Analytics Centre of Excellence Creation

CoE - Vehicle to Unlock the Hidden Potential of Data

No doubt Big Data, AI, and ML have the potential to enhance business opportunities, but the improvement is not automatic. To unlock its full potential, you need a holistic approach – a business analytics strategy that integrates people, processes, data, and technology.

Creating a center of excellence (CoE) is an effective way to synchronize business goals and achieve success on a broader scale. By partnering with Quadratyx, you can synchronize business goals with resources so that everyone is informed and working towards real and measurable ROI across the enterprise.

Major roadblocks when implementing CoE

People

(Upskill & retain talent)

Process

(Scalable delivery model)

Technology

(Connected infrastructure)

Business Model

(Collaboration)

Partnerships

(Vendors/suppliers)

Financial Performance

(Monitoring & reporting)

Data Governance & Management

(Support)

Leadership Strategy

(Business roadmap)

So, how will Quadratyx help?

Build Talent

Comprehensive training and workshops on data science related concepts and technologies.
Evangelize best practices in building effective teams to execute data science solutions.
Identify talent and train them on advanced analytics, big data, cognitive process automation, deep learning etc.
Mentor and actively guide business teams so that they holistically
understand the business problem and measure the success of its solution.

Strategic Planning

Charter roadmaps for short, medium, and long-term data science success.
Define and identify a list of analytic problems that can be solved along with their respective business impact.
Prioritize these analytics problems.
Recommend processes to be followed while building analytics solutions.
Identify relevant data sources and recognize key data points that are not currently being stored.
Recommend relevant external data sources.

Next-gen decision making

Advise on the solution architecture, tools, data management, security, and governance.
Devise strategies for optimal storage (Big data lakes, data warehouses, Cloud etc.)
Best suited methodologies and algorithms to solve the give business problem.
Solution to be scalable and adaptable to the latest technological developments.

How does it work?

Implementing a CoE model is not easy, it requires change within the organization and needs to consider other business aspects. At Quadratyx, our consultants take incremental approach – first comprehend your business and secondly, evaluate your IT infrastructure, people skills, business goals, operational model, and analyze risk areas. As next step, you’ll receive detailed recommendations and a road map, specific to your business needs.

Benefits of A CoE Model

Irrespective of the size of the organizations, more and more businesses are implementing the center of excellence model. Top advantages of CoE model include:

Achieve active synergies - best practices and learnings.
Make team collaboration more effective by trained manpower.
Centralized structure that supports multiple departments.
Control costs and lead operational efficiency
Enable people to be more creative and focus their time on high priority tasks.
Better allocation of resources and efficient team management.
Provides better insights into your business, resulting in better end-user services.

AI IN ACTION

OUR CUSTOMER SUCCESS STORIES

Knowledge Support: ACoE Implementation

A leading commercial Public Sector bank with presence in 25 countries across the world, with over 5500+ branches in India and 100+ offices overseas, wanted to setup an Analytics Center of Excellence (ACoE). That would serves as a central source of trust and collects, stores, transforms and cleanses data from disparate sources into actionable insights. But due to limited knowledge and lack of in-house expertise in setting up ACoE, Bank partnered with Quadratyx to guide and assist.

Quadratyx defined a 3-year vision and roadmap in terms of

ACoE Architecture requirement based on mapping client businesses, gap analysis and readiness assessmen.
Generated RFP’s followed by vendor validation & selection.
Identified client specific potential use-cases for Big data solution.
Proactively advised Bank on potential pitfalls.
Evaluated work done by selected vendor and ensure compliance.

Optimize and Build in-house capabilities

Technical Validation - Hardware , Software and solution components

Specific Data Science use cases