Transform Your Supply Chain Planning and Marketing Strategies with Google Cloud and SAP Integration

Cloud Marketplace

Revolutionizing Pharma Decision-Making: From Data Overload to Instant Insights

December 1, 2023 | Premangsu Bhattacharya

Blog / Revolutionizing Pharma Decision-Making: From Data Overload to Instant Insights

How much time did you spend on data analysis today? Data analytics professionals in the pharma industry often find themselves bogged down in the nitty-gritty of data management – from cleaning and organizing vast datasets from ERP, CRM, and various other sources, to deriving actionable insights from them. The challenge is not just the volume of data but the complexity and time it takes to turn this data into meaningful decisions using traditional business intelligence tools.

  Time with Traditional BI Tools Time with Planning in a Box

Analyzing clinical trial efficacy data

1 week

3-5 hours

Assessing patient adherence patterns

2-3 days

1-2 hours

Analyzing adverse event reports

1-2 weeks

5-7 hours

Monitoring production quality metrics

3-4 days

2-3 hours

Optimizing manufacturing process efficiencies

1 week

3-4 hours

Forecasting demand for medications

1 week

1-2 hours

Extracting key terms and compliance obligations from complex contracts

1-2 weeks

4-6 hours


What is Planning in a Box?

Planning in a Box is a decision intelligence platform developed by Pluto7, designed to make data analytics simpler and transform the way businesses make decisions. It leverages the power of Generative AI to analyze, interpret, and provide insights from vast arrays of data in an intuitive, user-friendly manner.

Core Features

  • Voice-Enabled Data Interaction : Allows users to access and analyze data using natural language, significantly reducing the complexity and time typically associated with data querying.
  • Generative AI Intelligence : Utilizes cutting-edge AI algorithms to provide predictive analytics, trend analysis, and deep insights from both structured and unstructured data sources.
  • Integration of Diverse Data Sets : Seamlessly integrates various data types, including internal ERP and CRM systems, along with external datasets, offering a comprehensive view for strategic decision-making.
  • Transparent, ‘Glassbox’ Methodology : Ensures clarity and trust in the AI’s decision-making process by using transparent methodologies, allowing users to understand and interpret the AI’s reasoning.
  • Customizable to Industry-Specific Needs : Adaptable to different industries, from pharmaceuticals to manufacturing, ensuring relevance and applicability to unique business challenges.
  • Comprehensive Decision Support : Provides a 360-degree view of business operations, market trends, and customer insights, supporting strategic planning and operational efficiency.

Use Case 1: Evaluating Potential Drug Interactions

Ask Your Data: ‘Cross-Check Drug X with Latest Pharmacological Interactions Database’

Traditionally, evaluating potential drug interactions involves a laborious process of combing through clinical trial data, medical literature, and patient records. With Planning in a Box, professionals can simply voice this query, and the platform does the rest.

  • Data Integration: The platform integrates data from disparate sources such as ERP systems for manufacturing information, CRM systems for patient data, and external medical databases.
  • Advanced Analytics: Utilizing tools like Google’s BigQuery, it analyzes large datasets to identify any historical patterns or reported cases of interactions involving the drug in question.
  • Generative AI-Powered Insights: Vertex AI is employed to interpret complex clinical data and draw connections that might not be immediately apparent, using both structured and unstructured data for a comprehensive analysis.

Outcome: The platform provides a detailed report on potential drug interactions, significantly reducing the time and complexity of the task.

Use Case 2: Monitoring Adverse Event Reports

Ask Your Data: ‘What Are the Recent Trends in Adverse Event Reports for Our Products?’

Monitoring adverse event reports is vital for ongoing drug safety and regulatory compliance. Traditionally, this requires manually sifting through thousands of patient reports and medical records, a time-consuming and error-prone task.

  • Data Processing: Planning in a Box aggregates real-time data from various sources, including direct patient feedback, clinical trial reports, and health databases.
  • Efficient Data Analysis: The platform processes large volumes of data to identify trends, frequency, and severity of adverse events associated with specific drugs.
  • Generative AI-Driven Pattern Recognition: Using Vertex AI, it intelligently identifies patterns and correlations in the data, highlighting potential areas of concern that require further investigation.

Outcome: The system presents a concise, actionable analysis of adverse event trends, enabling quicker response times for potential safety issues.

Use Case 3: Supply Chain Optimization

Ask Your Data: ‘Identify Bottlenecks in Our Global Supply Chain.’ 

Efficient management of the global supply chain is critical for timely drug delivery and cost control in the pharmaceutical industry.

  • Data Integration: The platform integrates data from global shipping logistics, warehouse inventories, and regional demand forecasts.
  • Advanced Analytics & AI Modeling: Utilizes Generative AI to analyze shipping routes, warehouse turnover rates, and demand patterns, identifying inefficiencies and potential bottlenecks.
  • Predictive Scenario Analysis: Employs predictive models to simulate various supply chain scenarios, considering factors like natural disasters, geopolitical events, and market fluctuations.

Outcome: Provides a strategic blueprint for optimizing the supply chain, highlighting specific areas for improvement and suggesting risk mitigation strategies.

Use Case 4: Manufacturing Process Efficiency

Ask Your Data: ‘How Can We Maximize Yield in Drug Production at Barcelona Unit?’

Maximizing production yield while maintaining stringent quality standards is a key goal in pharmaceutical manufacturing.

  • Real-Time Production Monitoring: Planning in a Box integrates real-time data from manufacturing lines, including machine performance, batch yields, and quality control results.
  • Process Optimization Algorithms: Uses machine learning algorithms to analyze production data, identifying patterns and anomalies that indicate inefficiencies or quality issues.
  • Continuous Improvement Recommendations: Based on the analysis, the platform suggests actionable improvements in areas like process adjustments, equipment maintenance, and resource allocation.

Outcome: Delivers a comprehensive analysis of the manufacturing process, pinpointing areas for yield improvement while ensuring quality compliance.

Use Case 5: Supplier and Contract Intelligence

Ask Your Data: ‘Evaluate Our Suppliers’ Compliance with New Industry Regulations.’

Ensuring supplier compliance with evolving regulations is crucial for maintaining product integrity and legal compliance.

  • Data Integration: Aggregates up-to-date regulatory information and cross-references it with supplier contracts and performance records.
  • Supplier Compliance Analysis: Analyzes suppliers’ historical performance, audit results, and compliance track records in the context of current regulations.
  • Contract Review Automation: Utilizes natural language processing to review contracts for clauses potentially impacted by new regulations, highlighting areas requiring attention.

Outcome: Offers a detailed compliance report for each supplier, along with recommendations for contract modifications to ensure regulatory adherence.

Activate Gen AI Insights on Your ERP Data in 4 Weeks 

Think about the hours you spend each week on data analysis and decision-making. Now, imagine cutting that time drastically, freeing you up for what really matters in your role. That’s exactly what we’re offering at Pluto7’s Gen AI Bootcamp.

We get it – massive data projects can be overwhelming, especially if you’re part of a large organization. But here’s the thing: you don’t need to overhaul everything to see real benefits. Our approach is all about tackling your specific business challenges head-on.

In just four weeks, we can help you develop a personalized decision intelligence platform – one that truly understands and adapts to your unique context. 

So, are you ready to save time and elevate your operations? Join us at the Bootcamp and let’s make it happen together.

Register Here


Premangsu B, is a digital marketer with a knack for crafting engaging B2B content. His writings are focused on data analytics, marketing, emerging tech, and cloud computing. Driven by his passion for storytelling, he consistently simplifies complex topics for his readers, creating narratives that resonate with diverse audiences.

Connect with Premangsu on LinkedIn