Peer Production

The Atomizing Hand The strategy and economics of peer production Umair Haque http://www.bubblegeneration.com Spring 2005

What is Peer Production?
Communities of prosumers or amateurs who collaborate to make things
Wikipedia
Metafilter
Flickr
OhMyNews
By…
Sharing information about inputs and outputs…
… which creates pooled knowledge
...which increases the efficiency of future production
And having open access to the means of production

Why Share?
Altruism
Because we care
Reputation
Because there are spillover signalling effects
Reciprocity
Because of implicit or explicit social control
Money
Because there are explicit incentives
Fun
Because we derive social utility from doing so
Etc…
… .No definitive answer (yet).
Empirical effects are unambiguous
File-sharing, Wikipedia, threadless, etc demonstrate that peers do share

Why Join a PP Community?
Simple answer:
Because you can do stuff more efficiently than by yourself
By taking advantage of others’ sharing?
No!
PP is not free riding – in fact, the opposite happens: increasing returns
When you do & make stuff, new knowledge is a side-effect
Knowledge in a peer production community is a public good
New users are attracted in proportion to the size of the knowledge pool
Because it’s the strongest signal of potential marginal productivity gains from joining that community
And new users increase everyone else’s productivity, growing the knowledge pool

Why is Peer Production Important?
Peer production enjoys very special economics
A new kind of scale economy which enables massively distributed and ultraspecialized microproduction…
Distributed economies of scale
Which lets knowledge about production pool within the community…
Which creates sustainable supply-side increasing returns
Under certain conditions, peer production communities will be more efficient than firms or markets
To understand why, I’ll try and explain why peer production is really about cheap coordination atomizing production…
… which makes it a fundamentally new mode of production
Or at least one analogous to modes of production that disappeared a very long time ago, like the putting-out system
… which makes it a great opportunity (or a great threat)

Network Economics 1.0 and 2.0 Primer

Network Economics 1.0
Demand-side viral effects
Massively decreases user acquisition cost
Low-cost imitation barrier to protect early-mover advantage
Demand-side network effects
One key resource: consumption network
“ Metcalfe’s law” – marginal utility increases in network size
No upper bound factored in – misreading of econ lit.
Switching costs rise nonlinearly with network size
Increasing returns to adoption
Strategic intent: scale – grow adoption
Rapid growth of network size
“ Demand-side economies of scale”
Search economies dominate strategy
How costly is it for you to find stuff on the network?
Cheapest solution wins: utility of network bounded by search mechanism

Network Economics 2.0
Supply-side viral effects
Massively reduces prosumer acquisition costs
Low cost imitation barrier to protect early-mover advantage
Supply-side network effects
Two resources: producer network and knowledge pool
“ Haque’s Law” – marginal productivity increases in network size
Upper bound: diseconomies of scale – large user network size creates knowledge network coordination costs
Switching costs rise nonlinearly with both
Increasing returns to knowledge
Strategic intent: speed – accumulate knowledge
Rapid growth of knowledge pool
Doing & making things faster than competitors
Coordination economies dominate strategy
How costly is it for you to make & do stuff on the network?
Cheapest solution wins: network utility bounded by coordination

Markets and Firms: Production 1.0

Apologies
Five somewhat painful slides to follow
Bear with me, because they’ll help us explain why and when firms are less efficient than peer communities
This is the most complicated part of the presentation
OK, I’m lying… 
… skip to the Summary slide if (when) you can’t take it anymore

Property Rights Organize Production
We will call 1 and 2 rights of coordination because they organize production
Liquid markets for 3 and 4 are prevalent
Equities, fixed income, options, futures
Markets to assign coordination rights often fail because of relatively high transaction costs
Copyright is the canonical example
Firms coalesce to economize on transaction costs of coordination rights assignment when markets fail
Right to use economic resources
Right to modify form and substance of resources
Right to benefit from use of resources
Right to transfer resources

Understanding Firms
What do firms do?
Coordinate:
The most efficient way to turn inputs into outputs…
… By internalizing the uncertainty inherent in risky transactions...
But economizing on transactions isn’t costless…
Firms replace transaction costs with coordination costs
How are coordination rights distributed within the firm?
Within the firm, who can access the means of production and key inputs?
Costs of administrative overhead
Internal transaction costs: negotiation, bargaining, and enforcement of coordination rights
These are essentially costs of information sharing and processing – firms internalize information costs, where they can be ‘managed’
As long as coordination costs stay less costly than transaction costs of inputs, firm is an efficient way to produce
But they don’t, because….

