Deployment and adoption of technologies and services for energy and sustainability management is accelerating. Global megatrends, such as a continued reduction in the cost of sensing technology and cloud-based processing, have made it easier for organizations to collect, store and analyze large amounts of data.
Corporations are now able to capture and monitor granular energy and resource consumption in real time. Yet many still struggle to turn this data into actionable insights.
The real data challenge
Data is readily available. What companies struggle with is ensuring data quality and using information to foster sharing and collaboration.
In many cases, these granular energy data streams are new to building operators and managers and provide more analysis and optimization opportunities than ever before. But the collection and analysis of energy and sustainability data can also be daunting for corporations, especially as the amount of available data continues to increase and the need to ensure data quality becomes acute.
One barrier to collaboration is the data source. A recent survey of more than 300 corporate energy and sustainability professionals, conducted by Schneider Electric and Greenbiz, revealed that 52% of respondents are still relying on spreadsheets to manage their energy and sustainability data, while only 18% report using IoT-enabled devices.
Data visibility and fluency are crucial
The ability to easily share data has significant benefits. The same research shows that 90% of the respondents who reported that “departments see all data” agree or strongly agree that they can make business cases to secure funding for energy and sustainability projects.
Yet, there are a variety of barriers that make data sharing a challenge. In some cases, the quality of the data is suspect, or it is difficult to manipulate, which may make it less valuable. For example, 48% of firms note that the data they collect is incomplete and 41% report having insufficient tools to use the data. More importantly, 40% of respondents note that they do not have the right internal expertise to act on data — a significant talent barrier in a rapidly digitizing world.
As data becomes more trustworthy, it also becomes more important to share. Respondents that said that they share all data have higher adoption rates of IoT devices and Energy Management Systems (EMS). They are also less dependent on spreadsheets.
Technology is only one key to success
The increased adoption of software and other technology to collect, manage and analyze energy and sustainability data makes it easier to share data across organizations and with third parties like reporting agencies.
However, even with these technology-enabled solutions in place, companies still need to develop internal processes to share data, analyze it and implement it across their organization. The research suggests this is trending. For example, companies that have deployed an EMS report that they are more successful in their efforts to develop a business case for sustainability projects and initiatives.
“We’ve really been handicapped with just not having enough resources to be able to dive into the data as much as we need to.” ~ Retailer
Taking action: learn from leaders
Here's how leading organizations have overcome the data collection and sharing challenge.
- Use of real-time metering with data shared across the organization: A leader in the commercial real estate business uses EcoStruxure™ Resource Advisor to create dashboards containing real-time metering data from across the property portfolio. Within minutes, the vice president of engineering can get a complete picture of energy demand. This allows his team to adjust quickly, instead of waiting 30-45 days until the utility bill arrives. Furthermore, he can share this corporate-level data with third-party partners like ENERGY STAR, LEED and GRESB, and use the data as proof with internal stakeholders to validate the program's success.
- Deployment of submetering systems and locally-configurable interfaces: A global aerospace organization has implemented submeters across its top 40 sites during the last 3 years, giving the company more granular energy consumption data. Each local team was trained so they could access and monitor the data themselves without corporate oversight. In another example, an agricultural company is leading a change management operation that will enable teams on the ground to take ownership of their day-to-day energy performance and increase proficiency.
- Investment in data analysis expertise: A leading global retail company admits to being handicapped in the past by not having enough resources to analyze its data. The current goal is to hire analysts to drive better decision-making based upon the data that is available.
- Alignment of corporate and sustainability goals: A banking institution ensures that all its internal departments have visibility into the overall business strategy and long-term organizational vision. Sharing of data becomes core to this exercise, which helps the sustainability team secure approval and funding for key initiatives.
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