By Morten Raaby, General Manager Europe at Titan Cloud
What if you had a powerful tool to detect, diagnose, and resolve fuel loss issues without the need for a service call? If you didn’t need to wait on a third-party vendor to get your operation back to optimal function, how would it strengthen your business?
Such self-sufficiency is possible.
Wetstock operators must continuously balance multiple priorities every day, from system functionality to optimised inventory processes, and the minute-to-minute anomalies that pop up every day. To be successful, they need industry-specific tools that can streamline a never-ending flow of information and turn it into actionable data.
Yet many are still flying blind. In the past, traditional wetstock management technology has focused solely on environmental compliance, without the capabilities to address key disruptions and systemic inefficiencies that can derail the downstream fuel supply chain. The resulting challenges are more than just logistical; they can directly impact revenue.
Silent Culprit: Inventory Variance and Fuel Loss
When fuel variance goes undetected, problems grow, impacting multiple points along the supply chain. The consequences of the cycle are costly. Here’s an example:
If a retail operator dispensing 300,000 liters of fuel per month has an undetected variance of 0.15%, it could translate into 450 liters lost monthly, or 5400 annually. This represents a revenue loss that could easily surpass €10,000 over the course of the year—for one site. Scale that number over multiple locations and the losses could mount into the millions.
Fuel variance also diminishes operational efficiency. Investigating discrepancies manually can cause extended downtime and divert resources. Managers are taken off value-added work to test and troubleshoot, or to schedule and manage service calls for techs who may or may not identify the issue quickly. Through all of it, the fuel loss continues, draining revenue with it.
Inventory variance can result from a myriad of factors, some common and others not.
- Terminals and loading racks. At the outset of the retail fuel supply chain, temperature differentials can cause expansion or contraction of fuel volumes, leading to inaccuracies in inventory calculations. Terminal level calibration can also introduce errors that snowball through the process.
- Haulers and carriers. Human error introduces the potential for incorrect product deliveries, overfill events, or BOL discrepancies. And even one dishonest driver skimming off the top can mean significant losses if undetected.
- Fuel theft. From individuals tampering with pumps, stealing thousands of litres, to sophisticated theft rings reselling fuel on the black market, theft is a worldwide problem costing billions annually.
- Outdated billing systems. When delivery data is logged incorrectly, it can compound into more complex errors in terms of what was delivered, what was billed, and what was in stock, complicating financial reporting.
- Storage tanks. Fuel stored in underground and above-ground tanks can be subject to evaporation, meter drift, and seepage, while ATG calibration errors can cause discrepancies between measured and actual fuel volumes.
The Importance of Data Accuracy
If inventory variance is the thief, inaccurate systems data is the accomplice. Outdated systems that manually process raw data leave the door open to errors which are then fed into calculations. This can prompt frequent false investigations, costing a fuel retailer time and money.
Conversely, integrated technology that unifies, organizes, and validates inventory variance factors can stop the cycle by answering vital questions:
- What is the root cause of the loss? Is it a controllable factor like meter drift or theft? Or uncontrollable, like weather or temperature fluctuation?
- What equipment do I need to utilize or install to address the specific cause of the variance? If it’s spillage, for example, theft protection tools aren’t going to help and would be an unnecessary cost.
- Do I need to dispatch a team or launch an investigation into the variance, or can I pinpoint the problem without spending additional money on those resources?
By using a connective data-capture platform, operators are provided actionable fuel analytics to fine tune the cause of inventory variance and make informed decisions about how best to proceed.
A Global Success Story
Following a series of acquisitions in 2019, a global c-store leader came to Titan Cloud seeking a high definition wetstock management solution. Their retail network had been challenged by inaccurate ATG readings, which in turn were increasing the amount of unmatched BOL reconciliations. Given their rapid growth, these issues were compounding. By the time they began working with Titan Cloud, the company had been:
- Reporting an average of 490 unmatched BOL delivery investigations per month
- Navigating an average of 5,000 investigations per year across their locations
- Only reconciling approximately 94% of their fuel deliveries due to investigation delays
Over four months, Titan Cloud worked with the retailer to integrate our platform, onboard their team, and measure success. Data-driven ATG technology introduced micro-level measurement accuracy, fuel loss investigation became controlled by algorithm, increased accuracy led to improved BOL reconciliation, and retail operators had full visibility via the platform.
Maintaining synergy between inventory accuracy, delivery reconciliation, and investigations, the c-store leader was able to:
• Reduce inventory variances on their established ATGs by 64% across their network
• Boost accepted deliveries to 99%
• Drop average investigations per month by 14%
Unify, Organize, Analyze, Activate
Retail fuel operators have massive amounts of data coming toward them at any given moment. But within those streams are the keys to better business decisions that save revenue and provide positive customer experiences.
Implementing an end-to-end fuel analytics platform empowers fuel retailers by unifying, organizing, and analyzing data into actionable and automated processes. The result is technology that ensures data accuracy while streamlining systems and optimizing fuel assets, far surpassing the capabilities of traditional methods.
