Data Validation | Page 2 of 5 | Locus Technologies

Artificial Intelligence & Blockchain Applied to Water & Energy

There are two promising technologies that are about to change how we aggregate and manage EHS+S data: artificial intelligence (AI) and blockchain. When it comes to technology, history has consistently shown that the cost will always decrease, and its impact will increase over time. We still lack access to enough global information to allow AI to make a significant dent in global greenhouse gas (GHG) emissions by merely providing better tools for emissions management. For example, the vast majority of energy consumption is wasted on water treatment and movement. AI can help optimize both. Along the way, water quality management becomes an add-on app.

AI is a collective term for technologies that can sense their environment, think, learn, and act in response to what they’re detecting and their objectives. Possible applications include (1) Automation of routine tasks like sampling and analyses of water samples, (2) Segregation of waste disposal streams based on the waste containers content, (3) Augmentation of human decision-making, and (4) Automation of water treatment systems. AI systems can greatly aid the process of discovery – processing and analyzing vast amounts of data for the purposes of spotting and acting on patterns, skills that are difficult for humans to match. AI can be harnessed in a wide range of EHS compliance activities and situations to contribute to managing environmental impacts and climate change. Some examples of applications include permit interpretation and response to regulatory agencies, precision sampling, predicting natural attenuation of chemicals in water or air, managing sustainable supply chains, automating environmental monitoring and enforcement, and enhanced sampling and analysis based on real-time weather forecasts. Applying AI in water resource prediction, management, and monitoring can help to ameliorate the global water crisis by reducing or eliminating waste, as well as lowering costs and lessening environmental impacts. A similar analogy holds for air emissions management.

The onset of blockchain technology will have an even bigger impact. It will first liberate data and, second, it will decentralize monitoring while simultaneously centralizing emissions management. It may sound contradictory, but we need to decentralize in order to centralize management and aggregate relevant data across corporations and governmental organizations without jeopardizing anyone’s privacy. That is the power of blockchain technology. Blockchain technology will eliminate the need for costly synchronization among stakeholders: corporations, regulators, consultants, labs, and the public. What we need is secure and easy access to any data with infinite scalability. It is inevitable that blockchain technology will become more accessible with reduced infrastructure over the next few decades. My use of reduced architecture here refers to a replacement of massive centralized databases controlled by one of the big four internet companies using the hub-and-spoke model concept with a device-to-device communication with no intermediaries.

This post was originally published in Environmental Business Journal in June of 2020.

The Horrors of Excel for Data Management

Locus has been preaching on the pitfalls of Excel for a long time. It’s no surprise that one of the worst imaginable errors in Excel that could’ve happened, did. Almost 16,000 COVID-19 cases in England went unreported because Public Health England hit the maximum row count in their version of Excel.

This is not the only example of Excel being misused or being the wrong tool entirely for the job. Excel is not in any way a data management system for complex or vital data. When it comes to sustainability reporting and environmental data management, the evils of the grid are a force to be reckoned with. We have highlighted a few examples that will have you shivering.

Case 1: The Evils of Autofill

Take a look at this harmless-looking chart. It shows monthly electricity consumption for a facility set to report:

Month	Monthly Electricity Consumption (MWh)
January 2019	133,500
February 2019	122,400
March 2019	138,900
April 2019	141,600
May 2019	141,601
June 2019	141,602
July 2019	141,603
August 2019	141,604
September 2019	141,605
October 2019	141,606
November 2019	141,607
December 2019	141,608

During review, the auditor notices a distinct trend from April to December, indicating false data overwritten by a stray double-click. Eventually, the auditor required re-entering all invoice data for dozens of facilities to correct the issue. Where the original data went and how autofill went astray remains a mystery.

Case 2: The Phantom File Editor

Imagine using a massive spreadsheet with lots of linked calculations for your annual sustainability report. One of the team engineers works on the file to input more data and get it ready for presentation. But in the final steps, they accidentally delete one of the formulas that sum up the indicators. The annual total looks great for the presentation since you’ve effectively removed a portion of your resource consumption, but afterwards you discover the conclusions were incorrectly calculated. How did that error get introduced? The spreadsheet has no auditing capabilities on the individual values, so you may never know.

