Data-driven Ways to Improve Safety in Warehouses

Data-driven Ways to Improve Safety in Warehouses

As part of a proactive management team in warehousing, you’ll have heard it before: “Labor productivity must go up.” “We need more qualified workers.” “Innovate!”

These challenges are complex. The answers to them may seem even more so. What can one company or even one manager do about them? How can your company stay competitive in a hyper-competitive, global economy?

It starts by finding the low-hanging fruit.

In an industry where labor productivity is declining, talent shortage is rising, and accidents and fatal injuries are at a high, your warehouse needs to rise to the challenge, snatch the low-hanging fruit, and enter the digital age on your terms.

And for small and medium-sized businesses, that means easy to use, cost effective and focused on the business outcomes. That’s precisely what you can do, with Simon AI.

 

Safety as the low-hanging fruit in warehousing

The average worker injury costs as much as $38,000 in direct costs and up to $150,000 in indirect costs. For small and medium-sized companies, that adds up fast. In fact, it’s damaging in numerous ways from your company’s pocketbook, to its reputation, and let’s not forget the actual person suffering the injury.

That’s what makes safety a key area for innovation in your company and an ideal launch point for furthering your company’s digital strategy.

Not only could it save lives, safety and security lay the groundwork for solving other common business challenges along the way. That’s the power of location and environmental data. That’s why we start here.

 

Why is safety a low-hanging fruit for innovation?

  • Safety and security of workforce is an important and worthy investment
  • When things go wrong, someone needs to be held accountable
  • Reputation damages resulting in decrease in hiring qualified workers
  • Direct and indirect cost to company

 

The importance of data in common warehouse accidents

So much data. So little time. At this point, you might be wondering, “why do I need data? where does data come from and how can it help solve business problems?” I thought you’d never ask.

Data is generated by sensors often embedded in hardware like BLE beacons and tags. Once collected, robust analytics scan data sets for patterns. Depending on the use case, these patterns form predictive models that help your business better-predict conditions about the future.

Imagine that one of your workers slips, falls, and injures themselves while walking between the loading dock and inventory. You rush to their aide and proper medical attention is provided.

Important questions immediately need answering, like:

  • Why did this happen?
  • How can we prevent it from happening again?

Until recently, to answer these questions meant relying on firsthand or even anecdotal data about the cause and course of action moving forward. Then came IoT. Using data from location and environmental sensors, data could be analyzed to reveal other aspects of the situation that were maybe not accounted for, like that humidity levels were above 80% – the same conditions of the previous two slips as well. It turns out the floor becomes slippery when humid. Mystery solved! From then on you realize the importance of controlling the humidity levels as it leads to fewer falls. Everyone wins.

Unfortunately, traditional IoT solutions such as these were built for large companies with large budgets who can absorb the high failure rate that has accompanied (and hindered) the Internet of Things for years. It’s been a complex and expensive ride for early-adopters.

For SMBs, IoT has been like being stuck between a technological rock and a financial hard place. There seemed to be no way around it.

 

Streamlining the added value of IoT

Then we created Simon AI: to provide industry managers with a solution that streamlines the added value of an expensive IoT platform into one, end-to-end IoT analytics suite built especially for small and medium-sized businesses.

It works because we gather data on location and environmental conditions adapted specifically to answer the pressing questions a proactive warehouse manager needs to know when an accident happens:

  • Where were workers at the time of incident?
  • What were environmental conditions?
  • Have incidents occured here before? Under what circumstances?
  • How long did it take to call for help?

On top of that, it automates the tracking and reporting of security incidents (and other common business problems) over time, so as a manager, you don’t need to fill out lengthy paperwork and reports. Rather than relying on firsthand accounts to understand operational problems and create change, data from BLE tags worn by the worker or attached to a forklift can be referenced in real-time to identify patterns that predict and prevent similar accidents from occuring in the future.

Data is the key to knowing these answers and providing managers with the insights they need to solve business problems in real-time.

Kontakt.io is the only company capable of providing a truly end to end IoT solution, built for SMBs, to solve problems of security and a host of other common business problems.

 

Data is key to greater security

While it may seem an unlikely candidate for technological innovation, safety in warehousing the perfect low-hanging fruit to apply technological innovation. In a digital world, data is the key to identifying and improving business operations giving companies who use it wisely a clear advantage over their competitors.

And the good news is that you can get started as early as today.

 


IoT in Warehouse Operations RTLS

Learn more about the value of location-based IoT data in our recent white paper.

 
 
 
 
 
 
 
 
 
 


Anthony Richardson - Photo
  • Anthony Richardson
Content writer interested in how technology is changing the way we work, live and relate to the world. Anthony will be living around the world for the next year and writing about it.

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