{"id":28554,"date":"2018-11-13T16:50:33","date_gmt":"2018-11-13T21:50:33","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-rctom\/submission\/illuminating-hidden-efficiency-gains-with-machine-learning-carbon-lighthouse\/"},"modified":"2018-11-13T16:50:33","modified_gmt":"2018-11-13T21:50:33","slug":"carbon-lighthouse-illuminating-energy-savings-with-machine-learning","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/carbon-lighthouse-illuminating-energy-savings-with-machine-learning\/","title":{"rendered":"Carbon Lighthouse: Illuminating Energy Savings with Machine Learning"},"content":{"rendered":"<h2><strong>Who is Carbon Lighthouse?<\/strong><\/h2>\n<p>Carbon Lighthouse (CL) is a clean-energy consulting firm that offers advice on how to reduce their clients\u2019 energy consumption. With a portfolio containing over five-hundred buildings and doubling annual revenue growth for the past seven years, they are clearly doing something beyond the every-day competition. What is their edge? They use machine learning and artificial intelligence to uncover hidden efficiencies beyond the typical low hanging-fruit of LED lighting and HVAC improvements. By using a complex network of sensors, CL monitors and corrects building performance to deliver sustained savings through a guaranteed subscription service. The company claims that these savings amount to an additional twenty to thirty percent efficiency gain above the typical Building Management Systems (BMS) offered by competitors.<\/p>\n<p>&nbsp;<\/p>\n<h2><strong>How Does it Work?<\/strong><\/h2>\n<p style=\"text-align: center\"><iframe loading=\"lazy\" title=\"3 Steps to Guaranteed Energy Savings: Our Process\" width=\"640\" height=\"360\" src=\"https:\/\/www.youtube.com\/embed\/DrD35jIUT4s?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe> [1]<\/p>\n<p>As described by CEO Brenden Millstein above, when CL is hired, they first deploy 50-300 sensors to measure electrical flows, chiller fluid flows, occupancy rates, pressures and lighting flows. The collected data is then sent to a cloud server, where it is analyzed by the company\u2019s proprietary machine-learning AI, known as <strong>CLUES<\/strong><strong>\u00ae<\/strong> (Carbon Lighthouse Unified Engineering System). CLUES\u00ae uses tens of millions of data points to predict the financial and energy-based benefit of thousands of potential actions to identify the best potential energy-savings measures for the client.<\/p>\n<p>These recommendations are twofold. First, CLUES\u00ae identifies possible one-time changes such as lighting retrofits, valve changes, and solar additions. Second, the system monitors and optimizes the building\u2019s controls every five minutes. It is this latter machine-learning driven control that differentiates CL from its competitors, generating 80% of the client\u2019s savings over time. [2]<\/p>\n<p><a href=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Method.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-large wp-image-33262\" src=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Method-1024x286.png\" alt=\"\" width=\"640\" height=\"179\" srcset=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Method-1024x286.png 1024w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Method-300x84.png 300w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Method-768x214.png 768w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Method-600x168.png 600w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Method.png 1178w\" sizes=\"auto, (max-width: 640px) 100vw, 640px\" \/><\/a><\/p>\n<h2><strong>How Important is the Machine Learning?<\/strong><\/h2>\n<p>Incredibly. Buildings are extremely dynamic; weather, occupancy, and energy demand change throughout the day, necessitating real-time control. Moreover, in the clean-energy business, too many building owners have been burned by unsuccessful energy-efficiency projects. Carbon Lighthouse\u2019s VP of Engineering, Matt Gasner, in an interview with GreenBiz reporting, stated that 20% of energy savings projects are performing at less than 50% of their expected benefit within a few years. [3]<\/p>\n<p>Hence, accuracy matters. To this point, studies have shown that in measuring and verifying energy consumption, machine learning methods are up to 50% more effective than traditional means. [4]\u00a0With such an increase in accuracy one might think one has to move more slowly, but the reverse is true. In fact, CLUES\u00ae has also sped up CL\u2019s implementation time from eighty person-days to just three. [5]\u00a0It\u2019s clear that the megatrend of Machine Learning is essential to CL\u2019s business.