Organisations often block their own path towards scaling by delaying innovations purely out of their loyalty to their core businesses. Unfortunately, fixed organisational structures and legacy operating models result in frailty, disabling the sight of potential market changes. Enterprises hesitate to build products or services with new technology as they are unsure of whether the growth rates would satisfy their shareholders.

Today, to compet in a VUCA environment, businesses and their change agents must consider relooking and reconsidering how they engage and conduct business with their customers and leverage innovative technologies to enhance or introduce products/services to the market.

With rapidly changing consumer buying patterns and preferences, enterprises are increasingly focusing on digitization to evolve their business models, they are being mindful of the efficiency of business operating units, which enables them to pinpoint areas that need additional focus or restructuring quickly. Some of the possible initiatives organisations can opt for are:

• Growth hacking:Organizations need to be agile and iterative in their approach to keep up with the changes in the industry. Having a growth mindset can enable management, embrace challenges, show resilience while working through obstacles, and bounce back from impediments sooner, leading to overall higher achievement. Organizations backed by a growthhacking mindset will be ableto foster innovation and generate higher financial returns.
• Retooling organization:Companies should ‘avoid putting all eggs” in one basket regarding technology infrastructure. The focus should be on adopting technology like building a Lego structure, where individual components are replaced if the scalability and validity for the current and future needs of the business aren’t met.
•  Adopting new age innovation rather reinventing: Applications of AI is evolving within the industry at a fast paced, which enables organizations to evaluate quickly, adapt, pilot and scale within the organizations. Reinventing AI would mean wastage of resources of time, instead organization precious resources can be spent on identifying the right opportunity to evaluate and scale the benefits of AI.The global COVID-19 pandemic has crushed standards and redefined how business is conducted, affecting most enterprises in some way or another. At the same time, enterprises were already leveraging data science and AI in the past few years.  A significantly greater number of organizations are now looking for ways to harness them to reinvent themselves. Key-focused areas remain in strategy building, decision-making and governance setup, business planning and budgeting, funding decision making, managing performance and company culture, risk management, and more.For businesses, resiliency will become even more significant than efficiency as they move forward and data science will help companies maintain. For instance, retail stores and restaurants that were more dependent on brick-and-mortar sales before the pandemic had to make drastic changes to survive and sustain. While some were forced to shut shop, the rest kept steering ahead with new business models to adapt and thrive. Data science helped companies stabilise their organisations, build new processes, establish new communication channels and workflow, adapt to the remote working environment, recognise (and adapt to) changing consumer patterns and identify the emerging trends by using AI and machine learning.Traditionally, legacy companies used to focus only on their core business. With the new wave of transformation and new opportunity post the pandemic, these prominentestablished players are reinventing themselves and creating businesses in new areas with a very different mindset and culture than their traditional organizations.The new digital era demands asignificant change in traditional thinking and focusing on the practical approach of collaboration, competition, and innovationthat can combine data science, AI,and business acumen to conceive, build and bring new digital products to market at scale.

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For companies operating in the transportation marketplace, speed and accuracy are paramount. Carriers and shippers alike are continually on the lookout for ways to be faster, less expensive and more efficient — to the point where standard delivery seems to mirror expedited shipping.

As the industry moves faster and faster, the documents and data generated grow at an exponential rate. Managing these documents often requires manual processes that are time-consuming and can bring any efforts to maximize efficiency to a standstill. The answer isn’t to work harder but to work smarter. To avoid wasting time and resources on document processing, it is crucial for every transportation company to update document and data management strategies. 

The transportation industry is in the midst of an artificial intelligence (AI) renaissance. Everything from workflow solutions to fleet management and financial decisions can be streamlined using an AI-based automated content management system (CMS).

A CMS is a software application that is used to manage a company’s digital content. Transportation companies rely on a CMS to upload, process and distribute the countless documents and data involved in the shipping process. These software applications must be able to interpret data quickly without compromising accuracy.

“Transportation organizations need to start applying more technology to manage and react to data,” said Larry Kerr, president and CEO of EBE Technologies. “In many cases, having the data and not reacting is worse than not having the data at all.”

EBE Technologies provides automated workflow solutions for the transportation and logistics industry. The East Moline, Illinois-based company’s SHIPS enterprise business process management solution is utilized by more than 600 transportation companies.

It goes without saying that everyone in transportation wants to achieve efficiency, reduce unnecessary costs and improve billing accuracy, but not all believe they have the power to upgrade. The truth, however, is that it’s never been easier for transportation companies to utilize an AI-powered CMS.

Convincing companies to adopt AI workflow solutions is not difficult, according to Kerr. 

“Recently, many of our clients have been affected by rising insurance costs,” Kerr said. “Rates have been softer, which means the additional revenue to cover such costs must come from improvements in operating efficiencies.”

However, simply using any CMS isn’t sufficient to manage workflows effectively. Some transportation companies are unaware of the additional operating costs associated with the use of their current systems. Many such systems lack the ability to provide interoperability among companies’ critical systems. In fact, market research firm IDC estimates that companies lose 20-30% in revenue every year due to inefficiencies related to process and content management.

