Finding Gold in Mountains of Data

August 24, 2016 meriah.jamieson

Finding Gold in Mountains of Data

Energy and environmental data comes from a number of sources. Resource consumption, supplier information, weather and facility information, utility contract information, efficiency projects and corporate metrics, such as sustainability goals, are all used in reporting and decision making. Some businesses track this data manually, some data sources are easily automated and some are much more difficult to collect.

What data can be collected?

Energy and sustainability data can be collected from a number of different sources including:

  • Utility bills
  • Onsite meters (water, electricity, gas)
  • Facility sub-meters (lighting, HVAC)
  • Facility and enterprise software
  • Supplier information and ratings
  • Employee and occupant surveysdata progression
  • Efficiency project performance
  • Energy cost metrics (price per kilowatt-hour, tariffs)

How is data collected?

Many businesses are not collecting data and when they start, they tend to use a manual process of entering data into a spreadsheet. It is obtained either from paper utility bills or project teams. This method is time intensive and error prone. As companies progress in maturity, a common next step is to implement a software application with automated data collection, which includes more granular data than is available in spreadsheets.

The most advanced enterprises have a system where data is automatically collected at every facility and aggregated in a cloud-based platform for analysis.

How much data is generated?

Consider the following example to illustrate the volume of data produced by a medium size business. This business has two manufacturing plants (under direct management),  more than 200 retail locations, and office buildings and logistics hubs. The data collection infrastructure varies from metered facilities with a building management system (BMS) to leased buildings with no access to metered data. At each facility weather information, energy costs and efficiency project information is also collected. How much energy and sustainability data is generated?

In this example more than 100 million data points would be produced in 5 years. 

This massive amount of data translates into a requirement for robust storage, redundancy and backups. If this data is located in separate applications or locations, aggregating and analyzing it can difficult to impossible. A scalable cloud-based platform, however, eliminates onsite data storage requirements.

So how does an organization go from spreadsheets to powerful software?

6 steps to an integrated data platform

1. Develop a strategy

Map out how data will be used to support sustainability strategy and energy reduction goals. Agree on what needs to be measured and what data exists, and identify gaps. Define frequency and level of granularity needed (monthly, daily, hourly or 15-minute data). Identify audience and interval for data reporting.

Common pitfall: Just because data exists does not mean it has value. Only collect what is required for metrics that can help keep energy use and costs down.

2. Collect and aggregate 

The following data should be collected in the enterprise energy and sustainability data platform: Manually enter project, supplier and financial data. For facilities that do not have interval data, collect data directly from the utility. Connect facility meters or sensor data. If required, import data residing in separate software programs such as BMS, enterprise resource planning and weather data

Common pitfall: Ensure data quality at this stage. As a point of reference, Schneider Electric has found that up to 80 percent of customer data requires data “cleaning”. If data quality is not maintained, problems can be overlooked and decisions made based on misleading data that have a significant financial impact on a business.

3. Develop a baseline

The next step is to develop a performance baseline. This baseline can be used to ensure that the goals a corporation set are realistic and achievable. Data can be reported throughout the organization to generate awareness and foster collaboration. An enterprise energy and sustainability platform allows departments — procurement, sustainability and operations — to share and report on the same data set. An enterprise platform also simplifies and expedites voluntary reporting, such as the Carbon Disclosure Project or U.S. Environmental Protection Agency’s Greenhouse Gap Reporting Program.

Common pitfall: Understand current performance before setting goals to ensure they are achievable.

4. Perform analytics

Data on its own is useless. The real value is in the people who make sense of this big data and find patterns that help an organization make better business decisions. A recent Intel study found when presented with a list of big data challenges, respondents overwhelmingly selected “data analytics” as the most significant hurdle, followed by “data expertise.” Enterprises often have data, but do not have the right resources to turn it into actionable information. It is essential to have the right internal team in place to manage data analytics or outsource this function to experts that can mine data to find efficiencies and deliver value.

Common pitfall: Not having internal expertise to translate data into actions.

5. Take action

Once experts have uncovered inefficiencies or areas to improve, either behavioral improvements or investments that deliver value need to be acted on. Clear priorities and return on investment requirements need to be established to enable quick response to problems. If an internal team is not available to prioritize and ensure action, identify a team of external experts who can help boost efficiency.

Common pitfall: Not assigning responsibility for implementing efficiency initiatives to ensure maximum ROI.

6. Monitor and improve

Once strategic improvements are made, results need to be tracked to ensure success and to refine the strategy as necessary. Without continuous monitoring, many efficiency projects do not meet their expected return and, over time, progress made is often eroded. In fact, a recent study by Accenture found that 50 percent of initial energy savings disappear within the first six to 12 months because of a lack of monitoring, analysis and corrective action.

Common pitfall: Not planning for continuous monitoring will erode efficiency gains.

Benefits of energy and sustainability data management

As transparency into corporate sustainability metrics moves from a luxury to a requirement, most businesses will be required to collect, aggregate and report on this data. Businesses must prepare for this fundamental shift by implementing an enterprise-wide platform that enables both corporate sustainability reporting and the ability to reduce resource consumption at each facility. Automated collection and aggregation of data makes what was once invisible, visible to enable better decisions and save money.

Learn more about how Resource Advisor enables accurate data with an all-in-one view.

The post Finding Gold in Mountains of Data appeared first on Schneider Electric.

 

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