Team Car Care is cruising beyond spreadsheets in its management of financial, workforce and demand planning and forecasting.
Chain Store Age recently spoke with Matt Castonguay, senior VP, finance, analytics and supply chain at Team Car Care, about how the operator of hundreds of Jiffy Lube locations spanning half the country is modernizing how it handles financial workflows with automation and machine learning.
What business issues was Team Car Care facing?
When I joined Team Car Care, the finance teams, who support 500 Jiffy Lube outlets in 26 states, were using spreadsheets as their primary financial planning solution. This was at the time the automotive aftercare services market was exploding due to the increase in demand for used vehicles during the COVID-19 pandemic.
Unfortunately, those spreadsheets were not equipped to help Team Car Care take advantage of the significant growth opportunity the changing marketplace offered. When it came to scenario and demand planning, we simply didn’t have the right technology or tools.
Why did you decide to solve these issues with automation?
Our old planning system was more like a database. It wasn’t predictive; you couldn’t build driver-based forecasts that incorporated external data or leveraged machine learning. And with a 20-year-old financial accounting system, we were forced to build temporary crutches just to function day-to-day.
Team Car Care knew we had a big problem to solve, so we set out the parameters for our new financial planning solution and made a list of must-have characteristics. We were looking for a system that could bring in a lot more dimensionality to the data to drive analytics and analysis.
In addition, Team Car Care wanted to be able to automate manual core business processes and use machine learning models to help reduce reporting time and develop more accurate scenario and demand forecasting.
What automation solutions does Team Car Care use?
We are using Workday Accounting Center to automate financial processes across our 500-plus stores to create one experience for our in-store general managers and district managers. Rather than having to manually post data and pull reports once a month, it’s all automated.
Our accounting team is now able to pull multiple reports a day with accurate, real-time data that provides valuable insight into the business. We can also access our POS data through our accounting tool, which means we can take transaction data like the type of car, which employee worked on the car, or time spent in the service bay, and use this data to inform planning and projections.
Team Car Care is also using Workday Adaptive Planning with machine learning technology that has been a game-changer for our forecast and demand planning. For example, we can forecast how many customers will stop by individual Jiffy Lube stores at various times during the day, then automatically feed that customer count into the company’s sales and workforce plans.
[Read more: Using Automation to Solve The Labor Shortage]
What results has Team Car Care obtained?
The employees on our accounting and planning teams are feeling reinvigorated and more engaged because they’re being freed from living in spreadsheets 24/7. Rather than barely keeping our heads above water, we’re now able to help guide the business, which makes our work more rewarding.
By automating our finance function, we’re reduced the cycle time of our forecast scenarios from a month to just days, allowing several iterations to occur simultaneously with all levels of management looking at the same set of numbers.
We’re also able to do more accurate demand planning. Because we have our data in one place, we’re able to plan 250,000 SKU-item combinations for our stores using machine learning models that adapt as demand and usage changes.
My team participated in the development of the intelligent demand forecasting capability in Workday Adaptive Planning. We were interested in looking at key factors that impacted consumer behavior and our business on any given day, and one of those was weather.
When people see rain or snow, they don’t want to get their oil changed. So, we pulled in weather data from government sources and fed that right into our plans. By doing that, Team Car Care able to not only normalize our data in the past for those weather patterns, but now when we have weather events, we’re able to more accurately predict that fewer people will be coming in for oil changes over the next couple days.
This allowed us to staff slower days accordingly and ensure we have enough employees in the stores to deliver exceptional service when it gets busier. This has had a real business impact because we’re able to better serve our customers by staffing stores appropriately.
Can you discuss any future plans relating to automation?
I believe eventually Team Car Care will be using machine learning to forecast how many of the 500 products we sell will need to be in stock in each store and to automate replenishment. In addition, we have been working with Workday’s accounting and technology functions to move Team Car Care toward a zero-day close.
While we are not there yet, we have the tools to automate tasks while improving day-to-day profit & loss visibility for our operators instead of waiting until month end to measure performance.