India's largest platform and marketplace for GCCs & AI

Sign in

India's largest platform and marketplace for GCCs & AI

3AI Digital Library

Global Captive Centers – The true enablers of Collaboration (Part-2)

3AI November 28, 2023

Featured Article:

Author: Vinodh Ramachandran, Neiman Marcus Group

In my previous article, I had spoken about some challenges due to a siloed working model within data & analytics teams in large retailers and how setting up a Data & Analytics CoE within the GCC can be a good solution.

Lets look at a few ways to structure the CoE within the GCC.

  1. Federated model (Data teams as verticals)
  2. Integrated model (Data teams as horizontals)
  3. Pod model/Pizza teams (Product based teams)

Federated model

In this model, the end-to-end capabilities within Data & Analytics is assembled aligning to the business teams. They will typically roll up to the GCC CoE leader who will have visibility to the project pipeline and will also have access to business leadership and the Chief Data & analytics officer (who they may report to). An illustration is show below:

The federated model has a few advantages:

  1. Business Alignment and working on priorities that drive business impact
  2. Availability of dedicated bandwidth for businesses to move at their own pace
  3. A sense of ownership and belonging within the data & analytics teams
  4. Visibility to project pipeline and ability to bring teams together for cross functional initiatives driven by the CoE leader role
  5. Talent migration across teams

Integrated Model

In this model, the Business Analytics teams are set up to be aligned to the different business units. However, the data teams – Data engineering, BI, etc. are set up as horizontals and are not aligned to business teams. They are capabilities that are available to the CoE to leverage. This model also rolls up to the CoE leader who will have access to both the business leadership and the technology group (CDAO, CIO, etc.)

The integrated model offers fewer advantages than the federated model:

  1. Business Alignment and ability to work on prioritized projects based on impact to the business
  2. Visibility to project pipeline and ability to bring teams together for cross functional initiatives driven by the CoE leader role
  3. Opportunity to work on projects across multiple business teams. This increases the exposure and motivation of the data teams.

The integrated model however runs into the prioritization challenge with lack of dedicated bandwidth available for business analytics teams.  Talent migration becomes a challenge and the CoE leader will have to create a career path that provides progressive increase in scope and impact to each individual.

Pod model/ Pizza teams

This is a popular model in e-commerce companies that are product based. For e.g. Search, Personalization, Last mile delivery, Customer returns, etc. In this model the teams are organized like the federated model, except they are aligned to product/ sub product teams.

A few advantages of this model over the federated model include:

  1. Razor sharp focus on business priorities (in this case product priorities)
  2. Drives depth in context and solutions
  3. Agile approach and hence focus is on speed to market. As an analyst, you will get to see the impact of your work very quickly
  4. Provides opportunities to closely collaborate with other teams within the product on a daily basis

These are some CoE models that I have seen through my experience. The role of the CoE leader, if defined right makes the biggest difference to the success of these models. Organizations must hence spend a lot of time to define this role right and hire the right individual to derive the maximum advantage.

My personal preference is the federated model as it checks a lot of boxes – business alignment, career pathing, motivated talent, and dedicated bandwidth. What is yours? Are there other models that you have come across? Please share your comments.

Disclaimer – All views expressed here are strictly personal and do not represent any company or team or individual

Title picture: freepik.com

    3AI Trending Articles

  • Combining the power of Generative & Predictive AI

    Featured Article: Author: Shuvajit Basu GenAI has taken the world by storm. I certainly don’t have to outline the numerous possibilities it brings to bear. Both GenAI and Predictive AI have their share of strengths andbopportunities. However, if we can combine the power of these Generative models with Predictive AI/ML models, we might be able […]

  • AI readiness – CEO’s most strategic agenda

    For the larger mass of professionals, the words “artificial intelligence,” or AI, often conjure up images of robots, the sorts of robots that might someday take their jobs. But at the enterprise level, AI means something different. It has enormous power and potential: it can disrupt, innovate, enhance, and in many cases totally transform a business. […]

  • Improving Customer Experience – AI/ML Driven Issue Resolution

    Author: Ashish Vashishta, VP – Technology, eClerx Customers across industries typically face issues with their purchased products/services. A troubleshooting system which can use latest AIML technologies to resolve these issues faster and more effectively can lead to a much better customer experience. As an example, a customer may have purchased a bundled product offering – […]

  • Mitigating Bias in AI Systems

    Featured Article: Author: Kritika Saraswat & Sreedhar Sambamoorthi, AB InBev Twenty Years ago, science fiction stories were ripe with futuristic scenarios with cars driving themselves, computer writing stories and human-like holograms responding to any and every query that we had. These scenarios were considered a figment of good writer’s imagination and books and movies on […]