Consumerisation of Health Care

I recently featured in a corporate video about the consumerisation of health care. I appear in the last minute or so (only a two minute video).

Click here to see it.

I think it provides an interesting flavor of some of the thought leadership at Optum (I work for OptumLabs, and Optum subsidiary), and some insight into major themes in healthcare today.

The backstory is that I spent some time being made up for a corporate video shoot a few months ago. 

The make-up took a few minutes, and then they interviewed me for an hour or two.

From that, they suggested some of the footage might be included in a corporate video.

The next thing I hear, a friend Moshe Cohen noticed the following on CNN Politics (phone screen shot). Thanks, Moshe!

Looking at UK and US Healthcare Systems

Here is a guest post I wrote for Healthblawg's 10th anniversary (with thanks to David Harlow for inviting me to contribute): US and UK Health Systems - Not So Different?

Choose Life

There is a verse in the Bible which includes the exhortation “I call heaven and earth as witness today, that I have set before you life and death, blessing and curse; therefore choose life!”

I have always loved that verse because of the very active emphasis on the word choose. The command is to choose, not to live, or live well, but to choose.

The reality of our lives lies between belief that we have some control over our world, and fear that we are at the mercy of random chance. What we always have, however, is choice about how to hold, frame, and behave in a world where control and random chance play against each other like streams of water carrying a leaf.

I recently came across this amazing commencement address by David Foster Wallace from 2005. I recommend listening to it – it captures these themes so perfectly – and it is worth taking the 20 minutes of uninterrupted time to do so.

This is water–David Wallace Foster

(Link here for those for whom the embed doesn’t show.)

Since this was triggered by me quoting a religious text, I suggest, along the lines of Alain de Botton’s “Atheism 2.0” TED Talk, that you listen to Wallace’s “This is water” every year, perhaps when Deuteronomy 30:19 is being read in the annual cycle of readings in Synagogue.

Characteristics of Big Data

Doug Laney is the original creator of the 3V’s definition of Big Data – referring to volume, velocity or variety of data that is hard to handle with traditional data management tools and techniques. In August last year I proposed a better definition of Big Data as Data growing faster than Moore’s Law. Many others have talked about extending the 3V’s definition of big data, and one of the additions is to insist on a fourth V: “Value”. In my personal view this is somewhere between irrelevant and dangerous. Any data may or may not have value, and that value is highly context sensitive. If you want to know the weather tomorrow, then knowing the stock market closing price from 1897 is of no value. The beauty of big data is that while most of it may be irrelevant, the patterns that can emerge are of real interest and value. Furthermore, the value of big data may not become clear until long after it is created (only once we had collected uncountable tweets from the early years of Twitter did someone realize you might find information relevant to stock prices buried in the stream of “valueless” data).

D. Robinson posted a great article in December called Big Data- The 4 V's - The Simple Truth; Part 4 - Making Data Meaningful. This talks about the need for Veracity (is the data reliably recording what is going on) and the problems of Variability (where a system may record different values for the same physical activity on different occasions). However, even these are not defining characteristics of big data, but are interesting attributes of any data collections.

Instead, let me offer some other extensions to the 3V’s definition. You don’t need all of these to have big data, but the more you have, the more likely it is you are dealing with big data.

Bonuses at Startups

Eric Paley of Founder Collective wrote a great blog post earlier this month: "Bonuses are toxic at startups” (which was later republished on CNN Money).

In my years working in VC (the first time I have used this phrase), I found myself in complex situations about bonuses with the leadership of several startups, but had not stepped back to think about the underlying patterns. I agree wholeheartedly with Eric’s analysis.

Back from the Dark Side

As many of my friends know, I recently joined the team at Optum Labs as Chief Operating Officer, located in Cambridge MA, working for the newly appointed CEO, Dr. Paul Bleicher. Also as many of you know, I was fortunate enough to be a co-founder with Paul at Phase Forward. Having worked together before, I was particularly pleased when he asked me to consider this opportunity.

Years ago, when I first joined Sigma Partners venture capital, everyone (including me) talked wryly about me “going over to the dark side.” (This is an industry wide joke; look at Mark Suster’s “about me” box on his blog, and what Andrew Manoske wrote in his article “Joining the Dark Side: Why I left engineering to become a VC.”) Even if Mark Suster and Andrew Manoske are still on the dark side, I am back on the operating side of the world – by corollary, back working for the Jedi knights, and remembering how to build my own light sabre.

