FEW DOUBT THE LINKAGE BETWEEN BASIC RESEARCH

We’re all familiar with the term research and development (R&D). It’s a phrase measuring the amount of money a corporation invests in gathering new knowledge or creating new products. Investors use a corporation’s expenditures on R&D as one factor in determining its potential for growth and competitiveness. But let’s dig a little deeper into the macroeconomic view of R&D.

First, let’s focus on the research component of R&D. Research can be divided into two sub-components: basic and applied. The National Science Foundation (NSF) defines basic research as “systematic study directed toward fuller knowledge or understanding of the fundamental aspects of phenomena and of observable facts without specific applications towards processes or products in mind”. Applied research focuses on acquiring knowledge related to solving a particular problem or meeting a particular need.

Why do we care about research? Well, basic research breeds innovation. This is evidenced throught the increase in patents filed over the last 5 years and the corresponding rise in these patents’ citations to scientific literature. More and more patents rely on core aspects of basic research.

Universities responsible for basic research are acting as publicly subsidized incubators. The Massachusetts Institute of Technology (MIT) has spun off 4,000 companies with 1.1 million employees and annual revenues of $232 billion, according to the Alliance for Science and Technology Research in America (ASTRA).

If basic research breeds innovation then innovation breeds economic growth. Several studies have indicated that 45-75% of all economic growth is directly attributed to innovation. It manifests itself in high-tech job creation, new infrastructure technologies like the telecom/internet industry and technology enabled, ‘new’, business models.

So what is the primary funding source of basic research in the US? Well, in 2003 the US government was responsible for funding 85% of all basic research (60% Federal, 25% State/Local) most of which was performed in universities and national laboratories. Private industry funds the remaining 15%.

The trend in government subsidized basic research is disturbing:

• Federal funding for basic research grew moderately in the 1990s.
• Funding for the Physical Sciences and Engineering has flattened since 1980
• Federal Funding for Physical and Mathematical Sciences and Engineering are now .16% of GDP compared to .25% in 1980.
• The US government’s fiscal year 2005 budget proposed record funding for federal development due to large increases in defense and homeland security expenditures. Because of severe restraints on discretionary spending, most federal basic research and even favored R&D agencies of past years, like the National Institutes of Health, will see increases barely above the expected rate of inflation of 1.3 percent.

Where are we spending our basic research money? Six departments and agencies are expected to account for 93% of research obligations in FY 2010: the Department of Health and Human Services, the Department of Defense, the Department of Energy, NASA, NSF, and the Department of Agriculture. The life sciences are expected to account for over one-half of the total research funding (54.3%). Engineering is projected to receive the next highest amount (16.9%), followed by physical sciences (10.0%), environmental sciences (7.0%), mathematics and computer sciences (5.2%), social sciences (2.2%), and psychology (1.9%), with “other sciences” receiving 2.5%.

The US economy has been milking the research done years ago in telecommunications, aerospace and electronics. The US has prospered due in part to the invention of the transistor over 45 years ago. Since 1980 the US government has under funded basic research

The basic research spending trends must be reversed. It is time for the US government to manage its deficits and invest in the future of innovation.

US executives were recently surveyed by BusinessWeek and asked: “what are the largest threats to innovation in the US economy?” The executives cited reduced R&D spending (46%), the public education system (45%) and corporate bureaucracy (36%). The online survey was conducted by BusinessWeek Research Services.

Executives get it. Will the US government?

I’ve been a technologist for over 30 years and have always felt a certain optimism about our country’s economic future. We humans have the ability to discover, invent and adapt. And our economic model rewards those successes like no other. It does so with wealth, job creation and an enhanced standard of living. 

The exponential increase in the power and sophistication of information technology is proof that a capitalist system creates wealth and power through creation of productivity enhancement. It’s the power curve or exponential increase in infotech that is unique with capabilities on processing power increasing every 18 months. Our modern economy, for the most part, is based on Moore’s law. 

