Opera Solutions has quietly built a strong and often vertically focused analytics practice within procurement and supply chain (among other areas), deploying a combination of technology (including BIQ) and applying a deep expertise to help companies identify a range of cost take out, recovery and other opportunities. It’s a company of statistician geeks who really know what they’re up to. And it’s now an organization that has much more in its coffers to target procurement, operations and other areas with advanced analytics offerings and solutions. Earlier this week, Opera raised $84 million in funding from a combination of Siler Lake Sumeru, Accell-KKR, Invus, Tola Capital and JGE Capital Management.
The WSJnotes that the deal values the company “at around $500 million.” Describing the organization in broad terms, the same article suggests, “Opera builds big-data computer systems that can suck in billions of pieces of data at once — from home and auto prices to real-time information on brokerage accounts or supply chains. It then analyzes that data to pull out ‘signals’ or insights about how consumers, markets and systems are behaving.”
In reading this, one might think that spend and supply markets analysis is only a small part of what they do. But one of the new investors spent an hour on the phone grilling a colleague and me a couple of months back about spend analytics specifically (with a lot of good, informed questions). Clearly, it would be wrong to dismiss this area as just a subset of a broader solution portfolio that Opera no doubt plans to further build out with this cash infusion. This week, I briefly caught up with Opera Solutions at ProcureCon and was quite excited to hear about some of the things they’re up to in the procurement and operations areas.
In the coming months on Spend Matters (and our sister site, Healthcare Matters), we’ll definitely be hearing more about these guys. In particular, we’re keen to better understand what Opera is up to in taking cost out of the healthcare supply chain through drilling into different information sets for customers. What I heard briefly sounded good. But the proof (as always) will be in the data — and results.
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