What lies beyond the Pandemic – A look at supply chain resilience

The world came to a standstill as the global pandemic led to the closing down of international borders. The unprecedented event brought up various challenges, from adjusting to the Covid-friendly norms or even ensuring the health and safety of the workforce while ensuring business continuity. Enterprises along with their organizational functions were widely affected, impacting the supply chain visibility and supply chain network.

The lack of resilience in the supply chain of all industrial units thus became more prominent. However, this could be considered a boon, only if dealt with correctly. But how?

Organizations could leverage this scope to target the operational deficits and fulfill the missing pieces through a thorough readjustment of the supply chain. To put it more simply, the firms, now more than ever, have the perfect opportunity to implement contingency methods and create a sturdier supply chain, mitigating any recurrent challenges. To garner a better understanding of this topic, let’s get into details.

The Expose

The global pandemic gave us the time and opportunity to introspect the traditional ways of the supply chain that failed us. Leveraging innovative methods has become the need of the hour. Enterprises that leveraged emerging technologies earlier on not just survived the pandemic but also thrived during the unprecedented times. However, for some enterprises, the pandemic exposed some grave shortcomings in supply chain management globally. Here are some of the limitations of the traditional ways that led to enterprises falling beyond recuperation.

With various restrictions exercised and the movement of people coming to a standstill, the industries suffered from the storage of resources. The entire flow of products thus was sent into a whirlwind, right from manufacturing units to the sales units.

The demand graph saw a swift hike with stock buying and panic all around, while, the supply graph took a deep dive downwards due to inadequate resources. Although some giant moguls upped their product availability during these times, most others faced a hard time keeping up.

The pandemic highlighted the shortage in supply chain visibility in the entire supply chain network. Due to the swift rise or fall in customer demands, inventory management saw several problems arising. This exposed the issue of deliberately creating a shortage of products to accelerate demand by many firms.

The lockdowns restricted the movement of goods and people, thus hindering the flow of the organizational operations. The lack of conjuring resources from the local sources was thus entirely exposed as it impacted the entire supply chain network.

How can we overcome these issues?

Here are some steps we could take to help with a more resilient global supply chain, capable of withstanding even an adverse situation such as the ongoing global pandemic.

Increased diversity

When the global factory, China came under the radar and was shut out by the rest of the world, a need for diversification of the supply units emerged. This will result in lesser dependability on them mitigating a grave problem.

Decentralization of manufacturing units

The firms have already adopted this trend alongside deploying the boons of technology, like automation and well-assessed production in smaller batches to cut costs on wastage.

Enhanced supply chain visibility

The only way to mitigate the challenge of minimum transparency along the supply chain is to increase visibility. Transparency has evolved as one of the top trends over the last decade, and the pandemic proved it to be the need of the hour. A transparent supply chain network becomes more resilient by identifying in advance any disruptions and strategically planning the contingency moves.

Localizing supply sources

This will encourage the local economy and acquire resources efficiently. In terms of future resilience thus, the supply chain networks can efficiently work with the local sources without disrupting the operational flow.

Going digital

In this age of rapid digital transformation, going digital is more of an immediate necessity than an option for all industries and processes. The supply chain is no exception to this change. Digitization of the supply chain networks will increase supply chain visibility. At the same time, automation will streamline the workflow making it more effective and flexible. It can thus be carried on even from the safety of one’s house and helps develop a resilient supply chain network.

How can EdgeVerve’s TradeEdge help?

TradeEdge offers a comprehensive solution that enables enterprises across industries to empower their end-to-end supply chain capabilities. TradeEdge aims to create a connected and cognitive supply chain experience, thereby ensuring supply chain resilience and visibility readjusted to meet the demands and scope of the post-COVID world.

Over the last decade, TradeEdge has assisted 25+ global enterprises and Fortune 500 companies encompassing CPG, F&B, pharmaceuticals, apparel, beauty, and technology industries in their journey towards a cognitive supply chain experience funded upon connectedness. To know more, click here.