Excel supports multiple users editing one document simultaneously, but not well. Multiple records are saved, edits are lost, and vital data vanishes, or at best is very hard to recover. The Track Changes feature is not infallible, and over reliance on it will cause hardship.

Case 3: Date of the Dead

Excel has a frustrating insistence of changing CAS numbers into dates, even if they are something like “7440-09-7″ turning into September 7, 7400. If you’re not explicit in your cell formatting, Excel isn’t happy leaving values as they are.

Case 4: Imposter Numerical Values

You meant to type 1.5, but you typed “1..5” or “.1.5”. Does Excel reject these imposter numbers or let you know of a potential error? No, it’s stored in Text format. This can throw off any averages or sums you may be tracking. This minor identity theft can cause a real headache.

Other Significant Cases:

Other data quality issues with using Excel include, but are not limited to:

Locations with multiple variations of the same ID/name (e.g., MW-1, MW-01, MW 1, MW1, etc.)
Use of multiple codes for the same entity (e.g., SW and SURFW for surface water samples)
Loss of significant figures for numeric data
Special characters (such as commas) that may cause cells to break unintentionally over rows when moving data into another application
Bogus dates like “November 31” in columns that do not have date formats applied to them
Loss of leading zeros associated with cost codes and projects numbers (e.g., “005241”) that have only numbers in them but must be stored as text fields
The inability to enforce uniqueness, leading to duplicate entries
Null values in key fields (because entries cannot be marked as required)
Hidden rows and/or columns that can cause data to be shifted unintentionally or modified erroneously
Inconsistent use of lab qualifiers— in some cases, these appear concatenated in the same Excel column (e.g., “10U, <5”) while in other cases they appear in separate columns

As you can see, the horrors of Excel are common, and terrifying. Without a proper system of record, auditing features, and the ability for data to vanish into the ephemera, Excel offers little in the way of data security and quality for organizations managing vital environmental and compliance data. Many are learning firsthand the superiority of database management systems over spreadsheets when it comes to managing data. Now is the time to examine the specific shortcomings of your current system and consider your options.

Contact us today to learn how Locus makes complex data management a little less spooky!

6 Ways To Get Data Into Your EHS System

Locus provides multiple methods to populate EHS, ESG, or any environmental data, including the following:

Integrations

Locus provides a full suite of REST API’s, and SDK that can be used to populate data from external data sources. Typical uses include utility data, CEMS, meter data and IoT data.

Surveys

Locus Survey tool enables you to issue survey questionnaires to people outside your organization, and enables them to securely and seamlessly respond directly into the survey form. Typical uses include supplier surveys, audits and customer questionnaires.

Mobile

User input forms can be optimized for input on a phone or tablet, which allows quick uploads of photos and also geotags your data so you can ensure it was collected at the right location.

Excel and Text Files

Locus provides a full suite of Excel upload tools that allow you to import data directly from Excel or CSV files. This option also allows you to work offline and re-sync your data later. Typical uses include laboratory data, periodic monitoring data and data migrations.

Manual Data

Like any system, Locus provides tools for users to directly enter data into the system. These include Locus sophisticated data validation tools which employs machine learning techniques to identify data entries which may be invalid, with visual indications of the expect range or ranges.

Email

Locus can be configured to directly read email input (as text) and place it into the system. Typical uses include instances where external users initiate a conversation, which then may be responded to from within the system, such as an inquiry, issue, or an incident report.

Contact us to learn more

Send us your contact information and a Locus representative will be in touch to discuss your organization’s environmental data management needs and provide an estimate, or set up a free demo of our enterprise environmental software solutions.

5 Keys to Navigating ESG

With sustainability practitioners strained to deploy limited resources internally to navigate the myriad of standards and frameworks to meet the growing appetite for environmental, social, and governance (ESG) information, we continue to ask, “Isn’t there an easier way to do this?” Anyone who has worked to align standards and frameworks, corral internal champions around disclosure requirements, and marry quantitative performance data with narratives on management approach, knows that this is no easy feat.

The uphill battle to integrate data and other systems is often complicated by trying to pull others along in the organization—regardless of where their hearts lie.

