2023 was a year full of challenges for supply chain leaders. Recovery from COVID-19, avoiding supply chain disruptions, mitigating geo-political risk and climate changes, and understanding the implications of ESG on the supply chain were some of the headwinds leaders had to navigate. Amidst all these challenges and the corresponding need for a resilient supply chain, all the buzz around GenAI and ChatGPT added to the complexity of the supply chain technology roadmap for vendors and clients. 

As we enter 2024, the supply chain industry continues to grapple with most of these challenges driven by regulatory requirements and the need for supply chain visibility, and this year will see strong demand for sustainability services and technology enabling resilience in the areas of planning, distribution, network optimization, and track and trace.

Here are the top five supply chain trends that may reshape the industry and vendors' offerings in 2024 and beyond:

Conversational & GenAI to improve user experience and drive efficiency

2023 saw vendors proactively investing in GenAI and conversational AI and developing POCs and MVPs, while clients have been looking to embrace these technologies with successful use cases within the supply chain. The existing use of technology within the supply chain revolves around self-service reporting and advanced analytics alongside platform and SaaS solutions coupled with RPA, AI, and ML-based algorithms and proprietary tools from service providers.

Supply chain leaders have been working on the digital transformation of the supply chain and end-to-end technology roadmap. Still, adopting new technology within the supply chain varies significantly depending on the client’s supply chain and technology maturity. The use of technology in areas such as planning, forecasting, advanced analytics, scenario modeling, and network optimization has been one of the most common themes across vendors and clients in the last couple of years. The use of GenAI and conversational AI is still at a very early stage. NelsonHall estimates that ~50% of supply chain-driven organizations are investing in GenAI or looking to invest in 2024 to improve the accuracy of forecasting and demand planning, and virtual assistants to improve user experience, create and process documents across the supply chain, order tracking, invoice management, and risk management.

Digital twin to see increased demand and adoption

A supply chain digital twin uses real-time data and snapshots to create a detailed simulation model and help with scenario planning and analysis. A supply chain digital twin can be an excellent tool for understanding the supply chain’s behavior, predicting bottlenecks and anomalies, and troubleshooting.

With a focus on improving planning, forecasting, and driving user experience, NelsonHall expects two-thirds of large organizations to adopt digital twins in the supply chain within two years. This can be particularly useful in industries with a complex supply chain, such as manufacturing, energy and utilities, oil and gas, consumer goods and durables, defense, etc. Some of the tangible benefits organizations can leverage from the use of digital twins include:

• Long-term supply chain planning and forecasting
• Sensitivity analysis to avoid disruptions
• Inventory optimization
• Improving supply chain resilience and agility.

As organizations embrace digitalization of the supply chain, improving supply chain visibility, real-time tracking and tracing, advanced analytics, and control tower operations, the cost of adopting digital twins and barriers to adopting them will reduce significantly. However, from a vendor perspective, digital twins require a strong hardware capability or partnership and a robust engineering capability. Buyers of supply chain services need to weigh up their vendors’ end-to-end capability adequately. 

Increased demand for touchless supply chain operations

Supply chain disruptions have become more real post-COVID, and the recent events have added to the complexity. Supply chain disruption challenges, along with evolving customer preferences and regulations, require leaders to act swiftly, thus making them shift to a more autonomous and agile supply chain. Various areas within the supply chain where touchless operations have been  adding value are:

• Touchless planning
• Touchless order management
• Touchless analytics and reporting.

Vendors such as Capgemini, Infosys, IBM, and other major players have touchless planning services and claim to deliver tangible benefits such as:

• Up to 80% reduction in operations cost
• Up to 5% increase in revenue base.

In today’s world, when organizations are grappling with an overload of systems, platforms, tools, processes, and technology,  along with complex business organizations, a touchless supply chain can immensely improve user experience. A touchless supply chain will also ensure resources are utilized for more strategic work and free up to 60-70% of their time from mundane and routine work. At the core of touchless supply chain operations is the technology network, including RPAs, machine learning models, and AI, that ensures standard processes can be automated and performed independently with minimal or no human intervention.

