The Council of EU Chambers of Commerce in India in association with Tiger Analytics has organized a webinar on “Implementation of AI & Advanced Analytics for Consumer Goods and Manufacturing Industry” on 15th January 2021.

Dr Joseph Shields, Co- Chairman of the ICT Committee welcomed speakers Mr. Durjoy Patranabish, Head of Global Business Tiger Analytics and Mr. Sriram Krishnamurthy, Vice-President, Data Science, Tiger Analytics and all present.

Mr. Kaushik highlighted that EU Chambers is one of the foremost trade promotion organizations in India established to promote, foster and extend commercial and economic relations between India and the EU. The Chamber’s primary promoters consist of European Bi National Chambers and European Bi National Business committees and its Chief Patron is the Ambassador and the Head of Delegation of the European Union to India.

The membership of the Chamber includes representation from several industry sectors- such as banking & financial, infrastructure, automobiles, Pharmaceuticals, electrical and engineering, shipping and logistics, consultancy, IT, Energy, Agricultural products etc.

EU Chambers also has functional advisory and sectoral committees across various sectors of the industries by very senior people from industry. These committees in the Chamber can support SMEs in various European countries seeking to establish strong business relationship with India whether it is trade partnership, technology exchange, joint venture, Green field investment. We shall be delighted to offer and extend our Chamber services to them.

ICT is one of the committees see a strong partnership between trade, technology exchange and investment perspective. During pandemic period, we tried our best to keep our members abreast with latest trends, happenings from business and technology perspective and this webinar is one such efforts.

We all know the importance of AI and Analytics in various sectors and specifically when we look at consumer goods and manufacturing Industry. I am sure today all of us will have an exciting time to hear Mr. Durjoy and Mr. Sriram on their perspective on how AI and Analytics are disrupting various industries and specifically for Consumer Goods and Manufacturing Industry. So Mr. Durjoy and Mr. Sriram welcome to the panel, we would like to hear from you. All the very best.

Excerpts from the speech of Mr. Durjoy Patranabish and Mr. Sriram Krishnamurthy

They discussed how is Advanced Analytics moving, what has been its journey so far, where are the areas where it is becoming more prominent and what are different types of solutions that are being used by different organizations. But more importantly what are key drivers of AI, Advanced Analytics and elaborated with two cases in consumer goods, manufacturing industry.

Basically, AI can be broken into 2 pieces, one is general intelligence and other is narrow intelligence. General intelligence is when you try to replicate what human being does under different circumstances, constraints. A complete system that is indistinguishable from a human. Many believe building a robust AGI is the ultimate goal. However, not much progress is made till date.

Narrow intelligence is replicating human behavior in specific areas, situations and that’s where we have made great progress, whether it is marketing and sales, taking manufacturing decisions, taking supply chain decisions and that’s where narrow intelligence comes into play. There has been progress that has happened in use of products or use of custom solutions that organizations have built for themselves now in product space there are multiple players similarly on services side there are multiple players.

According to a study by McKinsey Global Institute, AI is estimated to create an additional 13 trillion US dollars of value annually by the year 2030 and according to Gartner 15% of all customer interactions will be handled by AI Chatbots by 2021, that tells the speed at which AI is becoming more real. The data or information we capture as human beings is covered from various sources. A lot of utilization of image data, visual data, video data, audio data that is coming into play, IoT, sensor data is becoming huge. Use of Machine learning, deep learning has become huge in current world.  The whole AI ecosystem is becoming more mature. The more important thing is how you connect AI solution to end user that is important or else the whole anticipation of AI will not be anticipated.

The overall affordability of doing analytics with tools, products with variety of service providers and make it democratized in some sense that’s probably driving AI and advanced analytics. Today 31% of organizations are able to adapt valuable insights of existing data, they are trying to question the fact do we need to invest more where we are under using information using BI and other traditional analytics solution. Another thing is data has mushroomed over a period of time as we have built new business models, new applications, new infrastructure so therefore data are not joined up together.

Finally, in terms with talent pool that’s obviously in short supply again AI, data science is something new, people are trying to get trained themselves but also the fact that quality in the market may not be appropriate to build a robust AI solution.