So how is it that we can focus in on what’s relevant and minimize the reporting burden on others?

At the risk of seeming to oversimplify the process, I’ll attempt to breakdown some of the concepts mentioned here as a means for peering through the gray. The following five points have been central to my years of guiding organizations through this process.

1: Navigating the myriad of standards and frameworks:

Not only are there the long-time warriors (the Global Reporting Initiative, CDP, and the Sustainability Accounting Standards Board now merged with the International Integrated Reporting Counsel labeled as the Value Reporting Foundation), there are also larger north star initiatives, like the United Nation’s Global Compact or Sustainable Development Goals, and even those that are industry specific, like the Global Real Estate Sustainability Benchmark. There are also the investor-driven ratings and rankings, supply chain initiatives, and mandates disclosure requirements that organizations must contend with. Not everyone is blessed with sustainability departments powered by specialists of all types. In fact, most are managed by 1-3 individuals who often juggle multiple roles until they can prove the importance of an integrated strategy and leverage additional support. In the end, standards alignment comes down to one person dropping all disclosure requirements into an excel spreadsheet to make sense of all that is needed. There is no harm in this. It is a recommended first step in trying to better understand the nuances between all that is asked and whether it is possible to pull data to meet various requirements. The goal eventually, of course, is to automate reporting against all applicable requirements. Usually companies start by developing a comprehensive list of all that they can disclose, either initially or in the future. The key is not to exclude areas that the company is unable to immediately disclose on, but to press the “pause” button and keep those items in the horizon as areas that should be revisited in the future. Instead, stating where one is in the journey to retrieve information and manage inherent risks, while providing data for what is possible, is recommended. In that, clear “omissions” or “exclusions to the boundary” should be noted.

2: Determining the qualitative vs. quantitative:

Be it labor standards, human rights, training and education, resource consumption or greenhouse gases, there are both qualitative and quantitative features to grasp and disclose an organizations’ impacts. Granularity is based on what the organization is trying to achieve by pursuing efforts in a certain area. Will the level of detail provide a sharper view of potential risks? Will the data enable decision-making? Will it demonstrate the level of transparency the organization is willing to provide to match disclosure among its peer group? Will it result in greater recognition or even, leadership status? By asking these questions, organizations can determine their priorities and narrow in on data tracking mechanisms to pull, house, and analyze detail. Keep in mind, however, taking inventory always presents surprises. Try not to go down a rabbit hole searching for data that doesn’t exist or isn’t relevant considering the larger footprint. Report on what is available and explain what is being accounted for, what is missing, and why.

3: Pull others along:

Frameworks, data, and the endless requests for disclosure are enough to make anyone question their sanity—let alone the ongoing education that is needed to bring others along the path towards greater sustainability. Up until about five years ago, the role of the sustainability champion was often a lone wolf in the organization who felt committed to the charge. Boards were not involved, and it was because few companies saw sustainability as a strategic imperative. Today, it’s no longer effective to go at this alone. Markets have begun to regulate this space: the fear of shareholder resolutions, and the inability to access capital due to a lack of demonstrated ESG commitments, risk management, and performance disclosure has catapulted the need to activate players across functions. Regardless of standard, framework, or reporting platform, governance is critical to ensuring that sustainability sticks. It’s not enough to simply describe the organizational and leadership structure, but to describe how and where sustainability or ESG risk management sits within and what the role of the Board is. The sustainability coordinator, or Chief Sustainability Officer’s structure the group to facilitate action. Constant education and hand holding is necessary to inform the working group on the rapidly changing landscape and what is needed to maintain a license to operate from the stakeholder perspective.

4: Minimize the reporting burden:

If it’s not clear by this point, all that matters when it comes to reporting is 1) performance data, 2) an explanation of management approach, and 3) a description of your processes undertaken to identify material matters and manage risks. Stories and imagery provide color but not an overview of what the organization is doing to manage impacts. Begin by structuring your website to highlight data. Embedd data from GRI, the SDGs, and/or SASB indexes as companies such as Ball Corporation, BlackRock, and Coca-Cola. All have focused more efforts on tangible reduction and reuse, rather than creating beautiful communication pieces. This allows them to focus time and resources on doing the work that matters.

