Making Data Driven Decisions in Construction

The construction industry has seen huge shifts in ways of working, with technology transforming all parts of the construction process. These increasingly sophisticated, technology-enabled methods bring many benefits, including greater time- and cost-efficiency, improved collaboration and communication, and more accuracy.

Early examples of digital transformation include the adoption of Computer-Aided Design (CAD) in the late 20^th century. Using CAD rather than paper-based drawings, designers began to create drawings with more precision, efficiency, and flexibility. More recent technology innovations include the introduction of Building Information Modelling (BIM), common data environments to store data online rather than in filing cabinets or on devices, and the development of construction management platforms. 

All of these methods allow construction companies to collect, store, and analyse their data more easily. This has paved the way for the industry to begin benefiting from data-driven decision making, which is the practice of basing choices and actions on historic data that provide insights into how to work more effectively. 

The Fall of Excel

Using Excel for data management can be problematic because it's not designed for storing large volumes of data effectively. Companies often store Excel files in various locations, like SharePoint folders and local computers, leading to version control issues. These files are frequently emailed and edited by multiple people, making it challenging to ensure everyone is working with the same set of data unless a strict versioning system is in place. This lack of control can result in unlogged data manipulations, eroding trust in the data's accuracy. Additionally, formula and VBA code errors are common, further complicating data reliability. These issues often cause meetings to be derailed by debates over data accuracy, distracting from important decision-making tasks.

The Rise of Technology

In the construction industry, a significant shift is occurring in the perception and use of data. While there's a growing awareness of data's value, many still grapple with understanding its potential and application. The industry sees pockets of advanced individuals eager to harness data for more sophisticated operations, yet there remains a widespread gap in comprehending its true power.

A key aspect of an expert's role in this landscape is to educate stakeholders on the fundamentals of data analytics, its functionality, and its transformative impact as demonstrated in other sectors. This educational journey is especially rewarding given the prevalent enthusiasm for adopting artificial intelligence, fostering a collective ambition to leverage these technologies for enhanced business outcomes.

The Importance of Analysing and Tracking Data

Teaching newcomers in analytics about the impact of data tracking and utilisation begins with demonstrating tangible, quick results to showcase its value and stir excitement. In an industry weary from "innovation fatigue" due to failed or mismanaged tech implementations, it's crucial to swiftly deliver a benefit, like a real-time report. For large Tier 1 organisations, a real-time report showing the number of live projects can be particularly revealing, especially when disparate software tools provide conflicting data. This exercise not only underscores the immediate benefits of data analytics but also highlights issues with data cleanliness, shifting the dialogue from ambitious AI adoption to the foundational need for clean data. By offering these illuminating insights, organisations can foster a cultural shift towards prioritising data integrity and consistent analytics practices.

Building a New Data Culture

Building a culture that embraces new data collection and usage approaches begins by focusing on a single business unit or vertical within the organisation. The strategy involves prioritising initiatives that offer significant value with manageable effort, ensuring quick, visible successes. Identifying and empowering tech-savvy individuals and enthusiastic supporters within the company is crucial, as they become internal advocates who demonstrate the potential of improved data strategies. Their success stories serve as organic internal marketing, encouraging others to seek assistance with their data challenges. Over time, as teams witness their reports becoming more reliable and their data cleaner, trust in this single source of truth grows. This gradual transformation starts with delivering initial, impactful reports that build excitement and trust, laying the foundation for a data-driven culture.

A Single Source of Truth is Key

A single source of truth refers to maintaining a centralised, accurate repository of data from which everyone in an organisation can make informed decisions. This concept is akin to Segal's law: "A man with a watch knows what time it is. A man with two watches is never sure." The single source of truth acts as that reliable "watch," offering consistency and certainty in decision-making. When implementing this system within a company, it's vital to ensure that everyone has access from the outset. Making reports widely accessible, often through a prominent link on the company's intranet, allows employees to explore and utilise the data. Monitoring engagement with these reports helps identify who is actively using the data and who might need further encouragement or training. This feedback loop fosters trust and enhances the utility of the data, ensuring it serves the organisation's needs effectively.

AI’s Role in Enhancing Data

AI plays a crucial role in enhancing data quality and usability. Effective data-driven decision-making hinges on having a robust pool of accurate, historical data. However, many organisations, particularly those reliant on Excel, grapple with data cleanliness issues such as inconsistent date formats, misspelled project IDs, and incorrectly named documents. AI offers a significant opportunity to tackle these persistent challenges by identifying and correcting errors, ultimately leading to cleaner data. As AI continues to advance and refine data quality, organisational trust in data is likely to increase, facilitating more reliable and insightful decision-making.

How Construction Management Software Enables Data-Driven Decisions

Construction Management Software tools or platforms like Procore play a big part in helping construction workers make data-driven decisions. The software gives a construction team a single, centralised location to store project data so it has access to accurate and up-to-date information. This is often referred to as a single source of truth. Being able to collect, store, and access that data is the first step in being able to base decisions on evidence.

With these foundations in place, construction companies can progress to using data to improve their processes and ways of working. For example, decision makers can use real-time data analytics in construction management software to analyse and identify cost estimates and project timelines. This helps them to stay on-time and on-budget and to make any adjustments necessary to keep everything on track. 

Construction management software also allows users to automate reporting, which speeds up the creation of reports and reduces the risk of human error. Being able to access accurate reports faster means that stakeholders can use them to make decisions that affect the future of a project much more quickly than if they had to create them manually. In this way and in many others, a construction management platform helps its users make better decisions with more ease, speed, accuracy, and efficiency than relying on traditional methods. 

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