The use of a CMS does save employees a tremendous amount of time from the often tedious process of manually routing documents and entering data. However, these systems may still require each transaction to be manually processed, ensuring it’s routed safely to the proper department or critical system. According to an EBE Technologies white paper, a CMS with the power of AI workflows allows transportation providers to work by exception. Through this process, only out-of-standard transactions require staff intervention. AI allows providers to staff for exception levels, not 100% of the transaction levels.   

The AI-based work-by-exception process is further enhanced by optical character recognition (OCR) technology that possesses the ability to collect data by “reading” documents. Recognized OCR technology scans and automatically indexes a wide range of documents, including bills of lading, proof-of-delivery documents and invoices. A truly effective CMS, however, is incomplete without unstructured OCR processing, which converts unstructured text and optical marks into data and provides the catalyst for interoperability among critical systems, according to the white paper. 

Utilizing both AI and OCR technology allows employees to focus their attention on completing out-of-standard transactions and determining the root cause for the failure. Once determined, the AI engine can be configured to manage such exceptions going forward. As a result, overhead costs and time to completion are reduced while data accuracy is greatly improved. 

A CMS powered by AI workflows has a dramatic impact throughout the enterprise. As an example, it is not unheard of for companies relying on a traditional CMS to take upward of a week to gather and process the information needed to submit an invoice. The use of an AI-powered CMS with automated workflows has transportation providers benchmarking their invoice processing time to less than half an hour from the time of delivery, according to EBE.  

“With AI managing the required documents and how they should be delivered, the possibility of  human error is eliminated, which improves your billing functions,” Kerr said. “When you provide the right documents to your customer quickly, hopefully you’ll get your payment faster. With many shippers enforcing carrier scorecards regarding document and data availability, AI is now a requirement to meet shippers’ expectations without additional labor.”  

According to EBE, utilizing a CMS powered by AI has advantages beyond improved data accuracy and working by exception to lower costs within a transportation organization. In the accounting department, carriers no longer find themselves paying duplicate invoices, net 10 terms are realized and fees for late payments are eliminated. In recruiting, AI allows carriers to respond to and onboard qualified candidates more quickly. In the safety department, data from disparate systems can be analyzed to identify at-risk driver behavior and provide corrective action automatically. In addition, the expiration of Department of Transportation documents and endorsements can be managed through automated processes. These are just a few examples of how an AI-powered CMS eliminates revenue leaks in operations and mitigates potential incidents and fines within the safety department. 

Many transportation companies have embraced AI as a functional requirement, but not everyone is on board. As Kerr explained, the use of AI in the back office, as well as interoperability between systems, has only become viable in the last couple of years.

According to Kerr, in the past many systems lacked the ability to integrate with one another, resulting in redundant labor tasks. He noted that those barriers have now been broken, thanks to standard API interfaces among databases allowing for interoperability using AI. The API standardization greatly lowered the cost and risk associated with implementing an AI-based CMS.

EBE possessed the foresight to understand the critical relationship between the data within disparate systems. Through the open architecture of EBE solutions, the company was able to develop a robust AI-powered CMS solution, building upon its prior releases. This solution helps carriers achieve work-by-exception staffing levels, improve data integrity among systems and deliver a superior customer experience.

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Securities and Exchange Board of India (SEBI) Chairman Ajay Tyagi on January 23 said the regulator will adopt artificial intelligence (AI), machine learning (ML), big data analytics and natural language processing tools to monitor and analyse spot market manipulation, PTI reported.

“We want to acquire technology and unstructure data analysis because the structured data analysis is not helping much, manipulators use all sort of things,” he noted.

“Catching malpractices in the market using the standard tools that analyse only structured data of price and volume is increasingly getting difficult,” Tyagi said. As per the plan, a “data lake” project will be created to augment analytical capabilities.

The SEBI chief added that AI and ML tools could bring about a paradigm shift in the securities market landscape. He further said that blockchain could also be used to clear and settle activities.

SEBI is also acquiring capabilities to monitor and analyse social media posts to keep a tab on possible market manipulations, Tyagi said. He added that there have been cases where social media posts have helped in acting against manipulative activities.

A tender has also been floated for acquiring the technology. Even in the absence of such a focused tool, Tyagi said SEBI already has capabilities, wherein it screens social media posts after corporate announcements and the changes in price and volumes of a scrip.

He was speaking at the National Institute of Securities Markets at Patalganga.

AI/ML tools are being increasingly deployed in fund management, trading, supervision and surveillance functions in the capital markets, he added.

Further, Tyagi said there is a need for the technologists to invest time in research in these tools for applications in the capital markets.

Systemic risks are becoming important objectives for financial regulators, Tyagi said, explaining that this requires identification and monitoring of important financial institutions, leverage, inter-connectedness, risk concentrations and market sentiment.

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