[vc_section full_width=”stretch_row” css=”.vc_custom_1532085157436{margin-top: 0px !important;margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;background-color: #ffffff !important;}”][vc_row full_width=”stretch_row” css=”.vc_custom_1766983387352{margin-top: 0px !important;margin-bottom: 0px !important;padding-top: 40px !important;}”][vc_column css=”.vc_custom_1766983370160{margin-top: 10px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”][vc_column_text css=”.vc_custom_1766983354286{margin-top: 0px !important;margin-bottom: 35px !important;}” el_class=”text-block”]

DiLytics Boosts Client’s Energy Efficiency Efforts with An Enterprise-Wide Data Aggregation and Reporting Solution

[/vc_column_text][vc_column_text css=”.vc_custom_1766981513418{margin-top: 0px !important;margin-bottom: 35px !important;}” el_class=”text-block”]The Bay Area Regional Energy Network (BayREN), founded in 2013, is a collaborative effort of the nine counties that make up the San Francisco Bay Area. It operates in the Environmental Services industry and is overseen by the Association of Bay Area Governments (ABAG). BayREN’s mission is to implement successful regional energy-saving programs, leveraging the knowledge and experience of local governments in the Bay Area. BayREN achieves this by developing and administering programs that promote climate protection, resource conservation, and sustainability. [/vc_column_text][vc_column_text css=”.vc_custom_1766981595283{margin-top: 0px !important;margin-bottom: 20px !important;}” el_class=”text-block”]

Business Context

[/vc_column_text][vc_column_text css=”.vc_custom_1766981642584{margin-top: 0px !important;margin-bottom: 20px !important;}” el_class=”text-block”]One of the six programs that BayREN currently runs is called ‘Green Labeling’. This program focuses on conducting home energy assessments and providing scores to single-family residential properties. The Program started in the year 2018 with the objective of increasing the adoption of energy efficiency upgrades by educating homeowners about their property’s energy performance. These upgrades refer to improvements made to homes or buildings to reduce energy consumption and waste. This includes measures such as installing energy-efficient appliances, improving insulation, sealing air leaks, and upgrading heating, ventilation, air conditioning (HVAC) systems, and more. [/vc_column_text][vc_column_text css=”.vc_custom_1766981676232{margin-top: 0px !important;margin-bottom: 10px !important;}” el_class=”text-block”]The core activities of this program include: [/vc_column_text][rt_list_style list_style=”seven” list_extra_class=”text-block” list_css=”.vc_custom_1766981707409{margin-bottom: 20px !important;padding-left: 35px !important;}”]

• Home Energy Scores: This activity helps homeowners understand their home’s energy efficiency level by providing them Home Energy Scores (HES). These scores are based on the assessments developed by the US Department of Energy (DOE). BayREN assigns 3rd party assessor companies to conduct this assessment and provide HES on a scale of 1 to 10. Homeowners, who complete the assessment receive rebates for buying energy upgrades and a report that provides recommendations for improving their home’s energy efficiency. 
• Real Estate Training: This activity is about training Real Estate professionals like agents, appraisers, and lenders on energy efficiency topics related to real estate transactions. Each year, BayREN trains hundreds of Real Estate professionals through online and in-person classes. The data about Real Estate professionals’ participation in such training programs is collected for analysis. 
• Outreach Initiatives: This activity aims to achieve a wider impact by reaching out to a broader audience and increasing their awareness level. This results in more homes being assessed for energy efficiency, leading to significant environmental benefits for the region. This initiative is conducted through county partnerships, digital marketing campaigns, email outreach, and presentations to real estate associations. Data from this activity is collected for analysis.  

[/rt_list_style][vc_column_text css=”.vc_custom_1766981743765{margin-bottom: 10px !important;}” el_class=”text-block”]Though BayREN employed a very comprehensive approach and undertook a variety of activities toward achievement of the Green Labeling Program’s objectives, it suffered from several issues such as:[/vc_column_text][rt_list_style list_style=”seven” list_extra_class=”text-block” list_css=”.vc_custom_1766981770062{margin-bottom: 20px !important;padding-left: 35px !important;}”]

• Inability to identify Program’s impact at varying levels of granularity
• Declining interest among Real Estate professionals in virtual training events
• Lack of insights about Program’s performance and resource allocation
• Heavy administrative burden on the Program’s Lead Manager

[/rt_list_style][vc_column_text css=”” el_class=”text-block”]A root cause analysis of these issues pointed towards the following challenges: [/vc_column_text][rt_list_style list_style=”seven” list_css=”.vc_custom_1766982140723{margin-bottom: 10px !important;padding-left: 35px !important;}” list_extra_class=”text-block”]

• Fragmented Data:

