Big Data and Next Generation Analytics
Last Friday the Gartner Analytics Community, held a twitter chat discussing Big Data and Next Generation Analytics regarding business intelligence initiatives. Overall emphasis was put on aligning and defining metrics for improving business intelligence. Metrics unlike key performance indicators (KPI) and measures requires both direction and a control data set, inorder that comparison’s can be made to determine whether the appropriate measures are in place.
Next generation analytics can help in collecting the required information from job sites, accounting, human resources and collaboration tools. As more tools are becoming connected and big data, the ability to store large amounts of data relatively cheaply, is more accessible. Analytics on business processes can be collected to develop the metrics and compare management’s goals vs. actual.
The most important analytics would be those gathered from the work performed on site. Analytic collection can make use of current daily reporting processes to allow for the appropriate collection of information, whether it’s labor hours, area worked on, pieces of hardware installed. These analytics can be stored using big data and processed for similar future projects, as well as performing costing analysis post project. The most crucial step would be to develop the appropriate reporting and storing/tagging protocols so that there is not an overwhelming or paralyzing amount of data.
Another issue that was mentioned in the twitter chat was the relative importance
of real-time data vs. just-in-time data. In construction, most work schedules are set in either day or week intervals. It would be important to require the analytic gathering process to match a typical scheduling unit of the process, i.e. instead of reporting every hour, create reporting either at the end of every day or week. Once protocols are developed, its can be further optimized through development of a software or implementation of tracking technologies.
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