While time always heals everything, it is better to stay ahead of the times to survive and stay resilient during difficult times. All said and done, with the new normal gradually setting in, the enterprises have identified and adopted various new and innovative methods, with a noticeable increase in the supply chain visibility. However, further developments remain extensive as more and more enterprises have started implementing these solutions. Thus, it is safe to conclude that the future of the supply chain network looks quite promising beyond the Pandemic.

When AI and humans complement each other and produce the best business outcome

Perhaps one of the greatest draws towards the Artificial Intelligence and automation of the workplace is that software will never feel overwhelmed with enormous amounts of data, feel fatigued, or bored. By leveraging technology, process mining, contracts analysis; and data crunching that once needed an army of employees, days, months, perhaps years to complete can now be done in a fraction of the time. EdgeVerve’s XtractEdge Platform not only analyzes data, but it also curates the data analyzed to make it useful to your business, this consumable information will inform key decisions and ease the day-to-day workings of your business.

This enhancement of human experience leaves one question: where do we humans fit into all this? While AI technology can manage a vast amount of data, filter through and carefully analyze it, it is not immune to errors. In short, to obtain 100% accuracy a human must be present to supervise the operations of the software for the foreseeable future. Human participation in the workforce is a necessity as human input will deconstruct unstructured data.

Sentiment Analysis

Consider, for example, the field of politics. Dr Batista Navarro fed the speeches given by members of parliament into an AI-trained model. There was an enormous number of data to analyze in many ways, AI was essential. However, AI technology missed the often-ambiguous language used by politicians and could not understand the underlying political subtext. To navigate this minefield of words cloaked in party loyalty, vagueness, inconsistent voting patterns, and varying tonal differences, the algorithm needs human guidance.

An AI cannot fully interpret human communication the way humans do and cultural and linguistic conventions that vary from region and nationality only add extra layers of complexity. Furthermore, while it can say, identify the voting patterns of an MP, the AI may not draw meaning from change in the tone of voice, sarcasm or even pick up meaning from things like vocal affectations, it might be instinctual for us humans but nearly impossible for an AI. In a process as delicate as this, human intervention should not be an afterthought. They must be present from the start, analyzing the findings produced by the algorithm at several points, to catch errors, and to determine the purpose of the data, especially when it is quantitative.

What the Future Holds

The goal of introducing an AI-powered model in an environment is optimization. The jobs allocated to humans will change but never vanish entirely. AI in various environments seeks to offer consistency where humans simply can’t.

The onset of Fatigue: Humans can isolate key points of information for say, ten documents, perhaps another ten, however they would have reached their limit by the 32nd document brought in for analysis, and the whole process is prone to human error. XtractEdge Platform on the other hand understands text blocks, pieces together context and classifies a document with corresponding invoices, sales orders, and purchases. Furthermore, if the Doc AI cannot recognize a name, it will perform and examine a breadth of documents and data (full field value pairing) to obtain appropriate context and establish meaning, diminishing errors with no fatigue.

Climbing Cost: Paying already exhausted employees overtime to make sense of thousands of documents is a budgetary nightmare. Using AI to clear unstructured data for a fraction of the hours initially spent, is an efficient use of time and money. Every year, doctors, and the larger healthcare industry, lose 50% of their valuable time and growth to document processing. With XtractEdge Platform in place, they can have patient records at their fingertips and resources can be directed towards efforts to improve the patient experience.

Is Artificial Intelligence here to replace us?

The question has haunted job seekers, employers, scientists, and even the occasional science fiction author. A simple response to this preoccupation is that AI is not intended to ‘replace’ human intelligence. They provide much-needed scalability and productivity in industries that are overrun by data and require assistance. Tedious and time-consuming jobs will be given to the AI while tasks that require emotional intelligence will be assigned to humans.

Take for example the disastrous mistake made by large tech companies like Facebook and YouTube. their content moderation software has been on the receiving end of a lot of criticism because it filtered out videos that discussed controversial content, misidentified and demonetised videos entirely, threatening the livelihoods of many large and small creators, disrupted the media diet of many consumers just because the AI could not distinguish between upsetting content and culturally relevant post and videos.

