BENCHMARKING DATA ANALYSIS: FACT SHEET
Data Cleansing: Missing Data UNDERSTANDING WHY CRITICAL BENCHMARKING DATA IS MISSING PRIOR TO CLEANSING In order for a benchmarking program to have maximum effectiveness, the following two critically important energy benchmarking metrics have to be either collected or calculated for all properties covered by the program: the Energy Use Intensity (EUI) and, when applicable, the benchmark score. Based on empirical experience, most benchmarking programs find a significant subset of properties that didn’t report one or both of these benchmarking metrics. By performing an analysis to identify the underlying reasons why critical data is missing, program managers can develop the necessary information to follow up and offer feedback to building owners/operators who have incorrectly supplied building data. The development of this type of feedback loop can play a key role in increasing overall data quality in both the short- and long-term efficacy of a benchmarking program. Understanding why critical benchmarking data is missing from a benchmarking dataset usually requires a closer examination of the supplied data along with the use of some type of data forensics. When ESPM is used as a benchmarking tool, it generates two data fields – “Energy Alerts” and “Property Use Detail Alerts” – that can typically offer enough information about why an important benchmarking metric was not calculated. The two main problems that typically occur with a benchmarking program can be identified by looking at a property’s Energy Alerts and Propery Use Detail Alerts data fields when using ESPM: 1) A property is eligible to receive an ESPM score, but no score or EUI was generated (see the Table for a list of eligible ESPM property types); 2) A property was not eligible to receive an ESPM score, but no EUI was generated. In most cases, proper resolution of these issues will require follow up with building owners/operators (or third parties) that submitted suspect data. If data quality issues are not addressed, these issues are likely to reoccur, since future submissions for flagged properties may contain the same erroneous data.
DATA QUALITY ISSUE 1: PROPERTY IS CLASSIFIED AS A PROPERTY TYPE ELIGIBLE TO RECEIVE AN ESPM SCORE, BUT NO SCORE OR EUI WAS GENERATED BY ESPM: Check for the following issues: 1.
25% or more of gross floor area is associated with a non-eligible space use type;
2.
Building/space details were not defined for the whole calendar year, e.g., the number of occupants was not defined throughout the year;
3.
Certain input values were not within range, e.g., weekly operating hours were too low;
4. Energy use meters did not have monthly data for the whole year; 5.
Energy use meters did not account for all energy usage of property;
6. Source EUI was determined to be out of range;
DATA QUALITY ISSUE 2: PROPERTY IS CLASSIFIED AS A PROPERTY TYPE NOT ELIGIBLE TO RECEIVE AN ESPM SCORE, BUT NO EUI WAS GENERATED: Check for the following issues: 1.
Energy use meters did not have monthly data for the whole year;
2.
Energy use meters do not account for all energy usage of property;
3.
Source EUI was determined to be out of range;
4. Property type was reclassified to Not Available. The 21 ESPM property types (out of a total of 84 property types) that can receive a benchmarking score.
Bank Branch
Residence Hall/Dormitory
Barracks
Office
Financial Office
Courthouse
K-12 School
Wastewater Treatment Plant
Supermarket/Grocery Store
Worship Facility
Wholesale Club/ Supercenter
Retail Store
Hospital (General Medical & Surgical)
Data Center
Medical office
Distribution Center
Senior Care Center
Non-Refrigerated Warehouse
Hotel
Refrigerated Warehouse
Multi-Family