Our clients are people and organizations with ambitious missions. They want to unleash the power of data for their cause or business. We help them envisage, model and deliver on their mission.

“The price of light is less than the cost of darkness”

Our goal is to set realistic expectations with our clients, and then not to just meet them, but to exceed them — preferably in unexpected and helpful ways. We strive to make data and science simple to understand and easy to act on, and we stand side-by-side with our ambitious clients to make it happen. Here are some recent examples.

Advanced Analytics CoE for a large global eCommerce retailer

Setup of an advanced analytics innovation center for a multinational e-commerce giant

A multinational e-commerce giant with 162 million active buyers globally and over 800 million active listings wanted to create an exclusive global innovation hub driven out of its India Analytics Centre to support various analytics initiatives and create a substantial estimated  impact. The goal was to create a data science team that would be capable of identifying and solving diverse data problems for their different business functions and push the boundaries on what was achievable using data science.

Prescience got involved with the enterprise in the their journey into setting up a center and helped them:

  • Reduce talent acquisition time by recruiting high end talent –  85%  selection rate by client after Prescience selection, 100% after 6 months of CoE start
  • Create capability to solve a diverse set of problems like:
    • Online Deal Effectiveness buyer and seller side deal optimization

    • Business Performance scorecards and analytics

    • Business Risk Management and Fraud detection analytics

    • GMV Prediction Model  across product lines and Geographies

  • Build credibility through successful execution 
  • Create a sustainable model for delivery while creating a culture of innovation

Sales Channel Analytics for a large B2B equipment manufacturer

Sales Channel Analytics for a large B2B equipment manufacturer

A large B2B equipment manufacturing enterprise wanted an in-depth understanding of the performance of its Channel Partners and potentially identify areas  of improvement with respect to the channel partner’s (CP) performance with an objective of improving sales.

Prescience got involved with the enterprise and used data science to: 

  • Provide insights on their Channel Partners’ performance and the factors influencing performance
  • Life cycle analysis of Channel Partners – sustainability of the distribution model
  • Understand the effectiveness of new products launch process in terms of their partners understanding and their support
  • Provide recommendations on additional data to be captured to map the channel effectiveness better
  • Create Channel Partner scorecard and a road-map for getting to the maturity of providing prescriptive actions to improve Channel performance

Data advisory services for a multinational beverages company

Data advisory services for a leading multinational beverages company and the world's largest distiller

The client has established a Data and Analytics function as a core differentiation for the company enabling insights and analytics capabilities to improve innovation, and performance across a wide range of functions and activities globally. The client wanted expertise in data source strategy, curation and quality to ensure that the right data sources, both internal and external – sourced and created – are acquired, structured, integrated and consumed within the enterprise.

Prescience got involved with the enterprise and used our data engineering capabilities to: 

  • Analyse, profile, assess, validate, standardize and enhance the source data with real-time data lookup
  • Provide capabilities to process the raw data into quality checks and standardize the information
  • Streamline Product and Outlet information through our proprietary data governance framework using different data quality dimensions
  • Integrate source systems and streamline data collection process from multiple systems
  • Implement business rules to check and validate data and execute data quality assessment
  • Implement dashboards and measurement metrics
  • Implement cleansing solutions to correct bad data
  • Assist client in designing a process framework