5: Data collection:

As the saying goes, “what doesn’t get measured doesn’t get managed.” Pulling data from the ESG pillars and across functions often means that the data collection process tends to take shape like a patch work quilt. Utilizing an integrated, configurable system that can extract and consolidate data into a single source of truth allows companies to focus on results, rather than begging for data from sources internal and external to their organization. Where possible, automate the data collection process, and provide decision-making analytics that can be transferred to various disclosure platforms to streamline the process and further minimize the reporting burden.

Hopefully, these points will help reassure you that you’re on the right path. The reality is, there is no easy way. Many of the front movers know this all too well. Their approach has taken years to solidify. In addition to the 5 points listed above, try to remember that it is important to just get started. Improvements can be made over time and lessons aren’t typically learned through perfection.

[sc_image width=”150″ height=”150″ src=”23979″ style=”11″ position=”centered” disable_lightbox=”1″ alt=”Nancy Mancilla, ISOS Group”]

About the Author—Nancy Mancilla, ISOS Group

Ms. Mancilla is the CEO and Co-Founder of ISOS Group, a full services sustainability consultancy firm also recognized for its leadership as a GRI and CDP Certified Training Partner in the U.S. Since establishing the company, Nancy has orchestrated 300+ Certified Trainings, co-taught MBA programs, regularly serves as a conference guest speaker and thought leader on the non-financial reporting process. In addition to educational services, ISOS Group provides organizations of all types with sustainability assessments, reporting guidance and external assurance.

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Automate Your Vapor Intrusion Management

The Vapor Intrusion tools in Locus’ Environmental Information Management (EIM) software solve the problem of time-consuming monitoring, reporting, and mitigation by automating data assembly, calculations, and reporting.

Quickly and easily generate validated reports in approved formats, with all of the calculations completed according to your specific regulatory requirements. Companies can set up EIM for its investigation sites and realize immediate cost and time savings during each reporting period.

Contact us to see the Vapor Intrusion tool in action

Send us your contact information and a Locus representative will be in touch to discuss your organization’s environmental data management needs and provide an estimate, or set up a free demo of our enterprise environmental software solutions.

Getting Started With ESG Is Less Daunting Than You Think

One of the most frequent questions we get asked when it comes to ESG is, “Where do I begin?”. For many companies, the process of getting started with a new ESG program is the most difficult step. With nearly 1,700 frequently evolving ESG reporting protocols available, it can be daunting just to determine where to begin. This uncertainty associated with ESG reporting can unfortunately paralyze any progress for several organizations. The good news is that ESG doesn’t have to be an ‘all or nothing’ effort. In fact, getting started is a simple and straightforward process.

Regardless of what ESG reporting program you choose (or eventually choose), there are many common elements that can form the basis of your organization’s ESG program. Although social and governance KPIs have been undergoing rapid evolution recently, environmental KPIs have been comparatively stable. Environmental KPIs tend to be quantitative with established calculation methodologies, whereas the definitions and determinations as to what is important regarding societal and governance factors and how to measure them are still being evaluated globally. Considering this, many companies elect to start their ESG reporting program using monitoring and collecting environmental data.

Additionally, almost all reporting programs include the concept of a baseline, or a time period against which future ESG metrics are compared. Developing the baseline requires a good understanding of your organization’s current ESG performance, which of course requires a good set of data. Universal data that is required for any ESG reporting program includes data on greenhouse gas, water quality and consumption, waste, and energy consumption. The bedrock of an ESG program starts with the collection, management, and reporting of these data. This information can also help to inform further decisions for your ESG program, including which framework is most appropriate for your organization.

As part of this effort, you should make sure you are collecting and calculating your ESG metrics with software that supports the required complexity of environmental data. Often the companies who suggest a turnkey solution to ESG reporting are not only lacking in social and governance data, but are woefully underprepared and unequipped to handle environmental data as well. With over 25 years of experience in creating software for environmental reporting, Locus Technologies is equipped to help organizations collect and report ESG data in a way that others aren’t.