Technology and productivity are directly proportional, linked together in a recursive dance each driving the other. The traditional economic thought process goes something like this:

Advancements in technology drive larger and larger increases in marginal productivity. Productivity is the main driver of improvements in standard of living and economic growth. Productivity is a destroyer of existing jobs, but a creator of wealth. Wealth enables spending on additional products and services, replacing jobs eliminated by advances in productivity.

Two years ago I began taking a deeper look at the economic fallout created by the financial meltdown of 2007 and 2008. I like to sift through data and maybe considered, by most, to be a data nerd. The data I focused on was: unemployment, productivity and gross domestic product (GDP).

As we emerged from the recovery I noticed that productivity peaked at the zenith of unemployment. This IS to be expected as the productivity curve has peaked at the height of unemployment during 4 out of the last 5 recessions. However, as unemployment began to fall, the productivity curve fell at a slower marginal rate than ever before. And employment rose more slowly than other recoveries and was at higher than expected levels given the rising GDP. 

I blamed the disruptive technologies that were leveling the retail, publishing, manufacturing and many service industries. What else could it be?

I understood that technology had the power to destroy jobs; I didn’t think about it much, but I observed it first hand throughout the first decade of this century. I was always confident that technology would create more than it destroyed. However, during this recession, the reverse seemed to be true. Jobs were reappearing more slowly and there was no observable, proportional drop in productivity.

It was a form of systemic unemployment, not just a trough in the business cycle. 

I’m not now nor nor have I ever been a Luddite. But I was confronted with evidence that was pretty startling. Others noticed too. John Hagel et al wrote in The Power of Pull about the incredibly shrinking economic phenomenon. They described the ease at which jobs are shipped to the lowest cost provider overseas, and how service industries, leveraging explicit knowledge bases, were replaced with technology or were globally relocated because of technology.

This phenomenon surfaced during the 2008 recession and it became obvious to me as I read the economic tea leaves from 2008-2011. So with regards to job growth technology can take, but what does it provide in return?

I believe the answer lies within social, collaborative technologies. These technologies enable the rapid dissemination of information and ideas from the edges of the social network transferring it to the social core. Technology promotes rapid learning, it lowers cost and eliminate the time/location constraints. The Power of Pull enables us to learn at our own pace, at any time from any place. 

Is this a zero sum game? Can our labor force learn and develop new skills quickly enough to offset these systemic forces? Put another way: will the disruptive nature of technology overwhelm our economy’s ability to retool the labor force which has been disrupted? The rate of disrupiton is increasing. I’m not sure that our out-moded educational infrastructure can adapt.

So what’s the solution? I’d love to hear your thoughts.

It’s like a code. Every sentence can be translated from startup-speak to the English equivalent. I know I’m in for a long conversation, meeting or pitch when I hear any of these. 

Startup Says: ”We are a pre-revenue startup with a great team that has a proven track record. We’re getting early traction, our product has viral potential…just as soon as we get out of stealth mode.“ 

Translation: We’re giving our innovative product away to our friends and family, my mother-in-law really loves the dancing cats but nobody else knows we exist. 

Startups ought to leave this BS out of their elevator speach or product pitch opening. 

Startups Says: “We’re looking for $100,000 at a pre-money valuation of $1,000,000.” 

Translation: The actual valuation is closer to zero. We all know that. I’m totally open to negotiation. 

Every startup picks a muliple of a million dollars for preliminary valuation because it makes the math so much easier for angel investors to compute. Let’s face it; startups without performance metrics are impossible to evaluate…any attempt to determine value is a SWAG. 

So what are the common metrics? Well, it could be something like: customer acquisition over time, average number of minutes spent by user on site per visit, frequency of returning user, the number of transactions (pick one…) performed per user per day. Thes metrics can be turned into revenue projections, revenue into return and then return to valuation. 

Startups Says: “We’re a disruptive force…”

Translation: I heard someone at Y-Combinator say this about thirty times. Quickly check for a copy of The Innovator’s Dilemma in their briefcase but only after you’ve asked for their definition of disruption. Giving the product away isn’t disruptive, working 24/7 only disrupts their social life, ‘customerlessness’ is certainly not disruptive. It’s just a trendy way of getting attention. 

