In the energy sector, the ability to clearly articulate the value of data and AI SaaS investments is paramount. Executives are caught between championing digital transformation and the challenge of demonstrating tangible returns on investment. This can be a complex task, particularly when navigating the diverse perspectives and desired outcomes of multiple stakeholders.

The context and value within which SaaS benefits are interpreted, sold, and provided can vary significantly based on the customer lens being used. Compiling dollarized business cases for SaaS models can be particularly challenging due to the complex workflows they often support. Multiple decision-makers, bring varying views and require differing business values and outcomes to be satisfied. Unique demonstrable value gains are therefore necessary to engage each stakeholder and establish quantifiable business benefits.

Demonstrating the business impact of data and AI solutions involves presenting dollar values using a transparent and systematic approach that accounts for the complexities of various workflows. Those assessing the impact must investigate and establish rules and procedures for how data is collected, stored, processed, and used across systems. Key questions include: Is the data flow across systems fluid? Who benefits from the efficiencies created? How often per day, week, or month are these benefits realized? Does this efficiency lead to earlier project delivery, resulting in faster return on investment (ROI) and earlier or higher cash flow?

Industry articles advocate for these emerging technologies with claims they are driving improved products and services, faster time to market, better decision making, increased operational efficiencies, and, ultimately, higher profits. However, evaluating these metrics across the organization comes with its own challenges. What does this mean for an enterprise that’s eager to understand how to unlock additional business value?

We propose a methodological approach to addressing business value. The approach includes an efficiency calculator and a value prediction tool that require input from trusted and approved data sources. These tools provide appropriate ratios to calculate the quantifiable efficiency gains for industry workflows and specific projects using data and AI solutions.

When new digital technologies are deployed in a workflow, they may consistently shave seconds or minutes off an individual task. At this scale the impacts may seem minimal. However, when this task is compounded across an organization, substantial enterprise-wide efficiency gains are achieved. The value can be expressed as a percentage of operational efficiencies, which is tangible, to a degree. Showing how this translates into concrete value for your organization is what wins hearts and minds. And that’s not done with percentages alone.

With an understanding of the breadth of operations, it is possible to create a confidence index for them. This can quantify workload improvements, compute efficiencies for company resources, investments, improved tasks, and workloads. It requires the systematic development, documentation, and diffusion of value tools, processes, scalable services, and codified knowledge for broader organizational use.

The Lumi™ data and AI platform provides a compelling example of how to demonstrate and quantify this value. By analyzing specific workflows and identifying quick wins, it can be used to conduct detailed investigations to pinpoint areas where it delivers the greatest impact. For instance, imagine the potential of decommissioning on-premises systems and consolidating databases, leading to USD 10 million in annual savings. Or consider the impact of making trusted data easily accessible through a unified platform, unlocking USD 12 million in annual savings by streamlining data discovery and minimizing time wasted searching for information. These are not just hypothetical scenarios; they are real-world examples of how the Lumi platform can translate digital transformation into tangible financial gains.

Furthermore, by streamlining data ingestion, quality control, and access control, the Lumi platform can typically result in a 30% improvement in efficiency for data managers, freeing up a day-and-a-half of valuable time and resources every week to focus on more strategic initiatives. These quantifiable efficiency gains, when aggregated across the organization, paint a compelling picture of the value proposition that the Lumi platform offers.

This detailed approach to value quantification extends beyond just cost savings. It also encompasses improvements in operational efficiency, risk management, and overall business agility. By mapping out key workflows and processes, identifying bottlenecks, and measuring efficiency gains in terms of time savings per persona, we can create a comprehensive picture of the value that data and AI solutions bring to the table.

In conclusion, the ability to quantify the value of data and AI investments is not merely a technical exercise; it is a strategic imperative for energy companies seeking to thrive in a rapidly evolving landscape. Additionally, the injection of AI, machine learning and generative AI further increases the potential for new workflows and efficiency gains, unlocking additional business value—to remain competitive in an ever evolving and challenging market. By adopting a rigorous methodology and leveraging tools like the Lumi platform, you can unlock substantial cost savings, improve operational efficiency, and empower your teams with data-driven insights. This, in turn, enables you to more confidently navigate the complexities of digital transformation, secure stakeholder buy-in, and drive meaningful business outcomes.