Jevon’s Paradox

I’ve been finding it necessary to quote Jevon’s paradox several times lately and realized that I have NOT referenced it here.  Quite simply, understanding Jevon’s paradox is essential to understanding cloud.

The concept of the paradox is that when we make something more efficient (for example gas in cars), the demand for that resource goes up (we move further into the exurbs because driving is cheaper).  Notably, as Moore’s law drives computer efficiency up, we are using more and more computers.  Specifically, I have more computers in my house every year even though the efficiency of just one smart phone far (far) exceeds power of my son’s Sinclair 1000.

In cloud computing, Jevon’s paradox points us to the expectation that the rush of applications and activity in the cloud will continue to accelerate.  Since I expect competition and Moore’s law to drive increasing gains in cloud efficiency (and therefore customer advantageous price signals) the market will happily convert these utilization improvements into more and more interesting capabilities.

The cloud expansion means that we can sustain more providers entering the market.  In fact, Jevon would tell us that more providers will likely INCREASE demand for cloud as competition and capacity put downward pressure on prices.  [Q: where will they make up the margin?   A: Adjacent Services]

The loser in cloud’s exploration of Jevon’s paradox are non-cloud deployments (Dell strategists are you listening?).  These systems suffer because their ability to improve their efficiency is limited.

As I look down the road on cloud, I can see many opportunities for current applications to take advantage of cheaper cloud resources to provide even more value.  For example, adding map-reduce analytics to scan a customer’s data can provide tremendous insights.  Today, it’s a luxury like flying on the Concorde.  Tomorrow, it will be part like hopping the Nerd Bird from San Jose to Austin – just a normal part of our daily lives.


Note: A shout out to Dave McCrory who introduced me to Jevon’s Paradox.

Cloud Culture Clash Creates Opportunities

In my opinion, one of the biggest challenges facing companies like Dell, my employer, is how to help package and deliver this thing called cloud into the market.  I recently had the opportunity to watch and listen to customers try to digest the concept of PaaS.

While not surprising, the technology professionals in the room split into across four major cultural camps: enterprise vs. start-up and dev vs. ops.  Because I have a passing infatuation with pastel cloud shaped quadrant graphs, I was able to analyze the camps for some interesting insights.

The camps are:

  1. Imperialists:  These enterprise type developers are responsible for adapting their existing business to meet the market.  They prefer process oriented tools like Microsoft .Net and Java that have proven scale and supportability.
  2. MacGyvers: These startup type developers are under the gun to create marketable solutions before their cash runs out.  They prefer tools that adapt quick, minimize development time and community extensions.
  3. Crown Jewels: These enterprise type IT workers have to keep the email and critical systems humming.  When they screw up everyone notices.  They prefer systems where they can maintain control, visibility, or (better) both.
  4. Legos: These start-up type operations jugglers are required to be nimble and responsive with shoestring budgets.   They prefer systems that they can change and adapt quickly.  They welcome automation as long as they can maintain control, visibility, or (better) both.

This graph is deceiving because it underplays the psychological break caused by willingness to take risks.  This break creates a cloud culture chasm. 

On one side, the reliable Imperialists want will mount a Royal Navy flotilla to protect the Crown Jewels in a massive show of strength.  They are concerned about the security and reliability of cloud technologies.

On the other side, the MacGyvers are working against a ticking time bomb to build a stealth helicopter from Legos they recovered from Happy Meals™.  They are concerned about getting out of their current jam to compile another day.

Normally Imperialists simply ignore the MacGyvers or run down the slow ones like yesterday’s flotsam.  The cloud is changing that dynamic because it’s proving to be a dramatic force multiplier in several ways:

  1. Lower cost of entry – the latest cloud options (e.g. GAE) do not charge anything unless you generate traffic.  The only barrier to entry is an idea and time.
  2. Rapid scale – companies can fund growth incrementally based on success while also being able to grow dramatically with minimal advanced planning.
  3. Faster pace of innovation – new platforms, architectures and community development has accelerated development.  Shared infrastructure means less work on back office and more time on revenue focused innovation.
  4. Easier access to customers – social media and piggy backing on huge SaaS companies like Facebook, Google or SalesForce bring customers to new companies’ front doors.  This means less work on marketing and sales and more time on revenue focused innovation.

The bottom line is that the cloud is allowing the MacGyvers to be faster, stronger, and more innovative than ever before.  And we can expect them to be spending even less time polishing the brass in the back office because current SaaS companies are working hard to help make them faster and more innovative.

For example, Facebook is highly incented for 3rd party applications to be innovative and popular not only because they get a part of the take, but because it increases the market strength of their own SaaS application.

So the opportunity for Imperialists is to find a way for employee and empower the MacGyvers.  This is not just a matter of buying a box of Legos: the strategy requires tolerating enabling embracing a culture of revenue focused innovation that eliminates process drag.  My vision does not suggest a full replacement because the Imperialists are process specialists.  The goal is to incubate and encapsulate cloud technologies and cultures.

So our challenge is more than picking up cloud technologies, it’s understanding the cloud communities and cultures that we are enabling.