There are plenty blogs that have provided exhaustive definitions of what it means to be disruptive and the definitions often depend upon whether its a product or service. I’m not going to get into that here.

Startups Says: “We started up several years ago but after a lot of feedback we’ve pivoted…”

Translation: we’ve assembled a team of crack engineers or developers that were building a product that nobody really wanted. We’ve fired our product management team and are starting over.

Now don’t get me wrong, there’s nothing wrong with mid-course changes of direction…as long as your pivoting with your customer base, not away from them. Of course that assumes you have customers in the first place. It’s always best to talk about pivoting after its worked not in conversation with an investor or partner.

Startups Says: “We’re going to change the world…”

Translation: “I’ve recently returned from a Tony Robbins seminar and… I really love you man”

It is essential that entrepreneurial startups believe in their product or service; they have no other choice. I can’t imagine spending 3000 plus hours a year building a company that I didn’t believe in. So the startup gets points for enthusiasm but looses all credibility for the delusion. Put that sentence anywhere on your slide deck and you’ve lost me. Feel fre to talk about changing the world once you’ve actually started changing the world.

Startup Says: “The product is … a breakthrough, patented, innovative, yada-yada-yada”

Translation: “Lipstick is on the pig get ready to watch us make bacon”

When I hear these adjectives I’m prepared for a crappy demo or an unfinished product. My advice is to dispense with the adjectives. I want to know what the product does, who the target customer is and then I want a demo. In almost every case I’ll be able to detect the secret sauce if it’s there and I’ll be more excited because it was my discovery. After the demo reiterate the opportunity and then just shut up. The questions will come.

Startup Says: “We have no competitors…”

I never really know what to say when I hear this. The startup is either incapable of doing the research OR they’re pitching a product that has no market.  Competitors indicate that the market is prepared for the product or service; that’s a good thing. No competitors: bad sign. Go find some competitors…

OR be prepared to pivot because you can’t be disrupt a nonexistent market.  ;)

I’ve created a list that stratifies some of the more common revenue generation models that internet startups have employed. I’ll start by identifying a list of ‘general’ revenue generating methods. In a later post I’ll discuss pricing models in competitive and/or cornered markets. Finally, I’ll tie it all together by using several going concerns as examples.

The model is a bit muddy right now but I think it provides a framework for product planning, pricing strategy and customer acquisition. 

The revenue geeration models are:

• Subscriptions - freemium and premium per function pricing. Premium features may have multiple tiers each tier driven by functionality, additional user/per seat license.

• Content Consumption Subscriptions - fremium through monthly/yearly access to content. Fremium content can be metered e.g., access to a maximum number of assets/content per period.

• Ad Impression / Ad Network - usually piggybacked with free services, content or community functionality. This can be integrated within the fremium subscription model, premium subscribers receive no ads. Placement of the ad can be withiin web page, as commercials in videos, within a social stream or deliverd to a mobile device.

• Transaction Clearinghouses - companies facilitate transactions and take a percentage (the rake) from the transaction. A number of user interface, messaging and analytic features are often provided which increase customer acquisition. The clearinghouse model can also be tiered; where certain transaction types are free or at a low cost.

• Ecosystem Mining - Content warehouses (pictures, video clips, essays & blogs) offer methods to repurpose the content eg., print photos, place photos on mugs or photobooks. The ecosystem requires partners to accept the content and seemlessly deliver the physical good.

• Virtual to Physical - the ability to move digital assets from online view to offline delivery. Essentially an eStore for existing content; think the NY Times photo archive. 

• Donations - The consumer decides if they want to pay and if so, how much. Think of the PayPal contribution model of donating. Probably best for non-profits; I really can’t imagine this as a viable revenue generation practice, but quite a few organizations attempt it.

• Access Convenience - fremium or pay sites can offere mobile access to content, alerts etc., for a preimum price. Think of the the cbs.com mobile application for viewing network content from within a mobile platform.

• The Per Unit Price Model - it’s really a web store, virtual catalog and shopping cart. Physical or digital products are sold and delivered via drop ship, direct mail or digital download. Think iTunes Store, Amazon.com or Dell Direct.

