How to extract business value through data analytic?
At this article we are going to elaborate on real business value example delivered through data analytics for a petroleum company, that was using the cutting-edge NLSQL technology to manage their daily operations. The company has over 339 petrol stations across England, Scotland, and Wales, and each station manager had access to the NLSQL Microsoft Teams App. This app helped them with their routine queries about gas, diesel sales, electricity consumption, utilities charges, and convenience store sales and stock.
One day, an unexpected insight was born for one of the petroleum station managers. Due to a recent increase in electricity prices, he decided to dig deeper into the electricity consumption data of his petrol station. With the help of the NLSQL Teams App, he made an analysis of electricity consumption per litre of fuel sales for different time periods.
To his surprise, he discovered that the electricity consumption per litre of fuel was extremely high during the night. At first, he thought it was a mistake in the data, but after further investigation, he found that the results were consistent across different days and weeks. He decided to look for the reason behind this anomaly.
The station manager realised that a few years ago, they had decided to close the petrol station during the night to save on labor costs. This meant that fuel sales during the night were close to zero, but electricity consumption remained high due to the station's lighting. He considered turning off the lights at night to save electricity costs, but then he had a better idea.
He noticed that six out of the eight fuel pumps at his station had card payment terminals, which meant they could operate autonomously. He decided to make a trial period for leaving these six pumps operating during the night, while the remaining two pumps would remain closed. The trial period exceeded his expectations, as they sold an additional 1,000+ litres of fuel per day without any extra personnel, and improved the electricity consumption per litre of fuel sales ratio.
Excited by this discovery, the station manager shared his findings with the company's headquarters, which then passed the information on to other petrol station managers across the country. As it turned out, 54 other petrol stations had a similar operational issue. By implementing the same solution, the company was able to increase their daily fuel sales by 30,000 to 35,000 litres in the UK. This was equivalent to the sales of an additional average petrol station.
The story of the curious station manager and the NLSQL technology spread throughout the petroleum company, inspiring others to look for ways to improve their operations. The combination of NLSQL's AI knowledge-base and human curiosity led to an operational excellence improvement that significantly boosted the company's bottom line. And so, the petroleum company continued to thrive, thanks to the power of technology and the ingenuity of its employees.