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Reimagining Supply Chain Efficiency with Intelligent Automation

September 8, 2020 - Romil Bhalla Senior Analyst - Product Management, AssistEdge, EdgeVerve

Mr. Peter Crawley has been closely monitoring the developments globally since COVID-19 was declared a pandemic. Being the Chief Supply Chain Officer in a large retail enterprise with operations across the globe, Peter’s team has been working 24×7 to ensure seamless operations. Just like Peter’s organization, most enterprises today are facing challenges to stay afloat. In these testing times, the supply chain is being looked at to keep the operations running across industries like retail and manufacturing. These industries are completely dependent on the supply chain to keep their upstream and downstream operations afloat. To cater to the dynamic needs of these industries, the supply chain organizations should focus on combining agility, flexibility, and cost-efficiency with rapid product and service development¹.

A survey conducted by Deloitte² confirms the intent of enterprises in this direction. When Deloitte asked the respondents, “What functions are you prioritizing for future digital investment?” the supply chain emerged as the top overall answer, with 62 percent respondents choosing it over planning, product design, and smart factories.

Intelligent Automation is one such pillar helping the supply chain industry and functions achieve this by expanding the automation horizon. The focus on high accuracy levels and efficiency in operations make intelligent automation the key to this transformational change. Forrester has also called out the importance of Intelligent Automation (RPA+AI) as an important driving force to own the future of work³. In this article, we are looking at some of the key Intelligent Automation (IA) technologies that are reshaping the supply chain industry and its operations. We will also look at how the adoption of these IA technologies is redefining the role of knowledge workers across the Supply Chain industry.

Cognitive Search

With a large pool of customers, vendors, and other stakeholders, an ocean of data gets generated across the supply chain organization. The majority volume of this data is unstructured and is being generated by and spread across disparate systems. Combination of AI technologies such as Natural Language Understanding and Machine Learning (ML) help in organizing this data. Cognitive search is making the knowledge workers more agile by helping them make sense of the data and draw meaningful insights within much shorter time frames.
Machine Learning-based Decision Support

Supply Chain planning takes multiple aspects of demand and supply into account. By making the entire planning process much more efficient, Machine Learning based decision-making has proven to be a boon for the Supply Chain organizations. Easy to build and use, ML decision models make the entire process more agile. ML-based decision support is also beneficial for Logistics route optimization, which is essential especially for a large enterprise. Supplier selection and warehouse planning are other areas within the supply chain where optimal decision-making benefits the knowledge workers to a large extent.
ML Text Analytics

Supply Chain organizations deal with numerous documents daily. These range from simple structured documents to complex unstructured documents. Some examples of these documents are supplier invoices, purchase orders, contracts, credit memos, shipping notices, tax documents, customs documents, credit notes, and others. Machine learning-based Text Analytics helps with the extraction and understanding of unstructured content across these documents. Natural Language Processing (NLP) based text mining can be used to extract relevant information, keywords, and topics based on a set of rules. The knowledge workers overburdened with these documents can now manage the workload with this technology at hand. Lesser time is spent on identifying the relevant information more accurately than before. In addition to text analytics, Computer Vision is also revolutionizing the warehouse management process. Automated barcode reading is just a small application of CV, which reduces the manual errors and accelerates the inventory tracking across warehouses.
Predictive Analytics

Another pillar within Intelligent Automation, that has revolutionized the supply chain planning and operations, is predictive analytics. Knowledge workers across these functions have a better and more accurate means to forecast demand. They are well equipped with the right data to plan efficiently for shipments and order fulfillment. Analytics is also deployed to predict the expected traffic on shipping routes, guiding them on alternate routes or plan accordingly for expected delays, if any.
Conversational Intelligence

Be it answering the customers’ queries on the status of shipment or suppliers’ query on the payment against invoices, a combination of text analytics and predictive analytics manages these intelligently over chat sessions or automated replies over mails. The front office knowledge workers are also benefitted by these technologies. These intelligent chatbots provide accurate and prompt responses to the supplier and customer queries, enhancing the overall customer experience (CX).
Process / Task Automation

The deterministic automation powered by the basic RPA capabilities is freeing up the bandwidth of the knowledge workers by taking over the mundane tasks. Swivel chair-based data entry, posting entries to a general ledger, creating compliance reports are just a few examples where the knowledge workers have the time to engage in activities that result in improved customer experience and higher revenue generation.

The above examples give a glimpse of the endless capabilities for Supply Chain by deploying the right Intelligent Automation technologies across appropriate use cases. Let us look at the impact on Supply Chain with the advent of Intelligent Automation.

For a shipping company, operating across 139 countries on multiple systems and interfaces, EdgeVerve deployed over 400 AssistEdge RPA bots to offer price quotes and booking management within minutes as opposed to the previous 24-hour lead time.

Another US-Based company ensured business continuity in the wake of COVID-19 pandemic using AssistEdge RPA’s Intelligent Automation capabilities⁴. This transportation and logistics company operating in 30 countries, wanted to ensure that payment operations are on track, and payments processing can be done remotely and in a more agile manner. The solution helped them better manage the orders into Ready-to-bill (RTB) and ready-to-pay (RTP) status, resulting in a reduced Annual Daily Sales Outstanding of USD 2.5 M.

There are numerous other examples where supply chain organizations are already reaping the benefits of deploying Intelligent Automation capabilities across their processes. You can also take up similar initiatives by creating a core team that focuses on identifying the right use cases and assisted by a Process Discovery tool. They should look at the profiles of different knowledge workers, identify the areas which are best suited for specific IA technologies, and reimagine the supply chain.

References:

¹ Automation Singularity – https://www.edgeverve.com/assistedge/automation-singularity-expanding-horizons/

² Deloitte Industry 4.0 Investment Survey 2018 – https://www2.deloitte.com/us/en/insights/focus/industry-4-0/challenges-on-path-to-digital-transformation/supply-chain-paradox.html

³ Forrester Report – Embrace Six Success Drivers to Own The Future Of Work by Craig Le Clair

⁴ Stronger Together: AssistEdge RPA automated billing process for a global logistics provider during COVID-19 crisis – https://www.edgeverve.com/assistedge/case-studies/covid-19/automates-billing-process-global-covid-19-crisis/