This is also relevant in contracts analysis. While AI can help categorize, extract and analyze relevant data, it is the human quality of ‘emotional understanding and decision making’ that are rewarded and amplified as AI does the drier and more mundane tasks.

Dynamic socio-political nuances are simply beyond the comprehension of an algorithm, as it cannot be treated as just numbers and words. Humans who have a pulse on societal happenings prevent this. If the idea of a digital revolution in your work appeals to you, read more to learn about how EdgeVerve can optimize your business environment and bring you closer to your goals.

How can XtractEdge Contract Analysis Help Banking & Financial Services Enterprises?

Contracts analysis forms an essential part of operations across banking & financial services companies. These contracts vary extensively in types and include master agreements, general services agreements, purchase agreements, equipment maintenance agreements, and trade agreements, among many others. These different types of contracts are used by the procurement systems of the banking & financial services companies to deliver data & take care of their invoicing needs regarding the financial plans for billing purposes.

However, the banking & financial services companies are often unable to access detailed insights from these global contracts and, as a result, face numerous operational difficulties. Naturally, in such a scenario, they are prone to grave risk factors that reduce operational efficiency. Moreover, when done manually, the procurement process can be time-consuming and can restrict the quality & speed of results to a great level. Manual efforts simultaneously run the risk of increasing the number of errors in the procurement contracts.

Challenges in procurement across banking & financial services enterprises

Organizations irrespective of their size use procurement systems for global contracts. For instance, even though all the contractual information from thousands of global contracts is stored in the records and used for real-time invoicing & billing, large-scale organizations with massive international contracts often face severe problems capturing informative insights.

As a result, these organizations resort to manual efforts and spend hours after hours searching, extracting, and comparing the contracts before manually analyzing individual elements of each contract. Unfortunately, even using an automatic tool like the Optical Character Recognition (OCR) software can lead to significant quality issues with the data.Not only that, several other factors like the multi-party agreements, global delivery models, pricing constructs, etc., simultaneously increase the intricacy of analysis, thus making the procurement process increasingly tough, error-prone, time-consuming, inefficient as well as inconvenient.

This complexity in analyzing contracts is frequently accompanied by the complexity of the hierarchy of the arrangements. These are inconsistent in their innate nature. As a result, a solution that can effectively assess the imminent risks and mitigate them becomes imperative to ensure effective & streamlined procurement and contract analysis across banking & financial services organizations.

This is where XtractEdge Contract Analysis can help.

XtractEdge is an enterprise-grade AI platform designed to simplify the adoption of Artificial Intelligence across businesses & IT units. XtractEdge is well equipped with next-generation capabilities that support the end-to-end enterprise AI journey. This ranges from data management, model development to digitization, and to operationalizing models.

XtractEdge Contract Analysis leveraging XtractEdge is specifically tailored to meet the requirements of the procurement systems of enterprises, be it big or small. The software caters to the unique procurement needs of each organization. It enables businesses across various industries to derive valuable insights from their contracts and legal documents by leveraging advanced Machine Learning practices.

How can XtractEdge Contract Analysis help in procurement across banking & financial services enterprises?

XtractEdge Contract Analysis leverages a range of cutting-edge, next-generation technologies, including Natural Language Processing, Computer Vision, and AI document processing, to accelerate and accentuate the procurement process across companies in the banking & financial services sector. Banking & financial organizations can effortlessly identify and extract critical clauses and terms from thousands of global contracts. At the same time, using XtractEdge Contract Analysis further allows them to compare and redline the contracts more thoroughly, reduce the negotiation cycles by maximizing reviews and contract analysis, and minimize any scope of revenue leakage.

