The construction industry is generating data at an increasing rate, but are we reaching the same stage as the advertising industry, where people claim that only 50% of their advertising is effective, but they don't know which half? Autodesk recently conducted a survey across Europe of 1,115 industry professionals and four contractors to understand their challenges in using data. The aim was to determine whether it is delivering the benefits we expect it to.

The results of the survey have been presented in a report titled 'Harnessing the Data Advantage in Construction'. The problem appears to be that many organisations lack leadership, are too resistant to change or don't know where to start. The report outlines the reasons behind this and comes up with some simple steps that every business can take to overcome these hurdles and make more data-driven decisions.

First some stats - this is, after all, a report about data. Some 82% of responders said that they are collecting more data than they were 3 years ago, but 39% said that less than half of that is usable, with 40% stating that the data is inaccurate, incomplete, inconsistent - and late! 51% admitted that they didn't know what data they should be collecting, and 52% complained that they didn't know how to manage that data effectively.

We'll take a further look at the statistics throughout this article, but it worth noting here that the 58% of companies that responded stating they had an effective process in place also said that they had fewer safety incidents, a reduction in change orders, fewer missed schedules and less rework.

Is Collecting Data wasting our time?
According to the report, "Collecting and handling this level of information is taking up significant resources," with one respondee admitting that "Right now, our quality managers in the field and safety team capture all of the data we use. They give it to our data analytics team, who analyse it and build out the reports." On average it appears that 49% of project management and field supervision staff's time is spent collecting, managing and analysing project data each week.

Is the data being collected good, or bad? The average view is the 40% of the information gathered is bad, putting this down to a number of causes split between 'inaccurate data (23%), duplicate data (21%), missing data (20%), wrong data (20%) and poor data quality (17%)'. This not only makes the data unreliable, but extra work is involved in correcting mistakes and rechecking data, and basically creates, rather than solves problems.

What makes Data Bad?
Apart from the sheer amount of data coming in, and the prevalence of incomplete or missing data, data from multiple sources are often difficult to combine. Rather than pushing on with large-scale data collection, Autodesk suggests that taking the time to think specifically about the fundamentals and putting a strategic data plan into place, such as working within a cloud-based structure or collecting more data on site using modern technology, may help businesses to get more from their data.

The more problems you have with your data, though, the poorer the decisions made from it. This is probably exacerbated by the inexperience of decision makers when it comes to working with data, and their failure to recognise the impact of their decisions on the wider organisation.

It is not necessarily the data in this case that is bad, but the organisation, time and personnel factors that contribute to poor project decision making, with 70% of respondents agreeing that factors like schedule compression and stakeholder requests should allow them, as project managers and field supervisors, to have greater autonomy to make rapid decisions in the field.

Gut Feelings
There's an alarming section of the report that states that professionals often lack the data to make project decisions effectively, but which then cites statistics which state that only 9% of them always incorporate project data into their decision making - whilst 64% do it sometimes, rarely or never. Apparently, however, most decisions are made on a 'gut feeling', emphasised by a BIM coordinator at a German main contractor who said, "The level of decision making in the field has always been high, but these decisions have been made mostly on their experience and not analysis,"

The same coordinator noted that the main challenge is always communication between the ones that collect the data and those that use it. Although it is being collected, data might not be making it through to those who need it - ultimately increasing the project manager's reliance on instinct.

Where do we start?
Knowing where to start has been a main topic of conversation within the industry for many years now. 39% have established data reporting and monitoring practices at the time of collection and use and 37% of them, probably in the same subset, have structured data in a CDE. More important is the percentage of companies that have firmly entrenched themselves in the process by employing someone to just look after their data.

A very interesting fact is that, whilst 58% of construction companies have a formal data plan, 9% of professionals confessed that they didn't know whether their company had one or not!

Where data plans are in operation, they often have different main criteria. For instance, 52% of data plans outline the sources and collection methods for priority data, whilst 45% include the identification and description of the project data to be collected. 45% include quality assurance and control methods and 45% have standards for project data formatting and processing.

Importantly, companies with a plan to analyse data are seeing better outcomes on the ground, because they are able to learn from past outcomes. As one main contractor in Spain explained, "By tracking issues on our construction sites, we hope to avoid the same in the future. It's not just avoiding project-related problems; it's about avoiding legal problems as well. It has taken time to gather data across many projects, but it has been a good investment."

Overcoming the Barriers
Taking a pessimistic view of the above, it is hardly surprising that professionals are failing to see how data plans can add value to their business. They also point to the cost and resources required to develop a strategy. Another surprising barrier is stated to be a company's limited use of construction technology as a main barrier.

The pitfalls were expressed by one UK based manager who said, "we had a project that went terribly bad. A couple of years later, we had the exact same project. But because we did not have ready access to any data related to the first project, we made the same mistakes all over. Everything that went wrong was avoidable if we had the lessons learned from the first project available to our team."

Leadership is Crucial
Construction companies are far more used to handling technology today, but it is the people on the ground that matter - and the company culture. Companies need employees who are ready and willing to use new technologies and are prepared to train them up and support them to do so, providing formal training in data management and analysis.

And there are some cases where the company culture is opposed to change. "Some of our people just can't get their heads wrapped around the reports - and it's not because they don't understand them: it's more a culture change and shift in what people are used to," stated another respondent.

Here, leadership is critical. An Innovation and Quality Manager explained how his company responded to one particular challenge, where they had to change their approach. "One of the early challenges we ran into was our approach. "We were giving iPads to our field staff for taking photos and completing forms. They initially felt like it was more work and that we were adding stages that were not necessary. We had to explain to them why we were doing it and how it would save them time - and now they are really happy." Leadership is critical.

Here are three simple steps to get you on your way, although I would strongly advise you to go online and read the report first at the link below: Step 1. Start small and begin with data selection before data collection, Step 2. Focus on buy-in to gain organisational support. Step 3. Poor data equals poor results, so put quality first.

https://constructionblog.autodesk.com/adopting-construction-data-strategy-europe/