I have not until now written publicly about my recent efforts to raise a micro-VC fund, which I had called Big Data Boston Ventures (BDBV). That was because the SEC has not yet published new regulations (required by the JOBS Act) to allow for a more relaxed approach to marketing for VC funds. While I was raising a fund I couldn’t talk about it – now I have stopped that effort, I can.

Big Data Boston Ventures was conceived as a micro-VC fund that would invest in seed stage companies which fit into the big data theme. I have been writing about big data in this blog for a while, and the idea that I am bullish on this should surprise no-one.

Many of my friends in the entrepreneurial and investing community have said (at least to me) that my fund concept made lots of sense, that it was needed, that it was the right theme, that I would be a sought after investor/mentor (and hence get the opportunity to participate in great deals), and that, therefore, the fund would be successful. The LP community (those who invest in VC funds) are caught in a series of dynamics that mean they are just not interested in taking the kind of risks that such a fund might offer. Many GPs (VC general partners) with a better track record, and a more conventional (and in that way stronger) pitch story than mine have been finding it tough to raise new funds. This was all the more so for me as a solo GP going out with a first fund.

I had not actually given up on my fundraising when this new opportunity presented. I was making very slow progress, but progress nonetheless, and had certainly planned for another few months to try and get launched. However, when Paul called about Optum Labs, I was immediately intrigued, and quickly became very enthusiastic.

People know I am a very interested observer of healthcare and life sciences (HC/LS), and have made a point of staying current on trends in the industry and related IT. Ever since the inception of BDBV, people have suggested I focus on healthcare and life science (HC/LS) inside the big data theme, or even consider a pure HC/LS IT fund. My consistent response was that I believe that while there are great HC/LS startups that could fit into a fund with a broader big data theme, there just are not enough to justify a narrow industry-focused seed stage fund. This answer provides the background for my response when Paul called. Optum Labs provide the opportunity and challenge for me to work at the center of innovation in HC/LS. Optum Labs is a small startup inside a large, well respected organization partnered with leading players in the industry.

I plan to stay in touch with early stage startups in big data, and especially in healthcare and life sciences. I hope to continue to do some mentoring and be involved in other ways in the start-up community. Optum Labs is based in Kendall Square (One Main St) so I will still be close to the action.

Presenting to Win

“Whether you are presenting to investors or to startup competition judges, you are faced with some amount of random behavior.”

A while ago I wrote a piece on “How to Score an Investment for your Startup”. Following that theme you can now read “Presenting to Win”, my latest article written for Scalable Startups project at UC Berkeley.

Will your startup be around for the long term?

Who wants to know whether your startup will be around for the long term? Everyone.

“Investors want to invest in a company that will be around long enough to have a chance of making money. Customers don’t want to spend time and effort bringing on a new product or service that might go away. Employees (and their spouses) want to know the paycheck and benefits are at least somewhat stable (no matter how many stock options you give them).”

Check out my article on demonstrating some hope of longevity for the Scalable Startups project at UC Berkeley.

Your business in the Gartner Hype Cycle

I was recently asked to contribute to a series of articles for the Scalable Startups project at UC Berkeley. The first of my articles is now up and available for reading.

“Most new businesses that are based on new technology of any kind are at the mercy of the Hype Cycle.”

The gist of the article is that knowing where you are in the hype cycle is an important part of startup self-awareness.

Comments welcome!

Incentives without pricing?

When I get to refilling a prescription on the CVS website I am amused, and then sickened, by the announcement that “Price will vary based on insurance”. When I click on the link “Why can’t you tell me the price?” I get the response in the pop-up as shown in this screen-capture.

I could complain about the fact that they do have my insurance details on file and could at least tell me the the expected price assuming my insurance doesn’t change by the time I pick it up in two hours.

However, this is just the tip of the proverbial iceberg. Ask your doctor how much that blood test will be – he or she will likely not even know what the “list price” is, let alone what the negotiated rate for your insurer, or the status of your annual deductible. If you are referred to a specialist you can’t shop by price for the same reason.

This means that all this market based reform which is supposed to incent patients to use healthcare services “more wisely” is crippled from the beginning. If I can’t find out how much something costs ahead of time, how can I decide which is the cheapest. It goes without saying that I can consider various quality metrics to my thinking (some of which are possible to find ahead of time), but come on, be serious! Consumer oriented market based incentives without pricing information – it’s a fallacy.