Coordination & Hierarchy
Negotiating for coordination rights becomes combinatorially costly
I want a top engineer on my team
I negotiate with 4 VPs
Each VP negotiates with each other
Coordination cost explosion in firm size – negotiation doesn’t scale
How do we deal with this? Hierarchy – centralized decision-making
Hierarchy is designed to minimize coordination costs
In firms, coordination rights are governed by authority embedded in hierarchical implicit or explicit contracts
You’re my boss, you choose the ‘best’ products and features
I’m the product manager, so I get the top engineers
Hierarchy minimizes coordination costs by economizing on information
Managers and administrators collect and process information from subordinates

Coordination Diseconomies
Minimizing coordination costs by economizing on information creates a big problem…
Private info is never made completely public
Bosses, middle managers, bureaucracy, politics, bullsh*t, inertia all make revealing private info costly
Memos, reports, and meetings lose tacit info
Disutility: authority sucks
In firms, we can’t know if efficient solutions to assigning coordination rights are reached
Because information, expectations, and preferences about inputs and outputs are never fully revealed
Coordination diseconomies (1):
The efficiency loss of hierarchy in assigning the best coordination rights, due to information loss
This is an opportunity cost of hierarchy – we may forego a better coordination rights assignment

Coordination & Specialization
And…hierarchy does not eliminate coordination costs
It minimizes them
Coordination costs still exist
Direct costs
Admininstration, middle managers, bureaucracy
Indirect costs
Agency and influence costs – politics! Incentives dulled
Coordination bounds specialization
It’s economical to coordinate activities until marginal cost of coordination exceeds marginal gain from specialization
Intuition: even in firms, coordinating 10,000 microactivities isn’t economical
Or: 10 managers can coordinate 1000 activities, 100 managers can’t coordinate 10,000 activities
Marginal cost of coordination increases exponentially in firm size
Coordination diseconomies (2):
Specialization gains hits a coordination cost wall
Implication: eliminating coordination costs can realize specialization gains

Summary: Modes of Production
Markets fail
Because of high transaction costs
Firms coalesce but value creation is bounded by
High coordination costs, which limit any specialization gains
Hierarchies coalesce but value creation is bounded by
Coordination diseconomies
Total cost of hierarchy is high
Coordination costs bound specialization gains…
… and opportunity cost is optimal coordination righst assignment
Or: a trade-off between specialization gains and information loss
The more you minimize coordination costs, the more information you lose…
… but the more you minimize coordination costs, the greater specialization gains you realize
A more efficient form of organization…
… escapes the information loss vs specialization gains tradeoff, and realizes advantages in both
Zero coordination costs wenable huge specialization gains
Not having to economize on information means optimal assignment of coordination rights

Coordination & Specialization Coordination costs Specialization gains Coordination costs bound specialization gains Size Value Coordination costs exceed specialization gains

Coordination Diseconomies Hierarchy costs Specialization gains Coordination diseconomy : total costs of hierarchy are coordination costs and opportunity cost: not choosing the best coordination rights assignment. Specialization is effectively bounded at a small maximum efficient scale. Can trade off by either coordinating more, and losing less information…or coordinating less, and realizing greater specialization gains. Size Value Opportunity cost – information loss – increases costs of hierarchy Total costs exceed specialization gains

Peer Communities: Production 2.0

Peer Production
PP vaporizes the real-world costs of assigning coordination rights
Information sharing mechanisms aggregate and reveal private information and preferences frictionlessly
About inputs
What are the most efficient ways to produce our good?
About outputs
What are our most successful goods likely to be?
Using explicit mechanisms
Voting, ranking, pricing
Or Implicit mechanisms
Tags, playlists, reputation
Without coordination costs…
… so there’s no efficiency loss of centralized decision-making like in firms
How…?

Coordination Economies
Because information and preferences are public, most efficient coordination rights assignment is transparent
Public information regulates which inputs…
code, people, designs
… are granted access to means of production…
platform, community, architecture
… to create the outputs predicted to be most successful.
T-shirts, games, OS kernels, music
Frictionless, hyperefficient assignment of coordination rights: coordination economies
PP can assign more efficient coordination rights more cheaply than firms or markets
And so can realize gains from ultraspecialized production
Coordination economies are a significant source of strategic cost advantage

Coordination Economies
How does PP achieve hyperefficient assignment of coordination rights?
PP model is an implicit or explicit auction for access to means of production
Implicit or explicit price mechanisms combined with price or quantity auctions
Generally:
Peers self-select into activities – ex-post coordination
Distributed local information is aggregated
Implicit price of access to means of production is established
Peers are granted access to means of production (or not)
If peer activity value as measured by aggregate utility is greater than implicit price as measured by aggregate bid
Production without coordination costs
No need to economize on information – massively distributed info processing, just like in real-world markets
Costs incurred are market costs

