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Lalit Das, Co-founder and CEO, 3SC Analytics talks about the use of SaaS, Data Analytics and AI for business growth in supply chains.
How do you plan to use technologies like SaaS, Data Analytics and AI to achieve future growth?
Lalit Das - SaaS, Data Analytics, and AI have helped revolutionise the supply chain sector completely, by automating and streamlining operations for several industries. By minimising the need for manual human intervention and enabling end-to-end monitoring of logistical and operational processes, we plan to facilitate a more seamless supply chain solution that is as efficient and error-free as it is scalable, customised, and cost-effective.
SaaS, AI and Data Analytics have just breached the surface of Supply Chain and Logistics. The domain is extremely huge and there are many untapped opportunities to explore and create profitable business out of it while doing cutting edge work. With these technologies at the forefront of our product development, backed by our SMEs and an ever growing portfolio of customers and partners, we are poised to help companies
- Grow their revenues
- Cut their costs
- Delight their consumers and employees with operational excellence and efficiency
Our customer's needle moving growth and savings would lead to an ever-increasing growth in our product and business. Using technology enables us to be nimble and experiment-fail-learn fast. We look at the data to derive new product insights in-addition to our own research and customer interactions. AI, Machine Learning and Data Analytics not only helps our customers but also helps us keep optimising our own products, processes and methodologies.
The way we have envisioned our end-to-end Supply Chain Analysis and Intelligence (SCAI) is that it covers all aspects of an IBP(Integrated business planning) on which a customer’s/enterprise’s business runs on. The great thing about our platform is the way different modules talk to each other – automatically and intelligently, reducing the need for human intervention and decision making while allowing to take control wherever required, and fast time to value realisation. AutoML and intelligent workflows are not just buzzwords for us but core pillars of our products.
What are the challenges in supply chain which these techs can solve?
Lalit Das - The most common challenges faced in supply chain include cost optimisation, risk management, warehousing, inventory management, customer and supplier relationship management, market fluctuations, and logistical tracking. With the use of AI, Data Analytics, and SaaS, organisations can achieve streamlined automation and utilise predictive analysis to adapt to changes. In addition, these technologies also make it possible for every business process to be monitored and tracked in real-time, which helps in fast and efficient crisis resolution. As a result, businesses are also able to save on operational expenditure owing to the increased efficiency, and address customer queries and requirements quickly.
How do Data Scientists add value to supply chain logistics?
Lalit Das - Data scientists have today become invaluable for supply chain operations. By leveraging the power of AI, SaaS, and ML, data scientists can forecast the expected demand in various geographical areas. This helps supply chain processes manage the incoming traffic efficiently, especially adapting to variations in different parts of the world, as well as provide estimates for logistics, production, lead time, and more. Data scientists help coordinate several different functions of supply chain such as raw material procurement, inbound and outbound logistics, inventory management, order fulfilment, and more, ensuring each step of the process is driven by data, and customised according to real-time developments specific to the business and domain.
What is your strategy for multiplying future business growth?
Lalit Das - We are always looking out for growth opportunities – be it increasing our product portfolio into existing customers to further optimise their supply chain end to end, new product ideas, alternate verticals or closely aligned segments.
We use a lot of data and research– automated learning from what the data is telling us to primary and secondary research– talking to customers, SMEs, industry stalwarts and analysts like Gartner for example to carve our next path. We keep shifting the goal post to achieve even greater milestones while celebrating the wins and learning from the mistakes.
We also keep a close eye on government regulations and policies and are extremely dedicated towards our environment as well – for example carbon savings and emissions are not just a vanity metrics for us rather as important as our core revenue metrics and we prove the benefits of this to our customers as well. It is a joy that our customers take it as seriously as their top line.