• Social Revenue - methods of paying with social broadcast are emerging. Companies agree to exchange a digital good like a white paper, eBook or audio/video file in exchange for a Tweet, Facebook like or other social endorsement.

• Per Use - access to content, data or system functionality on a pay as you go basis; think of the movie rental principle applied to ebooks, contact lists or data mining applications. This is perhaps a subtype of subscription services; the transaction provides access with a predetermined time to live.

• Affiliate Networks - create a network of affiliates to help sell and/or distribute physical or virtual goods. Revenue is shared across the network on a per unit basis. 

• Pay for Influence - this method is tricky because it is more like social arbitrage. It is as much a business model as a revenue generation scheme. A communty of individuals is aggregated. The influence of the community is sold to a customer as a product: the community will provide some service to the customer. The customer pays the arbitrager. The community is compensated at some discount for participation. 

• Free to Subscribers - services like Twitter or Facebook have attracted customers en mass because they offer a product with high utility at zero cost. You can’t beat infinite ROI, and that’s the strategy for attracting customers. Monetizing the community is done through many of the other methods above, most notably giving advertisers (messengers) the ability to deliver a message at a price to a targeted audience. There is also an element of the ecosystem play there…I guess I could write an entire post on methods of revenue generation within social - perhaps I will.

I’ll probably add to this list over time but wanted to get it out there, attract some feedback and refine what I have. Drop me a line if you feel this list is incomplete, confusing or let me know if you have other thoughts on packaging and pricing an internet product or service.

=chuck=

The screw drivers were especially amazing. I learned quickly that I could disassemble almost anything and reverse engineer the contents. It didn’t matter if it was a new toy, my old train set or our telephone. They were assembled with screws, each had their secrets and I was going to crack the code. I poured over their innards like a voodoo witch reading the entrails of a chicken - it was magic, pure magic.

Needless to say my parents weren’t delighted with a disaassmbled telephone, that was the final experiment. In the 1960s phones were wired directly into the wall - yes, I disconected that too - and you couldn’t run out to Best Buy to buy a new one. I was punished, the tool box was taken away and not returned until my 15th birthday. I was taught a lesson: don’t experiment, quit being so curious and for God’s sake don’t break shit.

Over the years I’ve had the pleasure of working with a lot of smart people and innovative IT organizations. I’ve worked with startups, small businesses as well as Fortune five hundreds. Regardless of size they share many of the same traits and I’m often frustrated when they adopt the same early 60s philosophy laid down by my very conservative parents - they’re scared to death of breaking shit. 

There’s hell to pay when you break shit. 

You’re called into someone’s office to explain. You’re ridiculed in a meeting. You can’t be trusted to handle the cool stuff. There are consequences regardless of how fast you fix it. Organizations like this innovate slowly. Managers often say things like: ‘if it ain’t broken don’t fix it’. They are the stuff of innovation anti-patterns.

The fear of breaking shit ultimately results in endless design meetings, analysis paralysis, more rules, too many standards and the loss of all things pragmatic. The organization develops an aversion to temporary failure while innovation and optimization take a back seat to the ‘protect and maintain’ mindset. 

These teams have also dispensed with a valuable learning tool. You see, in order to put it all back together you actually need to understand how it worked in the first place. In order to innovate, you need to break the old, tinker with the new and deploy the results.

No startup can afford to be timid. A sign should be displayed on the product development team’s office walls with the caption: WE BREAK SHIT in 100 point font. It’s a take no prisoners pirate mentality that let’s great teams build great products without fear. 

What caught my eye wasn’t their business model, the products or the prospect that I might ditch PayPal for good. It was their value statement. Yeh, I know - value statement - kind of like a bulleted elevator speech for folks who don’t like run-on sentences. 

The five bullets were:

• Safety: Transactions should be safe and secure.
• Transparency: Users should always have access to their information and control of it.
• Speed: Transactions should be as fast as possible.
• Convenience: Our platform should be available on the devices people want to access it from.
• Value: Transactions should retain as much value as possible. The fees should be as low as possible.

