Real-time data analytics can provide detailed insights into the state and performance of the machines around your warehouse, allowing you to proactively diagnose and repair problems as they arise. Your quick action and the insight provided by data analytics can radically extend the lifespan of your warehouse’s equipment.
Explore how real-time data analytics works and the many ways it can be used to support your warehouse, helping your machines last longer.
What Is Real-Time Data Analytics?
The term real-time data analytics refers to technology that can generate and process information the instant it becomes available. If you’ve ever used a Global Positioning System (GPS), you’ve benefited from real-time data analytics.
These systems rely on sensors, Internet of Things (IoT) devices and software to collect and consolidate data from machines connected to the systems. They can then use this data to assess the machines’ location and efficiency, as well as how the mechanisms within the machines are performing.
That insider knowledge can inform decision-making and lead to more efficient and consistent activity within a warehouse setting while also protecting forklifts and other machines via preventive maintenance.
As time passes, the technology involved in real-time data analytics is only getting more powerful and useful. Warehouses around the world already rely on it on a daily basis to:
- Support decision-making.
- Track resources
- Save money.
The Power of Predictive Maintenance
Data analytics technology is transforming equipment maintenance by minimizing the need for repairs in the first place.
Typical maintenance is reactive. For example, a warning light flashes on an equipment console or smoke begins to pour from an engine, and that’s how you know that repairs are needed. This approach is costly and leads to bouts of unexpected downtime, during which the machine or machines in question cannot be used.
Real-time data analytics, however, allows you to be proactive. The sensors and IoT devices within your machines can detect and track wear and tear before any actual malfunction occurs. They can even generate models based on the equipment’s health and history that can predict when maintenance is needed and when a breakdown is likely to occur. All this information gives you the ability to step in and make repairs when they are at their least expensive and time-consuming.
In the long term, predictive maintenance data analytics can save you time and money while also extending the life of your machines and supporting increased equipment uptime.
Other Benefits of Data Analytics in Operations
Data analytics offers a wide range of benefits to warehouse operations, beyond just extending the lifespan of your equipment. These advantages include:
- Increased operational efficiency: Real-time data allows you to view and assess warehouse operations. When leveraged properly, it can optimize workflows and machine pathing, reduce bottlenecks and improve your facility’s resource allocation. It can even improve your ability to respond to sudden schedule changes or operational disruptions.
- Significant cost reductions: Preemptive maintenance and optimized operational processes can save you money by helping you avoid costly repairs, unnecessary downtime and excess effort. Over time, these processes can represent a radical reduction in overall costs.
- Improved inventory and asset management: Warehouse management analytics allow you to track inventory levels and equipment status across your facility, equipping you with accurate data that can support and simplify decision-making. Stock replenishment and asset management become far easier when you have locations, conditions and numbers at your fingertips.
- Increased safety and compliance with regulations: Equipment malfunctions and hazardous conditions pose a threat to the health and well-being of those who operate within the warehouse. Real-time data analytics can provide immediate alerts should there be a battery acid spill or vehicle malfunction, which can increase response times and prevent injuries. It can even be used to monitor and report on your facility’s compliance with the Occupational Safety and Health Administration’s (OSHA’s) standards for warehouses and other storage facilities.
Real-time data analytics leverage advanced sensors and other technologies to offer support, safety and savings across the entirety of warehouse operations.
Best Practices for Real-Time Data Analytics
Gaining access to the benefits above requires more than just investing in sensors and software. You must prioritize a strategic implementation that mirrors the data analytics life cycle and leverages all the strengths of the technology at hand across your warehousing operations.
To get the best out of real-time data analytics, you and other stakeholders should:
- Implement robust data collection systems: The sensors and IoT devices you invest in must be capable of collecting and reporting accurate data in real time to a central hub. If they report to other programs or pieces of software, ensure their data is standardized across all systems for consistency. Your data collection systems should also be widespread enough to capture all of the information needed for predictive maintenance, asset management and any other functions your warehouse is pursuing.
- Integrate data across all platforms: If data is collected using a number of different platforms, consolidate into a single system so that the whole of the data is easy to access and interpret. Otherwise, you risk creating data silos that can limit efficiency and lead to an incomplete picture of the warehouse’s operations.
- Prioritize data quality and security: All data captured through real-time data analytics should be periodically validated and cleaned to ensure accuracy and prevent errors. Robust cybersecurity measures should also be in place to protect sensitive data, such as inventory levels and financial information.
- Leverage predictive and prescriptive analytics: The more data your system has access to, the more accurate its prescriptive assessments and predictive models will be. These can be leveraged to assess your operational efficiency and anticipate issues with equipment and the warehouse as a whole. These models can be further supported by machine learning models and artificial intelligence systems, which can improve the accuracy of predictive models across time.
- Prepare staff for new tools: Real-time data analytics can support work across a range of departments, so be sure to train all staff who will be interacting with this new technology on how to use it properly. Human resources personnel, warehouse managers, maintenance teams and more can all use this technology to enhance operations and make their work easier.
- Foster a data-driven culture: The information provided by real-time data analytics should inform decision-making across every level of your organization. All stakeholders should have an appreciation for the insight provided by your organization’s data and understand that the insights it provides into the organization’s performance as a whole can transform processes and lead to better results for everyone.
Partner With Burns Industrial Equipment for Real-Time Data Analytics
If you’re looking to extend the lifespan of your fleet of forklifts, Burns Industrial Equipment has your back. Our information telematics services make tracking and managing lifts simple, and that power can save you money while minimizing downtime.
If you’re looking to upgrade your fleet, we’ve got you covered there, too. Our robust suite of forklifts comes from some of the best brands on the market, such as Yale, Hyster and Bendi.
To learn more, fill out our contact form online today.
