Haragopal Mangipudi, alumnus of the PGSEM programme (now offered as PGPEM) Class of 1998–2001, recipient of the 2016 Distinguished Alumnus Award (DAA) and Adjunct Faculty at IIM Bangalore, has been appointed as Chairman of the International Software Product Management Association (ISPMA), effective 11 June 2025.

Beneficiaries of social assistance programs that distribute undifferentiated commodities are typically assigned to a designated agent for collecting their entitlements. This arrangement grants monopoly power to agents, who often face little incentive to follow operational guidelines – especially in the absence of strong monitoring – leading to reduced uptake by beneficiaries. In response, some governments have introduced agent choice, allowing beneficiaries to select from multiple agents. However, the effectiveness of this policy may be constrained by the limited availability of alternative agents, the lack of meaningful competition in undifferentiated commodities, and the risk of collusion among agents.

The paper examines the impact of technology-enabled agent choice on entitlement uptake in India’s large-scale public food distribution program. The program, which accounts for nearly 1% of India’s GDP, provides subsidized food grains to around 160 million households through licensed agents operating Fair Price Shops (FPSs). Despite the significant budget allocation, beneficiaries often struggle to access their entitlements due to poor service, agent monopoly and weak monitoring.

The study focuses on the Indian states of Andhra Pradesh and Telangana, which implemented the agent choice policy at different times. The researchers employ a difference-in-differences framework, comparing areas that implemented the choice policy to those that did not, before and after its rollout. They also leverage variation in agent density to analyze how the intensity of competition affects outcomes.

The findings are striking: introducing agent choice led to a 6.6% increase in the quantity of entitlements collected by beneficiary households. The effect was significantly larger in areas with higher FPS density, highlighting that the presence of alternative agents is critical for the policy to be effective. More interestingly, nearly all of the increased uptake came from new beneficiaries collecting entitlements from their preassigned agent. This indicates that the mere presence of choice acts as a credible threat – agents improved adherence to operational norms, including better shop opening times, to avoid losing beneficiaries to neighbouring agents. The results indicate that even limited forms of choice – where location is flexible, but product and price are fixed – can meaningfully improve outcomes.

The study contributes to the growing literature on service delivery in public welfare programs, showing how simple policy design changes, coupled with digital infrastructure, can greatly enhance program effectiveness. The authors highlight the broader applicability of the model to other large-scale welfare programs, particularly in low- and middle-income countries, where agent monopolies and weak accountability mechanisms are common. The paper has important implications for public policy design, particularly in using technology to foster choice, reduce inefficiencies and empower beneficiaries in accessing critical social services.

Natural disasters create unprecedented challenges that demand immediate, innovative solutions. The study explores how emergency technologies are developed and adopted during disaster response efforts.

When Cyclone Gaja struck Tamil Nadu in November 2018, it caused massive damage to electrical infrastructure, leaving over 2.3 million households without power. The restoration team faced unique challenges: field engineers from different states were unfamiliar with local geography, rural areas had scattered populations living away from main roads, and traditional coordination methods through phone calls and manual map coloring proved inadequate for the scale of the crisis.

Within nine days of the cyclone, the response team developed a GPS-enabled mobile application (GE App) using a modular approach. This ‘invented-on-the-fly’ technology integrated electrical and revenue databases, allowing field engineers to update restoration progress in real-time while enabling monitoring officers to track work visually on maps and prioritize restoration efforts.

The research reveals fascinating insights on how people interpret and adopt emergency technologies. Initially, different groups viewed the same technology differently: monitoring officers saw it as a coordination tool, while field engineers perceived it as a monitoring device to supervise their work. This led to resistance and reluctant adoption.

However, as the crisis evolved, both groups discovered hidden features of the technology that helped solve emerging problems. Field engineers found they could use the app to identify water supply connections and locate nearby distribution transformers efficiently. Monitoring officers discovered they could prioritize restoration based on population density and create visual planning maps.

These discoveries of ‘abstract features’ during active use transformed everyone’s understanding of the technology. What began as a basic data collection tool evolved into an advanced prioritization and planning system. The technology became more valuable as users explored its capabilities while responding to constantly changing emergency situations.

This study offers crucial insights for disaster management and technology implementation. It demonstrates that successful emergency technologies often emerge from urgent need rather than extensive planning. More importantly, it shows that user acceptance and effective utilization depend not just on initial design, but on how people discover and adapt technology features during actual use.

The research suggests that policymakers and technology implementers should focus on creating adaptable systems that allow users to discover new applications during implementation, rather than trying to anticipate all possible uses in advance.

In decision-making under uncertainty, understanding how elements in a system interact is critical. For example, in warehouse location optimization, a business may face decisions about where to place distribution centres to minimize costs like transportation and inventory. This decision involves understanding dependencies between warehouse locations (how one warehouse affects another). Submodular functions, which exhibit diminishing returns as more resources are added, are commonly used to model costs in such problems. The paper explores how different assumptions about dependencies among system elements impact submodular cost functions that depend on these interactions. A compelling analogy to study such multi-element interactions comes from neuroscience, where cortical neurons are known to exhibit pairwise independence in their random firing patterns, while exhibiting higher-order (triplets, quadruplets, and so on) dependencies. The key point is that by assuming that the neurons fire completely independently, unnecessary and unrealistic structure is forced on their joint random behavior, leading to poor approximations of the cost function on an average.