I admit to being somewhat jaded - over the years I’ve read too much of this crap and I’ve always thought that mission statements are, well, for missionaries- and not applicable to cutting-edge startups that should be focusing on product not fluff.

My attention was drawn to those five simple words - safety, transparency, speed, convenience and value - and wether they COULD form the bounding box from which all current and future product development decisions can be made. Quite simply: no feature added to the product or the business model can violate the paramters established by the value statement.

In an era of too many words this short value statement is applicable to every disruptive startup’s product development plans; perhaps yours. 

The social web has been fertile ground upon which many Big Data startups have been planted. Open source movements like Hadoop, GridGain and Pentaho have iterated rapidly and have been used primarily to wade through the terabyte of data generated daily by social computing platforms.

Big Data technologies are already in use within the government, healthcare, financial services and retail sectors with more to follow.

That’s why today we begin coverage on the Big Data ecosystem by aggregating great content from thought leaders and practitioner from around the world. You can read more in the Big Data section of this site and stay tuned for more on Big Data startups.

First, microblogging has reduced the number of hobbyist bloggers. Those who once blogged have been whipped a state of retweet frenzy. Why take the time and make the effort to write a thoughtful post when I can retweet someone else’s thoughtful post; rinse then repeat?  

The 140 character limit has forced us to economize our thoughts but at the expense of clarity turning many ex bloggers into headline specialists, abbreviated linguists and link shortening specialists. After all what is a twitter post other than Blurb <link> Blurb <hashtag>. 

The channel is noisy - perhaps too noisy - with signal reception problems than can only be solved with client side technologies that filter out spam, porn and other unsolicited nonsense. A philosopher majoring in Yogi Barraisms might paraphrase with: “Nobody goes there anymore ‘cuz it always too crowded.” - Or just too noisy.

Ironically, this post will be advertised through Twitter, hopefully triggering numerous retweets and a cacophony of static in the twitterverse. Is this a great universe or what? 

The wonderfully crafted, cynical, sarcastic but truthful blog comment - once a work of art - is now Twitterverse casualty. With plug-ins Blogs can link to a Facebook like or comment, solicit comments via tweet or a one-click G+. Economical but at the expense of noise inducing hyper-shares.

While the Blog is alive and well, the blog comment has died a slow death - and we’ll miss it when it’s gone - So Long Live the Blog Comment…you were here for such a short while and we hardly knew ye. 

The quote is as true today as it was when it was first minted and the notion that “it’s your story go tell it” struck a chord in the social media music box that lately has become my mind. You see, there are too many opportunities within the socialverse today for your customer to tell your story for you - and get it all wrong. 

Products like Angie’s List, Yelp, Open Table, Four Square allow the customer to start a conversation about you. Positive word-of-mouth advertising is wonderful; a mediocre rating or unflattering commentary can be damning.

How do you control the damage once you’ve been tagged mediocre?  What do you do if the social conversation relegates you to a niche you never intended to occupy? It’s impossible to control the social conversation. So what’s the strategy?

Be the first to frame the conversation.

Extend your web presence through social media. Stake a claim to your corporate name on Facebook and LinkedIn. Microblog with Twitter and/or Tumblr . Develop an entrepreneurial persona by blogging passionately about topics related to your areas of expertise. Carve and occupy the niche you choose, build your social brand. 

The only way to keep others from telling your story incorrectly is to be there months ahead of them with the twenty-four carat gold original. 

Tweet-On.

Most of us would agree that higher education is overdue for a make over and most students would flock to an institution that offered a quality education at an affordable price. Last week Apple Computer tilted the playing field through the introduction of iBook Author and its integration with iTunes University. 

iBook Author lets anyone create rich, multimedia course content for free. Textbook authors can then publish their content to iTunes University where students can search, download and consume university quality courseware for much less than the price of a college credit. Many courses from prestigious universities like MIT, Cal Berkley and Stanford are free.

Undergraduate college students, on average, pay approximately $1,200 per year for textbooks; graduate students pay even more. With iBook Author, educators can take control of text book creation, eliminating the large publishing company middleman and reduce the price of textbooks. 

