Harnessing AI for Pharma R&D

The Challenge The client needed an automated system to extract English and Japanese publications across diverse databases using the same search strategies applied in English queries to identify KOLs without expert intervention. We leveraged machine learning and natural language processing to build a unified search system, optimizing cross-language database searches. The solution seamlessly integrated with Harnessing AI for Pharma R&D


Improving Reverse Logistic Repairs

The Challenge A Fortune 500 consumer electronics company faced challenges with its in-warranty repairs forecast process, leading to frequent fluctuations and inaccuracies. The existing heuristic-driven approach required extensive manual intervention, leading to over-predictions and impacting cash flow adversely. The Mu Sigma Approach Our approach aimed to enhance forecast accuracy by accounting for variations, leading to Improving Reverse Logistic Repairs


Behavioral Segmentation to Boost ROI

The Problem and Need for a New Approach Our client, the world’s most diversified casino-entertainment provider, had previously relied heavily on a methodology that predicted their customer’s average daily worth (ADW) based only on previous customer trip spends. This resulted in the inefficient allocation of their annual marketing budget, leading to reduced returns on their Behavioral Segmentation to Boost ROI


Strategic Revenue Management Framework

The Challenge A leading food sector Consumer Packaged Goods (CPG) giant grappled with understanding the key drivers behind its sales performance, hindering effective revenue management. They lacked reliable data to make informed decisions about trade promotions, including optimal expenditure allocation, effective strategies, and profitable investments. Mu Sigma’s Approach Leveraging proprietary tools muUniverse and muPDNA (Problem Strategic Revenue Management Framework


A Financial Planning Transformation

Cumbersome Financial Planning The client revamped its financial planning during the 2008 recession, focusing on detail and operational precision. However, as their business expanded, this process became cumbersome, inflexible, and too reliant on traditional methods. They envisioned a transformation: shortening their extensive quarter-long financial planning process to a more frequent and flexible monthly cycle. Achieving A Financial Planning Transformation


Demand Forecasting to Optimize Profitability

As a food manufacturer, strategic pricing is crucial for sustaining demand, whether during promotions or at regular times. Previously, the client relied on third-party vendors for pricing analysis, which proved costly. Recognizing the need for a more cost-effective and scalable solution, the client established an in-house team capable of conducting accurate and scalable pricing analysis. Demand Forecasting to Optimize Profitability

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