Drawing inspiration from this, the paper analyzes three models:

1. No Dependence Information Model: Assumes no specific knowledge about dependencies among elements. This serves as a baseline to evaluate other models.
2. Complete Independence Model: Assumes all elements are completely independent, which means every subset of the elements with two or more elements (pairs, triplets, quadruplets, and so on) are independent. While simple to formulate, this model can lead to significant inaccuracies. For submodular cost functions, it is known that the inaccuracy can be as large as e/(e−1) (approximately 1.58), when compared to the no-dependence-information model.
3. Pairwise Independence Model: Assumes elements are independent in pairs, while ignoring higher-order interactions. This is a weaker notion of complete independence. This model strikes a balance between realism and simplicity, with the inaccuracy shrinking from e/(e-1) to 4/3, as compared to the no-dependence-information model.

The findings demonstrate that with submodular cost functions:

• The pairwise independence model significantly improves upon the complete independence model in terms of model inaccuracy
• There is a fundamental difference in the joint random behavior of system elements when pairwise independence is assumed as opposed to complete independence

These results potentially indicate that significant cost benefits can be gleaned from assuming pairwise independence or other weaker forms of interaction between system elements.

HealCycle, from the Pre-Incubation Phase of the Women Startup Program, a CSR initiative by Kotak Mahindra Bank and NSRCEL, was selected as one of the ‘Top 10 Most Promising Women Founded Healthtech Startups in India – 2025’ by Asia Business Outlook. HealCycle is a digital health solution and community focused on improving awareness, diagnostics and care for premenstrual mood disorders (PMS, PMDD, PME) through a holistic, science and data-driven approach.

Volar Alta from the Incubation Program for Mobility Startups was selected as one of India’s Top 10 AI Start-ups for the prestigious IndiaAI Startups Global Initiative (ISG 2025) – an international accelerator led by the Ministry of Electronics and Information Technology in collaboration with STATION F and Incubateur HEC Paris. Volar Alta is on a mission to become the preferred one-stop-shop for drone-based inspections, data processing and analysis for the infrastructure space.

Niral Networks, a cutting-edge provider of Private 5G and Edge solutions, from the Sustainable Mobility Incubation Program in partnership with Alstom, won the prestigious Pandit Deendayal Upadhyaya Telecom Excellence Award 2024 for outstanding contribution to telecom innovation. With the flagship product NiralOS™, this start-up of NSRCEL aims to empower enterprises across industries with real-time, secure and scalable connectivity.

The Incubating Incubators Initiative (i-Cube), part of NSRCEL’s Ecosystem Capacity Building, was launched in partnership with SBI Foundation’s Innovators for Bharat program under the LEAP vertical, bringing together diverse stakeholders from India’s incubation ecosystem.

The incubators forming i-Cube’s first cohort includes Mizoram Startup Mission (MSUM), IIT Palakkad Technology IHub Foundation (IPTIF), Indian Institute of Management Tiruchirappalli, IIM Jammu-FEISD and CIED-IUST Foundation (Islamic University of Science & Technology, Pulwama).

The launch featured an engaging panel discussion on, ‘Working with the Central Government’, highlighting the central government’s vision for the way forward for the ecosystem.

The key speakers at the event were Aman Bhaiya, Vice President & Head of Strategy, SBI Foundation, Anand Sri Ganesh, CEO, NSRCEL, Himanshu Joshi, Program Director, NITI Aayog, Rajiv Kumar, Scientist – Technology, Translation and Innovation, Department of Science & Technology (DST), Snehansh Sinha, Assistant Manager, Invest India, and Sanjay Prakash, MD & CEO, SBI Foundation.

NSRCEL conducted a three-day bootcamp for the Healthcare Incubation Program, an initiative run in partnership with DailyRounds, welcoming its second cohort of healthcare innovators. Through this program, NSRCEL and DailyRounds aim to enable founders who are involved with solving complex healthcare challenges through innovation, business acumen and impact-driven thinking.

The event featured a panel discussion on, ‘Leveraging Partnerships for Accelerated Venture Growth’ that explored healthcare start-up journeys and delved deep into how incubators can support early-stage start-ups with partnerships or connects with clinics, hospitals as well as other ecosystem players.

The founders also had the opportunity to showcase their ventures to their peers and mentors, thus gaining feedback and insights.

The key speakers at the event included Ankita Mittal, Founder & CEO, Enhanced Innovations, Suresh Ramu, Co-founder & CEO, Cytecare Hospitals, Dr. Sanjay Sharma, Founder, FootSecure, Co-founder, StrideAide and Yostra Labs and Mentor, NSRCEL, Sridhar Ramanathan, Senior VP, IKP Knowledge Park, Prof. Sachidananda Benegal, former IIM Indore faculty, Prof. Sunil Handa, Founder, Eklavya Education Foundation and visiting faculty, Indian Institute of Management Ahmedabad, Dr. Srivardhini K Jha, Chairperson, NSRCEL and faculty of Entrepreneurship, IIMB, and Anand Sri Ganesh, CEO, NSRCEL.

NSRCEL hosted the Enable & Elevate Tech Bootcamp, where revenue-stage founders from Cohort 5 of the Women Startup Program’s Incubation Phase came together for two immersive days of learning the skills to adopt and integrate technology for smarter, scalable growth.

At the bootcamp, Manoj Jahgirdar, AI Engineer, Ecosystem Engineering Lab, IBM, offered insights on how to unlock the potential of AI & Machine Learning. Vijay Narayanan, Senior Executive Vice President, Kotak Mahindra Bank, explained the power of UI/UX in customer experience. The bootcamp participants broke down the tech landscape as non-tech founders with Saikat Ghosh, Managing Partner, X-Leap, along with Shobhit Mathur, and discovered how to craft a winning digital product strategy with Nitesh Shende, Founder, XRIOne. Prasanna Sundaram, Founder, Augmented Understanding (AU), helped them explore data-driven decision-making, while best-selling author Samhita Arni, author of NYT Bestseller Sita’s Ramayana, The Prince, etc., helped them find their voice and vision in storytelling-led leadership.