Obviously, AI and advanced analytics is that people are moving from piloting to operationalizing and generating business out of it. There’s definitely movement is happening in terms of expanding the scope of AI and advanced analytics beyond structured data so a lot of effort is going on around use of non-structured data in the form of audio or image or video form. Obviously, cloud is gaining popularity.

There is a lot of focus on real time decisioning so therefore continuous analytics is becoming new norm. Focus on data security is rising, each country through its laws is becoming more protective of consumer data so therefore it is becoming in some sense segregated. More and more data scientists are doing ML ops and ML engineering and data engineers have also started doing ML ops and ML engineering. So, there is cohesion between both data and advanced analytics world.

Emerging verticals traditionally such as BFSI, telecom, retail which were early adapters of AI and advanced analytics but now manufacturing, healthcare becoming strong advocates of AI & Advanced analytics. Companies are trying to acquire capabilities of AI & advanced analytics, they are trying to do either organically or inorganically.

Coming to consumer and manufacturing industry, these are sample set of solutions are built at Tiger for some of the clients whether in the R&D side, or on finance and operations side and manufacturing side we have done tons of work on predictive maintenance, anomaly detection such as environment, health and compliance, safety, IOT analytics, supply chain side. Tiger Analytics have done forecasting of out of stock, on shelf availability, supply carrier performance analytics. On the HR side,  they worked primarily around team optimization, team scheduling.

Similarly, on sales and marketing analytics from marketing stand point Tiger Analytics have done lot of work in emerging trend and business as they want to know what are the new product ideas and what are new ideas that should be focused on, prioritizing on R&D efforts. Similarly, consumer promo optimization and sales and strategic management, trade promotion optimization, pricing analytics and direct to ecommerce or direct to consumer channel, how do you manage your consumers directly so these are the broad landscape of what is being done on consumer industry and manufacturing industry.

Mr. Mr. Sriram Krishnamurthy deliberated on how Tiger Analytics have contributed in consumer and manufacturing industry to showcase what can be done with the breadth of AI.

Tiger analytics has created a methodology to map ASIN (Amazon Standard Identification Number), PPG (Promoted Product Group ) and successfully mapped ASINs corresponding to 91% sales. It has built machine learning models for 200+ PPGs across all categories corresponding to 80% sales with a weighted MAPE of 8%, developed a tool for future scenario planning to estimate lift vs cannibalization and identified sample pricing scenarios for enhanced true lift over base sales for one category which lead to gross lift of $3.2 Million (1.5% of base sales)

Manufacturing industry case study of India Steel Manufacturing MNC whereby Digital Twin Reliability Model Improves Predictive Maintenance and impact delivered was a saving of USD1.7 Million (INR 12.75Cr) in terms of cost of maintenance saved and additional production time gained. Current Equipment Anomaly Detection Process of the company used largely, operator driven manual inspection for anomaly detection with a few models for a few sensors and the company engaged with Tiger Analytics to improve equipment maintenance by building a digital twin model that is analyst independent and automatically selects the best model for equipment anomaly detection.

Tiger Analytics did predictive analytics solution for different equipment’s in the Blast Furnace area and analysis approach included Initiation & Data Discovery which involves extraction of raw data from equipment and data pre-processing and cleanup. Forecasting input gaps in time series data resulting from machine being idle/tested, tested arima, random forest, arimax, smoothing based on mape selected random forest.

Output was real-time dashboard that is updated to reflect system health, anomalous behavior, 72-hr forecast of reliability and sensor-based root cause analysis. Business outcome of the analysis done by tiger analytics is that their solution has so far resulted in a saving of USD 1.7 Million (INR12.75Cr) in terms of cost of maintenance saved and additional production time gained, scalable models are being deployed in blast furnaces, crushers, fans, transformers, and similar equipment across the company, transparent approach; no dependency on external IPs and solutions such as GE Predix and on-demand future upgrade possible due to open design concepts.

The webinar was concluded by a public Q and A session and a vote of thanks by Dr. Renu Shome, Director of EU Chambers of Commerce in India.