TCS helps an oil major prevent supply chain disruptions through a social media based event detection solution

A large oil and gas company wished to identify and mitigate risks to its supply chain using the non-traditional data source, social media. We implemented a social media based event detection solution that utilized advanced algorithms and Big Data programming techniques to prevent supply chain disruptions.  

The Customer

TCS' client is one of the world's leading international oil and gas companies and undertakes a range of activities, including production, refining, distribution and marketing. The company also engages in power generation with both traditional sources and renewable energy such as biofuels and wind power. It operates in over 75 countries.

Business Scenario

One of the six oil and gas 'supermajors' had operations all over the world and was at risk of supply chain breakdowns due to local events. While some information about such events reached the company instantly, they did not have access to the rest of it.  Much of this information was available on social media channels, but the company did not have systems in place to utilize this unstructured data to its benefit. The company therefore turned to TCS for a social media based event detection solution, given our deep expertise in implementing social media solutions for clients worldwide.


We have extensive expertise in data analytics and information fusion. We used this to provide the oil major with an innovative solution to harnesses data from Twitter. This solution provides information regarding potential disturbances to the business operations through events such as fires, explosions, oil leaks, earthquakes, and refinery turnarounds.

TCS’ Solution

TCS Enterprise Information Fusion (EIF) Framework fuses data from disparate, incongruous sources to allow organizations to handle multidimensional data with ease. The framework incorporates advanced algorithms developed by TCS Innovation Labs in the areas of data harmonization, entity resolutions, and information fusion. In addition, it uses Big Data programming techniques with NoSQL on a robust, open source-based parallel stream processing architecture. Due to the use of machine learning techniques, the performance of the solution improves over time.

The EIF solution was able to process all relevant tweets, filter out spam, and extract and disambiguate useful information such as the location and the timing of disruptive events in the company's supply chain — all in near real time. We linked, matched, cleansed, and transformed the data, fusing and correlating data sets and their hierarchies and linkages to enable semantic analysis.

Key Benefits

With our solution, the company has an effective way to intercept social media and get alerts on potential supply chain disruptions, enabling it to avoid risks and loss of business while providing business continuity. The company can identify and resolve exceptions faster and more effectively, take corrective action quickly, and thus minimize the impact of a disruption in the supply chain.  

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