Wait! there’s more to it. The implementation of XtractEdge Contract Analysis, more significantly, equips the procurement team of the company to initiate a more detailed search. In other words, the procurement team now can search for a contract, based on some defined parameters, namely, a combination of Keywords (indicating content), Intents (implying clauses), Entities, and Metadata. If any mistake in a particular contract is noticed later, the software reports it back to the operations resources, which is then captured by the knowledge base.

XtractEdge Contract Analysis helps the procurement teams across banking & financial organizations by replacing the manual tasks and automating the processing loads of contracts. It thus reduces a great amount of time, increases visibility to a significant level, enhances productivity unlike before, successfully mitigates operational risks, and effortlessly ensures contractual compliance in the procurement contracts management.

However, the role of XtractEdge Contract Analysis does not end here.

Benefits of XtractEdge Contract Analysis in banking & financial services enterprises

For example, leveraging our AI-powered contract analysis solution has been proven to:


The challenges faced by procurement in contracts analysis are undeniably extensive and demand special attention. Amidst these challenges, however, XtractEdge has come up with a powerful solution. XtractEdge Contract Analysis presents a unique approach to streamline and optimize the procurement process and enhance contract analysis capabilities across banking & financial services enterprises as an integrated AI-powered solution.

XtractEdge empowers the procurement teams by equipping them with AI/ML capabilities, NLP, and Computer Vision. It makescontracts analysis becomes faster, less risky, and more efficient than ever before.

Read how XtractEdge Contract Analysis helped a leading US Banking and Financial services company increase 10X productivity of their procurement team.

Supercharging Spot Bid Freight with Robotic Process Automation

Shippers and carriers alike have driven massive savings from optimizing transportation, primarily through the deployment of technology such as Transportation Management Systems (TMS). TMS systems are a mature set of applications with impressive track records of automating and optimizing transportation functions. This reduces freight costs in the supply chain for both shippers and carriers and increases the overall effectiveness of the supply chain.

The list of TMS value drivers is long and impressive:

More than anything else, advanced transportation technology has enabled collaboration and coordination of multiple entities who work in a shared, networked transportation ecosystem that includes not only shippers and carriers, but also freight brokers, logistics service providers, hubs, and ports.

However, despite significant advancements in transportation technology and widespread deployment, carriers and shipper still employ large teams of people to manage freight. Many functions still (and probably always will) require constant human interaction, especially those that deal with exceptions and require human decision-making as to how certain shipment or freight situations should be handled. Many transportation functions still rely on managers or analysts to monitor portals and work cohesively with technology to keep operations running, especially functions requiring data entry, approvals, reporting, or exception management.

Robotic Process Automation for Transportation

These human-driven transportation functions have created opportunities for layering in addition automation technology such as Robotic Process Automation (RPA) to further reduce the need for manual work. Transportation and Logistics are now mirroring what other business organizations are doing by deploying digital robots to handle TMS functions currently performed by humans.

Some examples of TMS functions that can be driven by RPA include:

In general, the marriage between RPA and TMS can be cohesive and beneficial if done in a technologically and functional, smart, and responsible way, enabling another level of automation within the transportation domain.

Dealing with the Growing Spot Market

Carriers, freight brokers, and logistics service providers have a unique and increasingly opportunistic challenge related to TMS technology and the enhancements offered by RPA. Most carriers have a split between their contracted freight and spot bid freight (contract freight is more regular shipments done at pre-agreed terms and pricing; spot bid freight is bid in real-time). While this varies widely by market, location, and mode, many analysts put the typical split between contracted and spot freight at 85/15.

However, the COVID environment of the last 18 months has affected all things supply chain, including the amount of volume and capacity on various lanes. This has also affected the split between contract and spot freight for many carriers, mostly by skewing the spot freight to as much as 75/25.

While not the primary source of revenue, spot freight is a critical piece of business for carriers. But it is also the least optimized in terms of process, efficiency, and technology. Bidding on spot freight requires carriers to deploy teams to monitor freight bidding portals from shippers, monitor what loads are available to bid, and make decisions on what to bid and for how much. Because not all shippers use the same TMS, carriers often have to perform functions across multiple portals and make time-critical decisions in direct competition with other carriers. Conversion rates for many carriers in the spot bid process are very low, often less than 10%.