With adequate planning, the latest technology, and domain knowledge, vendors have successfully delivered touchless planning and other operations for their clients. NelsonHall expects touchless planning, order management, and analytics/reporting/forecasting to have higher demand in 2024 and widespread adoption to 70-80% in the next 18 months.

Enabling end-to-end supply chain visibility

2023 was a dynamic and challenging year, with the ongoing Russia-Ukraine war, Israel-Hamas war, Panama Canal crisis disrupting trade routes, and Houthi attacks in the Red Sea. Not much has changed as we enter 2024 with most of these crises ongoing. This certainly means a lot of planning, decision-making, increased cost pressure, transportation constraints, and other associated challenges that supply chain managers will have to work with. These geopolitical uncertainties have exponentially increased the complexity for supply chain managers, and the situation warrants quicker and faster decision-making.

In today’s complex global supply chains, decision-making without real-time, end-to-end visibility can be costly and counterproductive for businesses. Lack of visibility of real-time transactions, orders, shipment status, and inventory significantly impacts cost, customer satisfaction, and associated supply chain risk. Vendors have developed an ecosystem of solutions that integrates real-time data across systems, allowing business users to make faster decisions and access actionable insights and decisions. NelsonHall expects the demand for end-to-end supply chain visibility services to stay strong in the coming months and years, driven by the need for transformation, digitalization, and faster decision-making.

Avoiding supply chain disruptions in 2024

Given the current market situation, the possibility of a major supply chain disruption is not too far-fetched. Companies must assess their supply chain resilience and identify and react to gaps. This may be a longer-term plan; however, companies must respond to ever-evolving internal and external factors to address and adapt to business challenges.

This may require a proactive approach and an assessment of the current supply chain landscape. Creating supply chain visibility will be the first step towards understanding the strengths and weaknesses of the existing supply chain. Without adequate data and insights, organizations may be sitting on a ticking time bomb in the current market scenario. Visibility of the supply chain can help leadership with sufficient insights and data points to proactively identify challenges and plan accordingly. While 2024 may be challenging, using technology coupled with adequate monitoring, planning, and partnerships can help organizations avoid potential disruption.

From NelsonHall’s recent discussions with the major service providers, some of the themes for 2024 that emerged were that clients are showing maximum interest in improved forecasting and planning accuracy, leveraging digital tools and technology and AI for transformation, use of GenAI in the supply chain, and sustainability services.

NelsonHall recently had a briefing followed by a demo of Tech Mahindra’s latest offering in field service management: Yantr.ai, an AI and ML-based bolt-on solution that can sit on existing scheduling systems. Yantr.ai provides a control tower solution to field service management, focusing on delivering operational efficiency, enhanced productivity, and improved workflow control by leveraging advanced analytics, artificial intelligence, and machine learning models to enable real-time decision-making. With Yantr.ai at the center of all data points, it can provide end-to-end visibility of granular operations insights.

Launched in 2022, Yantr.ai is an offering under Tech Mahindra’s BPS business with BPaaS and SaaS options. Tech Mahindra has been focused on offering BPS solutions with a combination of platform enablement in niche areas as part of its growth strategy. NelsonHall expects to see further similar offerings from Tech Mahindra in the coming months.

Yantr.ai Overview

Yantr.ai focuses on industries such as telecom, utilities, retail, oil & gas, pharmaceutical, and other similar industries where there is a sizeable workforce in the field, and field service directly impacts the customer experience.

With today’s Amazon and Google-like experience, customer expectations evolve almost daily. However, while many innovation and technology interventions have happened, effective field service management remains a key challenge. Customers expect excellent product quality, effective communication, and seamless support; and field service management is vital to customer satisfaction.

Yantr.ai focuses on transforming field spend, improving CX, and improving field workforce productivity. It incorporates a digital twin and control tower for field services, and focuses on creating end-to-end visibility, data-driven decision-making, and scenario and capacity planning to provide actionable insights. Tech Mahindra claims to deliver benefits such as a 1-3% reduction in operational spend, up to 10% improvement in operational efficiency, and up to 15% improvement in customer experience.

