Sunday, July 26, 2015

Driverless cars as a service: $16B+ for Google?

This past Friday four UCLA Anderson EDGE student teams competed in a case competition involving the future of autonomous vehicles (AVs). Teams were assigned to Google, Mercedes-Benz, Tesla, or Uber and were tasked with how each company should innovate in order to enhance its position in the battleground for the future of the automobile.

The Google team won, recommending that Google should enter the AVaaS (autonomous vehicles as a service) market. The team estimated that this initiative (which they code named GOOSE) could yield $16 billion in direct, transportation-related annual revenue for Google starting in the year 2020. The team assumed pricing for on-demand car services would fall by 50%, given that the "driver dude" would no longer be needed. (Of course, this analysis assumed that regulatory and other issues can be resolved.) In addition, the team estimated that Google could earn up to $7 billion in additional advertising related to this service.

The team argued that Google should "go to war" against Uber and become the leader in next-generation on-demand vehicle services. This possibility of  this battle has been widely reported on in the press. For example, in February, Business Week reported that Google was developing its own Uber competitor. Google was coy about its future plans, tweeting "we think you will find that Uber and Lyft work quite well. We use them all the time."

In 2013, Google Ventures (GV) invested $258 million in Uber at a reported post-money valuation of $3.8 billion. Since GV operates largely independently of Google with a prime directive of generating capital gains, it's not unheard of for GV to invest in potential competitors of its parent.

Uber, given the possibility of having to go head-to-head with Google, has not stood still. In March, Uber acquired DeCarta, a map-tech company. Then in May, Uber lured 40+ robotics researchers away from Carnegie Mellon University to significantly enhance the capabilities of its own robotics research center in Pittsburgh.

If the EDGE team is correct in estimating this market opportunity for Google, fasten your driverless seat belts.

Tuesday, July 7, 2015

Will Twitter's acquisitions in 2015 turn the company?

Twitter may be changing its CEO, but the company's M&A machine has certainly not been stuck in neutral. Our infographic depicts six acquisitions the company has made during the first half of 2015.

Overall, Twitter's acquisitions are continuing to move away from acquiring companies that build the core social network to companies that support monetization efforts. Consider some examples.
  • In January, Twitter acquired Periscope, which allows users to upload live video wherever they are and broadcast it for followers to watch. The consideration was estimated at less than $100 million in cash and stock, but skewed towards cash. The acquisition reflects Twitter’s move to bolster its video capabilities. Adding the ability to stream live video on Twitter capitalizes on the company’s strengths as a real-time broadcast service. This fall, Twitter plans to launch Project Lightning, which will provide special live event coverage for both Twitter users and non-users.
  • In April, Twitter acquired TellApart, which helps retailers leverage data by personalizing the customer experience and drive omni-channel commerce. According to an SEC filing the consideration was $533 million in stock. TellApart's integrated suite of marketing solutions has allowed marketers to deliver personalized messages in real-time across platforms such as display ads, Facebook, and email.
  • In June, Twitter acquired Whetlab, which develops technologies for machine learning, a branch of artificial intelligence that utilizes algorithms to detect patterns in big data and to make recommendations and predictions. Possible uses of Whetlab technology by Twitter include: 1) improving a user's tweet timeline; 2) enhancing the company's ability to target ads; 3) licensing data. While Google has information about user's search and Facebook has information about what people are doing, Twitter's cache of data is distinctive in capturing what "influencers" are thinking. Whetlab could help Twitter pattern such data into trends that are of high value to both consumers and businesses.
M&A success is about sound strategy, valid valuation, and intelligent integration. Twitter appears to have delivered on the first two elements. Let's see if it can pull off the third.

Saturday, June 20, 2015

Apple and Google algorithm for acquisition goodwill

When a company makes an acquisition it must identify and value the assets of the target and allocate net purchase price to these assets. If net purchase price exceeds identifiable net assets the balance is assigned to goodwill.

Now consider Apple and Google acquisitions over the past two years, for which these companies disclosed specific purchase price and associated goodwill.
  • Apple acquires Beats (music streaming): purchase price = $2.6 billion; goodwill = $2.2 billion. Goodwill percentage of purchase price = 85%
  • Google acquires Waze (crowd-source traffic information): purchase price = $969 million; goodwill = $841 million. Goodwill percentage = 87%
  • Google acquires Nest Labs (smarthome devices): purchase price = $2.6 billion; goodwill = $2.3 billion. Goodwill percentage = 88%
  • Google acquires Dropcam (smarthome monitoring): purchase price = $515 million; goodwill = $452 million. Goodwill percentage = 87%
  • Google acquires Skybox (nano-satellites): purchase price = $478 million; goodwill = $388 million. Goodwill percentage = 81%
No need to hire a Duff & Phelps or Houlihan Lokey. Looks like the algorithm is simple: goodwill allocation percentage must be a two-digit number staring with an 8!


Saturday, June 13, 2015

Innovation fuel: M&A or R&D?

One measure that indicates the extent to which a company intends to innovate internally or externally is the ratio of acquisition investments to R&D expenditure. Let's call this M&A/R&D.

During 2013, Apple's M&A expenditures were $496 million, while R&D amounted to $4,475 million. Thus M&A/R&D was 11.1%. In 2014 with the acquisition of Beats (eventually booked as a $2.6 billion cash acquisition), total M&A dramatically increased to $3,557 million. R&D expenditures were $6,041 million. And M&A/R&D mushroomed to 58.9%.

