by Ryan Craaybeek, Director, Solutions Consulting at Contruent
More and more data is being generated every year — to the tune of several quintillion bytes of data daily, according to an often-cited FMI report. It’s gotten to where construction companies, which have been slow to adopt technology, are coming around to and even embracing the fact that implementing technology is a must if they want to understand better and take advantage of their capital project data.
In theory, having so much data can be good — construction companies are eager to get the most out of it. But in practice, it’s proving to be more difficult than anticipated.
If you’ve encountered this, know you’re not the only one. Taking a different approach to gleaning data insights can overcome common challenges many companies have faced.
There’s an Industry Desire to Understand and Use Capital Project Data
Construction companies want to know what their data can tell them about project progress, real-time performance and emerging risks to make better-informed decisions supporting established outcomes.
It’s a popular ambition. According to a McKinsey report, 71% regard data-driven decision-making as a core strategic move to support their future success. They know that with so much data, there’s an opportunity to turn it into something meaningful by implementing a capital project analytics practice.
And yet, an eye-popping quantity of data (up to 95%) sits stagnant, collecting dust. A common refrain among construction companies is, “We’ve got tons of data. We want to make sense of it all, but we tried and failed to gain the insights and results we expected.”
But desire isn’t reality.
Implementing an analytics solution or strategy can be challenging. A 2019 Gartner report forecasted that 80% of analytics insights practices through 2022 wouldn’t be able to produce the business outcomes companies are looking for. That’s a shocking failure rate.
Certain Realities Cause Organizations to Fail to Establish an Analytics Solution
Why such abysmal results? They can be attributed to several universal issues.
Insufficient data governance. Data governance provides the framework around a more efficient process for gathering, storing, accessing, protecting and analyzing all the proliferating data. This lends integrity to the data. Without these defined responsibilities and activities and a decision-making protocol, any perceived insights risk being inconsistent or unreliable.
Poor data quality. Bad data is more common than we may care to admit. The opportunities for it to seep in are amplified by the sheer size of a typical project, the seemingly endless amount of data it generates and the extended length of time construction can take. What results is uncertainty over whether data is accurate and current, calling into question its usefulness in delivering insights that support project outcomes.
Lack of skilled personnel. It’s a huge undertaking to lead the transition to an analytics-based best practice that can scale to manage all the data that large capital projects produce. Construction organizations need skilled individuals with data literacy who understand the types of data being generated, what’s required and how to use analytics to get the most value from that data. A Deloitte report says 24% of construction organizations cite lack of access to skilled talent as a significant obstacle to gaining data insights.
No alignment between business and IT. We need to let go of the mindset that IT exists in a supporting role to help individual business processes run more efficiently. Construction organizations need a strategic partnership with IT to use capital project analytics to improve project and cost management and meet broader KPI objectives more efficiently.
Toward a Best Practice Approach to Capital Project Analytics
We mentioned earlier that taking a different approach to capital project analytics can deliver the deeper insights you’re looking for. It involves implementing a best practice that incorporates analytics-based technology to move past the limitations presented by the above challenges.
Think of this best practice as being a plan with end goals. With so much data overwhelmingly going unused and outcomes not being met, every capital project should have defined goals — specific KPIs and outcomes along with how to track and manage them — established at the beginning.
For such a plan to succeed, data quality must be priority number one. That calls for a data cleansing process to regularly eliminate duplicates, fix inaccuracies, fill in missing information, correct wrongly formatted data and remove anything that’s corrupt. Without this process, you can say goodbye to reliable insights because any analysis would be rendered difficult at best, detrimental to project-impacting decisions at worst. Centralizing it all in a data warehouse (a single source of truth (SSOT)) makes the cleansing function faster and more efficient.
To add meaning to capital project analytics, the data it uses needs context. Organizing it into an industry-specific data model lends the standardization that makes the data usable. This speaks to the data consistency and interoperability needed to ensure data governance. It helps project stakeholders and systems understand and work with the data using the same language. And it creates more direct alignment with business KPIs for more precise analysis when monitored in online dashboards.
Of course, data will be pouring in from many sources, requiring some preparation and integration. Employing the extract, transform, load (ETL) process provides the framework to make this happen. This multi-phase process extracts data from the broader project ecosystem (project management software, sensors, weather data, etc.), transforms it into a cleansed, defined and usable format, and then loads it into the assigned data warehouse so it’s available for analysis.
With clean, formatted data in place, a business intelligence (BI) authoring and visualization toolset makes it easy to take that data from the warehouse and produce meaningful output through analytics dashboards. Consolidating millions of bytes of data into straightforward visual outputs helps capital project teams understand KPI behaviors effortlessly and quickly. These dashboards deliver the holy grail they’ve wanted and needed: real-time insights. Teams become empowered by what those insights now enable them to do: identify potential risks, make timely decisions, enhance collaboration and, ultimately, improve capital project outcomes.
Changing the Approach Deepens the Insights
With instant access to real-time information and insights, construction organizations gain more control and make better decisions directly impacting the success of their projects. All it takes is applying a best-practice approach to capital project analytics. Establishing such an approach can be a turnkey experience with a partner like Contruent, who has already done the work. Explore more at Contruent.com.