His estimates were consistently incredibly lower than others. Related, there were comical product planning challenges with Russell. Then, the engineer, nervous not to offend the CEO, might agree, "well, maybe it's possible to do it that way", even though that was a theoretic possibility, not something 3VR could practically do in the foreseeable future. Russell was really good, in a bad way, at asking individual engineering specialists about specific problems, probing them to admit some way could be found. This was a huge problem, especially when 3VR faced real customer problems because Russell's reaction was to explain it away or offer some unrealistic but impressive-sounding non-solution.Ī great example of this was an informal 'Russell Rule' that the engineers had that no engineer should speak to Russell for more than 5 minutes. While he sounded great talking about technology, after a while, you began to realize that Russell was engaging in wishful thinking, at best and science fiction, at worst. The problem was that he was terrible at understanding and accepting reality. This was terrific for a startup because when hard things came up (like facial recognition), he had great answers. One of the most amazing things he would do is talk about all levels of technology and technical details, but unlike engineers, he would say it confidently and without hesitation nor examining exceptions. An incomparable pitchman, he combined self-confidence, humor, and intelligence in an extremely rare combination. He was incredible at getting people excited and convincing people things could be done. And, as the last decade showed, this is still a challenging problem today.Įnter CEO Steve Russell - simultaneously great and terrible. On the other hand, after carefully analyzing various field results, key engineering people knew the problems faced and that eliminating them was far beyond any reasonable short to mid-term action. It could have been field errors and even if it was not that, the technology could have possibly improved so much in the next few years that the issues would be resolved. In fairness to the optimists, it was not as clear back then. Obviously now, it is easy to look back and see the 'pessimists' (not surprisingly, myself included) were right. For example, many at HQ were understandably confused or skeptical about the problems in the field. This combined resulted in dramatically worse performance and false alerts / matches.Ī major internal problem that resulted from this was a debate about why these results were so much worse. They had lots more people, lots more restrictions on where cameras could be placed, challenges in how people moved (large hallways, turns, etc.). The real problem came when 3VR's facial recognition started to be deployed in larger public sites (e.g., hotels or multiple bank branches). Likewise, in smaller beta and early deployments, especially with friendly customers, it 'mostly' worked. With a small number of people to be analyzed and key engineering people to set things up precisely, 3VR worked pretty well inside 3VR's office. Like any analytic startup, 3VR started using their analytics in small areas - their own office with their own employees and people coming by for meetings (investors, prospects, etc.). One issue was a lack of experience in the surveillance industry but that was far less of a problem than not being able to deliver 3VR's core value proposition.Ī key challenge 3VR experienced, and something still an issue today for many analytics companies, is a false sense of confidence from demos and small systems vs problems in larger production systems. The stereotype of Silicon Valley as a center for talent certainly proved true. One thing that certainly was not an issue was talent. What did they try to do? Why did they not try other things? What lessons can be learned?Īs someone who was on the inside during the early stages (2005 - 2007, first as Director of Systems Engineering, then as Director of Product Management), my goal is to share perspectives and ideas that might help illuminate the issues involved. If you make it work, it has clear huge value.īut the more interesting question is: how did 3VR handle the problems? Obviously, they knew long before their firesale to Identiv that analytics had big problems. It is the same reason that Object Video bet on it in 2001 and Hikvision is betting on it in 2018. The reason they bet on analytics is simple too. 3VR destroyed transformed ~$65 million in VC funding into a $6.9 million exit.
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