Application Development for a Real-Time Labor Cost Tracking Tool
Analytics is helping sports industry experts make better decisions on a variety of issues ranging from sabermetrics to the way fans consume sports data. The objective of analytics applied to sports data is to turn it into value for both consumers as well as sports professionals. Advances in technology and the need for real-time analysis and prediction, the way in which we collect data, is evolving rapidly. Connected devices and the internet of things is going to play a huge role in this transformation. Wearable gadgets are now being produced that are designed to track daily workout routines and calorie burns are getting
more stylish and easier to include in our daily lives. Tracking, saving, sharing and comparing your workout statistics like route, speed, distance, calories burned and even your “Suffer Score” takes seconds. What does this have to do with manufacturing?
We can attest to the growing realization among many businesses that connecting employees, devices and machines can produce an improved bottom line. Small manufacturing companies are particularly susceptible to these costs. One of the key issues the SMMs face is that they do not have a good idea about how much effort their line workers spend on each of the many projects they work on. Getting a more granular view of the portion of their costs that comes from labor on a specific project can give them clearer insights about the overall profitability of each and every project.
Realization of the value of the information they can extract from the data generated by a connected network of employees and workstations is invaluable. To that end, they have instrumented their shop floors with an overhead GPS system which communicates with their employees. The shop floor is divided into several zones, where each zone is set up to handle a specific activity. For example, they can have zones divided by a specific product line and zones divided by an activity such as inspection. As employees move about from one zone to the next, the network recognizes this and generates a message. These messages are aggregated into a log file which is processed round the clock to accommodate the multiple shifts which they operate. The log file data is then converted into manageable tables from which point it is very easy to generate sophisticated and highly interactive dashboards for analysis.