Vijeta Soni, Co-Founder & CEO, Sciative Solutions

A Woman in Tech leader and a dynamic powerhouse, Ms. Vijeta Soni is the Co-Founder & CEO of Sciative Solutions. She is an alumnus of the prestigious IIM Bangalore and the University of Houston, Texas, USA. Vijeta is a proud member of Goldman Sachs 10K Women Entrepreneurs and an exceptional leader with over 16 years of experience in digital transformation, technology adoption, and client relations across retail, ecommerce, manufacturing, and education sectors. She has played a pivotal role in driving some of the large-scale projects in India and has worked with industry giants like Overstock.com (USA), Reliance Industries Ltd., Jio Institute etc. Vijeta along with Dr. Anshu Jalora founded Sciative in 2015 after realizing the need for AI-driven Dynamic Pricing to empower businesses to have the right price for every product, every market, every customer, every single transaction. The company through its wide range of award-winning SaaS products caters to a wide array of industries such as Retail, Travel, Entertainment, Cinemas, Hospitality, and more. She enjoys spending her leisure time hiking and trekking.

 

The revenue generated by the Indian Railways did not reach its maximum potential in the second consecutive year 2020-21 due to lower passenger ticket sales and higher expenditure towards maintaining Covid-19 safety guidelines. Also, Indian Railways incurred losses estimated to be about Rs 36.87 crore due to the agitations by farmers and other organizations during this year including other social issues. According to the Comptroller and Auditor General of India’s report in 2021, the railways incurred a loss of Rs 26,388 crore in the last one year, though the Ministry of Railways had claimed a net surplus of Rs 1,589 crore. 

Moreover, the railways’ overall fund balance, which was Rs 10,806.68 crore in 2015-16, turned into a negative balance of Rs 25,730.65 crore in 2019-20. In addition to the losses, capital expenditure of railways increased by 11% even as revenue expenditure decreased by 7.3% during 2019-20, while expenditure increased from Rs 3,20,110.17 crore in 2018-19 to Rs 3,21,169.55 crore in 2019-20.

However, there’s a foolproof solution for Indian Railways to reduce losses and maintain a dynamic structure of pricing right. The passenger mobility with cutting-edge automation and intelligent pricing technologies can seamlessly bridge the gap between unreserved seats in trains and audiences looking for budget-friendly prices. Indian Railways is entirely run by the Government and its pre-determined approach. But since it adds a great value to the Indian economy and lightens the weight of travel expenditure of the citizens, it requires a definite strategy that can help it boost up and hit its utmost potential even in times of discomfort like Covid-19. 

How Indian Railways can leverage AI powered dynamic pricing? 

Optimize Capacity Utilization – Current flat pricing structures results in thousands of people remaining without a seat on days when they ‘have’ to travel – like festivals, weekends, etc. On such days the seats get filled months in advance. Getting a tatkal booking is not only difficult, but a matter of chance. On the other hand, the same trains could be running with less than 70% capacities on normal days. AI powered dynamic pricing can help curb this problem by smoothly redistributing demands to low demand days with attractive pricing.

Affordability for Customers to Upgrade – Unlike conventional rule-based pricing which only goes directionally upwards, the AI powered dynamic pricing goes both ways. During low demand days customers will be able to purchase higher class seats at affordable prices thus escalating the overall travel experience for the customer. 

Self-Finance Investments in Customer Experience – Indian Railways is a service to the citizens of the country, therefore along with value it’s important to focus on services. One of the outcomes of AI dynamic pricing will be increase in revenues which can then be invested back in improving hygiene, safety, and connectivity. 

Optimal Allocation of Seats Quota for each Station – Real time demand prediction based on the most advanced deep learning technologies can help Indian Railways to simplify revenue management across a network that is vast and complex and is bound to fall under the category of manual errors.

Open-up Opportunities for Multi-Modal Transport – Enabling a dynamic pricing structure into existing ERP or CRM used by Indian Railways can help the department utilize a state-of-the-art technology that not only makes the entire process faster but as well as convenient. 

It is imperative for the Indian Railways to adopt and integrate intelligent pricing techniques since its network is vast and extremely crucial for both the Indian economy as well as the citizens. Moreover, the dynamic pricing structures can help align attracting the right audience and providing them with favorable prices. With such an ecosystem, the Indian Railways can flourish in terms of capacity utilization and saving resources with the support of a pricing domain expertise backed with high end technologies like Machine Learning and Artificial Intelligence. 

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