The construction industry is a major contributor to the global economy, generating trillions of dollars in revenue each year. However, it is also notoriously slow to adopt new technology. In fact, a survey from McKinsey found that challenges in understanding digital transformation and poor alignment of business processes and digital tools led most construction industry respondents to claim that their digital transformation efforts had been unsuccessful.
As the world becomes increasingly data-driven, your organization must adapt and adopt better data practices in order to remain competitive and thrive in a rapidly changing business environment. Implementing a strategic data practice can help you gain valuable insights into how to improve efficiency, reduce costs, and increase profits.
Common Data Challenges in the Construction Industry
According to IBM, bad or incomplete data costs U.S. businesses up to $3.1 trillion a year. And while there is a cost to storing data, the opportunity costs are greater. At any individual company, an ineffective or non-existent data practice can result in lost sales opportunities, ineffective marketing, inaccurate forecasts, wasted time, and a reduction in productivity.
If you’re dealing with the following challenges, it’s time to rethink your data strategy.
Siloed Data or Poor Source System Reporting
Construction companies may adopt a variety of systems and software throughout their years of operation. One system may be used for project management, another for financial management, and yet another for tracking equipment usage. The average company uses six separate systems, yet these systems may not be able to communicate with each other, making it difficult to integrate and analyze data from multiple sources.
Additionally, many of the software systems leveraged by construction companies are legacy systems with poor embedded analytics. Pulling data from these systems cannot be automated, so the entire organization must manually update spreadsheets for reporting. For these companies, it can feel like looking in the rear-view mirror because reporting is not updated frequently enough to make real-time, data-informed decisions.
The challenge isn't just about collecting data, though. Many organizations that do collect data still struggle to interpret what that data is saying. It's common for these organizations to experience “analysis paralysis,” a term describing what it feels like to collect every piece of data that is, will be, or may become important – and then just sitting on that data because they are unsure what to do with it.
Profit Margin and Gain/Fade Analysis
The cost of materials, labor and equipment is constantly rising, making it increasingly difficult to maintain profit margins. This can be a major challenge in the construction industry, as organizations must invest a significant amount of money into a project before seeing any return on their investment.
In addition to this, many construction companies do not have timely visibility into a project’s profitability, meaning a project’s profit margin is not clear until the end of the project. At that point, it is too late to adjust.
Utilizing data can help better track costs, identify areas to reduce costs, and make more accurate predictions about profitability. By using data to track costs in real-time, business leaders can make informed decisions about projects and take action to improve profit margins.
Over or Under-Utilized Assets
Some construction companies plan their projects based on available assets, and each asset has a finite number of hours it can be used in each work week. Without a data practice in place, decisions on assets are often made based off assumptions or intuition rather than evidence, leading to inefficiencies and an increased risk of over or under-utilization.
Managing assets manually without a good understanding of the equipment’s utilization rate leads to over-utilization issues, like using a machine on multiple projects and often for longer than it was designed for. This can lead to the machine breaking down more often, meaning less resources and more cost.
Understanding what assets are allocated and where and planning projects accordingly ensures the necessary equipment is available. It also ensures equipment is not over or under-utilized and that leaders are properly planning for maintenance or downtime.
Project and Personnel Management
Construction companies try to plan projects months in advance, and these projects often involve many tasks that need to be completed in a specific order.
By collecting and analyzing data on task dependencies, resource availability, and other factors, leaders can create more accurate project schedules.
Understanding employee performance, skills, and availability can also help identify which employees are best suited for a particular project. This can help to ensure that the right people are in the right roles, which can improve productivity and reduce the risk of errors.
Explore the basics of data analytics and discover how you can leverage that data to grow your business.
How to Improve Your Data Practice to Increase Company Performance
A comprehensive data practice can lead to improved decision making, better asset management, increased efficiency, better resource allocation, improved project management, and increased competitiveness. As an organizational leader, the steps you must take to build a comprehensive data practice include:
1. Understanding what data you have and what it represents.
Before you can effectively use data to improve your construction business, you need to know what you are looking at. This includes identifying different types of data you collect, such as project information, resource utilization, and financial data. Once you have a clear understanding of your data, you can begin to identify the key metrics and indicators that will be most important to your business.
