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Introducing Capgemini’s Intelligent Analytics for pharma solution

Capgemini
2022-05-09

I’ve enjoyed watching a number of companies in the life-sciences sector grow over the past several years. But this growth has often been rapid, making it challenging for companies to ensure their business processes can keep up with their needs.

For example, smaller pharmaceutical companies frequently rely on manual, labor-intensive processes to track stock levels and reorder materials. As these companies mature and grow, they often discover they need sophisticated solutions to manage a more complex supply chain. The basic spreadsheet that worked just fine when the firm launched is no longer sufficient.

In addition, they’re missing the advantages of automation and the valuable insights that any thriving company requires to effectively manage suppliers, customers, ordering, inventory, shipping, billing, payments, and other supply-chain activities.

The answer is an enterprise resource planning (ERP) system – and today, the dominant solution is SAP S/4HANA. But implementing an ERP system is a major undertaking. For example, supply-chain managers can generate discrete reports – and those are a useful start. What was missing was an easy means to tie these all together, to offer overall visibility into the supply chain.

Companies can undertake that work themselves, but the development of a custom solution is costly and can take up to 12 months so, while S/4HANA is an excellent foundation, my work with clients in the life-sciences sector made it clear they could use an out-of-the-box solution that works with their ERP platform to provide those much-needed data insights.

That’s why Capgemini created Intelligent Analytics for Pharma – a solution tailored to the unique needs of supply-chain management within life sciences. We launched Intelligent Analytics for Pharma as an app on the SAP Store in March, after more than a year of development, testing, and approvals.

Our goal was to create a ready-to-run solution that, from day one, could draw insights from historical data, open orders, and other information already in a company’s legacy systems. Intelligent Analytics for Pharma does this, enabling the company to immediately benefit from its ERP system. Potential benefits include:

  • Maximizing the ROI in inventory by reducing the impact of disruptions and inaccuracies
  • Enhancing business processes through tools that, for example, predict demand and automatically generate purchase requisitions
  • Extracting valuable insights to encourage and facilitate data-driven decision-making within the organization.

In its Starter Edition configuration, Intelligent Analytics for Pharma uses real-time insights from the company’s data to track and report on more than 75 key indicators and metrics across the supply chain. The app’s plug-and-play configuration provides full control of data, while strong governance ensures data remains high-quality, trusted, and secure.

Capgemini also offers this app in an Advanced Edition, which adds more KPIs and metrics, augmented analytics to enable automated planned independent requirements (PIR) configuration, and process automation of PIR using SAP iRPA.

In addition, while Intelligent Analytics for Pharma can satisfy the majority of a company’s needs out of the box, Capgemini’s Insights & Data practice is ready to help businesses with customizations to address any unique requirements.

SAP is encouraging its customers to use S/4HANA and is retiring older solutions, which means many life-sciences companies are in the process of upgrading their ERP systems. As these upgrades are being performed, the companies I work with are finding it’s an ideal time to embrace solutions like Intelligent Analytics for Pharma to maximize the value they realize from their new systems.

Author details

Mahendra Jain- blog author

Mahendra Jain, Head of Center of Excellence & Innovation for SAP Insights & Data
North America
-Managing large scale BI and Reporting implementation
-Integrating Reporting and Database for Data Analytics, Forecasting, Historical Performance
-Architect on Reporting and Analytical solution on Cloud, On Premise
-Data Analytics strategy and operational reporting
-Driving self-service Data Analytics using Modern BI tools in cloud