Should an Angel Investor also get Advisory/Board Equity?

It’s demo day time of year in New England. Last month was the big MassChallenge finale. Last week was demo day for BetaSpring in Providence, RI, as well as for HealthBox Boston. This week it’s Techstars Boston Demo Day. One thing most of the presenting companies have in common is that they are raising seed investment funds from the angel, micro-VC and VC communities.

Over the last couple of years entrepreneurs have asked me a few times about cases where a potential angel investor, often someone who has been a mentor to the company in the program, says that they want to invest, but that they also want extra equity for being an advisor or board member, because they “bring more to the table than just money”.

Those people may be right. Some angels can indeed offer more than just money, but the decision about who should be an investor is different from who should get equity for advisory or board help. Equity is very precious, and so advisory or board equity should not be granted lightly.

Here is my advice.

1. If someone can be really helpful, the chemistry is good, you like them and you think they can bring great value as an advisor or board member then you should be willing to bring them on in this kind of role and grant them some equity, whether or not they invest.
2. If someone is your lead (or a major) investor and their terms are to require a board seat (plus equity) then you can decide whether or not to accept those terms, negotiate them or reject them.
3. If someone is joining an existing structure for a seed investment but insists on this extra role and equity you can politely say that you are keeping those elements separate, and they are welcome to invest but you are not linking the two at this time. This may mean turning down an investor. Obviously if you NEED them to make the round come together then you are back to #2.

Certainly you can approach this cautiously... including asking for references of other CEOs and startups where this angel is filling this kind of role, ideally from companies in similar industries where the extra “sweat” contribution is likely to be similar.

You should make sure the extra equity is common stock (not preferred), that it vests with a one year cliff, and that you have the right to terminate the relationship without cause at any time if you feel the person is not really adding the value that you hoped.

Four Reasons for a Business Model

This week at Techstars during my office hours sessions, I was asked questions by several teams which each time led to the same place: please draw a business model diagram for me. Everyone could, or said they could, but in each case it was clearly not a practiced exercise.

A business model is not a business plan, although the two are often confused. How can you tell the difference? A business model fits on one piece of paper (or one flip chart page or one white board), is referred to regularly, and has all sorts of uses. A business plan is a big pile of paper that even the author doesn’t read all the way through, and certainly no-one else does.

A business model

A business plan

My favorite approach to a business model is (as previously mentioned) the Business Model Canvas. There are other approaches, but, to qualify, it must fit on one piece of paper, and must be a diagram of some kind.

Here are my four reasons to have a one-page business model picture

• Completeness: you can make sure you have addressed all aspects of the business model. This is not exhaustive completeness – it should be quite high level and avoid getting into the weeds – but you get to see if you have any glaring holes.
• Consistency: you can see whether all aspects of the business model are consistent with each other. For example, does the assumption about partners line up with the assumption about channels?
• Clarity: you can see whether (and ensure that) all your colleagues are clear about what you are doing and why. If asked to draw the model independently, would they draw the same thing? The model becomes a concrete focus for discussion about how it all fits together and brings out any misunderstandings or disagreements about what you are doing.
• Communication: you can draw and redraw the model as you tell the story of your business to mentors, advisers, potential recruits, and potential investors. It can focus a staff meeting, board discussion or investor presentation. You can much more easily remember a diagram (and recreate it from first principles) than you can remember a page of text.

If you have started to think about a business you have started to diagram things out. That’s where to start. Take an hour. Certainly stop after 90 minutes. Leave it on a white board. Share it with colleagues and advisors. Let them add post-it notes with questions. Go back to it with at least a couple of people around each time – let the brainstorming drive good thinking.

Don’t sweat the small stuff – even on the nine-sections of the Business Model Canvas, you only need six or seven elements to get going. Every company has “sales and marketing” as a Key Activity, and every tech company has “develop the tech platform” as well (and then “tech platform” shows up on the Key Resources panel, too). Don’t worry about that kind of completeness. Do worry about a value proposition for each customer segment, differentiated key assets and key partners, and revenue and cost components that characterize the economic drivers of the business. Advanced uses of a business model diagram include layering on key assumptions, generating explicit hypotheses, and building out tests of those assumptions.

