Monday, July 21, 2014

What will drive long-term value in the tech sector?


Will the tech sector continue to defy the gravitational rules of business with overheated valuations for unprofitable companies? Should we be collectively holding our breath that “the next big thing” will be the Internet of Things (IoT)? Or is it simply a case of too much angel, VC and acquisition money chasing too few really good new business model ideas?

Stratospheric Valuations.

Simple. Personal. Real Time Messaging. Gold.
The Wall Street Journal reported on the stratospheric valuations in the tech sector a few weeks back. They cited the $ 19 billion Facebook acquisition of WhatsApp back in February in a play to dominate messaging on phones and the web. Then there is the valuation of Uber at $ 18.2 billion in a recent round of funding. That makes Uber worth more than Whole Foods, United Airlines, and ALCOA. According to The Guardian's James Ball this valuation represents "...a nadir in tech insanity." 

Moving People. Stratospheric Valuation.
Doing the simple math, that's a whole lot of taxi-dispatched rides. Bell went on to say "So long as there are greater fools down the line - prepared to buying the hype and load up on tech stocks - the train will carry on...founders cashing in on the venture capitalist, who in turn get rich off the pension funds and 401ks who load up on these stock after buying into the west coast hype."  

Some scary thoughts around some really big numbers.

What's the next big thing?

A bad idea - that died quickly.
The WSJ Technology Columnist Christopher Mims went on to report on more start-ups a few weeks later in an article titled "Is Silicon Valley Pouring its Money Into the Wrong Stuff?
 They cited possibly the dumbest app ever "Yo" that allows users to send only one message is reported worth $ 10 million, and Washboard -  the start-up that launched a while back promised to  deliver a roll of quarters (worth $ 20) for only $ 27. Perfect for people who are lazy and hate standing on line at the bank. Thankfully, it just closed down.

The "Smart Things" value proposition. But is it good business?
Mims is not even convinced that "smart homes" powered by IoT are the next big thing. I tend to agree with this perspective. I don't wake up in the morning using my smart phone as the remote control device for the rest of my life. I actually get up, go running with my dog in Central Park and eat breakfast, all without any tech intervention.

Mims argues that the complexity added by automation outweighs the convenience. The WSJ visited "the smartest home in America" - inhabited by Smart Things CEO Alex Hawkinson. He says all these dumb objectives that are now connected promise to make life better...at least in theory. Watch the video and you can judge for yourself. The only thing that really made sense to me was the home security use case.

Is too much money chasing too few really good ideas?

Lots of start-up time and energy is being channeled into optimizing advertising platforms vs. creating life transforming businesses in energy, food production or medicine. Simple research shows that the entire market for US advertising is about $ 100 billion against the backdrop of the US GDP of $ 16 trillion. All these ad-optimizing sites are chasing 0.6% of the US economy. I didn't go to Harvard for business school, but I get the folly in this misdirected effort. Still this fixation on monetizing business models based their ability to generate ad revenue continues.

Where does the US need help?

The list of worthy sectors for investment and tech-driven improvements is not hared to find. Crumbling infrastructure, the "digital divide" of those with easy access to the Internet vs. not, affordable medical care, wellness education for a nation suffering an obesity epidemic and widespread substance-abuses. The list goes on and on. 

A smarter way forward.

I admire VC firms like Artiman with its one line description of "Partnering for the long haul" and its investments in companies that meet basic human challenges with "white-space investments."

They openly claim they love hard science and technology. They say that some of the most exciting disruptions come from technologies in the "ampersand" in R&D - proven research that hasn't been commercialized yet. 

Just look at their amazing portfolio of investments that cover a broad range from 
CellMax Life and OncoStem Diagnostics focusing on cancer diagnostics to that using leading edge technology to zSpace, a firm that enables natural interaction with virtual holographic 3D images for manufacturing, architecture and medical research. 

A venture investor taking this "doing well by doing good" approach to business is NGEN. They invest in companies that positively improve the environment and human wellness, that offer rapid growth and sustained profitability. What a novel idea.

These types of investment are not so glamorous, and I don't see may pitches for these kinds of firms at all the NYC tech meet-ups I attend. So I just might encourage my HS senior age son to take AP Chemistry and Physics this fall and major in a hard science in college. This education track may lead him to a career in medicine or being an engineer - and end up paying handsome dividends, not only for him but for many people in the long-run as well.





Monday, July 7, 2014

Big Data: A means to and end, or an end in itself?


Big Data: The Matrix in Reality?
Back in the spring of 2011 McKinsey declared “Big Data: The next frontier for innovation, competition and productivity. As usual, they called this explosive trend “Leaders in every sector will have to grapple with the implications of big data, not just a few data-oriented managers.”

Their estimations of value creation were nearly unbelievable back then. They declared big data a critical factor of production, along with labor and capital. They cited five broad ways using data might create value, from making information transparent and usable at higher frequency to improving performance and making better management decisions.

Experts cite the fact that many firms have jumped on the big data bandwagon -analyzing large streams of information - only to fall into common traps and have nothing to show for their efforts in the end. Some 44% of IT professional surveyed by business software firm Infochimps Inc. said they had worked on big data projects that ended up on the scrap-heap.

Last year the Wall Street Journal reported on “Big Data, Big Blunders” and cited five common mistakes firms make and ways to avoid them. # 1 was “Data for Data’s sake.” Many firms fail to agree on the most important question: What is our goal for use of this information?” Considering anything with an on / off switch throws off “data exhaust” there is a nearly inexhaustible source of data – but to what end?

A lack of qualified data professionals is also causing problems. The Harvard Business Review called “Data Science the sexiest job of the 21st Century” back in 2012. They say that demand has raced ahead of supply in the data scientist labor pool. The problem is magnified by the lack of formal training / degrees in data science, little consensus on where the role best sits in an organization nor how data scientists can add “the most value” possible. McKinsey estimated a short-fall in the US of 140-190,000 skilled analytic professionals, along with 1.5 million managers who can make better decisions based on their findings.

Marketing and IT departments discussing Big Data.
Another pitfall the WSJ identified as “organizational infighting” or “territorial spats” between departments over who owns a project. I have seen first hand knock down, drag-out fights in Fortune 500 firms between IT (who claimed ownership of the data) and marketing (who desperately needed the data to inform and measure business plans). 

Some claim a Chief Analytics Officer position is the solutions, but that person will be little more than a referee at an unruly sports match unless they control the budget allocation for data analytics.

One of the best uses of big data is IBM Watson – a big experiment in cognitive computing that searches massive amounts of data and serves up hypotheses (with confidence levels) on questions it is asked. And it is designed  to “learn” as it works with more data on a give subject matter.

In the end I am in the camp that supports use of big data as a means to an end.

For business - use of big data and analytics should help save money by defining the most cost- efficient ways to do things; drive incremental revenue by helping identity new business opportunities or optimization of investments by better measuring ROI of all sort of things from marketing spend to distribution strategies. 

Using big data as a means to an end supports one of the most pragmatic business lessons I ever learned: Test – Learn – Apply. Try different approaches, measure their success (or not) using data, and apply analytic-based learning to inform future efforts. Rinse. Repeat. Look smart and drive profitable growth in the process.