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Pomerleau, a large-scale infrastructure and construction company, was in search of an estimating and bidding software solution that would meet its requirements. The company needed a robust solution with advanced features to standardize the estimating and bidding process across the enterprise. A particular challenge was a complex project in the Montreal area consisting of the demolition and reconstruction of a bridge. The main difficulty in this project was the soil conditions, including underwater soil consolidation, large caissons, and an abutment directly on a very steep-angle rock surface.

Steed and Evans, a growing enterprise providing diverse services, ran into limitations with a spreadsheet-based estimating system developed in-house. They needed a more sophisticated and powerful alternative that could provide their estimators with a standard template and common resources. They also needed to enhance their field tracking and analysis capabilities while linking them directly to their estimating function. The company previously relied on its own Visual Basic program for field tracking and experimented briefly with Timberline before adopting the B2W solution.

Ripa & Associates, a civil construction company based in Tampa, Florida, was looking for an efficient way to manage their estimating process. The company had previously used HCSS Heavy Bid and Hard Dollar, but found these systems to be lacking in terms of reporting capabilities and ease of use. They needed a solution that would allow them to quickly see and modify cost, production, and other variables, and pass information to their management and accounting staff more quickly and efficiently.

R. Zoppo Corporation, a heavy construction leader in the Boston area, was relying on Excel spreadsheets for estimating and bidding. However, the limited capabilities of the spreadsheets no longer met its needs, prompting the company to search for a replacement in the form of a specialized estimating and bidding software solution. The company needed a solution that could enhance efficiency and accuracy, which are crucial to any construction company’s vitality.

Sherwood Companies, a diversified civil construction company, was facing challenges due to the use of multiple estimating systems across its various entities. The systems ranged from complex Excel workbooks and simple Excel spreadsheets, to Lotus and Quattro spreadsheets, to old-fashioned paper and pencil. One company had even purchased a standalone version of HCSS Heavy Bid, but never got it off the ground. The lack of a unified system was causing inefficiencies and complications in the estimating process. Furthermore, Sherwood often bids work for the Kansas and Oklahoma DOT’s, both of which have gone to mandatory electronic bidding, requiring a system that could integrate seamlessly with the DOT required bid files.

Team Fishel, a company specializing in the design and construction of utility and communication distribution networks, faced the challenge of standardizing its bid and estimating process across multiple divisions and supporting 125 estimators. The company operates out of multiple divisions and locations nationwide, working on a diverse array of projects for clients ranging from telecommunications, cable TV, gas and electric utilities to municipalities, government agencies, universities, commercial building owners, and residential real estate developers. The company needed a solution that would provide flexibility for estimators while allowing for standardization across the company.

C.A. Hull, a company specializing in full-service bridge construction and rehabilitation, was in search of an effective, streamlined software solution for its estimating and operations processes. The company wanted to move away from paper-based processes and adopt a more efficient system. The challenge was to find a solution that would be embraced by the employees and would improve the efficiency of their operations.

Lyndon Jones Construction, a general contractor based in Salt Lake City, Utah, had been using simple spreadsheets to handle their estimating process. They had even hired programmers to develop their own software. However, the company found that this approach was not efficient, especially when it came to facilitating prequalification bids. The company needed a solution that could streamline their estimating process and make it more efficient.

Romero General Construction was in need of a software package that would provide a centralized database to compartmentalize their resources and keep them organized. They were looking for a solution that would standardize the estimating and bidding process, keeping all of their estimators on the same page and eliminating the risk of errors. The company also wanted to save time and money by updating a specific part of the bid globally. Furthermore, they were looking to streamline their field tracking and analysis operations. Previously, reports were filled out by foremen in the field and faxed into the office, requiring someone to transcribe the report and enter it into the accounting system.

W.C. Spratt, a prominent sitework contractor in the Fredericksburg, Virginia region, was facing challenges with their existing manual, in-house systems for operations. The company was using spreadsheets for estimating which led to errors, delays, and added effort. Their in-house field tracking tool was not robust enough and lacked advanced reporting and a connection with estimates. The company was also struggling with maintaining their 130 assets and minimizing downtime.

EPC Services Company, a subsidiary of Electrical Consultants Inc., provides turnkey engineering, procurement, and construction management services for utility and power delivery projects throughout North America. The company typically works on three to five bids in any given week, with projects ranging in value up to $30 million. However, the company was facing challenges with its spreadsheet-based estimating system. The inability for multiple people to work on the same estimate at the same time was a major liability, especially for a company that operates out of several locations and on projects nationwide. The pressure to produce accurate bids in less time was also increasing, with project owners demanding bids in seven to ten days, compared to the three weeks EPC typically had in the past.

