Quantifying Excellence: Role of Data Analytics in CoE

Pallavi Khopkar

Excellence is an ongoing process and not an accident” – A. P. J. Abdul Kalam

So much has been said on excellence and there is a pressing reason for it. Pursuing excellence is more than just a necessity; it’s a commitment—a moral compass guiding us in every endeavor. This is all the more important in organizations striving to make their mark in a competitive world.

Enter Center of Excellence (CoE) – a group focused on uncovering strategies, insights, and innovations that define the blueprint for organizational success.

Center of Excellence is a lot of things! In this blog, we focus on the data-driven observer hat that CoE dons.

CoE as an Observer

CoE is a distinct entity, with unbiased observations and data-driven insights. Unlike other internal teams, a CoE operates as a third-party observer, standing apart from the day-to-day workings of various practices within an organization. This unique positioning allows the CoE to provide a holistic and impartial view of ongoing activities.

At the heart of this unbiased perspective is the CoE’s responsibility for pulling out statistical data and subjecting it to meticulous, objective review. This data-driven approach serves as the cornerstone of the CoE’s function, enabling it to decipher patterns, identify trends, and extract valuable insights. By relying on hard data rather than subjective opinions, the CoE becomes a reliable source of truth, offering an unfiltered lens through which organizational practices can be scrutinized.

One of the inherent beauties of a CoE lies in its ability to act as a catalyst for data-driven course corrections. Armed with a comprehensive understanding of statistical data, the CoE plays a pivotal role in steering the organization toward optimal performance. Whether it’s recognizing areas of inefficiency, pinpointing emerging trends, or uncovering untapped potentials, the CoE’s recommendations are rooted in objective analysis, ensuring that strategic adjustments are made based on concrete evidence.

A Data-Driven Approach for CoE

A data-driven DNA in CoE involves possessing the appropriate toolset, mindset, skillset, and dataset to transform a prominent brand and capitalize on diverse opportunities.

Procter & Gamble utilizes data analytics within its CoE to optimize its global supply chain. By analyzing data related to production, distribution, and demand forecasting, P&G can make data-driven decisions to ensure products are available when and where they are needed, minimizing delays and improving customer satisfaction. (
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NASA’s CoE employs data analytics to optimize mission planning and space exploration.

By analyzing vast amounts of data related to celestial bodies, spacecraft performance, and environmental conditions, NASA can make informed decisions to enhance the success and efficiency of space missions. (Reference Link)


Building a data-driven CoE requires a strategic and deliberate approach. Start by defining clear objectives and outcomes aligning with the organization’s goals. The Key Performance Indicators (KPIs) for your company have to be identified and then the performance against those KPIs needs to be measured. We need to know where we stand to chart our progress to achieving the excellence goal. KPIs must be similar to  SMART (Specific, Measurable, Achievable, Relevant, Time-bound) goals.

A data-driven CoE serves as the nucleus for informed decision-making, innovation, and continuous improvement, propelling the organization toward a future driven by data-driven insights.


Leveraging advanced analytics tools and reporting systems streamlines the monitoring process, facilitating real-time decision-making. Below are some of the KPIs and the tools that can help you measure them.

Fig 1. Examples of CoE Key Performance Indicators and Tools to Track Metrics

The role of Coe is not complete with mere capturing of data. Identification of trends and course corrections if required are the next step. CoE needs to act as a think tank here.

If the SLA compliance needs to be better, what can be done to improve it? If the productivity is low, how can the efficiency of the team be increased? What is the automation that can be introduced to increase productivity? How can cross-collaboration within the teams bring about a change in tapping skills?

Future Trends

Exploring emerging trends in data analytics offers valuable insights into the future trajectory of CoEs. As AI technologies advance, CoEs are likely to integrate machine learning algorithms and AI-driven analytics tools. AI can enhance predictive modeling, automate decision-making processes, and provide deeper insights into complex data sets within a CoE.

Also, in the near future, sustainability metrics and analytics are likely to become more prominent in CoEs as organizations prioritize environmental, social, and governance (ESG) considerations.


Final Thoughts

Center of Excellence may seem to be an additional investment for organizations nevertheless in the big picture it is not only beneficial but an essential investment. The hunger for excellence has to be the foundation of any organization and CoE’s role is to understand and steer the company towards it.


And finally, let’s remember a famous quote, “In God, we trust, for everything else bring data”.

About Authors

Pallavi Khopkar is a seasoned IT professional with over 14 years of experience in multiple domains and technologies. She currently heads the Center of Excellence initiative at Comprinno and is responsible for skill development, fostering collaboration among diverse teams, and ensuring the implementation of best practices to achieve excellence in the organization’s core areas of expertise.

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