Summary: Firms, Markets, and Communities
PP Models combine the microeconomic DNA of markets and firms:
Places where people can exchange decentralized information about preferences and utility (markets)
In order to coordinate centralized actions of consumption and production (firms)
Without the coordination costs of real-world firms
… or transaction costs of real-world markets, which create firms
Which scale combinatorially with firm size – cost explosions
Which makes complete information revelation uneconomical in firms
Which makes it impossible for firms to assign the most efficient coordination rights
Peer production is theoretically hyperefficient
It can assign the most efficient coordination rights more cheaply than real-world firms or markets
Or: PP lets the most talented people make the coolest things

Costs Shape Modes of Production Markets Transaction costs Firms Peers Coordination costs Information loss Hierarchies Market failure Sharing costs Corpocracy Growth failure Atomization Failure point Organization Type of failure

Coordination Arbitrage
What’s the implication of coordination economies?
Coordination arbitrage
Entrepreneurs will begin to use coordination economies – PP’s natural cost advantage – to atomize value chains
They will target industries with high coordination costs (and large efficiency losses due to information economization)
The coordination economy-diseconomy differential is the largest here: coordination arbitrage
Rents will be redistributed to peers as peer demand intensifies and outstrips supply
Prizes on Yahoo Labs’ prediction market
Firms will not disintegrate, they will move up and down the value chain
Peer management
Platform supply
Goods for which means of production/inputs access is limited or protected

Peer Production Economics

…So What?!
Where things get really interesting
After all, firms can (to an extent) realize coordination economies by using sharing/internal market mechanisms
PP redefines two economic orthodoxies
Diminishing marginal productivity
Resources become less efficient at the margin
Marginal productivity of variable inputs declines as quantity increases
Increasing returns
Positive demand-side network externalities: Your joining the network increases it’s value to me
Demand-side lock-in: My high up-front learning costs increase my switching costs
… So what makes peer-production special?

PP Economics are Revolutionary
PP models create increasing returns 2.0:
Sustainable supply-side increasing returns
How?
2 key mechanisms
Distributed economies of scale create increasing marginal productivity
Cars, computers, electronics, books, songs….
Many hands make light work at the margin
Knowledge externalities create increasing returns to adoption
My productivity increases in network size
Your joining the network increases my value to it
… because our knowledge in collaboration increases marginal productivity for lumpy goods
Increasing marginal productivity of labor

Peer Production Economics Distributed Economies of Scale and the Atomization of Production

Ultraspecialization and Microproduction
Massively distributed ultraspecialization
Doesn’t work in the real world…
Tiny chunks of ultraspecialized activities are valueless in isolation
Lumpy goods take time and collaboration to make
Who will pay for 1/1000 th of one of the ten car production activities?
Even less economical to assign coordination rights for ultraspecialization
Hierarchy or markets can’t handle it
How do you coordinate 10,000 tiny chunks of ultraspecialized activities in the RW? How do you contract/pay for 10,000 tiny chunks of ultraspecialization in the RW? Combinatorial cost explosions…
Combining microchunks requires costly coordination, integration, contracting, payment relative to every other microchunk
If 10,000 microchunks, 10,000 x 9999 coordination+transaction costs necessary
Massive coordination diseconomies for ultraspecialized collaboration
Result: market and firm failure for ultraspecialization in the real world

Distributed Economies of Scale
But…
PP enables cheap, optimal assignment of coordination rights at any level of divisibility
Overcomes coordination diseconomies
By leveraging cheap information sharing mechanisms to costlessly regulate access to inputs and means of production
Coordination economies make organizing microproducers for ultraspecialized production viable
Distributed economies of scale…
… Yield specialization gains
Finer and finer input divisibility lets us each specialize in our comparative advantage
Not simply ‘many hands make light work’ – many specialized hands make production more efficient
PP community can be a more efficient producer than firm at large scale
If enough microproducers contribute enough microchunks

Coordination & Specialization Firm coordination costs Specialization gains Size Value PP coordination Costs PP coordination costs exceed specialization gains Firm coordination costs exceed specialization gains Coordination costs bound specialization gains. Since peer community coordination costs scale linearly, peer communities realize more gains

Supply-Side Externalities
What can an ultraspecialized network of microproducers do?
Peers contribute ultraspecialized microchunks of value activities
I can produce 1/100 th of a DAC and 1/50 th of a spreadsheet application
These microchunks are combinatorial, not additive
So…
Network effect: positive supply-side externality
My marginal social productivity > my marginal private productivity
I can’t make lumpy goods efficiently by myself…
… Your joining the network increases my value to it in 2 ways
Microchunk modularity explodes production set
Combinatorial explosion in feasible activities
n^n-1 possibilities: 4 activities produce 64 possible combinations
Microchunk reusability yields increasing marginal productivity
I can reuse microchunks you’ve contributed in the past
In econ-speak, microchunks are non-rival and non-excludable in production

