AI-Enabled Robotic Automation for New Workforce Efficiencies

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By Ryan Martin | 2Q 2018 | IN-5101

Robotics are entering the workforce in new ways every day, as evidenced by enterprises like Amazon and Walmart. The interdependence of processes, people, and technologies will be key in determining best practices for new deployments.

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A Method to the Madness


Imagine what it might take to find one of the 167 million items in the Library of Congress. Now, think of the same scenario if every book was last placed on the shelf at random and you only have 1 hour. This is essentially what happens every day at an Amazon Prime fulfillment center, except it’s on purpose.

When a customer places an order for same-day (2-hour) delivery, it is entered into the system so a warehouse picker can scan, retrieve, and organize inventory. To do this efficiently, Amazon employs a process referred to as “random stow,” which scatters similar products in different, known locations throughout a facility, rather than together, as might be observed in a supermarket, for instance (though the unintended consequence is that something like packaging requirements become a useful input). The last step is to sort complete orders by destination and date for pickup and delivery.

The reason this process works is because it’s more in line with the way online shoppers actually shop. The challenge was to create a system that would also accommodate the way pickers pick.

Blurring the Boundaries of Convergence


Amazon’s physical footprint consisting of office space, stores, warehouses, and data centers grew 42% in the past year. Its headcount increased more than 66%, from 341,400 to 566,000 full-time and part-time employees (including the 87,000 people who work at Whole Foods, which Amazon acquired for US$13.7 billion in 3Q 2017), during the same period. But if the company’s goal is to be able to predict, pair, and prescribe procurement processes for just-in-time fulfillment across both digital and physical properties, what it is looking at is an optimization problem of global scale.

Implementing the same standards for operational excellence beyond Amazon-branded walls takes tremendous coordination. Anything short of this yields misalignment; misalignment impacts inventory, supply chain, and workforce utilization (variable costs); and unfavorable operating expenditure (OPEX) utilization necessitates additional infrastructure (fixed costs) to smooth gaps in supply/demand.

Consider new forms of delivery, for example. According to a 2018 PwC survey of 22,000 respondents in 27 territories, more than one-third (38%) of consumers would trust a drone to deliver their package; 22% for low-value products and 16% for any product. To make all of this happen, however, requires a complex network of robots, remotely-accessible storage lockers, and traditional cargo delivery, in addition to the integration of services across disparate parties and regions (for some of which these technologies are entirely new). Now, think of the same scenario with aisle-free checkout solutions like Amazon Go.

From Infrastructure Amplifier to Workforce Multiplier


Walmart, the world’s largest nongovernmental employer, is using robots from Bossa Nova Robotics to scan shelves for out-of-stock items, check prices, and identify missing labels for a near-real-time view of which areas of the store need most attention. Here, shelf-scanning technology are used in combination with robots to help associates with repeatable, predictable, and manual tasks so they can focus on better serving the customer. Lowe’s has a similar implementation with Fellow Robots, but for greeting and leading customers to the desired product.

Using robotics, function-based designations (e.g., “fulfillment”) can be relegated to software (but driven by operations); “preferred qualifications” become minimum functional requirements; and productivity key performance indicators (KPIs) have as much to do with uptime (opportunity versus inefficiency) as they do downtime (opportunity cost versus efficiency gains, e.g., load balancing when equipment is not in use). While public-facing pilot projects in retail, home care, travel, and tourism put Pepper-style solutions (Softbank Robotics) front and center, most of today’s robotics-based automation implementations go beyond this line of sight: autonomous travel, human-less fulfillment, unmanned data centers, semi-supervised and assisted automation, manufacturing and logistics, etc. It’s in these scenarios that Amazon’s use of robotics has been found to drive net-new hires, due to overall efficiency improvements in throughput.

Executed with the right tools and guidance, these technologies have the potential to greatly enhance the human experience by reducing the cognitive load on workers. In doing so, companies should:

  • Favor Collaboration, Cooperation, and Co-Creation: While familiar challenges around device functionality, power management, and integration with existing assets prevail, there is a softer side to innovation that rarely receives the attention it deserves, and it has to do with people; consumers, as well as employees, are left in a state of anomie when the rate of technological innovation exceeds that of non-technical drivers of adoption (cost, social acceptance, regulatory adherence, a clear business case).
  • Treat Collaborative Robotics Rollouts Like a Mergers & Acquisitions (M&A) Exercise: Embodying a unified corporate culture across two formerly independent entities—human + robotic workers—that need to find a fit for different competencies, and properly redistrict redundant roles and responsibilities.
  • Land and Expand: Enterprise-oriented IoT technologies, such as robotics, machine learning, and augmented reality, are tools that can augment or replace legacy systems, processes, and workflows; optimize operations; and smooth the flow of communication across teams, machines, and otherwise disparate departments. Aligning and integrating such solutions with peripheral innovation is where strategy turns tactical: efficiency and scale versus innovation and support; delegation versus collaboration; and speed to action versus quality of care.
  • Prioritize Safety and Compliance: Novel form factors often predicate changes to content and communication delivery. This was a hot topic in the earlier years of the wearables industry that drove a lot of today’s framing around end-user access to information (pull), rather than an input to initiate an action (pull/push). The fact that most IoT devices are headless (no display) further underscores the interdependence of people, process, and technology. Net-new capabilities, such as continuous biometric authentication, are also along for the ride.
  • Involve Information Technology (IT) in Operations Technology (OT): Although budget and decision-making authority often resides with customers’ internal innovation centers or, more specifically, the people responsible for managing the particular functions for which IoT applications are intended to be used, it also means that IT can assume a more operational role in favor of channel and partner program expansion.