Business intelligence: managing data complexity with analytics
Business intelligence (BI) is continuously evolving into a more powerful and versatile tool for dealing with the complex data landscape of today’s organizations. It can be used to provide insights and actionable information from disparate databases scattered within and outside of the organization and stored in a centralized data warehouse. BI can also support decision making in the context of the daily workflow, surfacing just the analytics that the employee needs to use in accomplishing a given task.
Intermodal trucking is a critical component of the global supply chain, which depends on ship, rail and land vehicles of various sorts to move goods all over the world. To track and manage the shipping process, transportation management system (TMS) software has been developed. The software captures and stores data, some of which is entered manually and some of which is captured by automated means, for each phase of the trip. Data includes the location of shipments, labor and fuel costs and total time from departure to final delivery.
Profit Tools is a well-established provider of TMS software. Co-founded by the owner of a trucking company and an experienced software developer, the company developed Profit Tools for Trucking. Customers value the ability of the software to handle the entire shipping process, from dispatch to billing, as well as to track the movement of its customers’ shipments.
Although the software included some analytics, Profit Tools wanted to add more sophisticated capabilities that would allow its customers to analyze the data in greater detail. This would provide a means for identifying patterns that were impacting performance, so customers of Profit Tools could optimize their operations and maximize profitability. One particular challenge was the difficulty of analyzing data that originated in different systems.
The company screened a number of different business intelligence (BI) solutions and even went so far as to spend three months building out a pilot solution. “We began to encounter barriers and limitations to doing what we wanted,” says Brian Widell, president of Profit Tools. “We then cast the net again and came up with Sisense. Within three days of contacting the company, we had downloaded the tool, pulled data into it and were able to overcome some of the data blending challenges that we were facing.” Sisense had the capacity for interoperability that was essential to meeting the objectives Profit Tools had for its TMS solution.
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