Growing heavy civil construction business brings on a modern data stack of Fivetran, BigQuery and Looker to gain a competitive edge.
As a traditional company, Emery Sapp & Sons spent hours doing manual reporting in Excel. The business needed to bring on a modern data stack to centralize on-premises and cloud-based systems into a data warehouse and to conduct deeper analysis on its data. With Fivetran, BigQuery and Looker, the Director of Technology regains 20% of time previously spent on data pipelines and builds out critical dashboards for revenue, branches, jobs and more. In an industry with small margins data is key to improving efficiencies and gaining a competitive edge.
Destination: Google BigQuery
Business Intelligence: Looker
Emery Sapp & Sons, Inc., headquartered in Columbia, Missouri, is a heavy civil construction company, focused on ground level and below. The business does everything from small residential jobs up to multi-million dollar, multi-year state and federal highway jobs. The business has grown organically and through acquisitions in recent years, requiring a more aggressive and successful corporate strategy for successful expansion.
Making better data-driven decisions at scale requires utilizing data and automating processes, rather than only relying on instinct. As Clayton Hicklin, Director of Technology, explains:
A ton of data is generated on a daily basis in construction. We have the usual administrative, financial and labor workforce data, but we also have data coming in from the field such as time spent on a job and a location, equipment runtime and utilization, and units of production. The only way we can grow and compete on a larger scale is by being smarter about our data and our tools.
Working with a consultant, Emery Sapp & Sons brought on a business intelligence (BI) tool but adoption was low. As a traditional company, people remained in Excel, sticking to the processes they were used to. Time was spent on manual work that tended to result in pulling inconsistent answers from different systems. While Excel is a great tool, it isn’t suited for BI at scale, and leaves room for inconsistency and human error.
Hicklin knew it was time to reinvest in a modern data stack to centralize on-prem and cloud-based systems into a warehouse from which the business could conduct real-time data analysis at scale and speed. This decision to modernize required a cultural shift from static, tabular reports and spreadsheets to a live data environment.
When Hicklin set out to build the data stack, he had a mission in mind:
"We now have a guiding principle: leverage cloud solutions when and where it makes sense to do so. I don’t want a team of people babysitting our architecture. We’re a construction company not an IT company."
He landed on BigQuery for a data warehouse, naming platform security and Cloud Identity Access Management (IAM) with Google Workspace as key factors. The next step was an evaluation of BI tools, which led him to Looker:
"We’re trying to accomplish a self-service environment and increase the level of data quality. Looker is user-friendly – data models are defined and exposed to the end-user and it’s very easy to show someone how to build their own queries and visualizations. With the LookML modelling layer, we can create a consistent view of our data. The version control and governance we have with Looker is something we felt that other tools couldn’t match."
The last piece of the puzzle was the data pipeline. Hicklin had started building scripts himself, and while he could maintain one or two sources, he knew it wasn’t sustainable or scalable. With Fivetran, he offloads pipeline management entirely, resulting in large time-savings:
"My goal is to unload the technical headache and maintenance involved with building pipelines. With Fivetran, we don’t require any technical expertise to maintain our data pipeline. I’m saving so much time that I actually shudder thinking about the past. I spent at least a day a week on pipeline management. Without Fivetran, I’d have to hire a dedicated engineer to maintain our current stack."
Within the first few months, Emery Sapp & Sons was leveraging insights from Looker reports and dashboards to transform the business. Manual processes are being eliminated and time is being saved as employees take advantage of the automation. Some of the key initial dashboards and reports the team build include:
Fuel report. Previously, it took 5-6 hours a month to generate the report which is now a real-time dashboard that helps teams more quickly identify large variances, unusual spending habits, etc., to react more quickly to a potential problem.
Revenue summary dashboard. A live dashboard that branch managers use daily which monitors what the business bills, the amount owed and paid, and progress against monthly and yearly targets. Building this dashboard included consolidating disparate accounting data from the three different accounting systems used by the three different legal entities of Emery Sapp & Son into BigQuery and mapping that data to standard dimensions for enterprise-wide reporting. This results in a holistic view of enterprise financial performance to set expectations with the board and a standardized understanding of performance for branch managers.
Accounts receivable dashboard. Shows total amount billed, outstanding and paid and the associated ageing. Comments inputted into Google Sheets sync into BigQuery and appear in the Looker report. Previously, this was a weekly report that took over two hours to run and was immediately stale.
Branch manager dashboard. Displays key metrics for each branch, including the revenue summary and accounts receivable summary, that are used to guide the day-to-day operations of the business.
Job Summary. Displays the top data points about individual jobs, which the business may soon embed into a public-facing website so customers can easily see milestones, progress and more.
By eliminating manual ETL, the entire company benefits. End-users no longer need to do manual Excel work and have moved from tabular, transaction-based reports to working with interactive key metrics that pinpoint specific performance measures. Individuals are dedicating their time towards more valuable activities rather than repetitive tasks. The technical team that Hicklin is building can put its energy towards strategy and analysis rather than the nuts and bolts of the tech stack. Ultimately, having that time back is helping the business gain a competitive edge, as Hicklin explains:
"The most significant results of our modern stack are the time savings and data consistency. The quantity of data we generate will only grow as we grow. We operate on narrow margins, so we have to work faster and smarter to improve efficiency and gain a competitive edge. Data is key to achieving that."
About Fivetran: Shaped by the real-world needs of data analysts, Fivetran technology is the smartest, fastest way to replicate your applications, databases, events and files into a high-performance cloud warehouse. Fivetran connectors deploy in minutes, require zero maintenance, and automatically adjust to source changes — so your data team can stop worrying about engineering and focus on driving insights.
About BigQuery: BigQuery is Google’s serverless, highly scalable, enterprise data warehouse designed to make all your data analysts productive at an unmatched price performance.
About Looker: Looker is the business intelligence (BI) and analytics platform part of the Google Cloud data and analytics suite. Transcending traditional BI, Looker powers data experiences that deliver actionable business insights at the point of decision and infuses data into products and workflows to allow organizations to extract value from data at web-scale.
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