How is data driving a new order for global capability centers (GCCs)?

It is a foregone conclusion that data in the right context at the right time is critical to the success of any large enterprise. Today, every large organization is making critical decisions regarding their future, based on data that is available in many different forms. Data engineering and data science are some of the most sought-after competencies today and every GCC is building a center of expertise around data. In the 2021 EY GCC survey, 76% of the respondents mentioned data as one of their critical areas for growth. 

Today we are seeing GCC’s invest significantly across the areas of intelligent data machine learning, image and video analytics and the use of chat-based robots that use textual data as a source of conversation. There are several examples of how data sciences, when used intelligently, can help in reducing or eliminating manual intervention with an increase in accuracy and efficiency. A retail GCC is doing just that by using product data (image, description, quantity, brand, category etc.) to group products correctly. Once grouped correctly, it helps the pricing teams to correctly price items that fall under the same grouping. This information is then visualized on a portal for the teams to make decisions accurately and in real time. In the past, such a process was error prone, manual, and cumbersome. Another GCC is using financial data with proprietary algorithms to provide higher visibility on cash-flow. The platform is used today to monitor cash-flow parameters such as account receivables, delayed payments, credit risk and bad debt and help make timely predictions on variation of cash and bad debt. Yet another GCC is using data science solutions to speed up their manufacturing process in factories. They have created search engines to search for historical problem statements and associated solutions. This helps employees on the production floor get quick assistance when issues occur rather than wait and lose precious minutes on a high throughput manufacturing line.

Data is only useful when it is clean, and another GCC is helping do just that in an automated manner. They have built data cleansing templates and algorithms which provide options to clean data according to rules that can be highly customized in over 20 different languages. This is further extended through machine learning to train the model to do this by itself with minimal monitoring. Another GCC is using data to generate a twelve-month rolling forecast of palm fruit yield. This helps estate managers at plantations plan operations accurately and identify gaps in yield taking. Numerous other examples exist today where GCCs are at the forefront of using data sciences to solve issues such as health and safety compliance, improve maintenance of production machines, reduce defects on a production line, improve logistics through accurate prediction modelling and speedier dispute resolution.

With the push to go digital, persistent worker shortages and a volatile supply chain, every single enterprise is increasing investment on automation and the intelligent use of data. This coupled with the challenges on data strategy, architecture, scalability, and quality management, requires GCCs to look for innovative options from their vendor partner ecosystem. EY helps clients leverage its data factory services to address challenges/requirements across strategy and architecture design, data engineering, data management, data science and Ops.

This article was first published on ET CIO.

(Ajay Kamat, EY India Technology Consulting Partner also contributed to this article.)