Cloud Gravity & Shards

This post is the final post laying out a rethinking of how we view user and buyer motivations for public and private clouds.

In part 1, I laid out the “magic cube” that showed a more discrete technological breakdown of cloud deployments (see that for the MSH, MDH, MDO, UDO key).  In part 2, I piled higher and deeper business vectors onto the cube showing that the cost value of the vertices was not linear.  The costs were so unequal that they pulled our nice isometric cube into a cone.

The Cloud Gravity Well

To help make sense of cloud gravity, I’m adding a qualitative measure of friction.

Friction represents the cloud consumer’s willingness to adopt the requirements of our cloud vertices.  I commonly hear people say they are not willing to put sensitive data “in the cloud” or they are worried about a “lack of security.”  These practical concerns create significant friction against cloud adoption; meanwhile, being able to just “throw up” servers (yuck!) and avoiding IT restrictions make it easy (low friction) to use clouds.

Historically, it was easy to plot friction vs. cost.  There was a nice linear trend where providers simply lowered cost to overcome friction.  This has been fueling the current cloud boom.

The magic cube analysis shows another dynamic emerging because of competing drivers from management and isolation.  The dramatic saving from outsource management are inhibited by the high friction for giving up data protection, isolation, control, and performance minimums.  I believe that my figure, while pretty, dramatically understates the friction gap between dedicated and shared hosting.  This tension creates a non-linear trend in which substantial customer traction will follow the more expensive offerings.  In fact, it may be impossible to overcome this friction with pricing pressure.

I believe this analysis shows that there’s a significant market opportunity for clouds that have dedicated resources yet are still managed and hosted by a trusted 3rd party.  On the other hand, this gravity well could turn out to be a black hole money pit.  Like all cloud revolutions, the timid need not apply.

Post Script: Like any marketing trend, there must be a name.  These clouds are not “private” in the conventional sense and I cringe at using “hybrid” for anything anymore.  If current public clouds are like hotels (or hostels) then these clouds are more like condos or managed community McMansions.  I think calling them “cloud shards” is very crisp, but my marketing crystal ball says “try again.”  Suggestions?

Cloud Business Vectors

In part 1 of this series, I laid out the “magic cube” that describes 8 combinations for cloud deployment.  The cube provides a finer grain understanding than “public” vs. “private” clouds because we can now clearly see that there are multiple technology axis that create “private IT” that can be differentiated. 

 The axis are: (detailed explanation)

  • X. Location: Hosted vs. On-site
  • Y. Isolation: Shared vs. Dedicated
  • Z. Management: Managed vs. Unmanaged

Cloud Cost Model

In this section, we take off our technologist pocket protectors and pick up our finance abacus.  The next level of understanding for the magic cube is to translate the technology axis into business vectors.  The business vectors are:

X. Capitalization:  OpEx vs. CapEx.  On the surface, this determines who has ownership of resource, but the deeper issue is if the resource is an investment (capital) or consumable (operations).   Unless you’re talking about a co-lo cage, hosting models will be consumable because the host is leveraging (in the financial sense) their capital into operating revenue.

Y. Commitment: PayGo vs. Fixed.  Like a cell phone plan, you can pay for what you use (Pay-as-you-go) or lock-in to a fixed contract.  Fixed is generally pays a premium based on volume even though the per unit cost may be lower.  In my thinking, the fixed contract may include dedicated resource guarantees and additional privacy.

Z. Management: Insource vs. Outsource.  Don’t over think this vector, but remember I not talking about off shoring!  If you are directly paying people to manage your cloud then you’ve insourced management.  If the host provides services, process or automation that reduces hiring requirements then you’re outsourcing it IT.  It’s critical to realize that you can’t employee fractional people.  There are fundamental cloud skillsets and tools that must be provided to operate a cloud (including, not limited to DevOps).


If you were willing to do some cerebral calisthenics about these vectors then you realized that they are not equal cost weights.  Let’s look at them from least to most.

  1. The commitment vector is very easy to traverse this vector in either direction.  It’s well established human behavior that we’ll pay more for to be more predictable, especially if that means we get more control or privacy.  If I had had a dollar for everyone who swoons over cloud bursting I’d go buy that personal jet pack.
  2. The capitalization vector has is part of the driver to cloud as companies (and individuals) seek to avoid buying servers up front.  It also helps that clouds let you buy factional servers and “throw away” servers that you don’t need.  While these OpEx aspects of cloud are nice, servers are really not that expensive to lease or idle.  Frankly, it’s the deployment and management of those assets that drives the TCO way up for CapEx clouds, but that’s not this vector so move along.
  3. The management vector is the silverback gorilla standing in the corner of our magic cube.  Acquiring and maintaining the operations expertise is a significant ongoing expense.  In many cases, companies simply cannot afford to adequately cover the needed skills and this severely limits their ability to use technology competitively.  Hosts are much better positioned to manage cloud infrastructure because they enjoy economies of scale distributed between multiple customers.  This vector is heavily one directional – once you fly without that critical Ops employee in favor of a host doing the work, it is unlikely you’ll hire that role.

