How to Implement a Data Strategy that Reduces Digital Waste

How to Implement a Data Strategy that Reduces Digital Waste

How to Implement a Data Strategy that Reduces Digital Waste

Eric Thomas, Manager, Construction Thought Leadership at Autodesk + Host of Autodesk's Digital Builder Podcast

Different things may come to mind when the topic of construction waste comes up.

Some might think first about production challenges or rework, or unplanned changes in project scope. For others, it's all about wasted time, talent, transportation, or effort on the jobsite.

Of course, each of these are important to consider when you’re looking to eliminate waste and operate within the principles of lean construction. However, there is one category of waste that should be increasingly prioritized, particularly as we continue to modernize our construction operations.

We’re referring to digital waste.

As construction technology advances, the industry is producing and capturing more data than ever before. Autodesk and FMI research has found that the amount of new project data being produced has doubled from 2017 to 2020.

And while having more information is arguably better than being kept in the dark, there are some serious costs associated with poorly managed data, especially when it’s inaccurate or unusable. Bad data leads to problems such as poor decision-making, increased rework, and wasted resources. Not to mention, a massive rise in project expenses; we’ve found that bad data cost the construction industry a whopping $1.8 trillion dollars in 2020.

This is why construction professionals must craft a solid data strategy.

Established systems, processes, and policies around data enable teams to move faster, make smarter decisions, and reduce project risk and waste.

How bad data leads to waste

To implement a proper data strategy and reduce digital waste, we first need to understand where bad project data comes from in the first place. The top contributors to this include:

  • Inaccurate/incorrect data (24%)
  • Missing data (24%)
  • Wrong data (21%)

Left unresolved, these issues can lead to poor project outcomes.

Working with poor data leads to suboptimal (and expensive) decisions

Firstly, making good business decisions starts with having good data. Numerous decisions must be made across the entire project lifecycle. Whether you’re designing, budgeting, or doing the actual building, you need to make timely choices to move the project forward.

When you have bad data, you may end up with suboptimal decisions that lead to mistakes, waste, and rework—all of which increase the time and money spent on the project. Industry data supports this; our research has found that bad project data leads to poor decisions 41% of the time.

Those poor decisions can then result in some very expensive headaches. Consider this: in 2020, we’ve found that 14% of all construction rework was caused by bad data. So, a contractor generating $1 billion would've spent $50 million in rework. Now, if 14% of that amount was because of bad data, we can assume that the contractor would've saved $7.1 million in waste if they were working with accurate information.

Not having the right information increases risks

Not having good data also inhibits teams’ ability to effectively manage risks, particularly when decisions need to be made quickly. This issue is more pronounced today where construction firms face tighter schedules and more pressure to complete projects on time.

When people lack access to good data or if they have to spend too much time digging for what they need, they’re more likely to move forward without the right information at all. In fact, our survey indicates that just 9% of construction professionals always incorporate data into their decision-making. Meanwhile, 64% say they rarely or never do it.

Getting started with a data strategy

These problems can be avoided when you have a proper data strategy in place. The specifics of this strategy will depend on the data you have already captured, as well as your systems and processes for collecting and analyzing information.

Here are some general best practices that can kick off your data strategy on the right foot.

Start small

Resist the urge to revamp all your practices at once. It can be tempting to make big, bold moves to transform your data strategy, but doing so will lead to overwhelmed employees and you’ll likely face challenges with obtaining organizational-wide buy-in.

If you’re in the early stages of establishing a data strategy, it’s best to be intentional and narrow your focus. Identify one area in the business that would benefit from improved data practices, then go from there.

To figure out what to focus on first, look for parts of the business where you already have captured a lot of accurate data. Another approach is to identify areas that are suffering the most from bad data and identify what’s causing the inaccuracies.

For example, if your firm is already tracking a lot of safety-related metrics or if you know that you’ll be able to improve project safety with better data, then it makes sense to focus on that component first.

This will help you narrow down your approach so the process doesn’t get too complex or overwhelming.

Once you’ve implemented a data strategy in that specific part of the business, you can look at the results and lessons learned, then apply those initial wins to your next area of focus.

Obtain buy-in and organizational support

People are a key part of your data strategy. For it to be successful, teams should be willing to share data and change their practices when it comes to managing information.

Getting people to accept this change requires open discussions about your plans, while ensuring that those involved have the tools and ongoing support they need to succeed.

If you encounter resistance, you’ll increase your chances of getting buy-in by taking a human-centric approach. Have an honest conversation with your team and discuss the benefits that everyone would gain when implementing a proper data strategy.

Will having the right data make their job easier? Reduce their stress? Save time so they can go home earlier to their families? Figure out what’s in it for each stakeholder and communicate it to them when discussing your plans.

Put quality first

A solid data strategy isn’t just about having a lot of data. Far more important is the quality of information and insights you’ll gain from your efforts. In short, data quality, not quantity should be a key element of your strategy.

You can achieve this by adopting one central platform or selecting tightly integrated solutions that can support the flow of information. This approach creates a common data environment that allows stakeholders to easily access the information they need to make important decisions and prevent waste.

Final words

Establishing a data strategy involves work, but the benefits you’ll achieve from it—including less waste, lower costs, and better outcomes—will make your efforts more than worth it.

Ready to craft a construction data strategy in your firm?

Autodesk and FMI’s report titled Harnessing the Data Advantage in Construction analyzes key trends in data management and discusses why construction pros need a formal data strategy. The report also sheds light on the challenges that come with establishing a strategy and how you can overcome them. Download it today.

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