What is Predictive Maintenance and Why is it Important in Field Services?

This blog has been updated on - March 04, 2024

What is predictive maintenance and how does it help field service professionals?

That is one of the most discussed queries among supply chain, manufacturing, and logistics firms.

Customer expectations are growing every day. Some field service businesses address them through predictive analytics and maintenance.

These organizations are equipped with connected asset tracking, which offers them a competitive edge, increases their revenue streams, and helps them gain operational efficiency.

Over 90% of companies focus on Maintenance, Repairs, and Operations to avoid downtime and prioritize predictive maintenance.

Let's explore how predictive maintenance can help your field service business achieve unparalleled excellence.

What Is Predictive Maintenance?

Predictive maintenance is a system that incorporates big data and analytics techniques that identify irregularities or defects in your operations, processes, and equipment.

That allows you to fix these defects before they result in a breakdown and impact your business.

With predictive maintenance, the frequency of upkeep is low, as it prevents accidental reactive maintenance.

However, few field service businesses have adopted this system – several still depend on the old-school manual setup. As a result, organizations fail to transmit the relevant resources at the right time and can't meet the customers' needs.

Neglecting predictive analytics for risk management forbids technicians from detecting or preventing machinery failures or other uncertainties. They can only resolve the issue after there's been a failure.

Advantages Of Predictive Maintenance for Field Management

According to a survey, the lack of a skilled workforce is one of the biggest challenges for over 30% of field service organizations. Besides that, they are concerned about unpredictable downtime and breakdowns, encouraging customer frustration.

Predictive maintenance and big data analytics can help prevent dissatisfaction by increasing workforce expertise, streamlining processes, and procuring accurate and timely data.

Let's now discuss the benefits of predictive maintenance:

Maximizing Workforce Productivity

Using IoT predictive maintenance in healthcare and field service management can enable your team to dedicate more time to critical maintenance tasks.

With the software analyzing the sensor data through an IoT-driven system, your technicians won't need to spend time gathering this information manually.

Traditional setups are bound to create several emergencies, leaving the engineers to focus on fixing them. However, predictive maintenance can enable your team to work on more critical tasks.

For example, many healthcare technicians use automated setups to get patients' health records anytime. Their systems are powered by AI-driven healthcare data analytics algorithms and business intelligence solutions to optimize medical efficiency.

Maximizing workforce productivity entails using the best predictive maintenance software. These are readily available in the market.

Keeping Your Customers Delighted

Customer satisfaction means excellent ratings for your business. Customers like to know what to expect from you. That allows them to work out their involvement.

The role of predictive maintenance is massive as it aids in interpreting a high volume of data and sharing insights or trends that aren't possible for humans to identify.

This is done through different types of data analytics tools equipped with advanced algorithms that can be highly beneficial for a field service business.

The chances of emergency interventions become low after gaining clarity on the service trends for every location.

Predictive analysis will enable you to consider a customer's requirements and create a schedule that works for them.

Overall, customer data analytics and predictive maintenance will keep your customers delighted and provide operational stability.

Cost-effective Investment

A US Department of Energy research paper states that predictive analysis is a cost-effective investment.

An organization with a field service management solution can receive exceptional financial gain with a remarkable ROI.

That can even continue with 70%-75% fewer failures, 35%-45% downtime elimination, and 25%-30% decrease in maintenance costs.

You must be aware that the traditional method costs you five to six times more because your team can only fix or repair the damaged parts after they have broken down.

Predictive maintenance technologies can help you respond to failures before they even occur, saving time and money.

Lowering Unscheduled Downtime

The most difficult challenge that field service businesses must navigate is unscheduled equipment downtime due to breakdowns.

It impacts the performance of engineers and technicians hugely and leads to severe costs and expenses.

The proactive approach through predictive maintenance supports risk analysis and management with early predictions and engagement.

This approach aids in avoiding any unexpected downtimes and allows the team to plan interventions.

Incorporating data-based solution software can allow your technicians to optimize equipment conditions.

That can have a minimal to no dreadful impact on the business and the customers.

There are several predictive maintenance tools that can help you in this. Also, smartly using predictive maintenance techniques can have numerous benefits for field management.

Why Should You opt for Predictive Maintenance in Field Services?

Predictive maintenance solutions have irrevocably helped reduce the automation gap in field service. The quality of service measures your organization's worth and the value you offer your customers.

Advanced digitization is making it easier for several businesses to understand customer data through statistical analysis. Predictive analytics can become a unique selling point that will help your team accelerate field service efficiency.

To take advantage of the slow-paced competition and know more about how predictive analytics tools can transform your business, hire certified data engineers at BluEnt. 

BluEnt is a top-notch business consulting, IT, and CAD engineering service provider with a global clientele and hundreds of projects in its portfolio. We specialize in enterprise data management, big data management, big data insights and analytics, big data implementation, and predictive analytics. 

We also offer enterprise-level services ranging from business process management to CRM solutions, business intelligence, enterprise content management, and enterprise mobility,  

You can opt for field service management solutions to streamline and make your field services more efficient. That will increase your competitiveness and enhance your revenue through customer satisfaction.

Ready to delight your customers with predictive maintenance tools? Contact us now. Check out our portfolio for more insights into our projects and other undertakings.

Frequently Asked Questions

What are the types of predictive maintenance in field services?

These are the four types of predictive maintenance models:

• Condition-based predictive maintenance: This type of predictive maintenance method involves motion sensors to examine the health of mechanical devices. It can detect flaws in rotatory machinery, such as motors and turbines used at large manufacturing plants at an early stage. That helps in reducing downtime and risks of sudden failures.

• Time-based predictive maintenance: Companies can rely on this predictive maintenance technique to avoid unforeseen machinery failures. They use historical data to track frequent patterns of performance issues or other glitches and take immediate actions beforehand. It helps technicians to schedule maintenance at the right moment.

• Usage-based predictive maintenance: This predictive maintenance is applied to loading machinery such as forklifts and cranes. It records the timeline for any machinery or device and alerts users when it reaches the usage limit. That reduces untimely failures and downtime due to the overuse of mechanical assets.

• Model-based predictive maintenance: Field service staff uses this predictive maintenance technique to manage devices or machinery with high failure rates.

How does BluEnt help in predictive maintenance in field service

At BluEnt, our data scientists collaborate with technical teams to analyze the internal operational setups and assets.

We further take these steps to shape a result-driven strategy for predictive maintenance analytics:

• Step 1: Identifying assets requiring maintenance with the help of an asset management system.

• Step 2: Monitoring the performance of equipment or machinery using advanced sensors.

• Step 3: Collect and implement data for maintenance scheduling before it fails.

• Step 4: Analyzing the results for future maintenance plans and schedules.