Contact Us to Get Started Today

Combat Green Skepticism with Accurate ESG Data

Greenwashing, or the presenting of misinformation to create a sustainable image, is common among organizations. While many consumers may not be aware with the term greenwashing, they are aware of how common it is. In fact, consumers are so aware of this trend that they’re overwhelmingly skeptical of all organizations presenting themselves as sustainable. Four out of every five consumers have expressed skepticism of organizations claiming to be sustainable. So, how does your company express your sincere desire to take steps that are sustainable for the environment? With accurate and transparent data.

With 2/3 of consumers seeking out companies that emphasize sustainable practices, the temptation to greenwash is certainly enticing. Sometimes it comes in the form of making irrelevant claims, like saying a product is free of something that is banned (like CFCs). Other times it comes in the form of half-truths, like saying that a product is sustainably sourced, despite the manufacture of the product being unsustainable or harmful to the environment. Any way you look at it, the demand for sustainable products is so high, as is the temptation to greenwash. The truest, and least disputable way to combat greenwashing is by collecting and reporting your data accurately.

Sustainability is now a broad umbrella term that encompasses not only environmental practices, but social and corporate governance as well, better known as ESG. This broadness reflects a change in consumer attitudes from generation to generation, perceiving more than environmental practices as important while holding environmental practices to the microscope. In fact, over 75% of Gen X consumers say that they have to trust a brand before purchasing from them, and over 85% of Millennial and Gen Z consumers say they same. This trust encompasses everything from the use of organic ingredients to company wellness practices, and is reinforced with buying practices. To do environmental, social, and corporate governance right, organizations have taken a data-first approach.

With Locus Technologies, you can take concrete steps towards achievable ESG goals. By taking a fully-digital approach, your organization can make the transformation by maintaining full visibility of raw sustainability data, calculations, and other factors, and also keeping data easily accessible and traceable. Reports are fully traceable back to the source, and are indisputable, allowing for increased trust from consumers or anyone else who has a stake in this information. Given that 7/10 consumers are willing to pay a premium to sustainable-minded companies who are fully transparent with their efforts, this move can provide a significant return on investment in the short term.

The benefits of data centralization also go beyond combatting greenwashing. A fully-digital and streamlined process will improve your ability to handle the data appropriately, and will ease any auditing and reporting responsibilities moving forward, making the entire process cheaper and faster.

With brand loyalty and purchasing decisions being reliant on sustainable decisions, the move to accurate and transparent data management is key. By implementing Locus Technologies ESG software, your organization can employ cutting-edge solutions to combat greenwashing by promoting your sustainability goals and actions transparently and accurately.

Request an online demo of our ESG solutions

Quicker Data Searching with Natural Language Processing

The recent year of lockdowns pushed many daily activities into the virtual world. Work, school, commerce, the arts, and even medicine have moved online and into the cloud. As a result, considerably more resources and information are now available from an internet browser or from an application on a handheld device. To navigate through all this content and make sense of it, you need the ability to quickly search and get results that are most relevant to your needs.

You can think of the web as a big database in the cloud. Traditionally, database searches were done using a precise syntax with a standard set of keywords and rules, and it can be hard for non-specialists to perform such searches without learning programming languages. Instead, you want to search in as natural a matter as possible. For example, if you want to find pizza shops with 15 miles of your house that offer delivery, you don’t want to write some fancy statement like “return pizza_shop_name where (distance to pizza shop from my house < 15 miles) and (offers_delivery is true). You just want to type “what pizza shops within 15 miles of my house offer delivery?” How can this be done?

Enter the search engine. While online search engines appeared as early as 1990, it wasn’t until Yahoo! Search appeared in 1995 that their usage became widespread. Other engines such as Magellan, Lycos, Infoseek, Ask Jeeves, and Excite soon followed, though not all of them survived. In 1998, Google hit the internet, and it is now the most dominant engine in use. Other popular engines today are Bing, Baidu, and DuckDuckGo.

Current search engines compare your search terms to proprietary indexes of web page and their content. Algorithms are used to determine the most relevant parts of the search terms and how the results are ranked on the page. Your search success depends on what search terms you enter (and what terms you don’t enter). For example, it is better to search on ‘pizza nearby delivery’ than ‘what pizza shops that deliver are near my house’, as the first search uses less terms and thus more effectively narrows the results.