Yantr.ai’s core modules are:

• Capacity planning: forecasts the demand trend by incorporating external factors such as weather and seasonality to empower planners to remain prepared and responsive
• Strategic planning: focuses on monthly and long-term (up to two years) demand optimization, identifying and addressing challenges such as unmet demands, skill shortages, demand reshaping, and permanent relocation
• Operational planning: focuses on demand optimization for the next 30 days, with daily demand, capacity planning, optimizations, and SLA visibility
• Jeopardy planning: offers real-time triage, jeopardy, and unscheduled work order management based on multiple dynamic factors and business rules
• Route planning and optimization: ensures all vehicles/trucks take optimized routes to save time and money, thus improving service efficiency
• Scenario modelling: simulation of distinct scenarios based on various economic and weather factors like wildfires, tornados, floods, etc.

Forecasting is supported by machine learning models covering ARIMA, exponential smoothing, Naïve, and neural network time series forecasting. Based on the data input and forecasting accuracy, Yantr.ai will dynamically select the best model for forecasting and plot different visualizations for actual demand, forecast demand, and variance between actual and forecast demand.

Client Cases

One example of the use of Yantr.ai for field service is for a major Australian telecom company where the benefits delivered by Tech Mahindra are:

• $15m to $20m savings to field operations spend
• ~4 % SLA improvement
• ~10 % to 15 % work being saved from external suppliers
• Truck roll reduced by 10%
• 40% FTE reduction.

The client’s business challenges were managing extensive field service operations, optimizing inefficient technician assignments, reducing response time, and improving customer satisfaction. The client also struggled with no real-time insights or dynamic scheduling capabilities. Tech Mahindra deployed Yantr.ai to optimize technician assignments, provide real-time job insights, and improve resource utilization. Dynamic scheduling capabilities were used to help the client adapt more quickly to unforeseen challenges.

Beyond field service, Yantr.ai has also been used by a major Australian media company to address route planning. In this case, the company’s challenges were improving customer satisfaction by meeting SLAs for newspaper/magazine distribution to retailers and end customers, and optimizing routing to help in vendor negotiation and cost savings. Tech Mahindra implemented Yantr.ai to build an optimal routing model to reduce cost and improve delivery SLAs. Key benefits delivered to the client were:

• 15%+ higher accuracy in route planning
• Improved SLAs and customer experience, along with reduced travel cost
• Ability to do scenario modeling/analysis, including demand changes
• Profitability analysis of routes and optimization of remote delivery points
• “Right location of depot” suggestions.

Yantr.ai also offers data ingestion through standard connectors/APIs and a custom data ingestion pipeline for ingesting from different formats, including CSV flat files. The tool has an orchestration system to manage complex workflows, which can be modified based on the client systems and processes’ requirements or updated as the project progresses and requirements evolve.

Tech Mahindra claims it is the first company to build a planning engine and control tower for enterprises in field services. The tool offers intelligent DSR (decision support recommendation), on-the-day risk mitigation, routing optimization, and other demand and capacity planning capabilities.

Implementation, Pricing & Key Benefits

Tech Mahindra offers modular functionality deployment options for Yantr.ai. The pricing mechanism is a one-time implementation cost and ongoing license costs based on the number of workflows, infrastructure deployed, and consulting support. In the BPaaS service, Tech Mahindra also provides managed end-to-end field service management support.

The typical time required to implement Yantr.ai is estimated to be 6 to 9 months for a mid-size organization.

Tech Mahindra categorizes the key benefits clients can get by deploying Yantr.ai with the 3Ps (people, planet, and profits):

• “People” benefits include an increase in workforce productivity, improvement in CSAT and NPS, and an increase in technician reskilling
• “Planet” benefits include reduced fuel consumption and carbon footprint and improved decision-making and situation planning during natural calamities or other emergencies.
• “Profits” include savings in operational spend, reduced field technician expenses, truck rolls, and workflow management-related expenses.

Tech Mahindra continues to invest in Yantr.ai, focusing on partnerships with ServiceNow, IFS, isMobile, and Celonis.

NelsonHall expects Tech Mahindra to leverage the technology and architecture behind Yantr.ai to increasingly deliver solutions beyond field services in areas such as logistics, fleet management, and demand planning. Tech Mahindra will likely focus on the telecom, utilities, and oil & gas sectors.