Distributed Economies of Scale
In general:
Your activity set means my marginal productivity is enhanced
Productivity increases in number of ultraspecialized microproducers
10 specialized car activities become 1000 ultraspecialized car activities
…… creating more ways to recombine activities to improve efficiency …allowing greater reusability of activities to improve efficiency
Recombining and reusing microchunks incurs massive coordination costs in the real world
Not all activity combinations in exploded production set are valuable…
… and dividing activities doesn’t always yield marginal productivity gains
Finding beneficial combinations – assigning coordination rights efficiently – is costly
But cheap information sharing makes searching for best coordination rights assignment frictionless

PP and Firm Production Functions Firm coordination costs Firm production function Labor/Network Size Output PP production function Firm is more efficient producer PP community is more efficient producer PP marginal productivity exceeds firm marginal productivity Distributed economies of scale mean that at large scale, peer communities enjoy a significant cost advantage over firms

Microproducers & Ultraspecialization
Ultraspecialization examples
Jane knows everything about ab exercises (consumption externality)
Dave’s built replicas of every shoe since 1500 (production externality)
Al knows everything about 80s Italo Disco (hobby)
Trekkies, game mods, blogging,
Why do microproducers ultraspecialize?
Production or consumption externalities
Hobbies
Local effects: family, friends
But mostly because they can :
the Net’s slashed search costs – specialization is less costly than it used to be
How did ultraspecialization evolve?
…

Traditional Value Creation Publishing: finance, marketing, procurement Management mediates transactions between primary value activities Management coordinates and exploits complementaries between supporting value activities Traditionally, value activities were integrated because market transaction costs were high Production : creation, editing, finishing

Disintermediation: Integration to Disintegration Publishing : finance, marketing, procurement Management coordinates and exploits complementaries between supporting value activities Disintermediation: Markets mediate transactions between primary value activities Cheap information disintegrates traditional value chains: value activities rearrange in horizontal layers, yielding efficiency gains Production: creation, editing, finishing

Microproduction: Disintegration to Atomization Cheap coordination atomizes disintegrated value chains: value activities rearrange in microchunks, yielding efficiency gains Publishing : finance, marketing, procurement Community mediates transactions between primary value activities Community coordinates and exploits complementaries between supporting value activities Production : creation, editing, finishing

Microproduction: Distributed Economies of Scale Microchunks have a positive supply-side network externality: a peer’s private productivity is less than his social productivity Why? User N contributes green microchunk G . This microchunk is reusable . Microchunk reuse increases marginal productivity: G’s complementarity with other microchunks reduces the marginal cost of future productivity. This microchunk is modular . Microchunk modularity explodes production set. G’s complementarity with other microchunks creates explosion in product set possibilities.

Distributed Economies of Scale - Summary
Coordination economies enable ultraspecialized production
Ultraspecialized production realizes network FX from reusing and recombining activity microchunks
Tiny bits of ultraspecialized knowledge can, aggregated across enough peers , make peer production economically advantageous, because of supply-side network effects Marginal productivity increases in network size 2 Mechanisms 1 Effect

Condition: Lumpy Goods
Distributed economies of scale obtain under 2 conditions
Lumpy goods and divisible inputs
Lumpy goods supply functionality in discrete bundles
Computers, cars, runways, sunglasses
They require specialized knowledge in multiple activities
Coordination, learning, and switching costs of production are high
Because opportunity cost of specialization is not knowing other activities
10 activities required to make a car:
10 workers/car - 1 activity each
Each worker is specialized – gains to specialization
2 workers/car - 5 activities each
Only 2 activities/worker are specialized, workers must still perform remaining 8 – relative productivity loss
Marginal productivity increases in workers
More activities/worker lower productivity

Condition: Divisible Inputs
Divisible inputs
Inputs must be able to be unbundled in arbitrarily fine increments by microproducers
You can contribute a sentence, a paragraph, or an essay
… a scene, a script, or a review
… a playlist, a vocal track, or lyrics
For some goods, this is not possible (yet)
Inputs are indivisible – can’t be unbundled
Because of cost, technology, regulation, or specialization
Examples: cars, runways, oil rigs, MRI scanners
Which goods have divisible inputs?
Digital media: music, films, books
Designs for low-complexity physical goods: T-shirts
Knowledge resources: Wikipedia, journals, blogs, genes
Without input divisibility, microproduction isn’t possible

Peer Production Economics Knowledge Externalities and Increasing Returns

Recap
PP models create increasing returns 2.0:
Sustainable supply-side increasing returns
How?
2 key mechanisms
Lumpy goods and distributed economies of scale
Cars, computers, electronics, books, songs….
Many hands make light work at the margin
Supply-side knowledge externalities
My productivity increases in network size
Your joining the network increases my value to it
… because our knowledge in collaboration increases marginal productivity for lumpy goods
Increasing marginal productivity of labor