Companies like Udacity and Udemy have constructed service offerings that enables community created content and university created content to be published online and consumed en mass. The on-to-many architecture of the Internet allows thousands of students to take the same course at the same time with the same set of instructors and moderators. These economies of scale can’t be duplicated by traditional brick and mortar universities.

One piece of the puzzle is missing though: accreditation. While online institutions like the University of Phoenix offer college credit at higher prices than the disruptive startups they also confer degrees and certifications; which for most is the driving force behind taking a college or continuing education course. 

Only when high quality, low cost courseware is integrated within cirricula offered by accredited degree conferring institutions will we see the true disruptive power of zero emerge. 

Somewhere a startup is brewing their own version of Higher Education 2.0. and in the near future a college education will be made available to a much larger economic demographic; and that my friends will be a very significant turn of events. 

GSD

How many programmers does it take to eliminate 10,000 jobs?  

The most notable example is probably Craigslist a small San Francisco startup. Founded in 1995 by Craig Newmark, Criagslist grew from a small apartment based dot-com into the industries leading purveyor of classified ads and in the process toppled the newspaper industry’s control over the classified market.  The loss of the lucrative classified revenue stream coupled with online news outlets caused approximately 450 newspapers to shutdown while shedding over 40,000 jobs since 2007. Craigslist employs approximately thirty with a technical staff of twelve. 

In late 2011 Borders finally closed its doors laying off approximately 16,700 jobs. The cause: Amazon.com and the evolution of the eBook embraced by Apple, Amazon and Barnes and Noble. Add to this the fact that over 1,500 independent bookstores have closed in the last seven years. 

A slumping economy coupled with software delivered online ads has forced ad agencies to cut over 125,00 jobs since 2008 while Internet ad revenues rose to nearly $15 billion in first-half of 2011. 

In their book Race Against the Machine authors Erik Brynjolfsson and Andrew P. McAfee write that during the last recession the economic downturn prompted many businesses to look harder at substituting technology for people, where possible. Since the end of the recession in June 2009, they note, corporate spending on equipment and software has increased by 26 percent, while payrolls have been flat. 

In an August, 2011 puff piece Marc Andressen explains why software is ‘eating the world’. He describes a dozen industries disrupted by ‘software company’ startups indicating that more productive, free software tools coupled with the power and scale of cloud computing is responsible for this trend. And the trend will accelerate and  so will the rate of ‘forced’ unemployment.

Perhaps the software startups should be thought of as serial job killers capable of putting hundreds of thousands out of work within a matter of years.  Classical economists would have looked at this as a healthy state of events eliminating labor inefficiency in one sector of the economy freeing and then deploying that labor (ceteris paribus) to other sectors where it could be put to more productive use. But, that’s not been the case.

A self proclaimed serial job killer John Jazwiec notes that “any job that can be eliminated though technology or cheaper labor is by definition not coming back. The worker can come back. They most often come back by being underemployed. Others upgrade their skills and return to previous levels of compensation. But as a whole, the productivity gains over the last twenty years, have changed the landscape of what is a sustainable job.”

So while inexpensive labor may, in some cases, be a substitute for productivity enhancing technologies it is clear that software’s voracious appetite and the automation of all tasks that were once performed by humans is the foundation of systemic unemployment

The cure? Well that will only come in another, better educated America.  ”Where does the before-gainfully employed professional learn how to compete for jobs?”, writes Jazwiec. “Monster dot com? LinkedIn? The unemployment office? What infrastructure exists to retrain professionals to compete in a free agent job market, where only creative unique value contributors thrive?”

Indeed. 

In the meantime there is hope. If you’d like to land a new job or possibly future proof your employment prospects just get online and learn to program. Sites like Code Academy, Udema and Udacity may make training and retraining the underemployed more productive and more affordable than every before.  

Sources:

1. Newspapers Layoffs  

2. Ad Industry Job Losses 

3. Craigslist Fact Sheet

4. Software eats the world

5. Serial Job Killers: