The Rise of Business Intelligence in Construction: Part I

Business intelligence focuses on intelligent reporting and existing data for better decision-making processes. Contractors can complement intelligence born from experience with intelligence born from information technology.
By Matt Harris
June 14, 2019

Living in the digital age provides access to more information and entertainment than ever before. People can explore the world or shop for rare items from the comfort of their homes; research virtually any topic with direct access to experts; socialize and collaborate with others in virtual environments to create art, share ideas or run businesses.

But as the technologies that open new doors and opportunities continue to advance, it subjects people to sensory overload — buried in data, tasks and demands to do more with the information at their fingertips. Modern contractors are no different as they struggle to make sense of the deluge of data that their projects produce while still meeting increasingly demanding expectations.

That’s why today’s innovative contractors are demanding their software do more than simply store and report historical information. They need solutions designed to help them better organize, analyze and share information – solutions that help them turn the deluge of data into a reservoir of intelligence that, with the right tools, can become a powerful advantage in a competitive market.

Redefining Business Intelligence

In an industry characterized by high-risk, low-margin projects, intelligence is an obvious requisite for anyone wishing to succeed as a contractor. Long ago people realized they could overcome the limitations of muscle power by applying steam, gas and electric powered tools. Today, contractors are beginning to complement their intelligence born from experience with intelligence born from new techniques and approaches in information technology.

These new technologies and techniques are often grouped under the umbrella term “business intelligence” or BI. There are, however, different ways and degrees to which data can be organized and analyzed. A key distinction is the one between business intelligence and business analytics. BI focuses on the intelligent reporting and presentation of existing data in order to help make decisions based on past and present performance. Business analytics applies algorithms to data in order to uncover new, predictive sets of information relevant to a business. In other words, BI is about making better decisions given what (should) already be known. Business analysis is about uncovering previously unknown relationships and providing new, predictive information to help guide business decisions.

Figure 1: Business Intelligence Heirarchy

Putting BI to Work

Intelligence for its own sake may be a noble pursuit, but in business it is only as valuable as the advantages it provides in the marketplace. The more effort a company makes to apply business intelligence tools and techniques, the greater the potential benefit. Here are several ways contractors who have embraced the idea of building their “business IQ” see real results:

  • More, Better Data. Once a contractor commits to improving its treatment and use of business data, one of the first realizations is how much data is missing, duplicative or just plain wrong. Step one of any approach to BI is to ensure the capture of accurate, timely and complete data. The process of implementing BI solutions can quickly point out the gaps – where key information is missing and where a company is hitting the manual speed bump of duplicated data entry. In addition to the benefit of having more information at hand to use in decision making, companies who implement a BI strategy also see improvements in data quality. This is in large part due to a reduction in the number of times raw data is entered into often multiple software systems. Part of the implementation of effective BI solutions includes consideration for the way data is captured and shared among different individuals, and this includes reducing the number of times data is entered and number of places it is stored.
  • Data-Driven Decision Making. One does not need advanced machine-learning algorithms to extract valuable insights into business operations. Consistent benchmarking – measuring today’s results against yesterday’s – is a simple but powerful tool in the BI arsenal. But before performance can improve, it must be measured, and to improve performance effectively, it should be measured against as many variables as makes sense.
    An example of this comes from a Heavy Highway contractor in the Southeast with significant capital investment in heavy equipment. A reduction of just 1% in fleet costs would translate to a six-figure increment to the bottom line, so it was worth the time to take a fine comb to the historic owning and operating costs of every machine in their fleet. BI reporting shone a light on the fact that, like many contractors, they were utilizing many machines well past the point of diminished marginal returns – well past the time when it would have made more sense to rent out or just replace them. By deciding to combine information on equipment finance, operations and utility time, this contractor was indeed able to realize those six-figure cost savings.
  • Rolling Weighted Dice. No one can predict the future – at least not all of it. But when intelligent algorithms are applied to large sets of data, it can be amazing what pops out. Companies who take BI to the next level and apply predictive analysis techniques to their data can have something approaching a crystal ball at their disposal to make better decisions based not just on past performances but on anticipated futures.

Where benchmarking uses historical performance to anticipate and improve current performance, predictive analytics applies algorithms that comb data for correlations that might not have been anticipated. It can expose business information that a company did not even realize it did not have – and which competitors most likely do not have.

Note that both benchmarking and predictive analysis can provide a view into the future. Benchmarking will help test the hypotheses about what’s working or not, but a company must come up with the parameters to measure and compare. Predictive analytics will look at data through the more general lens of algorithms meant to find things that may not have been anticipated. But as with all things in the world of Business Intelligence, it all begins with the data.

The Rise of Business Intelligence in Construction: Part II covers practical advice about implementing BI in an organization.

by Matt Harris
Matt Harris is Vice President and General Manager at Portland-Ore.-based Trimble Viewpoint, a construction management division of industrial technology company Trimble. He is responsible for Trimble Viewpoint’s overall business, including its long-range strategy and execution while leading a global team who is passionate about making a difference with construction technology.

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