On a very related note, Steve Blank recently wrote a great post on misunderstanding a business model methodology (and how to fix it). Heidi Allstop of Spill shared this great resource with me for those interested in an online canvas tool.

The Shortest Starbucks Order

Back in 2006 I posted on The Longest Starbucks Order (it is still a good traffic-source from Google searches). Today I want to talk about my shortest Starbucks order: no lid, please.

I have realized over time that barista handling of the lids always leads to one of those “I wonder how often they wash their hands” moments.

This train of thought began one day in my local Peet’s. They don’t put the lids on your coffee for you. They have a stack of lids next to the milk, sugar and stirrers. Why do they do that, I wondered. After all, Starbucks goes the extra mile and puts the lid on for me. And then as I reached over to put the lid on for myself I was conscious that my hand was all over where my mouth was about to be … and that gave me pause for thought. Over at Starbucks, I thought, they put the lid on for me, and it’s the cleanliness of their hands I have to worry about, which is indeed a little more worrying that the cleanliness of my own (call me a snob).

Starbucks stores all seem to be uniformly scrupulous about maintaining cleanliness of the area behind the bar, the milk steamers, the spoons etc. The staff are careful to use tongs and tissue for food items, baked goods, hot breakfast snacks, to ensure they are not touching the food. However, when I order my drink, the baristas do not wear gloves and their bare hands are touching the lid, smooshing it down all around, including from where I am about to drink. And, perfectly understandably, for they are human after all, these pleasant, happy, well-trained baristas, touch their own face, sweep back their hair, touch each others’ hands as they pass cups … in short, their hands are short of food-prep hygienic. Movie reference: “Outbreak”… ugghhh!

I don’t want to make Starbucks baristas’ lives harder. I don’t want them to wear gloves. In fact I want to make their lives simpler. Please just stack the lids and let me place my own.

Move over #SoMoLo … it’s time for #SoMoLoClo

After some frustrating searching for SoMoLo, I think the earliest reference I could find is in 2010. Keys-by-Tearn claims to have coined the term in 2009, but I cannot find verification for that online. (A prize will be given for the earliest verifiable mention found in 2010 or earlier and posted to the comments by end of year.)

SoMoLo is a contraction for “Social, Mobile, Local” and was coined and is current because of the confluence of Social Networks, Mobile Devices and Local (or Location based) intelligence driving new forms of consumer behavior. We use Facebook to tell friends what we have bought (and follow their recommendations). We use our smartphones to check for better prices than what we see in the store in front of us, and we check for other local stores that are open and have the item in stock. This term is a catchy one because it captures and points to marketing strategies being adopted in many segments where smartphone users are a desirable demographic. Search for SoMoLo on twitter and see what people are saying.

Before SoMoLo has really caught on outside the cognoscenti, let me elbow it aside and introduce SoMoLoClo – for social, mobile, local, cloud. This is more of a techies term, which I first noticed should be introduced last month, and tweeted about it for the first time last week when David Skok presented a great overview of the current Application Development landscape at a MassTLC event. He brought the use of cloud computing into sharp focus as an innovation driver alongside the SoMoLo facets. SoMoLoClo might not be a nifty marketing strategy that everyone understands, but by adding ready-to-run, on-demand, sophisticated capabilities based in the cloud to SoMoLo architectures, you get a very powerful technical platform. Kinvey, from the Techstars Boston class of 2011, is a great example of how a cloud capability can turn an merely interesting app, into something much more multi-dimensional.

So goodbye SoMoLo, hello SoMoLoClo! And remember, you read about it here first!

The Fog of Entrepreneurship

As I have quoted before, Paul Gompers of HBS succinctly notes that management is the optimization of resources and entrepreneurship is the optimization of opportunity. Optimizing resources is tough enough, and you can generally count your resources. Optimizing opportunity is fraught with uncertainty, starting with characterizing (let alone quantifying) what the opportunity really is. Entrepreneurship, and startup investing, operates in a field of uncertainty, often massive uncertainty.

Many others have written about how to manage that uncertainty, and I can say, with certainty, that even the good articles do not reduce uncertainty. At best they clarify that any decision is better than none, and send you out to test hypotheses, find failure through controlled experimentation and generally do more faster.

I don’t think I am adding deeply to the field of uncertainty studies with this posting, but here are a couple of interesting quotes and my own comments.