<\/p>\n<p>&nbsp;<\/p>\n<h2><strong>Management Addresses the Issues<\/strong><\/h2>\n<p>To combat the perception that energy-efficiency projects don\u2019t payoff, CL has instituted an energy savings guarantee, where they contractually oblige themselves to deliver a dollar amount of savings per annum. Should CL fail to deliver, they refund the difference. Thus, they have removed the upfront risk for the customer, while only exercising refunds in 3% of cases. [2]<\/p>\n<p>Strategically, management has also set up CL for long-term success. Most recently, the company landed a 27-million-dollar round of seed funding in order to pursue growth of their engineering teams and further develop the CLUES\u00ae product. [6]\u00a0Much of that growth has been focused in Hawaii where regulators have set an aggressive 100% renewable energy target by 2045, suggesting a need to reduce demand by four-thousand gigawatt-hours. [3]\u00a0Additionally the company appears to be focusing on long-term contracts that boost customer lifetime value, an example of which is Tesla, who has signed a six-year contract to reduce utility bills by $90,800 annually. [2]<\/p>\n<p>Thinking more long-term, the company vows it will stay private: \u201cWe aren\u2019t trying to build a \u2018flip\u2019 company to get acquired or end with an IPO \u2014 we\u2019re committed to solving the climate change conundrum for the next 150 years.\u201d [6]<\/p>\n<p>&nbsp;<\/p>\n<h2><strong>Recommendations to Management<\/strong><\/h2>\n<p>As CL\u2019s AI gets faster, consider shifting from large clients to smaller ones. Specifically, focus more heavily on small to medium-sized manufactures, as studies suggest they have significant energy savings potential and are unlikely to be able to reduce their consumption with internal talent. [7]\u00a0These are companies with fewer than 500 employees, less than 100-million-dollars in sales, and annual energy costs of 100 thousand to 2.5-million-dollars.<\/p>\n<p>&nbsp;<\/p>\n<h2><strong>Food for Thought<\/strong><\/h2>\n<ul>\n<li>Can CL use its rich data sets to inform product development of companies specializing in cleantech and IoT?<\/li>\n<li>CL\u2019s stated mission is to end global warming. CEO Brenden Millstein has remarked that they have saved four power plants worth of CO<sub>2<\/sub>, so that leaves only fifty-thousand more. How can CL scale their business more effectively?<\/li>\n<li>Do you agree that the company should remain private?<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p class=\"p1\">(790 words)<\/p>\n<p>&nbsp;<\/p>\n<p><strong>References<\/strong><\/p>\n<p>[1]\u00a0Carbon Lighthouse. (2018).\u00a0<i>How We Work<\/i>. [online] Available at: https:\/\/www.carbonlighthouse.com\/how-we-work\/ [Accessed 13 Nov. 2018].<\/p>\n<p>[2]\u00a0St. John, J. (2018).\u00a0<i>How Carbon Lighthouse Mines Wasted Energy From the Built Environment<\/i>. [online] Greentechmedia.com. Available at: https:\/\/www.greentechmedia.com\/articles\/read\/how-carbon-lighthouse-mines-wasted-energy-from-the-built-environment#gs.=qCwBK8 [Accessed 13 Nov. 2018].<\/p>\n<p>[3] GreenBiz. (2018).\u00a0<i>Day 1, Sidebar Discussion with Matt Ganser, Carbon Lighthouse<\/i>. [online] Available at: https:\/\/www.greenbiz.com\/video\/day-1-sidebar-discussion-matt-ganser-carbon-lighthouse [Accessed 13 Nov. 2018].<\/p>\n<p>[4]\u00a0Gallagher, C., Bruton, K., Leahy, K. and O\u2019Sullivan, D. (2018). The Suitability of Machine Learning to Minimise Uncertainty in the Measurement and Verification of Energy Savings.\u00a0<i>Energy and Buildings<\/i>, 158, pp.647-655.<\/p>\n<p>[5]\u00a0Carbon Lighthouse. (2018).\u00a0<i>How Carbon Lighthouse Got Its CLUES<\/i>. [online] Available at: https:\/\/www.carbonlighthouse.com\/carbon-lighthouse-got-clues\/ [Accessed 13 Nov. 2018].<\/p>\n<p>[6]\u00a0Carbon Lighthouse. (2018).\u00a0<i>Carbon Lighthouse Closes $27M Growth Round<\/i>. [online] Available at: https:\/\/www.carbonlighthouse.com\/carbon-lighthouse-closes-27m-growth-round-proving-profit-driven-carbon-elimination-is-a-thing\/ [Accessed 13 Nov. 2018].