Four Trends Driving Service Effectiveness
The construction equipment industry is undergoing a significant transformation, driven by technological advancements and the increasing recognition of data's value. Original Equipment Manufacturers (OEMs) are facing challenges such as global competition, price deflation, and rising commodity costs, which are squeezing profit margins more than ever before. Additionally, the widening skills gap significantly drives up service costs.
According to a recent benchmark report focused on industrial machinery published by Aquant, within leading construction equipment companies, the costs associated with bottom performers are only 20% higher than those of the top performers. However, the lowest-performing organizations have the most expensive workforce gap, with their bottom performers costing 128% more than the top-performing employees.
The good news is that OEMs have the power to change this. According to Aquant’s report, if all employees had the knowledge and skills to perform like the top 20% of the workforce, service costs could be reduced by 28.
There are four key service trends poised to transform construction equipment management. These trends underscore the importance of prioritizing data management through AI solutions. By doing so, construction teams can stay ahead in a rapidly evolving industry and shift their service business from a cost center to a profit center.
1. How improved data sharing enhances symbiosis between dealers and OEMs
The relationship between dealers and OEMs in the construction equipment industry is becoming increasingly interdependent. Enhanced data sharing is at the forefront of this evolution. Dealers and OEMs are moving toward a more collaborative approach, where data from all work orders—not just warranty claims—are shared.
These dealers are using data for customer service
- Bobcat North Texas manages customer maintenance
- West Side Tractor manages fleet’s PM across regions
- General Equipment & Supplies uses data in predictive maintenance
- Tyler Equipment marries old school with new tech
This comprehensive data sharing allows both dealers and OEMs to gain a holistic view of their service landscapes. For construction teams, this means better and more consistent service delivery and more informed training strategies. With access to detailed data, dealers can offer more precise maintenance schedules and anticipate potential issues before they escalate. For OEMs, this data helps in refining their machinery designs and developing more effective training programs for technicians.
The result is a more efficient service process, reduced downtime, and extended equipment lifespan. Construction teams benefit from fewer interruptions and more reliable machinery, leading to enhanced project timelines and cost savings.
2. How personalized AI revolutionizes service and training
The introduction of Personalized AI is revolutionizing the industrial machinery sector, particularly in service and training. This technology tailors AI tools to the unique characteristics of each machinery, component, user, and dealer. For the construction industry, where machinery complexity is high, such personalized tools are critical.
Personalized AI enhances predictive maintenance capabilities, providing accurate operational insights that streamline service models. For example, AI can predict component failures before they happen, allowing for timely interventions that prevent costly breakdowns. This predictive power not only reduces service times and costs but also improves the precision of repairs.
Read about how fleet managers can implement AI in their operations
Furthermore, Personalized AI offers significant advancements in remote support. Experts can guide technicians through complex repairs in real-time, even if they are not physically present. This reduces the need for travel and minimizes equipment downtime, ensuring that construction projects proceed without unnecessary delays.
On the training front, Personalized AI is transforming learning experiences. By democratizing the methods used by top performers, AI provides practical, hands-on training that accelerates skill development. This is particularly crucial in the construction industry, where the demand for highly skilled technicians is ever-growing. Efficient and effective training methods result in a workforce that is better equipped to handle the challenges of maintaining sophisticated machinery.
3. How value-added tools meet specific serview needs
The era of one-size-fits-all service models is fading, giving way to more personalized and flexible SaaS (Software as a Service) solutions. These tools are designed to meet the specific needs of different users, from dealers to OEMs, enhancing the ability to troubleshoot both simple and complex issues.
Key features of these value-added tools include remote monitoring, on-demand repairs, and predictive maintenance analytics. For construction equipment, these tools offer a significant advantage. Remote monitoring allows for constant oversight of machinery performance, ensuring that any anomalies are detected early. On-demand repairs and software updates keep equipment in optimal condition, reducing the risk of unexpected failures.
Predictive maintenance analytics is another critical feature, as it enables construction teams to schedule maintenance activities based on actual equipment usage and performance data. This proactive approach minimizes downtime and extends the life of the equipment, contributing to better project management and cost efficiency.
4. How increased connectivity enables proactive maintenance
Increased connectivity is set to revolutionize how companies service their machinery. Sensors and connected devices can now monitor machine performance in real time, transmitting data back to service teams. This facilitates proactive maintenance, allowing service interventions to be precisely timed based on actual wear and tear rather than fixed schedules.
The outcome is reduced unplanned downtime, optimized maintenance costs, and extended machinery lifespans. This trend improves operational efficiency and enhances customer satisfaction by ensuring machinery reliability and performance. For construction teams, the constant stream of data enables a more confident approach to diagnosing and resolving common service issues. Additionally, it empowers dealers and OEMs to be more proactive with their customers, anticipating needs and addressing potential problems before they escalate.
The integration of increased connectivity supports a more efficient service process, ultimately leading to fewer interruptions and more reliable machinery. This results in enhanced project timelines, cost savings, and a significant boost in overall operational effectiveness for the construction industry.
For construction equipment dealers and manufacturers, improved data sharing, personalized AI for service and training, value-added tools, and increased connectivity all contribute to more efficient and effective service processes. Enhanced data sharing and predictive maintenance capabilities allow for precise interventions and reduced downtime, which translates to increased machinery reliability and customer satisfaction.
Embracing these trends not only meets rising customer expectations but also positions service teams to deliver exceptional value.
About the Author
Assaf Melochna
Assaf Melochna’s experience incorporates strong leadership skills built upon a strong technical foundation. He is an expert in service, and has business and technical expertise in enterprise software. Assaf started Aquant with his co-founder Shahar with the vision of helping service companies transform the way they deliver service. Prior to starting Aquant, Assaf spent 10 years at ClickSoftware where he served in various positions in solution consulting and product innovation. Assaf brings a unique approach from his experience as a Major in the intelligence forces (IDF) where he specialized in turning massive data to knowledge, and knowledge to actions.