Data Analytics In Manufacturing

Dr Richard Lobo holds over 20 years of experience running large multi-billion dollar corporations. The bulk of it is within the Tata Group across Tata companies with a wide spectrum, from profitability improvement to delivering Business Excellence to launching businesses and so on. Previously, Dr Lobo was the corporate (global) Head of Strategy for the company; he was formulating strategies for the company in South-East Asia, Australia, Africa, South America and so on. Tata Chemicals' global footprint is spread across almost all continents; it has operations in the US, Kenya, UK, South Africa, Singapore, among others. In an interaction, Dr Richard Lobo shares his insights on how analytics can catapult and transform the manufacturing industry as we know it.

Enlighten us about the role of analytics in the manufacturing industry.

In my view, Data Analytics in many ways is not new to the manufacturing industry. The use of statistical tools to improve quality and productivity has been around for many decades. Today, the paradigm has shifted ­ it is not enough to focus on shop floor productivity and performance. Analytics are leveraged to improve decision making, deliver superior customer experiences, operate world-class manufacturing facilities, gather insights and take action on emissions, improve speed to market, increase service effectiveness, and much more such as ensuring the first line of cyber security in-house. The ability to capture any data, any time, and anywhere has transformed the ability of manufacturers to uncover real time issues, recognize patterns that allow them to enhance processes, boost supply chain efficiency and determine variables that impact production, and hence improve operational excellence and cost competitiveness.

What is the changing scenario on the same?

I believe that from a manufacturing standpoint, the spectrum is quite broad in terms of which companies would have adopted it first. But, if you look at it, during the 80s when we had commodity manufacturing, for instance, steel making, we had to make sure we used various kinds of data gathering mechanisms because the furnace needed to be run at a specific temperature, the production of the quality of steel needed to be monitored, and all other efficiency parameters needed to be of extremely high quality. As a result, deep statistical analysis was required for every effort to increase the availability of insights from data and hence reduction in the decision making time would tell the difference between a best in class performing and an average company. The Digital Transformation - With the advent and ease of access to artificial intelligence, advanced analytics, robotics, IoT-based sensors and devices, Industry 4.0 empowers manufacturers unlike never before. The significant changes induced would be Intelligent or Smart Automation, Democratisation ­ no longer are insights and knowledge the mainstay of domain experts, Hyper Customisation to User Experiences of Products and Services, Ease of accessibility to Analytical tools, many being off the shelf and finally, analytics has become a core function in many organisations, not to mention the multitudes of start-ups in the space.

What are the trends following in the past three to four years?

The world of analytics in manufacturing was largely focused on productivity and performance. But globally, if you look at it today, manufacturing companies, regardless of the sector, predominantly talk about the benefit of data. The trends that they put their bets on are things like predictive analytics, higher ability to gain insights into the supply chain etc. E-commerce companies are also leveraging this to get a better insight into discerning variations in supply chain management, better demand forecast for products, better warehouse management, ultimately aiding their inventory