In today’s clean energy landscape, where scaling operations and improving margins are paramount, implementing the right enterprise SaaS solution can mean the difference between surviving and thriving. This is even more true for asset owners, asset managers and O&M companies who need to focus on maximizing output, increasing resiliency and improving customer satisfaction, while also increasing revenue. Yet finding and implementing the optimal SaaS solution, for both energy management and business optimization, is increasingly complex and challenging. To meet the current demands, the typical software evaluation process needs to be redesigned.
Too often, companies embark on their software selection journey by creating a list of technical requirements for their core businesses. For instance, O&M decision makers will develop a feature wishlist like the following:
- A consolidated dashboard
- Real-time data
- Agnostic data integration from all vendors and data points
- CMMS with a direct connection to the assets and onsite technicians
- Configurable alerts for various events
- Basic reporting of production data
This type of tunnel vision and feature-only approach leads to a fractured software ecosystem that does not allow all departments and vendors to seamlessly interact with all stakeholders. For instance, this process has led the industry to standardize on single-pane-of-glass solutions that tend to only meet core O&M functions and miss opportunities for true business transformation. For example, the business needs of asset managers, such as lifecycle management, KPI tracking, document databases and project management remain unaddressed. Furthermore, this leads to business inefficiencies, bottlenecks and delays. That’s why software needs to be evaluated for its ability to align with and accelerate the broader, more strategic objectives of a business.
The enSights dashboard.
A 360° approach to evaluating clean energy management software means leading with business goals, such as operational efficiency, financial visibility and risk mitigation. This more comprehensive approach enables businesses to consider the full lifecycle of the electron – from onsite production through invoicing and billing. This means not only evaluating software for its asset monitoring and management features, but also for its interconnectivity and interoperability. As an example, it is important to confirm that a SaaS solution either provides native or robust API support of CRM, ERP, billing, CMMS, vendor and SLA tracking and reporting, plus different communication protocols to communicate with onsite hardware. This will require that the evaluation process spans multiple personas in operations, finance, IT and other departments, but it will improve cross-departmental buy-in and collaboration in the long run. In addition, this type of interconnectivity enables company-wide standardization on the same clean and reliable data.
That brings us to the second phase of the software buying process — data integration. Often overlooked, this can be one of the most challenging phases. Without a clear data integration plan or interdepartmental analysis, data can become siloed in separate systems and static repositories. Unable to interact in sophisticated ways, data can not provide meaningful or actionable insights.
However, when data integration is an upfront consideration, it has the potential to play a more active role across all operations. Warranties, insurance records, contracts, PPAs and site photos that would have been stored in isolated folders can be tied directly to live performance and operational data — turning static information into dynamic, actionable insights. For instance, a software solution that supports true data integration can transform a standard underperformance alert into a higher priority one if the relevant hardware’s warranty is about to expire. Overall, thoughtful data integration allows for smarter decision-making and more strategic resource planning — a true differentiator of modern platforms.
enSights
The final stage of the software buying process is internal deployment. Onboarding people, teams and an entire company onto new software can be challenging. While a user-friendly and intuitive interface is helpful, the ability of a solution to improve interdepartmental communication and teamwork can be key to successful implementation. Software solutions that are focused on only core business functions force people to operate in silos, meaning engineering, financing, and operations teams need to jump between multiple different platforms and applications. This can lead to miscommunications, mistakes and wasted time.
However, when an enterprise-wide solution is deployed, it empowers every department to interact in a much more seamless and integrated manner. For example, an asset manager can easily track alerts and also open and track ticketing and resolution on the same platform. But so too can the finance team see the real-time P&L calculations related to that alert. By providing real, tangible benefits and streamlining operations for cross-functional departments, team members voluntarily onboard themselves, vs. needing to be mandated.
This new approach to buying energy management software is more extensive, with enterprise-wide decision making and implementation. But it also means that the positive impacts for competitiveness, profitability, efficiency and growth are greater. Part of that is because it streamlines and optimizes the entire company, not just a single department. While an even more significant outcome of this cross functionality is the ability to clearly and consistently present revenue from electricity sales, further enabling a company to financially leverage itself with better terms and less cash flow pressure.
This approach doesn’t just help find the right software, but also the best long-term technology partner who is flexible, responsive, and attuned to evolving market needs. As this approach is adopted throughout the industry, standard monitoring and management platforms will likely be replaced by enterprise-grade management and optimization ecosystems.
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