Knowledge Pools
Knowledge pools are repositories
… for information sharing mechanisms about inputs and/or outputs
They store the community’s aggregated preferences and expectations…
To act as a collective memory for the PP community
Examples:
Product/feature reviews (Yahoo! Finance msg boards)
Tutorials, guides, and walkthroughs (GameSpy walkthrus)
User reputation systems (eBay seller feedback)
Stored product rankings (Amazon product rankings)
Archived playlists, tags, links (Blogdex archives)
Metainfo about community production (Metatalk.metafilter)
… Other metainfo

Knowledge Resources
Why is knowledge important?
Knowledge enhances productivity by more efficient use of inputs
Intuition: algebra vs arithmetic
Knowledge is an experience effect: a result of learning-by-doing
Knowledge pool is the key resource for PP communities
Users will select PP communities where they their marginal productivity is maximized
Knowledge pool is strongest signal of potential productivity gains
Signals potential productivity gains of joining community independent of network size
Or: signals current productivity per peer
And since microchunks are non-rival in production
Knowledge resources don’t get exhausted – they grow
Knowledge pool is a resource stock
That accumulates according to flow of knowledge externalities

Knowledge Externalities
Recap: private info and preferences about inputs and outputs is aggregated and made public
This info sharing has a macro supply-side externality:
Storing aggregated info creates a knowledge pool for the community to learn from/access/utilize
Inputs become more efficient
Output quality increases
Knowledge pool is a public good which acts as an input to increase the efficiency of future inputs
Initial knowledge pool is additive …
My productivity increases when you join the network
… Ongoing knowledge pool is cumulative
Every time we collaborate to produce a good, new knowledge is produced

Knowledge Pool Knowledge is an externality of value activities: learning-by-doing Knowledge pools when information and preferences shared during peer production are stored This knowledge enhances future productivity by informing peers about how to most efficiently modify inputs in order to produce the most-desired outputs Value activities (brown) have a knowledge externality, which flows into knowledge pool (silver).

Knowledge & Increasing Returns
Leveraging this externality creates increasing returns
Positive feedback:
Network size growth increases marginal productivity
Increased productivity generates new knowledge faster
… New knowledge attracts more users
Or…
Your adding knowledge to the network increases my value to it
Positive feedback:
Largest public knowledge pool attracts new users
My marginal productivity increases in network size
Public knowledge increases in my marginal productivity
Your marginal productivity increases in public knowledge
You join the network - my marginal productivity increases in network size
Increasing returns – productivity creates new knowledge, which attracts users, which increase productivity, which creates new knowledge
Knowledge within the PP network is a public good produced as an externality of learning by doing
Because innovation is cheaper
Because transaction and integration costs are vaporized
Doing and making cool stuff makes doing and making cooler stuff more efficient

Increasing Returns Overview Productivity Increase New users Which accelerates Information sharing which attracts ultraspecialized in different activities at the margin (distributed economies of scale) about inputs and outputs ultraspecialized in different activities … New users Public knowledge Which grows about the most efficient coordination rights

Knowledge & Community
How is knowledge related to network size?
Knowledge is an experience effect: learning by doing
The more you do, the more you learn
Productivity of users determines of knowledge growth
Since marginal productivity increases in network size…
Knowledge pool should explode in network size
Identifying and managing this relationship is the key strategic challenge in peer production
Because it’s the indicator (and driver) of increasing returns
Speed economies become crucial
Production throughput accelerates knowledge externalities…
… which build critical mass in pool and accelerate network growth: increasing returns

Increasing Returns
Increasing returns means:
PP communities will be winner-take-all markets
The resource to which there are increasing returns is knowledge , not just network size
The biggest network won’t win by default (like dot com 1.0) – the most efficient knowledge generator will.
Knowledge and network size are necessary to create natural monopoly dynamics
Dominant strategies leverage speed
To build larger knowledge pools fast…
Which attract new prosumers by offering discontinuous marginal productivity gains
… And build scale

Increasing Returns – A Short History
Where else do we see supply-side increasing returns?
Accelerating down the learning curve – BCG
Which came from…
Disembodied learning-by-doing knowledge as public good in production functions. Cumulative knowledge investment of all firms exponentially related to capital stock (Arrow)
Capital growth and knowledge externalities: (Romer)
AKA endogenous growth theory
How do these two theories of supply side increasing returns differ from PP models?
EGT assumes constant supply-side returns at the firm level, and increasing returns only at the industry/national level
Increasing returns in the BCG model aren’t sustainable – the learning curve flattens out
Supply side increasing returns in PP models are sustainable as long as knowledge pool grows .

