How to accelerate sale-to-install time and squash solar soft costs
By Pete Cleveland, VP of solar energy, EagleView
In competitive residential solar markets, a solar sales and installation company competes with a average of 20 solar companies for customers, referrals and market share. For many companies, the pressure to remain competitive has emphasized a new need to reduce system costs.
While total system costs in the United States have decreased by: 25% since 2014, largely due to advances in technology, customer acquisition and overheads have increased by 31% in the same time. According to SEIA, soft costs in the United States represent: 60 to 70% of the total cost of residential-scale solar PV systems.
This difference between rapidly declining hard system costs and the generally increasing percentage of soft costs points to the importance and opportunity of soft cost reductions.
Reduce soft costs to scale business
Soft costs represent the costs outside of hardware equipment associated with selling, designing and installing a solar PV system – including customer acquisition, design, licensing, installation, inspection, interconnection, business overhead and profit.
Overhead (general and administrative) and profit are the largest cost of a project, at 21% of the total system costs. Sales and marketing come in close second with 18% of total system costs.
Rather than sacrificing profit margins to reduce costs, companies have the opportunity to evaluate their sales and operations workflow to first identify inefficiencies and then identify powerful solutions to streamline operations. In particular, customer acquisition and related sales and design activities are a great place to start.
Prioritize accurate location assessment data
Site assessment data is fundamental to the solar sales and installation process. Roof dimensions, usable square footage and sun exposure are all data used during the sales, planning, installation and closing stages of a project.
Inaccurate location measurements result in less profitable jobs at best and canceled contracts and lost referrals at worst. On the other hand, high-quality location measurements result in a fast sales cycle from lead to installation, speeding up payment and cash flow.
Fortunately, new advances in remote measurement enable solar companies to bypass inefficient and error-prone site visits to measure and record roof dimensions, azimuth, slope and localized shading at a given location. In addition, some remote measurement technology, such as those derived from aerial photographs, captures thousands of measurement points. In comparison, the same rooftop measured manually with a portable device may only record a few dozen values.
Streamline the design process
Traditional solar sales processes begin with sales representatives using preliminary system designs from DIY software to develop an initial proposal that estimates how many solar modules will fit on different roof facets. In this preliminary design process, many contractors purposely underuse roof space to avoid problems in the final design or installation. (Small size of a solar PV system can help reduce risk, but this adds to soft costs, leaves money on the table for the contractor, and negatively impacts return on investment for the homeowner. .)
Once the contract is signed, a technician will visit the site to collect the necessary measurements and information to validate a final system. Unfortunately, when using a handheld device to log measurements, the potential for human error is high and can lead to costly errors over time.
However, with remote measurement technology, virtual location assessments use satellite or aerial images to capture data — including all roof measurements, pitch angles, and even obstacles such as vents and skylights — to create a detailed 2D or 3D roof model. Energy production estimates and rooftop solar visual layouts can be developed before direct contact with the customer. Not only does this prepare the sellers for an informed initial communication with a potential customer, it also optimizes outbound sales efforts by prioritizing properties with favorable roof facets and solar access values in the sales queue.
By coupling highly accurate remote measurements and high-resolution images with solar design and layout software tools, we efficiently deliver install-ready designs at the front end of the sales cycle, eliminating the need for “preliminary” designs. These designs are also optimized to fit more modules on the average roof and maximize the annual production of solar energy.
Benefits of an optimized workflow
Inefficiencies in traditional solar sales and business workflows often start with inaccurate roof measurements that lead to overly conservative designs, excessive truck rolls and change orders, and result in longer timelines that ultimately hurt a project’s profitability. There is also a higher risk of canceled contracts, unhappy customers and lost referrals.
Fortunately, implementing highly accurate data tools that facilitate virtual site assessments and installation-ready designs at the proposal stage presents solar companies significant opportunities to streamline workflow and gain competitive advantage and market share within their service area. By optimizing the available roof space, shortening project timelines, reducing labor and the possibility of human error, companies can increase their profits, customer satisfaction and their scalability.
Competitive and growing solar installers targeting customer acquisition costs through virtual assessments and installation-ready designs at the front of a project will significantly improve workflow efficiency, which in turn supports better business processes across the board. Changes like these, which speed up sale-to-install time and optimize system performance, are ultimately what will be needed to scale the solar industry to meet global clean energy goals.
Pete Cleveland is Vice President of Solar at EagleView, a leader in innovating accurate and accurate solar design software solutions through aerial photography and machine learning-based data analytics.