Canadian Manufacturing

Can you predict future trucker protests and avoid supply chain troubles?

by Sadi Muktadir   

Canadian Manufacturing
Financing Manufacturing Operations Research & Development Sales & Marketing Supply Chain Technology / IIoT Automotive Electronics Infrastructure advanced manufacturing AI financing In Focus Industry 4.0 Manufacturing Research supply chain Technology

ThinkData Works' platform provides a centralized view measuring public data signals so OEMs can avoid supply chain disruptions.

PHOTO: Supply chain/Nick Saltmarsh via Flckr

ThinkData Works Inc. may be onto something.

On Jan. 18, NGen, the industry-led organization funding advanced manufacturing businesses in Canada, announced $8 million in collaborative funding for ThinkData Works Inc., in conjunction with Palantir Technologies Canada and Martinrea International.

The funding is intended to help expand a supply chain resiliency platform that collects data and helps manufacturers like Martinrea make choices and decisions to avoid supply chain troubles, lockdown-relayed delays and materials shortages.

The platform intends to provide a centralized view with predictive analytics, real-time alerts, and recommended actions.


Bryan Smith, CEO of ThinkData Works Inc. explained how the project came together.

“Most manufacturers don’t have insight into public signals that could affect their supply chain. They’re not measuring government regulations, weather effects or things like that, so we wanted to bring our data platform and transition into new sectors like supply chain management to help manufacturers avoid those kinds of delays,” he explains.

When Jayson Myers, CEO of NGen Canada was asked about the decision to support ThinkData Works’ platform, he explained the importance of Martinrea’s involvement in the project.

“Our project with ThinkData Works, Martinrea, and Palantir aims to increase visibility throughout Martinrea’s complex network of suppliers to assess their capabilities and supply chain risks and help predict supply chain problems before they might actually arise. The solution will help Martinrea improve supply chain resiliency in the face of future risks – that will in turn improve their ability to sustain their business by avoiding future supply chain problems.”

Bryan Smith was also asked what a data platform could do for Martinrea through this funding, and if that would mean being able to avoid delays due to protests and trucker convoys potentially disrupting trade.

“We can definitely collect data around trucks crossing the border, ships being stuck in canals, and even extreme weather alerts. These kinds of public signals can help manufacturers model and forecast better to avoid supply chain issues. Ideally, we’d also love to be involved in policy-making as well with governments, so we can predict and avoid procurement problems and stay ahead of shortages.”

It is no secret as well that Canada is facing a talent shortage when it comes to its manufacturing industry, which is what funding like NGen’s hopes to also address.

“Canada has the potential to create an advanced manufacturing centre of excellence around this, and we already have some of the best engineering and data science programs in the world. I know NGen’s Careers of the Future program is already focused on that, but I think an investment like this definitely helps make the case too,” says Bryan.

ThinkData Works Inc. is currently recruiting for the second cohort of adopters, and they’re open to speaking to governments as well for policy simulations. They are interested in any manufacturer with a cross-border supply chain with a just-in-time shipping model.

“Those are the sorts of businesses that are going to see the biggest benefits from the supply chain platform, because they see the biggest impact from supply chain disruptions,” says Bryan.

Big data is helping Canadian businesses be more proactive rather than reactive in growing its advanced manufacturing landscape, and hoping to help forecast future troubles before they happen.


Stories continue below