Peer Production Strategy Understanding Value Chain Evolution

Value Chain Evolution Peers Platform Peers Aggregator Inputs Manufacturer Marketer Distributor Retailer Cheap information disintegrates value chains, because segment consolidators realize specialization gains and economies of scope – integrated production becomes costly Cheap coordination atomizes disintegrated value chains and explodes value activities within layers, because microproducers realize distributed scale economies Inputs, Manufacturing, Marketing, Distribution, Retail Costly info and coordination integrates value activities – most economical way to produce Peers

Value Chains & Value Appropriation Infrastructure Content Search ISP Telco Inputs In disintegrated value chains, industry profitability migrates to the center (aka the ‘coordinator’) Manufacturer Marketer Distributor Retailer Creatives Producer Publisher Distributor Retailer 5% 20% 50% 20% 5% Why? Market power in horizontalized landscapes – layer dominance – flows from relative scope (t he center can realize the greatest marketing scope economies of scope via marketing, branding, and advertising), or relative specialization (the center can develop the most economically advantageous core competences) EG: Nike, EA, SeanJohn, Google

Value Chains & Value Appropriation Platform Peers Aggregator In atomized value chains, industry profitability will migrate to the edges 40% 20% 40% Inputs Platform Peers Aggregator Reconstructor 35% 10% 10% 10% 35% Why? Market power in atomized landscapes is a function of relative scale: the edges can realize the greatest relative economies of scale via demand and supply side network FX. The middle of the value chain explodes and can’t realize scale economies. Core competences for disintegrated value chain coordinators become core rigidities – value capture requires competences at both edges of the chain

The Explosion of the Middle Peers Peers Peers Platform Peers Aggregator In atomized value chains, industry profitability will migrate to the edges 40% 20% 40% Why? The center explodes and atomizes – hypercommoditization – and value shifts to adjacent segments , because they can realize scale economies from the exploded center’s output. Examples: Blogger, Bloglines, Flickr

The Commoditization of the Edge In atomized value chains, the same technology that explodes the middle commoditizes the old edges (example: cheap connectivity enables blogging). Industry profitability migrated to new edges. 40% 20% 40% Coordination Production Aggregation Blogger bloggers Bloglines AudBlog podcasters PodWorld Community Owners reviewers Become Connectivity 0-1% BitTorrent ISP

Value Appropriation Examples In atomized value chains, industry profitability will migrate to newer (and newer) edges Platform Peers Publisher Aggregator Reconstructor 35% 10% 5% 10% 35% Coordination Production Publishing Aggregation Filtering Laptop audio Artist Label Club DJ Blogger bloggers hosting search Bloglines MMOG Developer gamers Mods & plugins Community sites Gaming Open Market

PP Dominant Strategy: Vertical Integration
The point:
Peer production communities are vertically integrated atomized value chains…
To capture the most value, integrate towards both edges
… Plus knowledge pools
Knowledge externalities don’t pool without integration
40% 20% 40% Coordination Production Aggregation Platform Peers Aggregator

Peer Production Strategy Competitive Dynamics

Peer Production Model Inputs (Coordination) Means of Production Outputs (Aggregation) Explicitly modifiable by community Sell access to users Competition for access, prizes Wikipedia raw content Open or community regulated access Advertising and sponsorship % Ad revenue Wikipedia CMS Efficient information sharing % Sales revenue % Revenue from outputs Wikipedia entry Knowledge pool grows New aggregated public info Requirements Revenue stream Peer incentive Example Increasing Returns

PP Competitive Dynamics
PP model competitive dynamics
You own a successful PP community facing new competitor entry. What do you do?
Positioning continuum
Quality
Operating model should be partly proprietary.
Tight supplier relationships.
New peer entry by invitation or referral.
Quantity
Operating model should be fully open.
Loose supplier relationships.
New peer entry open to public.
What resources and capabilities drive competitive advantage?

PP Strategy Building Blocks
Key capability:
Market-making
Engineers increasing returns by exploding knowledge pool as user base grows…
… By creating efficient information-sharing mechanisms
Which create coordination economies by vaporizing transaction and coordination costs of production
Results in:
Economies of speed
New users are attracted…
… by accelerating knowledge pool growth
… which increases productivity
Or: the faster your throughput is, the faster knowledge pools…
And reduces unit cost as network grows

How to Make a Market
Markets don’t become automatically efficient
Efficiency emerges from:
Liquidity : assets are theoretically tradable
Low transaction costs : assets are actually tradable
Implications: graininess of information sharing mechanisms is key to minimize information asymmetries between peer producers
Profit maximizing traders
Implications: must create incentives/gains for peer producers
Peer producers must be able to internalize those gains
Only way to avoid prisoner’s dilemma – everyone expects someone else to vote, Bush wins
Goods traded can’t be purely public goods
Implication: access to means of production must be restricted to highest valued peer producers: quasi-public goods
What’s the desired result?
Information about which inputs used by which means of production most efficiently produce the most desired outputs…
… is traded and arbitraged, and the best solutions are revealed

