Staying on Top of Deliveries

Canada Post adopts the SAS®9 platform to deliver precision pricing for postal services

On an average day, Canada Post delivers more than 40 million messages, physical pieces of mail and parcels to more than 14 million destinations in Canada and to millions more around the world. Canada Post operates as a crown corporation and, with annual revenues of CAD$6.9 billion (US$5.9 billion), goes head-to-head with global competitors like FedEx and UPS. That level of competition requires precision pricing – and with more than 70,000 price points for parcels alone, pricing is highly complex.

Three years ago, CPC began exploring options for enhancing modeling capabilities and reducing turnaround required for data collection and reporting. Although an ERP system provided valuable aggregated reporting, incorporating the external data sets, multiple formats and predictive models required for dynamic pricing analysis was so cumbersome as to be virtually impossible. To remain competitive, the organization needed to leverage all available data to determine optimal price points for each industry and service offering to better structure future rate actions.

Surgical pricing, impressive ROI
“We needed a BI platform to access and analyze transactional data in real time,” says Brian Shea, General Manager of Pricing Strategy and Analytics. “Our current system and process were extremely slow. It could take up to several days to run a simple report. And, we couldn’t drill down and get the kind of granular information we needed. Our system just wasn’t working.”

In addition to pricing determinations, the team is now able to get a complete view of customers and apply different weights or elasticity variables to each customer type. This enables CPC to predict the impact of a price change in one or more product lines to the organization’s revenue, operations and resource allocation. Access to such powerful customer data also puts Canada Post in a position to improve customer insight to make better, faster and more informed decisions.

Gabriel Toichoa, CPC’s Director of Pricing and Modeling Solutions

“We can set the optimal price for the entire portfolio,” says Gabriel Toichoa, CPC’s Director of Pricing and Modeling Solutions.  “We understand customer behavior and can be more precise – surgically precise – in choosing prices.”

Toichoa says SAS BI and applications have revolutionized CPC's approach to pricing and raised the bar on improving customer insight. It was results like these that made believers out of initially skeptical business analysts. “They didn’t believe we could provide all these answers. Now they believe,’’ Toichoa says.

The perfect partnership
CPC turned to SAS because executives wanted an integrated suite of software technologies and solutions supported by a single vendor to reduce the complexities of data sharing and project management. SAS worked closely with Canada Post to evaluate the organization’s needs and develop a comprehensive plan to address them. “They listened to us and came up with a plan,” says Shea. “The support from SAS was brilliant. I would say it’s a true definition of a strategic partnership.”

The platform was fully operational in 12 months, and CPC users are now able to bring all the data points they need into one centralized area with real-time access to information. With SAS, they are able to answer questions in record time and show growth in revenues by product management lines of business, marketing, finance and others. “We can drill down into areas we’ve never been in before. And when you start drilling down, you may find areas that are in trouble, or areas where there are opportunities and can develop new pricing strategies accordingly,” says Shea.

Ease of access to queries and standard reports has freed up the time of power users so that they can focus on strategic analysis rather than manual data integration. “Now we’re able to bring it all together using the SAS Enterprise Intelligence Platform. And with the business analytics, we’re able to extract the data and develop the models to provide more precision in our pricing and improve our fact-based decision making,” concludes Shea.

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