A global biopharmaceutical company on the S&P 500 set ambitious sustainability goals across its development and production network, including reducing greenhouse gas emissions, minimizing water usage, reducing waste, achieving carbon net-zero operations, and transitioning to renewable energy by 2030. To move fast enough, the company needed a practical sustainability plan grounded in real operational data.
2030 Target for carbon net-zero operations and renewable energy transition
70,000ft² California development and production facility selected for the first analysis
65% Improvement in visibility and clarity in energy consumption and spending
The company had already set broad sustainability objectives, but achieving them required a much clearer view of operational performance across research and production environments. The first step was to perform an energy assessment and analysis of U.S. facilities, using historical data to understand energy and water consumption, associated costs, and carbon footprint.
That analysis needed to do more than describe the past. The customer wanted to identify inefficiencies, uncover improvement opportunities, and create a foundation for future predictive and prescriptive analytics. A 70,000-square-foot development and production facility in California was selected as the first analysis site, with the expectation that the methodology could later be replicated across the broader network.
The challenge was compounded by data-collection complexity. An internal sustainability working group was supporting the effort, and the company had engaged a third-party platform to help govern and validate greenhouse gas data across Scope 1, Scope 2, and Scope 3 emissions. But IT complexity and limited resources made it difficult to gather the breadth and depth of data needed to perform the analysis effectively.
Build a sustainability plan fast enough to support 2030 environmental targets
Assess energy, water, cost, and carbon patterns at a 70,000-square-foot pilot site and create a repeatable model
Stellix was brought in to provide both energy sustainability expertise and life sciences domain knowledge. The team developed the overall data and analytics roadmap and successfully executed the first two phases of analytics work: the energy assessment and predictive analytics.
That work included integrating data from multiple sources, analyzing historical performance to better understand energy usage patterns, cost, and carbon footprint, and monitoring both equipment energy and water usage. Stellix also supported asset-health monitoring, emission-output calculation and tracking, forecasting of energy and water usage, and identification of usage and cost anomalies.
Rather than stopping at a point-in-time assessment, Stellix helped define a path toward a more operational sustainability model that could continue to mature over time.
Executed the first 2 analytics phases: energy assessment and predictive analytics
Connected multiple data sources to monitor usage, cost, emissions, asset health, and anomalies
The engagement gave the customer a practical data and analytics foundation for sustainability decision-making. By completing the initial assessment and predictive-analytics phases, Stellix helped the company create a clearer baseline for understanding current consumption patterns and identifying where operational improvements could have the greatest effect.
The work also positioned the organization for subsequent phases, including asset-failure prediction, equipment predictive maintenance, ongoing tracking against sustainability goals, and continuous monitoring measures. Just as important, the initial methodology was designed to scale beyond the first California facility so the company could apply a more consistent approach across other sites.
Established a roadmap for ongoing monitoring, forecasting, and goal tracking
Created a model that could be replicated across additional sites over time
With the analytics solution in place, the company gained approximately 65% better visibility and clarity into its energy consumption and spending. That improvement gave teams a more consistent way to manage energy practices across locations and a stronger basis for future sustainability planning.
The work also enabled the organization to explore investments in more energy-efficient technologies, evaluate transitions to renewable sources, and build broader internal awareness around sustainability performance and opportunities.
Improved visibility and clarity in energy consumption and spending by approximately 65%
Enabled more consistent energy management practices across sites
Whether you are starting with one facility or building an enterprise-wide roadmap, we can help define the data, analytics, and execution model needed to move faster with confidence.