Making Markets: Efficient Information Sharing
In the real world…
How do you build efficient information sharing?
By building incentives to leverage reputation and reciprocity
By minimizing the risk of contribution
By imposing punishment costs
How?!
By using an implicit or explicit currency
Links are the currency for link aggregators
Feedback points are the currency for eBay’s reputation system
Ratings are the currency for Amazon’s book reviews
Which is liquid and tradable
Which creates incentives to profit
To gain more links
To get positive reputation feedback
… and by eliminating transaction costs

A Quick Currency Case Study
What is a currency?
Karma/rating is not an implicit currency
It’s not tradable…
… It has use value but no exchange value
If I give you good karma, what does it cost me?
Nothing – i have little incentive to reveal my true preferences
Conversely, if I have good karma, what does it benefit me?
Generally, I receive more privileges…
But I can’t trade it to get what I really want
So I have little incentive to reveal my true preferences
Your currency has to be more than a ratings system…
… but not so complicated that peers won’t use it
What currencies have use and exchange values?
Links – use value is linking from, exchange value is linking to
Implication:
Ratings and karma fail because exchange is unidirectional
Real currencies succeed because exchange is bidirectional

Making Markets: Sources of Transaction Costs
Asset specificity
Make information sharing objects not specific
Example: tags
Frequency and duration
Make information sharing either frequent and small, or infrequent and large
Example: playlists (infrequent and large) vs tags (frequent and small)
Complexity and uncertainty
Make info sharing mechanisms easy to navigate and predictable in results
Difficulty of measuring performance
Connectedness to other transactions in system
Interdependent transactions can require complex coordination

Key resource:
Peer network
Owning the largest user network realizes increasing returns
… .but only when knowledge pool explodes, attracting even more new users, increasing productivity
Knowledge pool explosion depends critically on market-making capability creating efficient information sharing
Results in…
Economies of scale
Speed and scale are interdependent
If you can build both, you will achieve increasing returns
… efficient information sharing mechanisms drive speed…
..and supply-side viral and network effects turn speed into scale
Unit cost falls as marginal productivity increases in network size
many specialized hands make production more efficient

And economies of scope:
Scope is a secondary economy
Production set explosion means unit costs can fall in network size…
… but only if means of production are flexible
… and inputs are tradable
It’s no good having a community of diamond miners when DeBeers owns all the mines
Drivers: Knowledge network size

Relative Advantages Efficient Info Sharing Peer Network Public Knowledge Productivity New Users Without a market making capability… … public knowledge doesn’t pool … new users aren’t attracted … marginal productivity doesn’t grow … increasing returns fail

Peer Production Revenue Sharing
PP is not about getting others to make your stuff for ‘free’
PP is way to create more value via coordination arbitrage
… But there’s no such thing as a free lunch
Revenue sharing will emerge as supply-side price competition
Peer producers will appropriate more value as communities grow
Should you share revenues? Yes!
Sharing creates incentives for productivity and knowledge growth
But share strategically – not as margin-eroding price competition
Strategic revenue sharing targets constant margins and revenue growth in network size
Strategic revenue sharing
What determines the peer producer revenue share?
Rivalry for peer producers within your industry
Pre-empt margin erosion…
By limiting rivalry for peer producers
The more effectively you limit rivalry, the more you can share without margin erosion
What limits rivalry for peers?

Peer Production Industry Structures & Rivalry Suppliers & Buyers: Control access to key technologies, inputs, and distribution channels – vertical integration Control buyer/supplier scope economies by controlling high-value complements Fragment/commoditize key technologies or inputs if you can’t control them Example: Amazon – Fedex deal

Peer Production Industry Structures & Rivalry Suppliers: Control access to key technologies or inputs – vertical integration Fragment/commoditize key technologies or inputs if you can’t control them EG: Complements: Create larger numbers of higher quality complements than competitors Raises switching costs by lowering relative value of substitutes Example: lightweight, open standards (RSS) drive cheap complementarity Anti-example: Apple closing off iPod/iTunes platform kills complementarity Buyers: Control distribution channels – vertical integration Fragment/commoditize distribution channels if you can’t control them EG: New Entrants: Vertical integration creates strong entry barriers Scale and speed economies in network markets create strong entry barriers Other sources: first-mover advantage, preemption, deterrence, complements, nonlinear pricing, differentiation Example: eBay’s user network

Where PP is Inferior
PP is an inferior way to organize the production & design of goods
For which access to means of production is unavailable
Tightly controlled by suppliers
Aggregate peer network learning costs higher than opportunity cost of production
Capital and connectivity intensive
For which sharing isn’t viable
No learning externalities
Connectivity issues
Inherent properties of goods
Goods not lumpy
Durable goods
These properties limit rate of knowledge pool growth and kill increasing returns…
Or limit ultraspecialization gains and kill distributed economies of scale

