power BI reporting
The Hiboo API connects multiple data sources: data from OEMs and various telematics providers (TigerCat, Link-Belt, Caterpillar, Komatsu, Isaac, Geotab, etc.) is consolidated into a single data stream, then feeds Power BI directly.
This integration replaces manual exports and imports while relying on optimized data storage to accelerate report refreshes.
1. An invisible excess fuel consumption detected, leading to major fuel and maintenance savings
On the pilot account The Wood, continuous fuel consumption monitoring through the Hiboo API revealed that one machine was consuming 7.62 liters per hour more than comparable units.
For equipment operating continuously, this difference represented an estimated 60,000 liters of fuel per year, equivalent to nearly CAD 144,000, or approximately €96,000 (based on diesel priced at around CAD 2.40/L, or €1.60/L).
In the field, a few extra liters per hour can easily go unnoticed. By analyzing this discrepancy, the team identified it as the symptom of a developing mechanical issue, with hydraulic pumps operating under excessive load.
By intervening early, they avoided a more serious breakdown and the costly equipment downtime that would have followed.
2. Structured monitoring of machine anomalies and fault codes
For Marc-Olivier Simard, machine anomaly data is one of the two key performance indicators monitored daily, alongside fuel consumption.
Across the monitored fleet, Hiboo identified more than 3,700 machine anomalies, all categorized by severity level. This classification helps anticipate interventions and better plan maintenance operations.
3. Reliable reporting that supports business growth
By consolidating multiple data sources and ensuring the reliability of daily data, Marc-Olivier Simard Consultant benefits from dashboards it can confidently rely on when working with its clients.
This reliability builds trust, reduces the time spent verifying and correcting data discrepancies, and makes it easier to support new forestry operators, including smaller businesses.
