Today, the Warren, Michigan-based wholesale food distributor delivers 150 truckloads of groceries daily to around 8,000 customers, including supermarkets, convenience stores and cafeterias, and has expanded into new areas including seafood and confectionary products. Its ambitions have seen it acquire a number of food businesses in recent years, including Wisconsin-based Jim’s Cheese and Michigan-based Dairy Fresh Foods.
As its reach grew, insight started to lag behind at Lipari Foods. Until its implementation of the WebFocus data analytics platform from Information Builders, employees throughout the business relied heavily on the IT department for hard-coded reports and queries. Multiple reports were often required to make particular decisions, according to Joe Beydoun, Director of Supply Chain Management and Business Intelligence at the company:
For many years, we simply did reporting against some critical back-end systems, such as the warehouse management system, and it all happened in IT. There was no ad-hoc capability, so every new request or the need for a new column meant creating a new report. We were a much smaller company back then and I don’t think we could operate that way now. In fact, I know we couldn’t.
Tackling two priorities
Beydoun saw that two things needed to change if employees at Lipari Foods were going to have the information they required to do their jobs to the best of their abilities.
First, they needed self-service BI capabilities that reduced their reliance on the IT team. And second, they needed reports based on a much wider pool of data sources.
With that in mind, the WebFocus project began with a focus on sales and purchasing, based on getting information into dashboards that define sales plans and targets versus actual sales.
It was a good start, but a more urgent - and complex - requirement lay elsewhere in the business. Employees in the warehouse and transportation departments needed information that could help them mitigate the risk of late deliveries and spoiled food. After all, the company ships a wide range of perishable goods, such as fresh chicken and dairy products, says Beydoun:
Once we’d been successful with sales and purchasing, we soon turned our attention to operations. We’re a sales-driven company, but in the last couple of years, it seemed like we were at risk of having to slow down on sales because we just couldn’t operate anymore. We were just shipping so many cases out of our single warehouse.
New acquisitions, he adds, clouded the picture, with a newly acquired company typically adding between 4,000 and 7,000 new SKUs with which warehouse staff had to contend. On top of that, the company wanted its supply chain analytics to reflect the sophistication of its operations. As Beydoun explains:
Supply chain data has evolved to more than just transactional data from an ERP or warehouse management system. Today, in 2018, we have various data sources that we capture, collect and react to in a near real-time state.
More systems, more insight
That data includes delivery vehicle telematics and data from warehouse equipment such as forklift trucks, as well as transportation management systems. And in a bid to make sure everyone can see and use that information, Beydoun says dashboards are available on TV screens in the warehouse, on iPads for supervisors and on cell phones for the sales team.
Actionable key performance indicators (KPIs) are displayed on these dashboards and exception-based reports are automatically distributed when activities fall outside of typical parameters, helping the company to spot and quickly tackle potential errors in orders and shipments.
The next step, says Beydoun, is to implement more of the data discovery capabilities available in WebFocus. While employees can use their dashboards to ‘drill down’ into data, he says, their confidence is growing and there’s now a good case for enabling some of them to start building their own dashboards too:
We see a lot of efficiencies to be gained from making it easier for employees to explore their own data - to spot issues and put them right, or simply make a process more efficient. We don’t want to put limits on their ability to do that, so the idea of data discovery has a lot of appeal for us.