Where PP is Superior
PP is a superior way to organize the production & design of goods
For which real-world production transaction costs are high
For which real-world production coordination costs are high
But for which , virtually, production and consumption information can be efficiently shared, realizing coordination economies
For which ultraspecialized knowledge is dispersed throughout the larger population
Which can realize distributed scale economies
For which inputs are divisible
For which the means of production are accessible

Summary: Peer Production Economics
Assigning coordination rights is costly in the real world
But virtually, coordination economies make atomized microproduction viable
By efficiently sharing information about about who and what should have access the means of production
Atomized microproduction…
Yields ultraspecialization gains
Reusing modular microchunks of production create increasing marginal productivity
Distributed economies of scale result
Knowledge pools
When goods are produced, and new shared information is stored
Increasing the future productivity of the community
Attracting new users, who make it more efficient to produce more goods…
… sustainable supply-side increasing returns

Summary: Peer Production Economics
Disintegrated value chains will atomize
Cheap coordination will atomize and explode the center, where production of goods generally happens
… and value will migrate to newer and newer edges
The dominant peer production strategy
Is to vertically integrate across the entire value chain
To capture the most value by providing infrastructure, inputs, and marketing/aggregation/filtering of outputs
This can be seen as a shift from goods to services in many industries
In order to achieve this strategy, you need…
Key resources and capabilities in market-making …
In order to enable efficient info sharing and engineer increasing returns
… and a sufficiently large and productive peer network…
In order to realize distributed economies of scale

Summary: Peer Production Models
Open or community-regulated access to the means of production
Open or community-regulated access to modify inputs
Low level inputs require little technical knowledge
content, designs, ideas, proposals
High level inputs require complex technical knowledge
product architectures, interfaces, features
The catch:
Supply-side productivity gains depend critically on information sharing to create knowledge externalities.
How do you know how to modify inputs?
Without knowledge externalities, the PP model can’t reach hyperefficiency.
Supply side effects alone are not enough

Summary: Peer Production Models
Demand-side sharing mechanisms make private info and preferences about inputs and outputs public
Playlists, tags, votes, ranks, values, reputations…
Aggregating sharing mechanisms reveals:
Utility functions & preferences – most efficient outputs
Private technical expertise & info – most efficient inputs
The cream will rise to the top - the most efficient inputs and outputs become transparent
Assuming search costs are low
Efficent sharing pools knowledge
Which creates sustainable supply-side increasing returns
No sharing without market-marking
Leverage implicit or explicit currencies to build incentives
No productivity gains without sharing
Knowledge must be a public good

Thank You

Heuristics

Peer Production Advantage Dot Com 1.0: Search engines, portals, networking services Peer Production Yellow Pages Fabs Low Search Economies High Coordination Economies Low High

Coordination Arbitrage Criteria Hedge Funds, VC Ford, GM Lifestyle goods Peer Production Sweet Spot Media… Low Input Indivisbility High Coordination Diseconomies Low High

Relative Advantages in… Amazon Peer Production Community Out of the Game Vital point eBay No Community Size Yes Market Making Capability No Yes

Who’s Attracted? Slackers: Inefficient info-sharing Restrict peer entry by invitation/referral Shift to part-closed model Control quality of complements Everyone : Sweet spot No one: Vital point Geeks: Expand scope Shift to fully open-access model Leverage viral effects & complements to win peers Low Knowledge Pool Size High Knowledge Pool Quality Low High

Productivity Explosions Productivity Implosion Real-World Productivity Real-World Productivity Productivity Explosion Low Community Size High Knowledge Pool Size Low High

Peer Production Cost Advantage Disintegrated Gains to Specialization Size of Production Set Atomized Integrated

Peer Production - Resource & Capability Dynamics Speed Effects User network Knowledge pool Action Coordination Information Exchange Knowledge Externalities Increasing returns Productivity Output Scale & Scope Effects

Analyzing Network Economics 2.0
3 dimensions of next-gen b-models:
Horizontal scope (products)
Vertical scope (features)
Peer productivity (knowledge network size vs user network size).
3 economic variables:
Scale, scope, and speed drive positioning on the above dimensions.

2.0 Strategy Space Vertical Scope (Product Depth) Horizontal Scope(Portfolio Breadth) Peer Productivity Scope Scale Speed

Scale, Scope, and Speed Economies
Scale
Reduction in unit costs due to increase in operational size
Scope
Reduction in unit costs due to increase in number of products marketed
Speed
Reduction in unit costs due to increase in number of products put through supply/demand chain

Coordination and Transaction
Coordination
Search
Matching
Transaction
Negotiation
Bargaining
Enforcement

http://www.techgig.com	86
http://wikicorsoweb.altervista.org	35
http://crittjarvis.com	10
http://thoughts-illustrated.blogspot.com	8
http://infoeco.blog.hu	7
http://www.slideshare.net	4

Peer Production

by papadavo on Oct 26, 2006

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Peer Production — Presentation Transcript