The unequal cost weights pull our cube out of shape.  They create a strong customer pull away from the self-managed & CapEx vertices and towards outsourced & OpEx.  I think of this distortion as a cloud gravity well that pulls customers down from private into public clouds. 

That’s enough for today.  You’ll have to wait for the gravity well analysis in part 3.

Rethinking the “private cloud” as revealed by the Magic 8 Cube

The Magic 8 Cube

This is the first part of 3 posts that look into the real future for “private clouds.”

This concept is something that was initially developed with Greg Althaus, my colleague at Dell and then further refined in discussions with by our broader team.  It grew from my frustration with the widely referenced predictions by the Gartner Group of a private cloud explosion.  Their prognostication did not ring true to me because the economics of “public cloud” are so compelling that going private seems to be like fighting your way out of a black hole.

We’ll get to the gravity well (post 3 of 3) in due time.  For now, we need to look into the all knowing magic 8 cube.

Our breakthrough was seeing cloud hosting as a 3 dimensional problem.  We realized that we could cover all the practical cloud scenarios with these 8 cases.  Showing in the picture (right).

Here are the axis:

  1. X: Hosted vs. On-site – where are the servers running?  On-site means that they are running at your facility or in a co-lo cage that is basically an extended extraterritorial boundary of your company.
  2. Y: Shared vs. Dedicated – are other people mixing with your solution?  Shared means that your bytes are secretly nuzzling up to someone else’s bytes because you’re using a multi-tenant infrastructure.
  3. Z: Managed vs. Unmanaged – do you’re Ops people (if you have any) able to access the infrastructure that runs your applications?  Unmanaged means that you’re responsible for keeping the system operating.

With 3 axis, we have a 8 point cube.

  1. MSH – a PaaS offering in which every aspect of your application is managed and controlled.  GAE or Heroku.
  2. MSO – remember when people used to buy a mainframe and them lease off-hours extra cycles back to kids like Bill Gates?  That’s pretty much what this model means.
  3. MDH – a “mini-cloud” run by a cloud provider by dedicated to just one customer.  Dr. Evil thinks this costs one milllllllllion dollars.
  4. MDO – a cloud appliance.  You install the hardware but someone else does all the management for you.
  5. USH – IaaS.  I think that Amazon EC2 is providing USH.  It may be a service, but you’ve got to do a lot of Ops work to make your application successful.
  6. USO – OpenStack or other open source cloud DYI frameworks let a hosting provider create a shared, hosted model if they have the Ops chops to run it.
  7. UDH – Co Lo.
  8. UDO – The mythical “private cloud.”  Mine, mine, all mine.

In thinking this over, we realized that cloud customers were not likely to jump randomly around this cube.  If they were using MSH then they may want to consider MDH or MSO.  It seemed unlikely that they would go directly from MSH to UDO as Mr. Bittman suggests; however, the market is clearly willing to move directly from UDO to MSH.

We had a good old-fashioned mystery on our hands… the answer will have to wait until my next post.

Buy virtual goods at Seven-11! Zyanga offers MafiaWars burrito.

Even in the cloud provider business, we sometimes scratch our heads about how much people are willing to pay for virtual products.  A colleague was ranting enviously about a $20 virtual horse offered in World of Warcraft that sold thousands of units in the day hour it was offered.  That’s over two million dollars of revenue for a vanity accessory made of brightly colored pixels! 

In some ways, this is a generational challenge because I want to see real commodities in return for my cash.  Last week, my elementary age daughter did a grueling hour of yard work so that she could purchase some brightly colored phoenix shaped pixels Webkinz.  Normally, she’d have to buy a stuffed animal to get the unlock code but now she can bypass the plush closet dweller.  When I asked if she wanted the toy that normally accompanies the virtual goods she looked at me with the “Daddy, you are stupid but I love you anyway” look.  To her, the virtual item WAS the commodity and the toy was disposable packaging.  Upon reflection, I realized that this is a much better economic model than requiring her to purchase landfill fodder transported from sweatshops on the other side of the planet.

But I digress….

I was pumping gas today and noticed that Seven-11 is pimping concessions that are co-marketed with Zyanga.  This is not just a Zyanga advertising campaign – it is a fully integrated physical-for-virtual-goods marketing genius.  Here’s the deal: if you buy physical food from Seven-11 then I suspect that you get codes to things like unlock virtual food in FarmVille, yoyos in YoVille, and Seven-11’s to rob in MafiaWars.  They even appear to target specific foods to individual games – the MafiaWars burrito was simultaneously spooky and inspiring.

I suspect that ultimately these items will only by available by purchasing goods at Seven-11.  We’re already seeing applications like Gowalla that hope to bundle physical experiences (visiting specific stores) with coupons (free Starbucks).  It’s a logic step to assume that we’ll soon be directed to physical activities (buying a slurpee) to shape virtual experiences (bumping off a crime boss).   Since it seems like a marketer dream come true, I’m absolutely certain that you’ll see it coming to a social network near you.

So now I’m watching for the day when having physical lunch with my virtual Facebook friends may earn us some useful currency.  I wonder what that currency will be.