<\/p>\n<p>[7]\u00a0DuttaGupta, A. &amp; Egbue, O., PhD. 2017, &#8220;Energy Efficiency Using Machine Learning \u2013 Targeting Small and Medium- Sized Manufactures&#8221;,\u00a0<i>IIE Annual Conference.Proceedings,<\/i>\u00a0pp. 976-981.<\/p>\n<p><strong>Additional Background<\/strong><\/p>\n<p>[8] Heikell, L. (2014).\u00a0<i>Meet Carnegie Mellon\u2019s Energy Sleuths<\/i>. [online] Microsoft Stories. Available at: https:\/\/news.microsoft.com\/features\/meet-carnegie-mellons-energy-sleuths\/ [Accessed 13 Nov. 2018].<\/p>\n<p>[9] Hsieh, E. (2017).\u00a0<i>How Carbon Lighthouse uses machine learning to achieve energy efficiency<\/i>. [online] GreenBiz. Available at: https:\/\/www.greenbiz.com\/video\/how-carbon-lighthouse-uses-machine-learning-achieve-energy-efficiency [Accessed 13 Nov. 2018].<\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Carbon Lighthouse delivers 20-30% energy savings to their clients using a cloud-based, machine-learning AI.<\/p>\n","protected":false},"author":11041,"featured_media":33045,"comment_status":"open","ping_status":"closed","template":"","categories":[26,130,346],"class_list":["post-28554","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry","category-clean-energy","category-energy-efficiency","category-machine-learning","hck-taxonomy-organization-carbon-lighthouse","hck-taxonomy-industry-consulting","hck-taxonomy-country-united-states"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-rctom\/assignment\/rc-tom-challenge-2018\/","yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Carbon Lighthouse: Illuminating Energy Savings with Machine Learning - Technology and Operations Management<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/carbon-lighthouse-illuminating-energy-savings-with-machine-learning\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Carbon Lighthouse: Illuminating Energy Savings with Machine Learning - Technology and Operations Management\" \/>\n<meta property=\"og:description\" content=\"Carbon Lighthouse delivers 20-30% energy savings to their clients using a cloud-based, machine-learning AI.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/carbon-lighthouse-illuminating-energy-savings-with-machine-learning\/\" \/>\n<meta property=\"og:site_name\" content=\"Technology and Operations Management\" \/>\n<meta property=\"og:image\" content=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Participation-Log.png\" \/>\n\t<meta property=\"og:image:width\" content=\"500\" \/>\n\t<meta property=\"og:image:height\" content=\"126\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"5 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/carbon-lighthouse-illuminating-energy-savings-with-machine-learning\\\/\",\"url\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/carbon-lighthouse-illuminating-energy-savings-with-machine-learning\\\/\",\"name\":\"Carbon Lighthouse: Illuminating Energy Savings with Machine Learning - Technology and Operations Management\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/carbon-lighthouse-illuminating-energy-savings-with-machine-learning\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/carbon-lighthouse-illuminating-energy-savings-with-machine-learning\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/wp-content\\\/uploads\\\/sites\\\/4\\\/2018\\\/11\\\/Participation-Log.png\",\"datePublished\":\"2018-11-13T21:50:33+00:00\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/carbon-lighthouse-illuminating-energy-savings-with-machine-learning\\\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/carbon-lighthouse-illuminating-energy-savings-with-machine-learning\\\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/carbon-lighthouse-illuminating-energy-savings-with-machine-learning\\\/#primaryimage\",\"url\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/wp-content\\\/uploads\\\/sites\\\/4\\\/2018\\\/11\\\/Participation-Log.png\",\"contentUrl\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/wp-content\\\/uploads\\\/sites\\\/4\\\/2018\\\/11\\\/Participation-Log.png\",\"width\":500,\"height\":126},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/carbon-lighthouse-illuminating-energy-savings-with-machine-learning\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Submissions\",\"item\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"Carbon Lighthouse: Illuminating Energy Savings with Machine