by 
Shannon Flynn
Some of 2020’s challenges were keenly felt throughout supply chains, and many could result in lasting changes to workflows and processes.
Reducing uncertainties while boosting efficiency and shrinking turnaround times requires a set of modern supply chain and logistics tools. That means leveraging automation. Recent events helped drive home the need for a more resilient and predictable supply chain. Can automation get us there?
Why is autonomy important in the supply chain?
An autonomous supply chain anticipates disruptions and provides a relief valve before they manifest.
“Logistics partners have ‘Covid surcharges’ [now] similar to the ‘fuel surcharges’ that were introduced a few years back,” said Dave Doherty, president of Digi-Key. Maybe it didn’t have to be that way, though.
Doherty is only referring to the most publicized challenge facing supply chains currently. Others include unpredictable weather events, geopolitical disruptions, ever-changing sanctions, regulations and tariffs, difficulty sourcing raw materials, and pressures to make distribution, pick-and-pack and customer returns faster than ever.
All this makes a clear case for automation throughout the supply chain. Will the sector ever go fully autonomous? Here’s what’s in motion today.
Automating real-time data collection
Automatic data collection is a must if one does business in the supply chain. By 2025, Earth’s human population will likely generate and store 463 exabytes of data per day. Automation provides the means to leverage vast amounts of information that might otherwise go unused.
Data serves as the backbone of the rest of a supply chain’s optimization and automation efforts.
Suppose you can automate the gathering, transmission and sorting of data gathered from each supply chain activity. In that case, you have the means to make each of those activities faster, more efficient and better equipped to recover from setbacks or outside influences.
This part of the sector’s pivot toward full automation is well underway. Some companies use big data to shed millions of driven miles each year from their delivery itineraries.
Practical areas to apply automation in the supply chain
Supply chain companies have ample opportunities to put gathered data to work and lots of choices on the market for how to do it. Digital process automation and machine learning are capable tools for automating manual tasks that are important but also error-prone, like:
- Scanning incoming freight
- Sorting merchandise for storage or packing
- Monitoring levels of consumables, like packaging
- Identifying bottlenecks in workflows
- Delivering alerts when essential or in-demand inventory runs low
These processes can be automated by supply chain teams, whether they’re involved in manufacturing, distribution, warehousing, transportation, port management or final point-of-sale:
- QR codes and RFID tags allow automatic and/or hands-free scanning for incoming freight
- Big data platforms and intelligence tools study industry trends to anticipate material or personnel shortages
- Distributed sensors and computing identify underperforming material handling lines, personnel or processes and implement changes while measuring outcomes
- Automated back-office functions make paperwork generation, like audits and schedules, automatic and seamless
This data transmission will be faster and more seamless than ever with the speeds and low latency of 5G, which facilitates faster responses to the gathered information.
Automating warehouses and distribution facilities
Recent staffing shortages during the pandemic and the “great resignation” showed that key supply chain workflows require the thoughtful application of automation. That’s especially true for areas with personnel working in close and frequent proximity, like distribution and warehousing facilities.
Automated guided vehicles (AGVs) allow the automatic conveyance of freight without significant need for foot traffic across a facility. Moving pallets of goods can be difficult and ungainly. However, the robotics market has produced a host of options for eliminating the human element from these and similar processes, along with the associated crushing and pinching accidents.
Automating final mile and general delivery
Is it possible tomorrow’s supply chain will automate final-mile delivery? Signs point to yes, given that some of the largest retailers are actively experimenting with it. Drone delivery is an obvious step in this direction.
This is to say nothing of the coming automation wave that’s expected to sweep across the trucking industry. Some in the industry anticipate shifting a considerable amount of freight via autonomous trucks by 2024 or 2025. This is a watershed moment for logistics and says something about how automated the future supply chain will be once driverless technologies mature fully.
Automating payroll and back-office processes
A global marketplace means a global talent pool. For companies that operate across jurisdictions and borders, maintaining compliance and thoroughness during onboarding, payroll, and time and expense tracking is a more complex task than for the average company.
That’s why automation in payroll and other back-office processes is gaining steam. Some estimates peg its benefits at around an 80 percent savings on the cost of processing alone. Part of the reason for this transition was due to tightening financial regulations. The rest of the benefits involve saving HR departments time and energy for activities that require a human touch.
Automating demand forecasting and planning
The days of making a “best guess” about how much merchandise to fabricate, warehouse and drop-ship are behind us. Historical demand forecasting is useful, but automation and machine learning can use historical and more recent data to form an actionable picture of the future.
Automation and predictive analytics are why companies that distribute allergy medications have an uncanny ability to know when and where their products will be needed most. According to Anuj Agrawal, a vice president at Orchestro, “If it’s taking you a week to organize the data and to see you have an out-of-stock somewhere, you’re losing.”
Modern modeling tools aren’t just for seasonal products, either — they’re for any product category. Demand can shift due to factors like changing regulations and tariffs and unpredictably severe weather events. However, enterprise planning tools powered by machine learning are getting better at determining the greatest impact on demand and the company’s ability to meet it.
Know which technologies to watch
All these factors paint a clear picture of an industry in transition. The result will be a global apparatus that is streamlined, efficient, and resilient against inside and outside factors, like fluctuating politics and climates.
The ultimate expression of automation in supply chains is the “lights-out” factory. They first came online years ago, and one of them even won a “Plant of the Year” award. The means to automate almost 100 percent of a factory, minus some human QC and maintenance specialists, exists today.
Automating and using real-time data collection requires an eye for emerging technologies like machine learning and artificial intelligence. However, turning the gathered data points into results you can see on a warehouse or distribution hub floor will always require human insights.
