Packer Fastener, based in Green Bay, Wisconsin, is a distributor of all things nuts and bolts to major construction companies and manufacturers in the US Midwest. Its recent expansion has been helped by switching on NetSuite OneWorld for financial management, as Bill Feck, its CTO, explains:
We went live in 2023 and that really was a big move for our company. We're growing fast and at the time we were only in two or three different States, now we're in seven. NetSuite has really helped to accelerate that growth.
Packer Fasteners was founded in 1998 after three salesmen met for a beer and decided to create a company that focused on customer service, speed and availability. It now employs more than 160 people, has 10 physical branches throughout the Midwest, an e-commerce operation, a supply and logistics subsidiary, and a specialist manufacturing arm.
Its CEO and one of the original founders, Terry Albrecht, believes the culture at Packer Fastener is the main driver of its high employee retention rates, and overall successful growth. It's known as 'Swagger' and was introduced in 2015, focused on people, attitude, drive, and results.
CTO Feck is an example of those high retention rates, having been with the company for 13 years. One of his primary concerns is the inventory management issues of handling 300,000 different products, around 30,000 of which can be active at any one time. AI is now helping with that challenge as well as being used to predict potential customer churn.
The NetSuite implementation replaced legacy ERP systems and spreadsheets and brings accounting for the company's different business units together. A notable results was reducing the monthly close cycle from 20 days to five. Meanwhile, NetSuite's Analytics Warehouse has allowed it to combine ERP, transport management, and payroll onto a single reporting platform.
When it comes to AI, Feck said the company's philosophy is that it really wants to empower its people and customers with the latest, greatest tools and technology. He says:
We've been leaning into a lot of machine learning and NetSuite's Analytic Warehouse. It has some out of the box ML capabilities and AI chatbots that are delivering high level insights really quickly for our users.
Other AI capabilities come from connecting to other systems such as Open AI's ChatGPT. He goes on:
We've been prototyping the SuiteCloud Model Context Protocol (MCP) AI Connector, and we've been really getting a lot of uses out of that. We also do a lot in SuiteScript and customization, and we use things like ChatGPT to help assist our developers.
We've gone from some projects taking what could have been two months, down to two weeks. We've also been developing our own AI agent, that's a little bit outside of NetSuite, but I'd say the extensibility and the ability to get data in and out of NetSuite has been instrumental in that.
Feck says getting leadership teams involved in AI implementation, and getting their feedback has been critical.
When we're launching something I really like to get feedback. So it starts with my own R&D, turning it on and seeing what it does. Then I present it to the leadership team to try it out, because I'm not going to be the one that's coming up with all the examples and use cases throughout the company. I can only know so much. It's really those people, that are living and breathing that department every day, that are going to come up with really impactful use cases. They are also going to be my layer of validation and vetting the data. They know the data so well, whereas I only know it at a high level.
Once we feel comfortable at that level, then we can start spreading it throughout the organization, further and further as they seem comfortable, and then before you know it, we have the whole company using AI powered insights.
With its extensive inventory, managing all the surrounding data is a big challenge. Feck says:
As demands are growing, we're trying to very quickly analyze all that data and get ahead of our reorder points, our safety stock, and what we're keeping on the shelf.
Packer Fastener uses Analytics Warehouse on a macro scale to see what the expected demand is going to be. It can run different algorithms to find out things like, for example, whether a demand is going to be seasonal, or where a trend is going to be to be, or what the demand is going to be in a month, and then project out what it needs to buy ahead of time. Feck says:
Our inventory is changing every day. You get one big order, and it shifts your available products. So the AI is continually looking in your inventory to tell you there's a trend, and we need to stock up on this.
"It's a process, because each flavor of ML has different models. To start with I didn't know any of them. And then you kind of understand what ones are good. And then you have to get back to the business end user and show them the results.
Building trust with the business units takes time, according to Feck, and requires work to help them understand AI, and what it can do for them. He says:
We launched an initiative earlier in the year, where we had three or four sessions of me and the CFO, trying different things and showcasing them to the company. Showing what it's capable of, and giving a sense of what it is. Sometimes it isn't a black-and-white science. You put a prompt in and you don't necessarily know what's going to come out the other end. For some people that's a little bit of a leap of faith.
Packer Fastener isn't getting rid of the human-in-the-loop in its production-ready ML models in the near future, but once it has been working for a while, Feck might review that. He says:
I'd say most, if not all, of the AI functionality we've been launching absolutely relies on a human in the loop, at least at the foreseeable moment. Give it a year, and maybe that's not going to be the scenario.
But Feck thinks another challenge for companies in an AI era is planning for the future, in terms of staff. He comments:
The way we see this is we're going to grow and scale efficiently, and we're absolutely not going to cut headcount because we're launching AI automation. Instead we're growing and cutting the mundane tasks out of our workforce so that they can pivot and do other stuff.
The company's 'Swagger' culture and current high staff retention rate looks set to continue into the AI era.