Minger Construction, a Minnesota-based company, was seeking to improve its safety, quality, and efficiency. The company had been using B2W Estimate and added unified elements from the ONE Platform to manage field tracking and analysis as well as resource scheduling and dispatching. However, they needed a solution to collect safety information more effectively and efficiently in the field and to get it to the office faster. They also wanted to be able to generate reports easily without the tedious, manual effort and sorting through papers that was required in the past.

Bluebird Contracting Services Ltd. and the Trotter & Morton Group of Companies were looking to transition from paper-based field data collection to a more efficient and accurate electronic system. The delay in getting information from the field about operations and safety was a significant issue with paper forms. The lag time hampered responsiveness as well as strategic decision making. The structure, integrity and even the legibility of data on paper forms were also problematic. They needed a solution that could provide real-time data from the field, enhance safety and performance, and offer immediate, event-triggered alerts and notifications.

Barriere Construction, a fourth-generation family-owned contractor, was struggling with inefficient paper-based processes for data collection and analysis. The company, which employs nearly 500 people to complete paving, heavy civil, and industrial construction projects across Louisiana and Mississippi, was finding it difficult to collect data effectively in the field and access it in real time across the enterprise. The long, labor-intensive path between paper forms and actionable intelligence was hindering the company's ability to make informed business decisions. The company was also struggling with an aggressive equipment auditing and inspection program that was paper-based, causing delays in identifying and correcting problems.

Kitsaki Projects, a company with close to 200 employees focusing primarily on utility-based construction projects in Saskatchewan, was facing challenges in their estimating and field tracking processes. They were using independent systems for these processes, which made it difficult to understand why some jobs were unsuccessful. Economic challenges in the Canadian market were forcing contractors to focus on improving efficiency and productivity through specialized software. Kitsaki's estimators previously relied on Excel spreadsheets to produce bids, but the process was long and prone to persistent errors. The company also had a paper-based process to get better and consistent visibility into productivity, labor, and materials in the field. However, this solution was too slow and cumbersome to keep the company competitive over the long-term.

Emil Anderson Construction, a company based in British Columbia, Canada, was facing challenges with their self-built solutions for estimating and field tracking. With the volume and complexity of work increasing, the limitations of their existing systems were becoming more apparent. They recognized the need for specialized applications and a unified solution. The company was also struggling with cohesive, coordinated estimating across several sites in British Columbia. Having multiple people work simultaneously on an estimate was impossible with the spreadsheet-based system. Incorporating input from estimators in different locations and keeping everything up to date was also a big challenge.

Triple B Services, a leading earthwork, highway, and utility contractor in southeast Texas, was facing challenges with their existing estimating process. The company was using Excel for estimating, which was slowing down their operations. The lack of integration with the Department of Transportation (DOT) and the inability to export data easily to their accounting and project management software were also significant issues. The company needed a solution that could streamline their estimating process, integrate with DOT, and export data to their accounting and project management software.

W.L. French Excavating Corporation, a family-owned company with 150 employees, was initially focused strictly on field operations, not software and computers. As the company grew and evolved, they realized the importance of technology in their success. They faced internal resistance, particularly from field and maintenance employees loyal to familiar, manual systems. The maintenance team relied on paper-based processes and whiteboards to manage more than 200 pieces of heavy equipment. Maintenance of equipment accounts for a significant percentage of their annual operating budget, and they saw a big opportunity to impact profitability through process improvement.

The Utah Valley University construction management program regularly participates in competitions to enhance the educational experience of its students. One such competition is the Associated Schools of Construction (ASC) competition, which is considered a must-attend event for students pursuing a degree in the field. In this competition, industry leaders offer active projects for students to solve. However, the students faced challenges in estimating and bidding on these projects due to the lack of effective tools. They had to rely on a combination of loosely integrated tools, including Excel, to estimate project costs. This approach limited their visibility into the overall project goals and hindered their ability to advance past the preliminary competitions.

M. A. Mortenson Company, a national leader in vertical commercial construction, was looking to expand into the self-perform horizontal markets, particularly civil work. This expansion drove the decision to implement B2W Estimate in 2013. The company needed an estimating software solution that was especially strong in supporting projects where they self-perform the majority of the work. They needed to be able to set up crew options in the software that included both labor and equipment and they needed the ability to easily report overall crew production rates as well as individual man-hour production rates.

Harry’s, a leader in the direct-to-consumer industry, faced a challenge with the explosion of new, disparate data feeds due to the diversity of product lines, retail outlets, and customers. The data science team needed to expedite the process of ingesting, transforming, and delivering these data feeds into a robust shared data model that connects all brand information across every retail delivery model. The retail analytics team needed a faster, simpler way to get new analytics up and running, and a platform to ingest and transform these disparate data feeds in a low-code sandbox environment. With a current ecosystem of mostly homegrown and open source solutions that rely on a heavily burdened data engineering team, it could take weeks to get new, critical retail data sources connected to Looker, the company’s business intelligence and analytics tool of choice.

