When real-time data can drive down costs
Senior managers of the downstream arm of a major integrated oil company knew they were leaving money on the table—lots of it. The business unit refines petroleum and distributes the refined products—gasoline, mostly—to gas stations. But every time the downstream operation failed to truck the goods to gas stations at the time that gas levels in underground tanks were at optimal replenishment levels, it leaked money.
The business unit’s supply operation relied on daily gas-level information reported from stations and imperfect sales forecasts that its finance department manually prepared. Inadequate information about gasoline inventories and sales led to (1) high delivery costs when tanks were refilled too soon and (2) gas run outs when refilled too late. Recognizing the opportunity to reduce expenses and boost revenue, the downstream unit’s CFO called in AlixPartners to help eliminate gas run outs while minimizing transportation costs through deliveries made at ideal gas levels.
An internet-of-things strategy improves execution
We worked with the client to capture real-time information from sensors fitted to gas pumps. The sensors calculated the fuel remaining in each underground tank and transmitted that information to the downstream unit, giving employees real-time readings of gas tank inventories and sales. That data then fed into a sophisticated algorithm that we developed. This algorithm took into account not only a retailer’s inventory but also the size of the trucks that deliver fuel to each gas station, the dimensions of each underground storage tank, and even the time of day, holiday weekends, and weather, which affect demand. We also created visualization tools that make it easy for the client to see inventory levels at all gas stations at any time with alerts any inventory to shipment issues.
When it really matters
The algorithm, together with the predictive analytics it powers, now enables our client to calculate the perfect time to send out its delivery trucks. It can thus maximize the amount of gas it transports to customers and at the same time prevent product shortages (known in the trade as runouts). By replacing imprecise forecasts with accurate predictive analytics, we helped the downstream unit lower transportation costs by more than $10 million annually. Runouts have been all but eliminated thereby resulting in increased gas sales. And we accomplished all this in a matter of months.