The Solution

Create an equipment, component, and recommendations data library incorporating all scenarios of a MI inspection so that the technician can build the specific assessment template for each client. Each client template automatically syncs to a mobile application that instructs the onsite technician to record the requirements and photographic documentation. The technician is also prompted to choose the proper recommendation based on International Institute of Ammonia Refrigeration (IIAR) regulatory codes.

The app needs to be flexible enough to add new equipment directly from the mobile device in case anything is missing in the pre-inspection setup and the ability to sync operations between the mobile and the web app for reporting purposes and to capture historical readings for future inspections.

The Solution

In the fuel delivery business, there are three key metrics:

1. Out of Gas – The customer is bone dry on refill.
2. Zero Gallon Delivery – You deliver, but there is no room in the tank.
3. Early Delivery – Customer on the route that doesn’t need a delivery.

Early deliveries are by far the most common. An 8-hour shift delivering propane costs the same whether you provide 1,000 gallons or 2,500 gallons, although the cost to deliver the propane is significantly higher in the former. Therefore, the goal was to determine the optimal number of drivers to minimize early deliveries.

To quantify the opportunity, we created a monthly driver efficiency score model based on the number of gallons remaining in the truck at the end of the day. A driver efficiency score of 1.0 meant you finished your shift with an empty truck. A driver efficiency score of 2.0 meant you finished your work shift with a truck that was half full. Your delivery expense for both routes was equal. The model allowed us to identify over and under-capacity based on location and seasonality to augment workflow appropriately.

The Solution

This is the classic case of the “devil being in the details” and “too close to the forest to see the trees.” The data analyzed across millions of rows identified the course of action, and site visits to a production plant, inventory storage yard, and retail sale location helped confirm the hypothesis. Location and seasonality also played a role in inventory control issues. Observations included:

1. No one section (Plant/Staging Yard/Retail) in the supply chain owned tank inventory
2. Operations did not trust the technology that was put in place to track inventory
3. No disincentive to hoard inventory
4. Staging yards held peak season capacity year-round in all locations

A modeled-based approach could reduce idle tank inventory from 13 and 27 days to 5 days based on historical delivery schedules between the plants and the storage yards. In addition, a reconfiguration of the staging yards into trailer pallets (Full on one side/Empty on the other side) significantly improved hand inventory counts for management reporting.

Most importantly, management’s #1 concern of retail out of inventory was driven by delivery frequency, not tank inventory.

The Solution

The current technology was past its useful life and required a lot of manual workarounds. This was sufficient after 2-3 acquisitions but became unwieldy as the company grew. We needed a solution that consolidated and automated many of the back-office functions. The answer was to create a web-based and mobile application that reduced twenty (20) and counting SQL databases into one database. This accelerated the month-end close, simplified management reporting, and armed sales with a real-time mobile app to manage client expectations better real-time.

The application sits in the middle of the technology stack and communicates seamlessly with the front-end CRM and the back-end accounting system. We also placed a business intelligence layer with Tableau for real-time management reporting and analytics across the organization.

The Solution

NetSuite OpenAir was selected over Workamajig immediately after our engagement in this project. Our first goal was to revamp and standardize the workflow management across the business units so that we were not automating a flawed process. We held multiple sessions to reach a consensus to take to the OpenAir implementation team. The high-level workflow is below: