Video · October 28, 2024
How Stake Center Locating went from a two-week manual close to rolling AI-powered forecasts every month
About this video
Stake Center Locating, the second largest utility locating company in the United States with 1,500 associates across 48 states and 30% annual growth, was held together by legacy Access databases, entirely manual budgeting and forecasting, and a close process that took two weeks. David Kennedy was brought in specifically to make back office operations enterprise-ready, and OneStream became the foundation for that transformation.
Close, consolidation, account reconciliations, and budgeting are now all running on one platform. Quarterly forecasting that previously took weeks to months has been replaced by a rolling 12-month forecast updated every month and a two-week AI-powered forecast updated every week. That two-week model gives Kennedy the ability to adjust field headcount in real time ahead of volume spikes, directly improving profitability. His assessment is unambiguous: game changer, revolutionary.
Speakers
Chief Information Officer | Stake Center Locating
Key takeaways
- Legacy Access databases, a two-week manual close, and quarterly forecasting held together with bubble gum and duct tape had to go. Stake Center Locating was growing at 30% annually and needed back office operations that could scale with the business rather than constrain it.
- OneStream replaced the entire legacy stack with close, consolidation, account reconciliations, and budgeting on one platform. Getting all the legacy complexity out of the way first created the stable foundation needed to layer in more advanced forecasting capabilities over time.
- Quarterly forecasting that took weeks to months has been replaced by a rolling 12-month forecast updated every month. By the time the old quarterly forecast was finished it was already wrong. Monthly rolling forecasts keep Stake Center Locating ahead of the business rather than perpetually catching up.
- A two-week AI-powered forecast updated every week enables real-time headcount adjustments ahead of volume spikes in the field. Running on a separate AI model from the monthly forecast, this short-range view gives operational leaders the precision they need to deploy resources profitably across 48 states.
- The moreaccurate the forecast, the more profitable the business. That connection is now direct and measurable. For a company growing at 30% annually in a field-intensive business, the ability toanticipate and respond to demand in real time is not a Finance capability. It is a competitive advantage.
Read Full Transcript
My name is David Kennedy. I'm the Chief Information Officer of Stake Center Locating. We are the second largest utility locating company in the country. We have about 1,500 associates located throughout the lower 48 states.
We do underground utility locating and grow in about 30% a year roughly over the last several years. I was hired in to redo the back office operations and solutions to make it enterprise ready. Everything was very manual.
Budgeting and forecasting completely manual. Closing the books took roughly two weeks. Old legacy access databases kind of held together with bubble gum and duct tape. Hard to do analysis. Hard to do budgeting and forecasting.
I couldn't push it back into the GL. So it was really looking at what tool could help us do that and be more efficient in our close process. That was the underlying problem we were trying to solve. I had looked into one stream before as we were kind of already down that path.
Did the demo. Did some reference calls. So we decided, you know, to take the plunge. And so we started with close consolidation and reporting. Layered in account reconciliation. And then budgeting and forecasting.
So we got all the legacy junk out of the way and kind of had a stable base. We did forecasting from a full top -down level and sometimes bottom-up. But it was done quarterly. It took me weeks to months to do that.
Which is why it was only done quarterly. Well, by the time you get done, your forecast that you just did is wrong. So we now do a full forecast of rolling 12 months every month. And every week, I do a two-week forecast for the next two weeks.
They're running on two different AI models. But that two-week analysis gives me the ability to go into the field and actually adjust my head count where I need to be when I'm going to see volume spikes.
The more accurate I can be, the more profitable I can be. Game changer. Revolutionary.
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