I can’t find the source of the quote “confusion is a prelude to clarity” (though you can buy the t-shirt), but it brings to mind the most unlikely seeker of uncertainty, Alfred Sloan. Sloan was the legendary CEO of General Motors and is credited with being one of the fathers of modern management. When chairing a board meeting in which an important issue was being discussed, Sloan said “Gentlemen, I take it we are all in complete agree­ment on the decision here . . . Then I propose we postpone further discussion of this matter until our next meeting to give ourselves time to develop disagreement and perhaps gain some understanding of what the decision is all about.” (Note: sources differ on the exact wording.)

Another great quote, which I hesitate to admit I first read in a Tom Clancy book, is “no plan survives contact with the enemy” (Helmuth von Moltke). I prefer the variant “no plan survives contact with the enemy and no battle was won without a plan.”

The conclusions are unsurprising for those in the startup world, but intriguing coming from regimented management practitioners and military minds: embrace and seek uncertainty, expect uncertainty, prepare for uncertainty.

Why Google should buy RIM

Google should buy RIM, makers of Blackberry smart phones, and this is why.

Everyone who uses Blackberry phones loves the physical form factor, especially the keyboard, and this means the phones are great for email. The famous security adds to this, and makes enterprises and even governments happy (or unhappy, if they like eavesdropping). People also love BBM (Blackberry Messaging service).

However, that's it. Everyone hates the Blackberry browser, the other apps, the integration etc. In my view (and not only in my view I think) RIM is on a slow decline, despite their new tablet and touchscreen phones.

Google is looking to extend its platform to everywhere. Put the two together, and you have a great combination.

Google could get the patent portfolio to allow them to use (or better, out-license) that great keyboard, instead of the crappy one on, say, the Motorola Droid slide-outs. Google could even choose to spin off the hardware altogether to a handset manufacturer (HTC?), to reap the benefits of getting Android onto the platform but avoid competing with their channel.

Google could leverage the intense loyalty of BBM across it's entire messaging line, adding to Gmail chat, etc. Google could add the great enterprise security that Blackberry has. The BB phones would probably enhance the relationships Google has with the mobile carriers, although I am not sure how important that really is. Google would be able to put Android on the BB platform which would make current BB phone users very, very happy.

That's it... Any comments?

Update: Check out a TechCrunch post that points in this same direction (or certainly points out BBM is in for a steeper decline), punchline “New BBM feature: f**ked.”

How to score an investment for your startup

There is one timeless question in the world of early stage investing: What does it take to get an investment from a VC firm, or for that matter from a seed or angel investor?

The answer is that you need to score 100 points to get an investor to write a check. The same goes for all kinds of investors: VC's, angels and seed investors – it’s the same 100 point game.

How do you score those 100 points? Well by different kinds of scoring plays… and like a touchdown vs a field goal vs a safety, different plays score different points. (With apologies to my non-US readers for the references to American Football; you should all know that I recently became an American citizen and it is now unconstitutional for me to use cricket metaphors. If I were to risk such a thing we are looking at singles, fours and sixes.)

Usually the plays investors are looking for include a great team, previous successes, excited customers (or prospects), good IP, big market, great product vision, market urgency, etc...

The NFL changes the rules each year, but in the investment game it is worse still. Every investor scores these plays differently and some give you points for things others will not, and each investor scores differently from day to day depending on anything from market conditions, recent portfolio events or what they ate for breakfast. On some days, you get points for the sun shining (good mood), or lose them for the same reason (wish I was at the beach). Perhaps this is the source of the entrepreneurs’ lament: “VCs have deep pockets, but short arms!”

Although you can score 100 points with just one or two things, investors prefer that the points cover multiple facets. Betting everything on the team and the idea means much more scrutiny of both those than if you also had customers, developed product, well known large, growing market, etc.

Point scoring is at best highly variable, and I am sure feels pretty random … those investors sure love to move the goal line. One day an investor will tell you that you need more customers, and when you finally get more customers they tell you the market isn’t big enough. Next day you get lucky and the Wall Street Journal writes about the huge market and the investor wants to dig in to your product source code. Can you ever win those coveted 100 points? And what about the startup with a bad market, no product, no customers and a $9 million investment? How did they score those 100 points? Did they win them at the 15th hole over a wager in a sand trap? Who knows, but they scored 100 points somehow!

