Sustainability and Energy Action Plan

IMPLEMENTATION GRANTS PASS SUSTAINABILITY AND ENERGY ACTION PLAN The granularity needed is one record per month per service meter or location, which matches the billing cycle of most service providers. For fueling, the data is typically provided as one record for each fueling event. The data scope could either be determined by a list of meter numbers provided by the requester (City) or using some agreed -upon tag or assigned identifier that is associated with a set of meters, addresses, or vehicles (a Customer ID, for example). The format needed is simple, such as a text file with comma separated values ( CSV file). It is important that once such a data exchange is established , it remains consistent from one request or time period to the next. This reduces the effort required to process the information received and supports automation of data consumption to populate reports, monitoring dashboards, charts and summaries. Having a consistent, uniform format would also encourage reuse of tools, processing templates, and data sharing across public (or even private) entities. While utilities have been responsive to requests for utility data when made, the following challenges have been encountered over the past year: 1) The format of the data provided changes depending upon the customer service person fielding the request or the methodology used in completing the request, including different data elements or elements with different headings or in different order or format. The response to each data request appears to be ad -hoc. 2) Data sets cover different sets of meters for each request, often with some meters missing from the data extract , requiring manual identification of missing meters and repeated follow -up requests to obtain missing data. 3) Basic fields such as kilowatt hours of electricity consumed may be missing from some meters due to underlying complexity on the utility's end related to their billing formula. This requires the data recipient to research and understand the complexity in order to "back in" to required basic data values using other data values provided in the extract. In some cases, the City does not capture data that would be very useful in monitoring. For example, the City has almost no data regarding solid waste other than the capacity of the containers in which waste is collected. This makes it difficult to improve solid waste reduction to reduce costs and benefit the environment. 95