[/rt_list_style][vc_column_text css=”.vc_custom_1766982058352{margin-bottom: 10px !important;padding-left: 55px !important;}” el_class=”text-block”]- Data for single-family homes is stored across multiple databases. This makes the process of combining the data from multiple databases a challenging one
– Similarly, data about Real Estate professional training is captured across multiple Microsoft Excel spreadsheets. This makes the process of accessing data, analyzing it, and reporting on it a difficult one[/vc_column_text][rt_list_style list_style=”seven” list_css=”.vc_custom_1766982123561{margin-bottom: 10px !important;padding-left: 35px !important;}” list_extra_class=”text-block”]

• Manual Process:

[/rt_list_style][vc_column_text css=”.vc_custom_1766982209251{margin-bottom: 10px !important;padding-left: 55px !important;}” el_class=”text-block”]- Data analysis and report generation are currently manual processes that are performed in Microsoft Excel. This is not only time-consuming but also error prone. Further, Microsoft Excel, as a data visualization tool, does not provide a rich set of features to present information in a clear and compelling way
– Reports are not made available to users from a centralized location. Rather, they are distributed to them via email. This makes it difficult for users to locate and reference reports in an easy manner[/vc_column_text][rt_list_style list_style=”seven” list_css=”.vc_custom_1766982287037{margin-bottom: 10px !important;padding-left: 35px !important;}” list_extra_class=”text-block”]

• Inaccessible Historical Data:

[/rt_list_style][vc_column_text css=”.vc_custom_1766982311038{margin-bottom: 20px !important;padding-left: 55px !important;}” el_class=”text-block”]- Historical data about the Program is stored in legacy systems and this data is inaccessible for analysis. This lack of accessibility of the past data makes it difficult to perform year-over-year comparisons and identify trends. This, in turn, makes it difficult to track the Program’s progress and measure its long-term impact[/vc_column_text][vc_column_text css=””]To address these challenges, BayREN identified the need to implement a data analytics solution that will source data from multiple sources, store it in a persistent form in a centralized location, enable its analysis from different stakeholders’ perspectives, and present it to users in a visually appealing manner.  

Through a competitive bidding process, BayREN chose DiLytics as its partner to implement such a solution.[/vc_column_text][vc_column_text css=”” el_class=”text-block”]

DiLytics’ Solution 

[/vc_column_text][vc_column_text css=”.vc_custom_1766982371167{margin-bottom: 10px !important;}” el_class=”text-block”]DiLytics went about the task of implementing the solution in a phased manner which comprised the following phases: 

 [/vc_column_text][vc_column_text css=”.vc_custom_1766982529983{margin-bottom: 20px !important;}” el_class=”text-block”]

1. Discovery Phase 

[/vc_column_text][vc_column_text css=”.vc_custom_1766982552690{margin-bottom: 10px !important;}” el_class=”text-block”]DiLytics started the Discovery phase by identifying the various stakeholder groups involved in the Program and gaining an understanding of the role that they play in carrying out Program activities at the ground level. Based on this understanding, DiLytics created structured questionnaires for each stakeholder group and shared it with them well in advance of the scheduled discovery workshop date. Utilizing the structured questionnaire as the basis of the discovery workshop discussion, DiLytics elicited the stakeholders’ required information pertaining to the various aspects of the program.  

 

The different stakeholder groups that DiLytics held the workshops with, included: [/vc_column_text][rt_list_style list_style=”seven” list_extra_class=”text-block” list_css=”.vc_custom_1766982488359{margin-bottom: 20px !important;padding-left: 35px !important;}”]

• Program Lead Manager: who oversees all aspects of the Program
• Program Implementer: who are involved in the compilation and management of home assessment data, feeding the data in the database, and extracting data from the database to send information to different stakeholders
• Key Business Users: business users from the various counties
• IT Team: responsible for maintaining the IT infrastructure

[/rt_list_style][vc_column_text css=”.vc_custom_1766982582574{margin-bottom: 10px !important;}” el_class=”text-block”]DiLytics also conducted a thorough review and analysis of the Program’s existing IT architecture, processes, data flow, and technical design. Leveraging its extensive experience in Data Warehousing, Data Integration, and Analytics, DiLytics evaluated BayREN’s current platform, identified issues, gaps, unrealized opportunities, and technology deficiencies.  

 

DiLytics utilized the insights gathered from the workshops to: [/vc_column_text][rt_list_style list_style=”seven” list_extra_class=”text-block” list_css=”.vc_custom_1766982610494{margin-bottom: 20px !important;padding-left: 35px !important;}”]

• Understand the current state of the Program
• Draw the future state desired by various Stakeholder groups
• Identify strategies to take the Program from its current state to the future state
• Create a roadmap for implementing the identified strategies

[/rt_list_style][vc_column_text css=”.vc_custom_1766982656227{margin-bottom: 20px !important;}” el_class=”text-block”]The output of the discovery phase was a comprehensive report that captured the findings related to the current state of the Program and the future state desired by stakeholders; analysis of those findings; recommendations about the proposed solution, its architecture, tools for various architecture components; and the roadmap to implement the solution.[/vc_column_text][vc_column_text css=”.vc_custom_1766982694725{margin-bottom: 20px !important;}” el_class=”text-block”]