Search engines also support the use of symbols (such as hyphens, colons, quote marks) and commands (such as ‘related’, ‘site’, or ‘link’) that support advanced searches for finding exact word matches, excluding certain results, or limiting your search to certain sites. To expand on the pizza example, support you wanted to search for nearby pizza shops, but you don’t want to include Nogud Pizza Joints because they always put pineapple on your pizza. You would need to enter ‘pizza nearby delivery -nogud’. In some ways, with the need to know special syntax, searching is back where it was in the old database days!

Search engines are also a key part of ‘digital personal assistants’, or programs that not only perform searches but also perform simple tasks. An assistant on your phone might call the closest pizza shop so you can place an order, or perhaps even login to your loyalty app and place the order for you. There is a dizzying array of such assistants used within various devices and applications, and they all seem to have soothing names such as Siri, Alexa, Erica, and Bixby. Many of these assistants support voice activation, which just reinforces the need for natural searches. You don’t want to have to say “pizza nearby delivery minus nogud”! You just want to say “call the nearest pizza shop that does delivery, but don’t call Nogud Pizza”.

Search engine and digital personal assistant developers are working towards supporting such “natural” requests by implementing “natural language processing”. Using natural language processing, you can use full sentences with common words instead of having to remember keywords or symbols. It’s like having a conversation as opposed to doing programming. Natural language is more intuitive and can help users with poor search strategies to have more successful searches.

Furthermore, some engines and assistants have artificial intelligence (AI) built in to help guide the user if the search is not clear or if the results need further refinement. What if the closest pizza shop that does delivery is closed? Or what if a slightly farther pizza place is running a two-for-one special on your favorite pizza? The built-in AI could suggest choices to you based on your search parameters combined with your past pizza purchasing history, which would be available based on your phone call or credit charge history.

Searching in Locus EIM

The Locus team recently expanded the functionality of the EIM (Environmental Information Management) search bar to support different types of data searches. If a search term fits several search types, all are returned for the user to review.

Functionality searches: entering a word that appears in a menu or function name will return any matching menu items and functions. For example, searching for ‘regulatory exports’ returns several menu items for creating, managing, and exporting regulatory datasets.
Help searches: entering a word or phrase that appears in the EIM help files will return any matching help pages. For example, ‘print a COC’ returns help pages with that exact phrase.
Data searches: entering a location, parameter, field parameter, or field sample will return any matching data records linked with that entity. For example, searching for the parameter ‘tritium’ returns linked pages showing parameter information and all field sample results for that parameter. Searching for the location ‘MW-1’ returns linked pages showing all field samples, groundwater levels, field measurements, and field sample results at the location.

EIM lets the user perform successful searches through various methods. In all searches, the user does not need to specify if the search term is a menu item, help page, or data entity such as parameter or location. Rather, the search bar determines the most relevant results based on the data currently in EIM. Furthermore, the search bar remembers what users searched for before, and then ranks the results based on that history. If a user always goes to a page of groundwater levels when searching for location ‘MW-1’, then that page will be returned first in the list of results. Also, the EIM search bar supports common synonyms. For example, searches for ‘plot’, ‘chart’, and ‘graph’ all return results for EIM’s charting package.

By implementing the assistance methods described above, Locus is working to make searching as easy as possible. As part of that effort, Locus is working to add natural language processing into EIM searches. The goal is to let users conduct searches such as ‘what wells at my site have benzene exceedances’ or perform tasks such as ‘make a chart of benzene results’ without having to know special commands or query languages.’

How would this be done? Let’s set aside for now the issues of speech recognition – sadly, you won’t be talking to EIM soon! Assume your search query is ‘what is the maximum lead result for well 1A?’

First, EIM extracts key terms and modifiers (this is called entity recognition). EIM would extract ‘maximum’, ‘lead’, ‘result’, ‘well’, and ‘1A’, while ignoring connecting words such as ‘the’ or ‘for’.
Then, EIM categorizes these terms. EIM would be ‘trained’ via AI to know ‘lead’ is mostly used in environmental data as a noun for the chemical parameter, and not a verb. ‘Result’ refers to a lab result, and ‘well’ is a standard sampling location type.
EIM then runs a simple query and gets the maximum lead result for location 1A.
Finally, EIM puts the answer into a sentence (‘The maximum lead result at location 1A is 300 mg/L on 1/1/2020’) with any other information deemed useful, such as the units and the date.

