Tesla CEO Elon Musk introduces the Tesla Semi truck and an updated version of the Tesla Roadster at a 2017 unveiling. (Tesla via YouTube) Tesla today reported wider-than-expected financial losses in the first quarter — due to what the company said were delivery challenges, a seasonal dip in demand and the unanticipated effects of pricing decisions. Despite the downturn from what had been a profitable couple of quarters, Tesla CEO Elon Musk was bullish on several fronts, including rollouts for the company’s and , plus the opening of Tesla’s Gigafactory in Shanghai, China. Musk is even planning to offer car insurance policies starting next month, with pricing determined by the data that’s received from the company’s cars. “We have direct knowledge of the risk profile of customers and the car,” he explained during today’s teleconference with financial analysts. “If they want to buy Tesla insurance, they have to agree to not drive the car in a crazy way. Or they can, but then the insurance rate is higher.” If it’s done right, in-house insurance could add another revenue stream to Tesla’s bottom line. That could help ease the pain for Tesla’s accountants as well as for investors, who have seen share prices slump due to concerns about long-term profitability. (The price slipped nearly 2 percent during today’s trading, to $258.66 at the close.) Net losses amounted to $702 million, and adjusted net losses per share were $2.90. That’s 13 percent worse than the year-ago figure and . Revenue was $4.5 billion, which was better than the year-ago figure but not as high as analysts thought it would be. In its , Tesla said there was a production jam-up that forced a large number of deliveries to be deferred into the second quarter. “This is the most difficult logistics problem I’ve ever seen, and I’ve seen some tough ones,” Musk said. In all, 63,000 electric cars were delivered during the first quarter, which fell far short of expectations. In addition to the logistical challenges, Tesla said pricing changes for its Model S and Model X cars caused a higher-than-anticipated return rate. One disincentive to sales was the gradual phase-out of federal tax credits for electric vehicles. Previously: The good news is that powertrain improvements have boosted the performance and range of those two models: The maximum range was extended to 370 miles on a full charge for the Model S, and 325 miles for the Model X SUV. For the past two years, Tesla has been focused on ramping up production of the Model 3, which finally . Tesla reported producing 63,000 Model 3 cars during the quarter and is aiming to raise that figure higher. “If our Gigafactory Shanghai is able to reach volume production early in Q4 this year, we may be able to produce as many as 500,000 vehicles globally in 2019,” the company said in its shareholders’ letter. “This is an aggressive schedule, but it is what we are targeting.” Musk said that the Shanghai construction project was “going incredibly well,” and that he was receiving “midnight Gigafactory email” on an almost nightly basis. On other financial fronts: Tesla’s cash on hand fell by $1.5 billion over the course of the quarter, to $2.2 billion. A $920 million convertible bond repayment accounted for most of that reduction, and the delivery snag was an additional factor. Another, linked to Tesla’s SolarCity subsidiary, is said to be due this month. One analyst asked Musk whether he wished that he had persevered with efforts to take Tesla private last year — efforts that ended up getting him in hot water with the Securities and Exchange Commission. “I would prefer that we were private,” Musk replied, “but unfortunately that ship has sailed.” Musk told analysts that “at this point I do think there is some merit to raising capital,” but he didn’t provide further details.
Sales automation startup Outreach was the only Seattle company to make CB Insights’ list of future unicorns. (Outreach Photo) Can algorithms predict the next billion-dollar companies better than human venture capitalists? It seems possible, at least based on a formula created by CB Insights and The New York Times. Back in 2015, the companies published a list of 50 startups that would eventually becomes “unicorns,” or those valued at $1 billion or more. It identified candidates using CB Insights’ which analyzes the health of a startup based on various data including strength of market, financial performance, and overall traction — a “FICO score for startups,” as described by the investment data firm. Fast forward to today, and 48 percent of the companies on the 2015 list are now considered unicorns. “At the risk of sounding immodest, that is pretty good,” CB Insights this month. “And if we were a venture firm, this kind of hit rate would make us legendary.” That’s why it’s worth giving a look. (CBInsights Photo) The 50 future unicorns hail from various industries and the median company has about $111 million in total funding. A majority are based in the U.S., with 22 from California, five in New York, and two in Massachusetts. Outreach CEO Manny Medina. (Outreach Photo) There is just one from Seattle: sales automation startup , which this past spring, announced it was space this summer, made its , and was the only Seattle company to crack the top 25 in list for 2018. Outreach CEO Manny Medina said the company more than doubled its revenue in 2018 and met all goals and metrics. Outreach now has more than 3,100 customer accounts and 50,000-plus users. It employs 315 people and plans to reach 450 by the end of 2019. “This upcoming year we will make more investments in scaling the business efficiently and prepare for an IPO a few years out,” Medina told GeekWire. “This includes continued investment from our product to support, measure, and automate customer facing workflows. Our job is to make all sales reps great and drive higher revenue efficiency for their companies.” The 5-year-old sales engagement platform uses machine learning to help customers such as Cloudera, Adobe, Microsoft, Docusign, and others automate and streamline communication with sales prospects. Medina, a former director at Microsoft, originally launched a recruiting software startup called GroupTalent in 2011 with his co-founders Andrew Kinzer, Gordon Hempton, and Wes Hather. But the entrepreneurs in 2014 to focus on building tools for salespeople. Chris DeVore, managing director at Techstars Seattle — Outreach was a 2011 graduate of the accelerator — said the company is a good example of why he focuses on investing in people over ideas. “Outreach is one of my favorite stories,” . “The business they set out to build wasn’t working, but because they stuck together as a founding team and kept adapting and learning, they figured out how to find a productive thing. But that wasn’t because of where they started or the early metrics. It was because as humans, they were so committed and resilient and so gritty that they figured it out. “And that’s really what you’re betting on,” DeVore continued. “It’s a 10-year journey and it’s never always up and to the right. There are always setbacks and near-death moments. It’s the human capacity for resilience and persistence every time that will turn a bad investment into a good one.” While it’s a safe bet to invest in tenacious and dogged founders, CB Insights’ track record with its Mosaic score shows how data-driven formulas can drive smart investment decisions. That strategy has worked well for firms such as Seattle-based , an online revenue-based funding vehicle that uses proprietary technology to figure out which companies to back. Lighter Capital has invested in more than 300 companies across 500 deals since 2012 and plans to invest in close to 200 startups this year, CEO B.J. Lackland . A recent found that 38 percent of venture capitalists use data to source and evaluate investment opportunities. “Our survey shows strong adoption of data to inform investment decision-making and a growing appetite to increase usage,” Steve Bendt, vice president of marketing at PitchBook, said in a statement. “While the majority of respondents believe VC investing will always involve the human element, there’s enthusiasm to explore how machine learning can automate traditional VC.”