2. Implementation Phase 

[/vc_column_text][vc_column_text css=”.vc_custom_1766982721856{margin-bottom: 10px !important;}” el_class=”text-block”]DiLytics went about implementing the solution by leveraging its established methodology that comprised the following phases: [/vc_column_text][rt_list_style list_style=”seven” list_extra_class=”text-block” list_css=”.vc_custom_1766982755562{margin-bottom: 20px !important;padding-left: 35px !important;}”]

• Solution Design
• Solution Development
• Key User Training
• User Acceptance Testing
• Solution Deployment
• Post Go Live Support

[/rt_list_style][vc_column_text css=”.vc_custom_1766982796586{margin-bottom: 10px !important;}” el_class=”text-block”]The solution entailed an automated data integration process that extracted data from various sources such as Postgres databases and flat files; consolidated the data into a cloud-based data warehouse on Snowflake; and disseminated insights to users via a data visualization tool, Tableau. A high-level architecture of the solution is depicted in the schematic below: [/vc_column_text][vc_single_image image=”15154″ img_size=”full” alignment=”center” css=”.vc_custom_1766982813787{margin-bottom: 20px !important;}”][vc_column_text css=”.vc_custom_1766982839846{margin-bottom: 10px !important;}” el_class=”text-block”]The solution enabled a series of interactive reports that offer visual representations of key metrics across various aspects of the Program, allowing for easy interpretation and analysis.  

 

Some of the key reports that the solution provided include:  [/vc_column_text][rt_list_style list_style=”seven” list_extra_class=”text-block” list_css=”.vc_custom_1766982879663{margin-bottom: 20px !important;padding-left: 35px !important;}”]

• Home Energy Score Report: Provides details about home energy score assessment, including home energy score details, energy consumption by homes, carbon footprint of homes, and energy improvement recommendations
• BayREN Monthly Report: Provides an overview of the program’s performance, including rebate figures and recommendations for improving home energy efficiency
• Annual Green Labeling Summary Report: Describes the progress of the program in comparison to last year’s performance
• BayREN Annual Report: Offers a comprehensive overview of the program’s activities and achievements throughout the year

[/rt_list_style][vc_column_text css=”.vc_custom_1766982923665{margin-bottom: 10px !important;}” el_class=”text-block”]Some of the KPIs that the solution enabled included: [/vc_column_text][rt_list_style list_style=”seven” list_extra_class=”text-block” list_css=”.vc_custom_1766982975627{margin-bottom: 10px !important;padding-left: 35px !important;}”]

• Home Energy Scores

[/rt_list_style][vc_column_text css=”.vc_custom_1766983022658{margin-bottom: 10px !important;padding-left: 55px !important;}” el_class=”text-block”]- Approved Score: shows the total number of assessments approved by the Assessor Company
– Submitted Score: shows the total number of assessments submitted by individual homeowners
– Average Home Energy Score: shows the average home energy score received within a county
– % Homes with ECL: shows the % of homes who completed ECL (Electrification Checklist Assessment)
– ECL Payments: shows the total amount paid to homeowners who completed electrification checklist assessments[/vc_column_text][rt_list_style list_style=”seven” list_extra_id=”text-block” list_css=”.vc_custom_1766983089145{margin-bottom: 10px !important;padding-left: 35px !important;}”]

• Real Estate Training

[/rt_list_style][vc_column_text css=”.vc_custom_1766983118845{margin-bottom: 35px !important;padding-left: 55px !important;}” el_class=”text-block”]- Number of training sessions conducted
– Number of attendees
– Number of unique attendees
– Percentage of registered candidates who also attended the training sessions[/vc_column_text][vc_column_text css=”” el_class=”text-block”]

Outcomes

[/vc_column_text][vc_column_text css=”.vc_custom_1766983202968{margin-bottom: 10px !important;}” el_class=”text-block”]The solution resulted in the achievement of the following outcomes for BayREN:[/vc_column_text][rt_list_style list_style=”seven” list_extra_class=”text-block” list_css=”.vc_custom_1766983275006{margin-bottom: 0px !important;padding-left: 35px !important;}”]

• Optimization of Training Delivery and Outreach Strategies: Insights into – online versus in-person preferences, training program performance, participant demographics, repeat attendance, and registration versus attendance – enabled optimization of training delivery and outreach strategies, ultimately enhancing participant engagement, improving program effectiveness, and increasing overall attendance and satisfaction
• Enablement of Targeted Program Management: Report-level security at the county level enabled counties to access reports specific to their jurisdiction. This facilitated in doing targeted program management. In addition, granular insights into program performance across individual cities within each county helped in creating localized strategies and doing effective resource allocation
• Enhanced Efficiency and Accuracy in Delivering Program Insights: Automation of the data integration process and creation of a centralized data repository enabled efficient data access and analysis, reduced manual effort significantly, and eliminated data inconsistencies. This led to the delivery of efficient, reliable and accurate insights into various aspects of the Program

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DiLytics Delivers

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