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The concept of "repeatability" in construction is more than simply, “If it works, do it again.” It’s about knowing what exactly worked, why it worked and how to continuously replicate and improve upon that success. That type of strategic understanding requires a precise and comprehensive approach to data. 

Collecting and analyzing data on various phases of projects — such as site selection, resource allocation and operational efficiency — can help to streamline processes, minimize waste and errors, make the most informed decisions possible and reduce risk dentifying potential issues and implementing mitigation strategies ahead of time.

Here are five mindsets needed to master data-driven repeatability, with a focus on renewable energy construction. 

1. Embrace predictive analytics.

Predictive analytics uses data from past projects to help make informed decisions on future projects, such as helping with the abilities to optimize site selection, improve resource management and prevent and manage risk.

During site selection, teams identify ideal sites by using data on weather patterns, permitting processes and proximity to consumption zones. Maximize performance with predictive models, such forecasting sunlight availability to determine ideal spots for solar panel placement or analyzing wind patterns to guide turbine positioning. 

Teams can also improve overall resource management by using data to identify potential challenges, minimize downtime and manage availability and locations for materials, equipment and workers. 

Data is also a powerful tool to forecast potential risks before they become issues, such as supply chain disruptions or equipment failures. 

Data-driven decision making and replicable project outcomes require investing in predictive analytics training and tools. Many construction software programs help gather, store and visualize data from different departments, across various workflows and from the start to finish of every project. 

2. Consolidate data to avoid silos.

Information siloes occur when data or information is isolated within a specific department, team or system. Siloed information can lead to inefficiencies, redundancies, uninformed decision-making and– when attempting to replicate outcomes– having to recreate systems and workflows. 

In order to create systems to replicate success, teams need access to accurate and comprehensive data from all phases of a project, from initial planning to execution — and from different departments. 

Integrating data from different parts of projects and consolidating it in one platform leads to increased collaboration and holistic decision-making. In addition, creating dashboards that visualize captured data can be used to increase efficiency and predict capital needs. 

3. Refine and improve with each project.

Improvement is easiest to achieve when success has been clearly defined, often through KPIs and benchmarks based on past performance or industry standards. A clarity of goals improves the usefulness of analytics, and captured data can be used to measure progress over time.

Many tools have the capability to create project templates that can be copied for each new project, allowing for quick comparison and optimization between sites and projects. 

4. Get granular.

For large-scale and fast-moving projects, repeatability is about reducing cost and improving efficiency without compromising quality. That requires precise data on what’s working and what needs to be improved upon. Tracking cycle times for phases and projects can help identify how workflows can be improved and the exact point breakdowns occur. 

Holistic cost analysis should include information on all parts of the construction process, as well as direct and indirect costs related to a project, such as capital expenditures, operational expenses, maintenance costs and potential future upgrades.

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5. Plan to be adaptable.

Having reliable systems that can replicate parts of the construction process should mean that team members can better respond to the parts of projects that are uniquely challenging. Renewable energy projects often take place in remote locations with unpredictable conditions and changing regulations. 

Copying project templates, using predictive analytics and being able to access up-to-date information is part of creating a foundation that helps stakeholders respond to challenges and handle uncertainties. Adaptability is made possible by high quality, real-time data analytics, which can provide insights to help pivot, problem solve and maintain project momentum.

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