From efficiency to resilience: using hyperautomation to address new supply chain priorities

The pandemic has prompted many companies to rethink their supply chains. As companies around the world face up to the realities of an economic downturn, they will need to adapt business models. Robotic process automation (RPA), in combination with advanced technologies like AI, IoT, and chatbots, will help drive efficiencies by scaling up automation rather than scaling down employees.

For many years now, supply chain leaders have been using "just in time" business processes to maximize outputs while minimizing the cost of production and sales. This approach was an inventory strategy in which materials were only ordered and received as and when needed in the production or sales process. It's an efficiency-based approach that has served manufacturers and retailers, minimizing the holding costs associated with storing inventory that remains unsold. A firm's holding costs include the price of goods damaged or spoiled, as well as storage space, labor and insurance.

Over the last year, we've seen major disruptions to supplies, in addition to shifts in levels of demand for different product formats. For example, food and drink products designed in smaller packages for "on-the-go-usage" and impulse purchases were no longer as popular as bulk-buy formats as consumers spent more time at home. Just-in-time supply chains have always been subject to uncertainty. But the pandemic has prompted deeper thinking on how digitization can increase flexibility and agility moving forward.

There is clearly a need to streamline and speed up how companies execute high-volume business processes along the supply chain to enable them to adapt to changes in consumer demand and the availability of supplies from each vendor. Processes within supply chains are crucial to getting product inventories right, ensuring that quote-to-cash and procure-to-pay purchase orders are accurate and timely, and making invoicing system workflows operate efficiently in environments that change rapidly.

Traditionally these have been manual processes carried out by human workers augmented by technology. Now these processes can be automated with robotic process automation (RPA).

The rise of the robots

RPA in a supply chain can help bridge the gap for system-to-system communications and overcome the types of supply challenges created by the pandemic. RPA can run global stock checks 24/7, for example, to ensure parts or components are available to be shipped to where they are needed, updating inventory systems as supplies tagged with IoT devices arrive instantaneously.

RPA is on the rise in general. According to the third annual Deloitte Global RPA Survey of companies that are implementing RPA now, 78% plan to invest even more by 2021. Respondents also said that RPA "meets and exceeds expectations in terms of compliance, quality, accuracy, productivity and cost reduction."

What areas of supply chain can benefit from RPA?

Order management, predictive maintenance, procurement, contract management, fulfillment and accounting are all areas in a company's supply chain where RPA can deliver significant improvements and benefits.

In order management, there is scope for identifying and correcting common master data management (MDM) errors on orders. Orange has worked on an internal project to use machine learning (ML) to identify incomplete or poor-quality quotes and proactively request clarification. An RPA bot then takes the data and inputs it into the company's accounting software to generate an order, execute payment and send the customer a confirmation email.

This is an example of what Gartner refers to as "hyperautomation." Forrester calls it "digital process automation", and IDC calls it "intelligent process automation." RPA is ideally suited to simple, routine, repetitive and stable tasks that occur in high enough volume to justify the cost of building a bot. However, business processes are not always simple, routine, repetitive and stable, as the pandemic has shown. This is where technologies like IoT sensors, machine learning, conversational intelligence and process mining can complement RPA. For example, using machine learning, an RPA bot can learn the best course of action and initiate a chatbot discussion with a supervisor if clarification is required.

Predictive maintenance in manufacturing is another proven use case enabled by hyperautomation. Production line machinery can be equipped with IoT sensors that gather data and send it to the cloud to be analyzed. Any maintenance required on the machinery is then scheduled by RPA bots, eliminating any delays typically caused by human workers taking more time to evaluate data and schedule maintenance. It can also eliminate errors, improve response times and enhance operational efficiency.

The Orange Business company, The unbelievable Machine Company (*um), worked with a major automotive firm on a successful pilot project to use RPA and AI to automate quality control checks in automotive manufacturing. AI-enabled data analytics tools run automated tests on advanced driving assistance software to check that cars set to cruise control will automatically brake if another car moves into the lane ahead. RPA, in combination with AI, dramatically speeds up the comprehensive test procedures.

RPA can enhance procurement by improving inventory monitoring and matching demand and supply. RPA bots can check on the inventory levels of raw materials, works-in-process and finished goods in a manufacturing company. They can then initiate a purchase order should supply levels dip below specified levels. Similarly, in supplier pricing, AI can be used to predict the future prices of raw commodities based on historical and real-time information on the impact of weather and global demand on the availability of supplies. RPA can extract relevant pricing data and update e-procurement tools to initiate purchases at the optimum times. This use case is already in place at one Orange customer, an energy industry and marine solutions provider purchasing iron ore and metal in Asia Pacific.

Fulfillment also benefits

RPA bots can create lists of ready-to-ship items for logistics service providers and generate email updates on delivery status. They can even capture proof-of-delivery documents from websites to update transportation management systems. This is in addition to generating and sending notifications to customers in the event of any delays, enhancing customer experience.

According to Gartner, by the end of 2022, 85% of enterprises will have some form of RPA implemented in their business. Forrester estimates that the RPA market will exceed a 50% CAGR by 2023, going from roughly $500 million to $2.8 billion. Meanwhile, Coherent Market Insights forecasts that the global hyperautomation market will increase by 19% CAGR between 2019 and 2027, surpassing $23.7 billion by the end of the forecast period.

Any organization that's looking to benefit from digital transformation and perform well in the post-pandemic business world should consider adopting a hyperautomation and RPA strategy.

Find out how you can optimize your global supply chain by using real-time data to create a more agile and responsive ecosystem.

Dheeraj Saxena
Dheeraj Saxena

Dheeraj has over 18 years of digital transformation experience working with large organizations in multiple industries. He has helped organizations build specific digital point solutions utilizing niche technology levers like RPA, AI and analytics. As a Global RPA Practice Head at Orange Business, Dheeraj is responsible for running multiple projects within IT service management, supply chain and logistics domains for Orange customers.