Business Intelligence Case Study

- Pizza Delivery Scheduled By Cognos 8

Pizza delivery seems pretty simple - a customer calls, someone takes the order and tells the customer it will be there in 20 minutes.

If it arrives in 45 minutes - whilst albeit hot and yummy - the customer is dissappointed.

Key Business Requirement

Pizza maker Papa Gino's shared the growling customers hunger pains and decided to make delivery time a key performance indicator in its operation to meet customer satisfaction targets.

Business Benefit

Improved Customer Satisfaction, Improved Process Performance, More Accurate Planning & Scheduling.

Solution Delivered

With more than 370 Papa Gino's pizzerias and D'Angelo sandwich shops, this was a pretty big undertaking. About one-third of Papa Gino's pizza business come from customers placing home-delivery orders - so to monitor and measure and improve a third of their business was an ambitious project.

In December 2007, Papa Gino's began analysing delivery data with Cognos 8 business intelligence software.

The results were immediate and tangible. Customer satisfaction levels improved when pizza buyers were given more accurate delivery times.

Previously, the point-of-sale system clocked the time:

• A customer order is received
• Delivery time the customer is promised
• When the delivery left the store
• When he or she returned.

But the information was stored in spreadsheets and was hard to access.

In comparision, Cognos 8 is used to analyse the data and look for exceptions in an effort to improve delivery-time estimates. This helped restaurant managers set better customer expectations and possibly how to speed up deliveries.

In addition, improved forecasting capabilities has given store managers a better idea of how much product they should order and how many workers they should schedule.

Planned Next Step

The data BI generates can help them be more creative in their business performance improvement efforts.

Business Feedback

• Customer satisfaction increased
• Business processes were improved
• Materials planning and scheduling reduced costs
• Staff scheduling ensured delivery targets could be met and reduced costs.

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