Lumiata, a company focused on making healthcare smarter, was facing challenges with their data pipelines. They were using a mix of Apache Airflow, Apache Spark, Python and over 100,000 lines of custom code to create a Curated Table, which is the basis for their Data Science team to develop the Lumiata Insights. However, with increasing volumes of client data and faster SLA requirements, the process began to strain. Onboarding each new client required bespoke development and the over-extended data engineering team was responsible not only for this development, but also for maintaining and monitoring the pipelines, as well as the health and performance of the underlying Apache Spark jobs. The data science team required a certain amount of experimentation and iteration to develop the Lumiata Insights, but were completely dependent on data engineering to provide necessary adjustments to the Curated Table. This whole process would take six weeks or more, and induced a heavy maintenance burden to keep everything running. As the company looked to scale to take on more clients with their existing team, they needed a new approach.

EverQuote, a large online marketplace for insurance, was facing challenges with its in-house custom OLAP solution. The system, which was over ten years old, had several bottlenecks that prevented many use cases and suffered from poor query performance. As the company grew, it also found it difficult to scale self-service analytics to non-technical employees. The company needed a modern data architecture that could democratize data analytics for all.

PT Bank Rakyat Indonesia (BRI) was facing challenges with data analytics. They had performance issues when processing and visualizing their data. They also had storage and load time issues caused by moving data from the data lake into an RDBMS for visualization. Additionally, they had an issue with the processing time it took to provide data for queries. If they gave the wrong instructions, they would have to create, build and run each job over again. This was an inefficient and expensive way to provide executives with the analysis they use to make business decisions.

Tyson Foods, a global food giant, aimed to deliver self-service data analytics to its 144,000 employees. However, the company faced a significant challenge due to its fragmented data spread across diverse platforms. The primary goal of their analytics modernization journey was to better connect their data. With massive amounts of disparate data moving across data lakes, it was a challenge to navigate this information effectively. The business was stuck in an analog experience and needed to pursue a more scalable and flexible data strategy to stay competitive and successful.

When COVID-19 hit the US, public health officials scrambled to collect and analyze as much data as possible about the disease to better understand and share its impact with the public and Centers for Disease Control (CDC). The Boston Children’s Hospital (BCH) team introduced CovidNearYou.org as a way to crowdsource self-reported symptom data so that public health officials could derive insights about the spread of the disease across North America. Their challenge was to be able to quickly query all the data being collected from a variety of sources and visualize the results so that their research partners could identify patterns and stop the spread of the disease. It was a manual, time-consuming process.

Wayfair, a fast-growing ecommerce retailer, was facing challenges with its existing analytics infrastructure. The company was using Microsoft SQL Server Analysis Services (SSAS) for mission-critical analysis, but as the business grew, this solution was not scalable enough. Wayfair decided to modernize their analytics infrastructure and move to a cloud platform, specifically Google BigQuery. However, they needed to ensure that the transition didn't disrupt the hundreds of business analysts who relied on SSAS for their daily operations. The company also wanted to maintain a hybrid on-premises/cloud environment for a time to ensure business continuity.

Toyota, an international automotive company, was faced with the challenge of consolidating 35+ constituent North American companies into a single structure. This required a transformation of their data warehousing and analytics architecture across the business. The IT department was tasked with creating a semantic layer that supported high performance analytics that could be leveraged by all business analyst teams. Prior to the project’s implementation, analysts would often need to wait weeks for manual data engineering to take place. This delay hindered their ability to provide actionable insights on key business questions. The company's backend infrastructure was partly to blame for the slow query response time, as data was siloed across thousands of individual data marts.

Cardinal Health, a multinational healthcare services company, had a fragmented set of systems due to a series of acquisitions. This made managing and accessing data complicated. The company needed to forecast six months in advance to make sound business decisions, but business analysts across the pharmaceutical, corporate, and medical business lines didn’t have easy access to data for analytics and reporting. In addition, many business systems analysts (BSAs) were using shadow IT or unapproved applications to track metrics. As Cardinal Health moved into the future, the company needed to simplify its data landscape to streamline data and analytics access throughout the organization.

The Company’s operational data was siloed and difficult to access. Users wanted to leverage modern BI tools such as Tableau and Excel, and were being forced to extract data from databases and work with local copies. This “pump and dump” strategy of extracting data and working locally meant analytics were scattered across employees’ desktops, data governance and accuracy problems were endemic and the Company struggled to maintain one single version of the truth for their analytics. The Company developed strict criteria for their intended data solution: Ease of Use, Tool Agnostic, Disruption Free, and Single Source of Truth.