#252: What Is the Best Way to Evaluate Electric Vehicle (EV) Success and Forecast Its Future?, & More

Recent research suggests that the best metric to evaluate battery success in the EV market is not $/kilowatt-hour (kWh) but $/charging rate, or miles of range added per minute of charging.

Our research aims to forecast the price and performance of EVs during the next five to ten years. To date, we have used Wright’s Law to forecast battery cost declines. Because the battery is its largest cost component, typically 20%, we can forecast the long-term decline in EV sticker prices. Forecasting other EV specifications is less straightforward, particularly metrics like range, efficiency (range/kWh), time to accelerate from 0-60mph, and battery pack size. Complicating the analysis further are battery cell chemistries with different $/kWh costs and performance tradeoffs.

Incorporating all specifications and equilibrating the comparison is a metric called “charging rate”, or miles of range added per minute. As measured by $/charging rate, most EVs today have yet to match the Tesla Model 3 circa 2018.  Our analysis indicates that none come close to the 2020 Model 3.

The rapidly evolving life science tools space is ushering in a renaissance for optical systems. Previously, ARK published a breakdown showing how Illumina’s (ILMN) research on super-resolution optics offers a path towards the $100 short-read sequence of a human genome. Along with next-generation DNA sequencing (NGS), optical advancements are enabling new classes of instrumentation like digital cell biology and spatial profiling.

Pioneered by Berkeley Lights (BLI), digital cell biology uses light and high-resolution imaging to collect functional – phenotypic – information focused on single cells, giving scientists an unprecedented view into cellular biology. NanoString (NSTG) and 10X Genomics (TXG) are using clever combinations of chemistry, machine learning, and optics to advance the field of spatial profiling. As a result, researchers can see the 3D-spatial organization of genetic material in tissues.

Novel microscopy techniques, such as Cryo-EM, seem poised to transform in silico drug development pipelines. When broadly available, Cryo-EM should be able to depict the structures of complex molecules. These structures form the training sets for AI-based computational biology like DeepMind’s AlphaFold. Continued progress in optics could cause a ‘rising-tide’, improving the performance of the entire life science tools sector.

Bitcoin has recovered from its second-largest price decline in history. After dropping 80% from December 2017 to December 2018, the bitcoin price broke out this week to an all-time high, $22,750 at this writing. The recovery took 730 days, a record for bitcoin. Bitcoin has broken out from previous all-time highs two other times, we believe a guide now to its potential upside.

In one of the worst cyber-attacks in years, hackers inserted malicious code into the software of numerous government agencies including the Department of Defense, FBI, DHS, CDC, and the United Kingdom’s Home Office, not to mention more than 400 of the Fortune 500 companies.

Instead of attacking organizations directly, the hackers inserted a digital backdoor into Orion, a widely used network monitoring tool sold by Texas-based software company SolarWinds. The backdoor allowed hackers to transfer files, execute scripts, and disable system services in the guise of legitimate processes. The hack exploited the complex patchwork of tools that manage on-premise IT systems built atop the Windows stack.

In our view, this breach is another catalyst for governments and enterprises to move toward Linux/Unix based systems as well as cloud environments. While theoretically on-premise computers are more secure than more centralized systems, the complexity of managing them makes them easier targets than computers in a centralized cloud.

To prevent follow-on attacks, SolarWinds has deployed CrowdStrike’s Falcon Endpoint Protection. In recent years, CrowdStrike has displaced legacy anti-virus providers by combining a lightweight client with a cloud-based, AI-powered threat detection graph.

As they have been grappling with anti-monopoly government policy changes, China’s internet giants also have been waging ferocious wars against one another. Pinduoduo, Meituan, Didi, JD, and Alibaba have been spending billions of dollars to launch community group buying across key regions in China.

Community group buying is a business model that enables contracted community leaders to offer group purchase discounts on, and pick-up points for, farm goods and fast-moving consumer products within 24-48 hours. Community leaders serve as liaisons between shopping platforms and consumers — organizing group purchase links on WeChat and offering their homes as micro-distribution and service centers — typically earning 10% commissions for their services.

With laser-thin contribution margins, this model is difficult to execute given the logistical challenges associated with cold-chain storage, last-mile delivery, and perishable goods, not to mention the difficulty of building customer loyalty. That said, given scale and operational consistency, the business commands high repeat purchases and can be quite profitable in absolute dollars.

We believe the community group buying war is unlikely to last long given its capital intensity. The ecommerce players left standing will have access to five trillion RMB (~$770 billion) in China’s fresh food sales which, according to Euromonitor, had online penetration of only 6% in 2019.¹

[1] ARK Investment Management LLC, 2020 based on data sourced from China Renaissance Report.