Impact of Automation on the Moving Industry: Emerging Technologies to Watch

When it comes to innovation, you can either lead, follow or get left behind (just ask Polaroid, Blockbuster or the Guild of Professional Elevator Operators).

One of the primary drivers of innovation is automation, which has already transformed entire industries. Examples include automobile manufacturing (robots), banking (ATMs) and travel (online booking). Similar trends will soon transform medicine (artificial intelligence), transportation (driverless vehicles) and elder care (robot companions).

In this article, we’ll sample a few technologies that may have a profound impact on the moving industry.

Artificial Intelligence (AI) for Cost Estimation

AI is so hot right now. And if you’ve ever used Google, Siri, Alexa or Facebook, you’ve already met AI.

AI encompasses multiple disciplines, including Natural Language Processing (NLP), machine perception (MP), machine learning (ML), etc. Today’s AI is less about Lt. Cmdr. Data from Star Trek and more about statistics. Once properly trained, MP and ML algorithms are really good at recognizing subtle correlations between images, sounds, documents, etc., and categorizing them into groups. This makes AI useful for analyzing things like mammograms that may contain barely perceptible tumours, tiny ripples in stock prices that could presage a recession, or Instagram posts that might feature your bestie.

In the moving industry, software has already partially automated traditional ‘pencil-and-paper’ tasks such as customer booking and resource scheduling. The next likely target for automation is cost estimation, and AI could be the right tool for the job.

Authors like Ryan Carrigane ( and Ray Inskip ( predict that instead of sending an estimator on a physical walk-through of a customer’s home (time-consuming, expensive), a video captured by the customers themselves could be analyzed by AI algorithms to calculate the type and number of items to be moved. In addition to being faster and more precise, an AI solution will also appeal to younger customers who favour DIY app-driven services. Since this technology is already emerging for the construction industry, it is reasonable to expect similar AI solutions will be available to movers within the next few years.

Driverless Moving Trucks

Driverless vehicles have gone from a concept to reality in just 15 years. The Institute of Electrical and Electronics Engineers (IEEE) predicts that 75% of all vehicles will be driverless by 2040, including commercial trucks.

Within the next decade, the first impact on the moving industry is likely to involve ‘trans-modal’ long distance moves. Conventional trucks would be used in the start and destination cities, with loads being transferred to long-haul driverless transports in between.

Robotic Assistants for Lifting and Carrying

We’ve all seen YouTube videos of Honda’s ASIMO android or Boston Dynamic’s zoo of (literal) robotic workhorses. Although these demonstrate human-like ability to carry objects and climb stairs, their high cost puts their entry into the moving industry years away.

However, simpler robots and robotic assistants are already being used for material handling. Companies like Amazon and Ford are currently using Autonomous Guided Vehicles (AGVs) as “virtual conveyors” to move items around their warehouses and plants. Motorized stair-climbing carts are already available to movers.

“Uber-fication” of Moving Services

The “Uber” business model has expanded well beyond on-demand ride services and food delivery. Technology to automatically pool, schedule and deploy freelance “movers” (i.e., people with a vehicle and space to spare) is already here. Uber-like companies like Bellhops, Dolly and Buddytruck reach their customers via automated apps. For conventional moving companies, automation through “Uber-fication” represents a new competitive pressure that must be addressed.

Cost-Justification for Automation – Sample ROI and Payback Calculation

Adopting automation only makes sense if it results in a net gain on the bottom line. Gains are measured over the lifetime of the investment and may be realized in three ways:

  • Lowering expenses (spending less to do the same job);
  • Improving productivity (doing more for the same cost);
  • Growing sales (gaining a competitive advantage).

A decision to automate is based on its return on investment (ROI), defined as

ROI = (Gain – Cost of Automation)/Cost of Automation

Here’s an example: Based on test data, the “Doll-E” stair-climbing cart offers a time-saving of 35% on a typical 3-bedroom/2-storey residential move. If that job required a three-person crew, it can now be done with two. Assuming “Doll-E” has a useful life of 4 years with an initial cost of $8,000 and a worker earns $30,000 annually, the ROI would be

ROI = (4x$30,000 – $8,000)/$8,000 = 1400%

In other words, “Doll-E” pays for itself 14 times over.

Another useful metric is the payback period, which is the time needed to recoup the initial investment. In this case the payback period would be

Payback Period = Cost of Automation/Annual Gain = $8,000/$30,000 = 0.27 years = 3.2 months

When evaluating the value of automation, it’s not always about speed. “That robot is moving awfully slowly. My guys can walk twice as fast.” While true, the robot is also carrying six times more weight. In this example, the robot would be 50% x 6 = 3 times more productive than a human.

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To conclude, industry-changing developments in automation technology are inevitable. Savvy movers must make best use of these developments, because after all, resistance is futile.