A similar process could be done for tasks such as ‘make a chart of xylene results’. In this case, however, there is too much ambiguity to proceed, so EIM would need to return queries for additional clarifications to help guide the user to the desired result. Should the chart show all dates, or just a certain date range? How are non-detects handled? Which locations should be shown on the chart? What if the database stores separate results for o-Xylene, m,p-Xylene, plus Xylene (total)? Once all questions were answered, EIM could generate a chart and return it to the user.

Natural language is the key to helping users construct effective searches for data, whether in EIM, on a phone, or in the internet. Locus continues to improve EIM by bringing natural language processing to the EIM search engine.

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[sc_image width=”150″ height=”150″ src=”16303″ style=”11″ position=”centered” disable_lightbox=”1″ alt=”Dr. Todd Pierce”]

About the Author—Dr. Todd Pierce, Locus Technologies

Dr. Pierce manages a team of programmers tasked with development and implementation of Locus’ EIM application, which lets users manage their environmental data in the cloud using Software-as-a-Service technology. Dr. Pierce is also directly responsible for research and development of Locus’ GIS (geographic information systems) and visualization tools for mapping analytical and subsurface data. Dr. Pierce earned his GIS Professional (GISP) certification in 2010.

Streamline and Save on Your Title V Reporting

Simplify your air quality data management and reporting with Locus’ unified software solution. Our Air Quality application resolves most common issues with managing and submitting your site emissions data. Locus handles all required regulatory data from your facilities in one centralized platform and makes it possible to streamline your tracking and reporting requirements for programs such as Title V, GHG, Fenceline, and LCFS.

Contact us to see a demo of the Air Quality app

Streamline and Save on Your DMR Reporting

The DMR tool in Locus’ Environmental Information Management (EIM) software solves the problem of time-consuming, labor-intensive, and expensive manual report generation by automating the data assembly, calculations, and formatting of Discharge Monitoring Reports. Depending on the type of discharge and the regulatory jurisdiction, you may be required to report information such as analytical chemistry of pollutants, flow velocity, total maximum daily load, and other parameters. For companies that report on multiple facilities, producing a DMR also becomes a major expense.

Thanks to Locus’ DMR tool, companies can generate DMRs within minutes with validated data in approved formats, with all of the calculations completed according to regulatory requirements. Companies can set up EIM for its permitted facilities and realize immediate cost and time savings during each reporting period. Locus users have saved over $2,000,000 on DMR reporting.

Locus continues to enhance the Discharge Monitoring Report (DMR) tool, recently implementing calculations needed to handle reporting of divalent metals. New formats, such as Florida DEP ezDMR, are regularly being added, so customers can meet their reporting requirements.

Artificial Intelligence & Blockchain Applied to Water & Energy

6 Ways To Get Data Into Your EHS System

Integrations

Surveys

Mobile

Excel and Text Files

Manual Data

Email

Contact us to learn more

Send us your contact information and a Locus representative will be in touch to discuss your organization’s environmental data management needs and provide an estimate, or set up a free demo of our enterprise environmental software solutions.

5 Keys to Navigating ESG

1: Navigating the myriad of standards and frameworks:

2: Determining the qualitative vs. quantitative:

3: Pull others along:

4: Minimize the reporting burden:

5: Data collection:

Automate Your Vapor Intrusion Management

Contact us to see the Vapor Intrusion tool in action

Send us your contact information and a Locus representative will be in touch to discuss your organization’s environmental data management needs and provide an estimate, or set up a free demo of our enterprise environmental software solutions.

Getting Started With ESG Is Less Daunting Than You Think

Contact Us to Get Started Today

Combat Green Skepticism with Accurate ESG Data

Request an online demo of our ESG solutions

Quicker Data Searching with Natural Language Processing

Searching in Locus EIM

Streamline and Save on Your Title V Reporting

Contact us to see a demo of the Air Quality app

Streamline and Save on Your DMR Reporting

Contact us to see the DMR tool in action

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