The variability in scoring points is what allows you to raise money at all. If all investors were rational and used the same (magical) methodology, only the very few really big deals would get funding at all. Investors would fight tooth and nail to get into those, and nothing else would score point one, or dollar one.

Some observations on why point scoring may be tough… If your start-up requires 15 software engineers, 2 years and $8 million to get to market you will find it harder to score points (although Sigma regularly invests in those kinds of deals). If investors like to invest locally and you are located more than 40 miles away, you will find it harder to score points. If you are in a market with notable failures and no recent successes you will find it harder to score points. If you are making hardware you will find it harder to score points than if you are making software (unless the investor is a hardware nut, in which case, reverse that).

One more thing – you can lose points, too – for example, through incurable inexperience, or perceived arrogance (yes, I know, pretty ironic comment coming from a VC). You should be passionate (+) without being too promotional (-); you should be decisive and show leadership (+) without rejecting all suggestions, coaching and mentoring (-); your projections should show fast growth (+) without showing 80% net margins after 3 years (-).

Smaller investments at the angel and seed stage are similar to VC investments. It’s still 100 points to win, but it is much easier to score those points, because the amount of capital at risk is smaller. For these investors the game is played for a higher risk-reward ratio because they have an even wider portfolio spread (10’s of investments a year, not the 1-2 investments per partner at the multi-million dollar VC level). You could argue that it’s the same scoring rigor, but fewer points needed to win – but point scoring is so random, and 100 is such a nice round number, I prefer to imagine you just score them more easily at the seed stage.

This is not a familiar model to investors (at least not yet – more retweets, please!) … so you can’t ask “how do I score my 100 points round here?” And, as I mentioned, the point scoring one day will change completely the next. So, how do you turn this to your advantage when you are raising money?

Try to identify the universal point scorers in your startup and look for ways to strengthen and leverage them. Take a cold, hard look at the elements of the pitch which don’t resonate, which people seem to ignore during Q&A, and work out if they are helping or hindering. Where are you gaining points, and where are you losing them? Don’t blame the investors for being stupid (though we may be), or capricious (though we are) – such blame becomes bitter one-liners on The Funded. This is the game you have to play, and you need 100 points to win. Don’t blame yourself either – at least not yet – just get back in the game and work at scoring more points.

At best, this provides is a model which describes (but, by definition and unhelpfully, doesn’t predict) investor behavior. In the spirit of “all models are wrong, but some are useful” (George Box) this model doesn’t change the dynamics of raising money,  but perhaps it gives you one more way to score a point or two.

The Pace of Change

Things have happened so fast going from zero to global wired and wireless internet in such a short time, haven’t they? (Netscape IPO, August 1995). The music industry has been experiencing its death throes over the last short while, too, right? (iTunes Store opened April 2003). Smart phones took over the world in no time at all, as well, didn't you notice? (Blackberry released 1999, iPhone January 2007 - that’s four years!)

You get my point. We all think, and in many ways quite justifiably, that all this new tech has taken over our lives in no time at all. However, really it has taken several, or even many, years.

In the venture capital world we observe that things always take both longer and shorter than we expect (or experience in retrospect). It has taken forever to get a self-driving car, and recently we have seen the DARPA Grand Challenge and the Google car, both of which are really only concepts. A few high end cars now “park themselves”, but self-driving hasn’t really happen yet. When it does it will feel like it happened overnight. (And as I type this I hear a commercial for the very affordable Ford Focus which now has this self parking feature… that was fast!)

I have been blogging sporadically about the approach of the $1,000 Genome (bringing the marginal cost of sequencing an entire human genome down to below that price). That phrase itself ($1,000 genome) is a few years old already, and the Human Genome Project itself was first completed about a decade ago. Although we are getting close to large labs bringing the cost down to the magic number, the real revolution will be instruments in your doctor’s office accomplishing this, on-demand. That is not yet on the horizon, and it will take longer than we think based on recent progress, but when it happens it will also feel like it was overnight and will accelerate major changes in healthcare very quickly.

Green technology adoption cycles have the same contradictory feel about them, despite complex concerns about investments from VC firms in the field.

