Big data is a phrase used so much in today’s business world that it is nearly a cliché.
There are a number of different definitions for big data, and all are correct. Today, big data can refer to large data sets or to systems and solutions developed to manage such large accumulations of data, as well as for the branch of computing devoted to this development. Whichever application of the term, it’s important to focus not on how you categorize your company’s data, but rather that you recognize the value of the data itself.
This not only includes your financial and accounting data, but also any additional data in your organization. But how do you extract the value from your data? More importantly, how do you become an insight-driven organization—one that uses the data and analysis to improve your organization’s daily operations?
Data analytics is the answer to all of these questions. Simply stated, data analytics is a set of procedures and methods designed to extract useful information from your data to answer a strategic question.
Analytics can be applied to virtually every area of the business, from marketing to accounting to project management. However, successful implementation of those analytics requires a solid framework by which to design and apply them.
Find a framework that works best for your company, such as the following:
- Ask a strategic question.
- Define objectives to answer the question at hand.
- Obtain the data necessary for analysis and follow-up.
- Develop and apply comprehensive analytics procedures.
- Analyze the results.
- Manage and use the results.
This framework is designed to allow you to apply analytics in virtually any area of your business by changing the strategic
question. The following questions offer a strategic approach to consider when applying analytics in your organization.
- How can we improve our overall cost-control efforts?
By applying analytics to historical job performance, construction companies may be able to identify what went well on profitable jobs and what went poorly on unprofitable jobs. Essentially, this would be a root cause analysis to determine the overall drivers of profitability on jobs with a specific focus on the cost-control components.
- Which subcontractors perform best?
While executives and project managers will undoubtedly have a feel for the best and worst performing subcontractors, applying analytics can help identify the characteristics of top performers. Further, analytics can help develop a system of warning signs that indicate a subcontractor is falling into the poorly performing category. While these metrics can be used to identify overall performance, they can also be used on a project-by-project basis to more closely manage the costs of a specific project.
- How can we reduce our company’s equipment downtime?
With the growing number of sensors and data coming from construction equipment, there is an increasing amount of opportunity for companies to proactively manage equipment downtime. Using analytics, companies can begin to learn the patterns of activity that indicate a looming equipment failure and identify the preventative measures needed to minimize that equipment downtime.
- What will lead to significantly increased employee productivity?
More and more, companies are equipping their employees with the tools necessary to improve project productivity. However, many of those same companies are seeing little to no improvement in employee productivity. The tools used to improve productivity are typically designed to track data regarding usage, location, idle time and other key metrics. By segmenting employees by location, department and role, companies can begin to learn what leads to increased productivity on a more granular level. This will allow companies to better equip employees in every area of the company with the specific tools needed to improve productivity.
- Where in my organization does fraud currently exist?
The fraud triangle theory holds that for fraud to exist, an individual must face a perceived financial pressure, have a perceived opportunity to commit fraud and still be able to rationalize the action. Organizations maintain an increasing amount of data regarding the three legs of the fraud triangle in the form of email communications, instant messages and communications via company devices. Further, transactional testing for indications of fraud can help organizations identify fraud early in their cycle. These principles may apply in accounts payable, corporate credit cards, payroll, general ledger and other areas of the accounting cycle.
These strategic questions are designed to get you thinking about the potential applications of analytics in the construction industry. They are a starting point from which you can begin the process of transforming your organization to being driven by insights.
One of the keys to success in becoming insight-driven is incorporating data analytics into the culture of the organization. If the use of data analytics is viewed as something performed in addition to the existing operations, pushback from your most valued employees is much more likely to occur. However, when data analytics are viewed as integrated into the operations of the organization, they are viewed through the lens of the effectiveness and efficiency gains produced.
So, how will you integrate data analytics into your organization? Get started using the framework and questions provided, and determine the highest priority area in your organization to begin the transformation to become insight-driven.