In the fast‑moving biotechnology industry, operating on a global scale means that every decision influences operational efficiency and cost outcomes. In this high‑stakes environment, a global biotech organization faced a daunting challenge. Its SAP BW environment used on‑premises infrastructure that had reached 90–95% capacity, creating an urgent need for scalability. As a result, the organization explored two options: investing in new hardware or migrating to the cloud.

Ultimately, the company decided on moving to Microsoft Azure, marking its first experience with cloud technology. Initially, the business opted for a short-term subscription to minimize risk, but this came with high monthly costs. During the annual budgeting cycle, the company realized Azure subscription costs and memory sizing would be critical decisions for the next fiscal year.

As the budgeting process unfolded, the biotechnology organization identified three key challenges:

  • Scalability: The on-premises infrastructure was nearly maxed out, limiting growth
  • Cost management: The short-term Azure subscription was expensive, and committing to a long-term plan without accurate sizing posed financial risks
  • Resource optimization: It had become necessary to reduce memory usage on both on-premises and Azure environments to avoid unnecessary costs

The stakes were high. Without optimization, the company risked locking into a costly long-term subscription with oversized memory allocations.

Smarter sizing for cost efficiency

To address these challenges, Capgemini proposed two disaster recovery strategies. First, Log Replay would introduce a smaller secondary instance that could rapidly scale to full production during recovery, offering faster recovery times and using standard network bandwidth. Second, Delta Data Shipping offered an even smaller secondary instance for greater cost savings, but with longer recovery times and higher bandwidth requirements.

After analyzing memory utilization and recovery needs, the company chose Log Replay, which provided 2 TB of breathing space.

But we went further by disabling the preloading of column-store data into memory for disaster recovery (DR). Instead, the column-store would remain on disk and load only when DR was activated. This reduced the amount of memory used from 7.7 TB to 5.7 TB without sacrificing performance, which in turn delivered significant cost savings and improved efficiency.

Commitment to security and resilience

The optimization resulted in $1.2 million in total cost savings over three years, representing a 67% reduction in storage-related operational costs. In addition, the solution ensured scalability, improved disaster recovery readiness, and positioned the company for future growth without compromising performance.

This partnership not only addressed immediate financial risks but also optimized operational efficiency, enabling the company to continue its vital work in biotechnology without the burden of excessive costs. By leveraging Capgemini’s expertise, the organization implemented a sustainable, cost-effective approach to managing cloud resources, turning a potential crisis into a strategic win.