The good news is that the transportation function is an area that has seen some of the most significant improvements in terms of automation, reduced human effort, and revenue conversion using RPA technology.

Spot Bidding using RPA

Any use case that involves the consolidation of data from multiple portals, rapid analysis of information, and automating data entry tends to be a good use case for RPA. Automating the spot bid process for carriers falls directly into this category.

Carriers today are finding that they can use RPA bots to monitor the spot bid portals from multiple TMS systems from multiple shippers. These bots can also aggregate spot bid opportunities that come in from other sources, like email or EDI. Once aggregated, carriers have the option to present the aggregated list to transportation analysts or use business rules to allow bots to automatically bid on the best loads that meet certain criteria.

The results can be dramatic once carriers use RPA to consolidate spot bid opportunities and automate the bidding process. Not only are the manual human hours eliminated, but carriers immediately start bidding on more loads and more of the right loads at better prices. This more centralized and holistic approach increases their spot bid conversion rate and the revenue and margins of this business segment.

Learn more about AssistEdge Spot Bid, our best-in-class automation solution for all bidding activities.

This assisted automation use case at carriers is growing in popularity as RPA bots are expected to ‘auto bid’ on $100Ms of freight in the coming year. This will drive more revenue and margin for carriers, and better match shipper freight with transportation providers, improving the overall network.

Five Ways AI can Optimize your Workplace

The penetration of new technology in the workplace is impossible to ignore. Algorithms are working in tandem with humans and pushing enterprises to achieve new and more innovative business goals. The struggle to comprehend a deluge of data to uncover underlying business value continues to increase. This puts additional pressure on the workforce to spend considerable time and effort processing diverse, domain-specific, and complex documents manually and finding precise answers to business questions from across enterprise documents.

The good news is that the grind of repetitive and tedious work is decreasing as Artificial Intelligence (AI) is aiding in tasks like Intelligent Document Processing, hiring new talent, transcribing zoom calls, and everything in between. However, a one size fits all approach to document extraction, processing, and comprehension does not apply in most enterprise scenarios.

With a voluminous amount of data entering our systems every day, enterprises are struggling to comprehend a deluge of data, and users are not equipped to process diverse and complex documents. The workforce is spending more time processing documents manually, which is hampering strategic decision-making. To successfully unlock business value from enterprise documents regardless of their complexity or domain specificity, a purpose-built document extraction, processing, and comprehension platform like XtractEdge Platform is required.

How XtractEdge Platform will work for you:

We live in a time where so much information is digitized. Thanks to AI, be it text-heavy pieces like books and journal articles, a treat for the eyes like plush magazine articles, brochures, and infographics, form-based documents like invoices, forms, and receipts, and images like photographs are all carefully dissected for analysis. A variety of texts offer a great deal of data that deal with a different topics and circumstances, the XtractEdge Platform can help unlock Insights by examining the content for context.

This is achieved by preparing the XtractEdge Platform to interpret a variety of components like images, logos, special symbols, charts, numbers, words, positioning, orientation, colors, white space, and much more. All components that make up that piece of communication are scrutinized, something OCR or Optical Character Recognition (a precursor to this technology) was simply unable to do. This wholistic process of exhaustive research carried out by the AI is akin to how the human brain processes and interprets information; the speed varies, but the accuracy of the information that is extracted is uncompromisingly accurate.

Here are five ways XtractEdge Platform optimizes multiple processes in data management.

Artificial Intelligence is in a near-constant state of progress. With rapid advancements being recorded every single day, we can say for sure that with AI, the workplace will be productive, faster, and more creative. With its advanced AI capabilities that use an ensemble of various Machine Learning and Deep Learning-based techniques, flexible data management, and analytics pipelines, XtractEdge Platform structures the world’s complex multi-document data, makes it consumption ready to unlock the latent business value.

Download the e-book on XtractEdge Platform and unlock enterprise document intelligence with AI.