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Robotic Process Automation and beyond : Redefining Logistics in a Smart World

Robotic Process Automation and beyond : Redefining Logistics in a Smart World
February 14, 2018

For the logistics industry that is defined by thin margins, minimizing operational costs is a critical profit driver. A number of technology trends are promising to reshape the logistics industry, including robotics, IoT, 3D printing, blockchain, and autonomous vehicles. However, Robotic Process Automation (RPA) stands out as a solution that can quickly bring down costs.

With the labor market at full employment and a shortage of skilled labor, RPA can automate tedious and repetitive back-office tasks, reduce transaction times, drive process standardization, and provide quick cost savings.

Over the next three to five years, investments will shift from mobile and IoT toward robotics and artificial intelligence (Figure 1). An ISG study postulates that 72% of companies will rely on RPA by 2019, all in the interest of productivity, compliance, cost, and transaction times.

Supply Chain

Figure 1: Investment Focus Areas Source: Supply chain 24x7

The same study states that RPA can facilitate a 43% reduction in time for processes such as billing, credit, and collections. Supply Management’s study extends these findings, suggesting that vendor management, recruitment, and talent management activities can be processed 32% faster and invoicing 34% quicker with the support of this technology. Other areas that could benefit from RPA include inventory management, order management, and collections. But with advancements in AI technologies such as machine learning, cognitive computing and NLP – forward-looking organizations are already moving beyond RPA to “cognitive process orchestration." This new paradigm looks at the front, mid, and back end of any process and applies various smart technology levers across to bring efficiency-, effectiveness-, and experience- related benefits, beyond costs savings. Consider the following examples:

  • Procurement and inventory management: Bots can monitor inventory periodically and when inventory levels hit a threshold, a purchase requisition (PR) can be automatically created. Robotics and artificial intelligence (AI) drive this process seamlessly, and NLP can drive efficient chat bots for front-end interfaces.
  • Purchase order creation: Bots driven by business rules can automate requisitions and vendor assignments for the PR. Additional manual tasks that can be automated include PO placement with vendors and stock optimization and modification; driven by machine learning to even automate decision- making in the “mid-office,” which would be traditionally dependent on human ability.
  • Order management process: Incoming orders can be monitored and validated by bots. These bots can then ensure that the sales order with the right pricing and discounts is generated and updated on the ERP. Once the order is shipped, invoices can automatically be sent out to the customer. Cognitive interfaces can even transform the whole experience for customers.

#Logistics industry is benefiting from #Robotics Process Automation by reducing the operation expense

Recognizing the benefits of RPA and AI, the logistics industry has been an early adopter of this technology, and it won’t be long before cognitive process orchestration becomes commonplace.

A provider of transportation and logistics services in the US faced major challenges in mileage billing, like having a fragmented process to collect data and capturing inaccurate data. Implementing RPA led to:

  • Multi-million-dollar revenue growth over a period of five years
  • Increased potential to bring down the operating cost
  • Improved customer satisfaction through process optimization and accurate billing

For those contemplating RPA initiatives, it is important to ensure that the initiative is business-driven rather than technology-driven. The first step should be to identify the right processes that can drive cost savings and leverage optimization opportunities. Appropriate technology selection should follow next.