Synthesizing all these examples brings us back to this realization that technology driven shifts really do take longer and shorter than we think. The very fast moving Location Based Services arena (think FourSquare) may not change much for a few years now as the market catches its breath and works out where the impacts are most meaningful. In the end, our experience of feeling this burst on us very quickly will be tempered by the reality that it will have taken a while to settle.

We, as investors, can take comfort from this because the windows of opportunity are longer than we fear. This is tempered by concern about placing bets too early or committing to spending on ramping up sales efforts before the markets are really ready.

2.0 3.0 = 4.0?

No-one was quite sure what Web 2.0 was when the term was first used. Did it refer to the technology behind Google Maps? This revolutionary approach allowed the server to update the browser as you dragged your cursor around the map, without having to press Submit to get a new response. Did Web 2.0 refer to user generated content such as blogs and wikis (and much later, social media like Twitter and Facebook)? No one really knew then, or really knows now. (Even Wikipedia, at the end of November 2010, is not sure about it, saying in its Web 2.0 article “This article needs attention from an expert on the subject.”)

But Web 2.0 was exciting, and indeed the subject of trademark claims. We all knew Web 2.0 was not Web 1.0 (which only existed as a counterpoint to Web 2.0 – no-one used Web 1.0 before Web 2.0 was coined). Web 1.0 was the old web, the static web pages, boring forms with submit buttons – nothing changed unless the whole page changed, and basically you read Web 1.0, and someone else wrote it. Web 2.0 was exciting because it was dynamic, and maybe even you helped write it, even if we didn’t know exactly what it was.

Then someone coined the phrase Web 3.0. This is never really caught on except with uber geeks, and I think it refers to semantic web technologies, where computers can read online data and make sense of it. The whole march of 1.0, 2.0, 3.0 then seemed to peter out.

Until now that is … Apparently the Marketplace Economy blog is called “Economy 4.0”. There is just too much wrong with this to spill ink (or bits) on it. Just don’t let me catch anyone doing anything 5.0.

There are many kinds of database

Bob Metcalfe always used to say there are just two kinds of network: Ethernet and Ethernot. He was commenting that any network not based on Ethernet was going to end up losing to Ethernet in the marketplace. With the demise of AppleTalk (Apple), Token Ring (IBM) and DECnet (Digital), he was more or less proved right.

Bob has an axe to grind, as one of the co-inventors of Ethernet, but that doesn’t make him wrong. This is not Metcalfe’s Law, coined by the same Bob Metcalfe, that the value of a network increases proportionally with the square of the number of participants. Perhaps I can call the Ethernet/Ethernot comment Metcalfe’s Hypothesis (not all his predictions were correct).

Sigma’s investment in Gainspan is a bet that Metcalfe’s Hypothesis will continue to be right, this time with respect to Zigbee and other approaches proposed for sensor networks.

The database world has been dominated by the relational database model for many years, and all the famous commercial databases such as Oracle, Sybase, IBM DB2, MS SQL Server and open source MySQL are relational database management systems (RDBMSs). The relational data model referred to can be thought of as tables of data which are related to each other (like a table of bank accounts is related to a table of banking transactions). These systems are also known as SQL databases because they use Structure Query Language (SQL) for programming, and SQL was created for RDBMSs and is an absolute standard for their use. Separate from the data model and the language to talk to the data, RDBMSs are mostly expected to be able to manage transactions properly (and be ACID compliant). Simply put, this is the capability to ensure that, for example, a money transfer is properly recorded in both the sending and receiving accounts, and making it impossible to record only one side of the transaction without the other.

Now there are a new gang of databases in town, and they have gathered themselves together under the “NoSQL” banner. These are clustered around BigTable and Hadoop technologies made famous most notably because of their Google-related provenance.

Many (most? all?) NoSQL databases do not have transactional or ACID capabilities, and don’t seem to need it, at least for now, because the use cases that prompted their development really are that different. NoSQL databases are not gaining popularity because they are better at the same things as an RDBMS. This is not about more or faster money transfers. This is about new problems which don’t need transactional integrity and do need to analyze data sets bigger than an RDBMS can economically manage (or manage at all). Sigma’s investments with Michael Stonebreaker (see earlier post) are, in many ways, bets on the future of multiple kinds of databases flourishing.

So I am tempted to postulate Dale’s Hypothesis, somewhat in opposition to the idea of Metcalfe’s Hypothesis, that there can be many kinds of database, and you don’t need SQL to have a sequel.