2. Implementing robust data collection and management systems.
One of the biggest challenges in the construction industry is the lack of centralized, accurate data. To overcome this, consider investing in robust data collection and management systems. These systems should be able to handle a wide variety of data types, from project plans and resource utilization to financial data and customer feedback. This will help to ensure that data is accurate and up to date, which is essential for making informed decisions.
3. Using data visualization tools to make data more accessible.
Your employees are often busy on the job site and may not have the time to sift through large amounts of data. To make data more accessible, consider investing in data visualization tools that allow them to quickly and easily view key metrics and indicators. These tools should be intuitive and easy to use so that even non-technical employees can understand and use them.
4. Investing in data analytics and modeling.
Once you have a clear understanding of your data and have implemented robust data collection and management systems, you can begin to use data analytics and modeling to improve your business. This includes using data to optimize project schedules, identify inefficiencies, and improve resource utilization. These tools can also be used to predict future trends and make more informed decisions.
5. Automating data solutions to improve operations.
As your company grows, it will inevitably create technical debt — older, legacy systems that don’t make sense to replace, yet still need to interact with the new, cloud-based tools you implement.
One solution for this technical debt is Robotic Process Automation (RPA). RPA can automate repetitive, time-consuming tasks such as data entry, data extraction, and data processing, freeing up human resources to focus on more value-adding activities and reducing the risk of human error. This can help to improve the accuracy, efficiency, and speed of data collection, processing, and analysis.
Consider the invoice approval process in your organization. Starting with a PDF invoice from a subcontractor, RPA can scan the invoice, pull out the needed information and send the approver a message in Microsoft Teams. The approver is then able to see the invoice details, modify them if necessary, save the invoice in SharePoint, and then approve or reject the invoice. Once the invoice is approved, the automation launches the invoicing application, uploads the data and saves the record. When finished, it closes the application and sends an alert that the invoice was created. The invoice is added to an Excel spreadsheet that logs every transaction.
You can watch how this process works in this video.
6. Creating a data-driven culture.
To truly reap the benefits of a better data practice, you must create a data-driven culture in your organization. This means that data should be integrated into all aspects of the business, from project planning and execution to decision-making and resource allocation. By creating a data-driven culture, you will be able to empower employees to make better decisions and drive business success.
- Get started in your journey to become a data-driven organization by downloading our Data Analytics Playbook.
Challenges in Implementing a Data Practice
Data and reporting projects can add much value to your organization’s executive team and bottom line, but they do not come without challenges. These challenges are not unique to the construction industry, but they are something to consider as you embark on your data project.
For many construction companies, the first challenge is accepting change. Many organizations have established processes and ways of working that may be resistant to change, especially when it comes to introducing new technology.
Additionally, there may be a shortage of internal or external technical expertise to implement and manage new data practices and systems. Many construction companies may have very limited IT staff. Or, if they do have the personnel, those individuals do not have the time to lead such a major initiative. This goes hand-in-hand with another challenge – training. Having someone who can help employees adopt a data-driven mindset will go a long way in ensuring the success of the data practice. Especially if employees are resistant to change in the first place, they need to understand how these tools will lead to better business outcomes.
Finally, once a data practice is in place, an organization must take additional steps to ensure data security. Construction companies often handle sensitive and confidential information, so protecting that data and ensuring compliance with data protection regulations is a major concern.
Get Started One Step at a Time
Technology is only advancing, and businesses that are unable to adapt to the ever-changing business landscape will face consequences as time goes on. By understanding your data, implementing robust data collection and management systems, using data visualization tools, investing in data analytics and modeling, and creating a data-driven culture, you can improve your organization’s operations and make better decisions, ultimately driving business success.
And the best part? You don’t have to do it alone.
The Eide Bailly Data Analytics Team can help you with all your data needs – from strategy, to warehousing and analytics, to visualization, and much more.
Are you ready to unleash the power of your data? Contact our team today.