Consider Google. During 2013, the company purchased Waze for consideration of $969 million. Total acquisitions for the year added up to $1,458 million, and R&D amounted to $7,137 million. Hence Google's M&A/R&D for the year equaled 20.4%. Then (as was the case with Apple, M&A accelerated in 2014, with acquisitions that included Nest ($2.6 B), Dropcam ($517 M), Skybox ($478 M). Total acquisition investments summed to $5,061 million, while R&D grew to $9,832 million. For this year M&A/R&D was 51.5%.

Three takeaways.

1) The M&A/R&D ratio is hardly stable. In particular, it's highly sensitive to years in which large deals take place.

2) Much of present and future R&D can be related to past M&A. So the impact of M&A on innovation efforts may be understated.

3) For technology companies such as Apple and Google, the trend for M&A to fuel a large part of company innovation is likely to persist.

Tuesday, June 9, 2015

Twitter's acquisitions point to monetization

So far in 2015, Twitter's acquisitions are moving away from buying companies that build the core social network to companies that support monetization efforts and build MAUs (monthly average users).

Not a completely new strategy, but the corporate business development direction has become more clearly tuned to top-line growth.

The monetization potential for Periscope, a mobile live-streaming app that lets users shoot and broadcast video to followers in real time, is particularly promising.

See our infographic depicting Twitter's 2015 acquisitions at www.trivergence.com/market.asp?MarketID=4208

Saturday, June 6, 2015

Apple creating augmented reality ecosystem via M&A

The time has come for power tech companies to build augmented reality (AR) ecosystems. Augmented reality involves overlaying digital media and information on the real world. Think pointing a smartphone at a restaurant from a distance and automatically seeing its menu and Yelp ratings appear on your screen.

Google's Glass, much maligned but certain to re-surface with improved design, is a prominent instantiation of the technology,

Apple's recent M&A activity signals a ramp up of its own AR ecosystem.

Organizational ecosystems can be built using influence or using control, Taking an influence approach implies emphasizing partnership or minority investment arrangements, whereas control suggests acquisition or majority ownership.

When Apple built its original music ecosystem in the early 2000's, it influenced music labels to license content in order to build the iTunes platform. Now as Apple enhances its augmented reality capability, it is initially using control via M&A to build an AR ecosystem.

Consider three recent Apple acquisitions.

  • In late 2013, Apple acquired PrimeSense, a developer of 3D machine vision technologies for digital devices for an estimated $360 million. PrimeSensor is a system on a chip and a 3D sensing device that can see, track, and react to user movements. The company had worked with Microsoft to develop its successful Kinect motion-sensing gaming/television technology.
  • In April 2015, Apple acquired LinX Imaging for an estimated $20 million. LinX develops miniature cameras for use in tablets and smartphones. The company's cameras capture multiple images simultaneously using proprietary algorithms that can assess depth and create 3-D image maps. The acquisition continued Apple’s pattern of deals in Israel. (PrimeSense was also based in Israel.)
  • Then last month, Apple acquired Metaio, which creates technology that blends real-world imagery and computer-generated elements into video presentations. Metaio's augmented reality technology has been used to develop virtual product showrooms by retailers as well as visual repair manuals for industrial equipment.
M&A ecosystem clusters signal a company's future movement. Apple is clearly intent on throwing its design expertise behind building cool AR products and experiences to show off in upcoming Developers Conferences.

Thursday, May 7, 2015

Robots, start your engines

The Indianapolis 500 automobile race has been a Memorial Day tradition in the United States since 1911, going back almost as far as the last time the Chicago Cubs won the World Series in 1908. (We Cub fans live on in everlasting hope and frustration!) The dramatic starting command of the race is: "Gentlemen, start your engines," which is modified to "Ladies and Gentlemen, ..." when female drivers are in the race.

Could this starting command be further modified for races in the decades to come?

In early 2014, Google acquired DeepMind for a reported $625 million. DeepMind is an artificial intelligence company that builds learning algorithms for applications such as recommendation systems for e-commerce. The company was founded by neuroscientist Demis Hassabis (former chess child prodigy and master gamer), Jaan Tallin (Skype and Kazaa developer), and Shane Legg (researcher).

Google's acqui-hiring of Deepmind helps it compete against other players focusing on deep learning. Facebook has recruited Yann LeCunn (former NYU professor) to head the company's artificial intelligence lab. IBM is investing $1 billion in its Watson supercomputer division that is working on deep learning to support applications such as medical diagnosis. Yahoo acquired the LookFlow team to lead its deep learning initiative. And on it goes.

The field of artificial intelligence (AI) has undergone several cycles of boom and bust since AI was christened and sent out the door with research momentum at The Dartmouth Conference of 1958 organized by Marvin Minsky and others. Periods of buoyant optimism for the technology have given
way to AI winters. But in 2014, an AI spring had returned. Google’s purchase of DeepMind  reflected the new-found confidence in what AI could accomplish in multiple business sectors of interest to Google.

In March 2015, Google's DeepMind team revealed an algorithm that can teach itself from scratch to play early computer games with skill equal to or better than a human. The team eventually plans to work on three-dimensional games. According to Dennis Hassibis: "if this algorithm can race a car in a racing game, then with a few extra tweaks it should be able to drive a [real] racing car,"

Am wondering if DeepMind could start working on a pitching algorithm for the Chicago Cubs. Help us, Dennis Hassibis, you're our only hope.