Learning\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/#website\",\"url\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/\",\"name\":\"Technology and Operations Management\",\"description\":\"MBA Student Perspectives\",\"potentialAction\":[{\"@type\":\"性视界Action\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Carbon Lighthouse: Illuminating Energy Savings with Machine Learning - Technology and Operations Management","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/carbon-lighthouse-illuminating-energy-savings-with-machine-learning\/","og_locale":"en_US","og_type":"article","og_title":"Carbon Lighthouse: Illuminating Energy Savings with Machine Learning - Technology and Operations Management","og_description":"Carbon Lighthouse delivers 20-30% energy savings to their clients using a cloud-based, machine-learning AI.","og_url":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/carbon-lighthouse-illuminating-energy-savings-with-machine-learning\/","og_site_name":"Technology and Operations Management","og_image":[{"width":500,"height":126,"url":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Participation-Log.png","type":"image\/png"}],"twitter_card":"summary_large_image","twitter_misc":{"Est. reading time":"5 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/carbon-lighthouse-illuminating-energy-savings-with-machine-learning\/","url":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/carbon-lighthouse-illuminating-energy-savings-with-machine-learning\/","name":"Carbon Lighthouse: Illuminating Energy Savings with Machine Learning - Technology and Operations Management","isPartOf":{"@id":"https:\/\/d3.harvard.edu\/platform-rctom\/#website"},"primaryImageOfPage":{"@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/carbon-lighthouse-illuminating-energy-savings-with-machine-learning\/#primaryimage"},"image":{"@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/carbon-lighthouse-illuminating-energy-savings-with-machine-learning\/#primaryimage"},"thumbnailUrl":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Participation-Log.png","datePublished":"2018-11-13T21:50:33+00:00","breadcrumb":{"@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/carbon-lighthouse-illuminating-energy-savings-with-machine-learning\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/d3.harvard.edu\/platform-rctom\/submission\/carbon-lighthouse-illuminating-energy-savings-with-machine-learning\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/carbon-lighthouse-illuminating-energy-savings-with-machine-learning\/#primaryimage","url":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Participation-Log.png","contentUrl":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Participation-Log.png","width":500,"height":126},{"@type":"BreadcrumbList","@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/carbon-lighthouse-illuminating-energy-savings-with-machine-learning\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/d3.harvard.edu\/platform-rctom\/"},{"@type":"ListItem","position":2,"name":"Submissions","item":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/"},{"@type":"ListItem","position":3,"name":"Carbon Lighthouse: Illuminating Energy Savings with Machine Learning"}]},{"@type":"WebSite","@id":"https:\/\/d3.harvard.edu\/platform-rctom\/#website","url":"https:\/\/d3.harvard.edu\/platform-rctom\/","name":"Technology and Operations Management","description":"MBA Student Perspectives","potentialAction":[{"@type":"性视界Action","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/d3.harvard.edu\/platform-rctom\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"}]}},"_links":{"self":[{"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/hck-submission\/28554","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/hck-submission"}],"about":[{"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/types\/hck-submission"}],"author":[{"embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/users\/11041"}],"replies":[{"embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/comments?post=28554"}],"version-history":[{"count":0,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/hck-submission\/28554\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/media\/33045"}],"wp:attachment":[{"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/media?parent=28554"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/categories?post=28554"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}