Stephany Lapierre originally founded Matchbook, a service designed to find the right suppliers for companies streamlining procurement processes. Within its first year, the company became profitable and started to become a tool that went hand in hand with sourcing.
Her proactive, responsive, passionate approach led to the creation of TealBook. Clients’ needs developed to require support in building procurement functions to be more strategic, transparent, faster and prioritise cost optimisation over savings – so she provided that.
“As I provided these solutions, it started dawning on me that the problem with procurement was not software people or processes – actually, we overprocessed everything. It was a data problem,” Stephany explains.
“If we had good data and we could feed good data across these systems, it would drive better compliance and value of those systems and we could get built-in intelligence that would allow us to better optimise the investment made in suppliers.
She saw the clear issues in running companies without data-driven procurement and turned her focus from Matchbook to TealBook.
Stephany continues: “I thought if I don't do it, I’ll regret not doing it or worse, nobody's going to actually think about the problem this way and then it will be a decade or two later and it will still be high software dependency with siloed and disparate data. And I just didn't think that was acceptable.”
Stephany and the TealBook team leveraged machine learning (ML) to source and store trusted data.
“The thesis is that suppliers are more likely to update their websites before they update a bunch of supplier portals,” Stephany explains. “If we could capture the name, address, goods and services, team structure, any sort of logo of certificates or customers and any sub-site that would link us to other companies, then we could probably get a pretty good picture of what that company does.”
This led to the creation of universal supplier profiles, upon which TealBook expanded the data foundation.
“That was pretty novel at the time,” the CEO adds. “We could automate the collection, verification, and the enrichment of supplier data, create our own profiles and we didn't need to depend on D&B or other sources.”
And so, TealBook became an AI-first company that used automation to collect, verify, and enrich supplier data. Since then, the company has expanded its data foundation to pull more data at scale, fully automate that data and bring transparency and visibility into the quality of the data it is able to send back to customers.
The ethos behind TealBook is clear – quality data first. Regardless of the technology it requires, Stephany consistently delivers.
Read the full report HERE
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