crowdsourcing a pandemonium for disruptive innovation

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MAInnova)onManagement 2010-12

Crowdsourcing

A Pandemonium for Disruptive Innovation

Cristbal Ortiz Ehmann

Master of Arts Innovation ManagementCentral Saint Martins College of Art & Design, London

This article is based on the dissertation submitted in partial fulfilment of the requirement ofthe degree of Master of Arts in Innovation Management at Central Saint Martins College ofArt & Design, London.

The original dissertation includes four elements: a hypothesis, a research plan, a criticalevaluative report, a feasibility report and the appendix.

Only bibliography relevant to this article has been included in the respective section.

For any questions or inquiries please contact the author at: [email protected]


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Contents

Introduction! 3

What is the degree of innovation that an online community hasbrought about for an organisation?! 6

The concept of innovation! 6

The concept of crowdsourcing! 8

Current results of crowdsourcing initiatives! 9

What could be the possible reasons for the results discovered?! 11

Can disruptive innovations be actively brought about?! 11

Can groups, as opposed to individuals, cause disruptive innovations?! 11

Can online communities produce disruptive innovations?! 12

Is the design of the online crowdsourcing process adequate to realise

disruptive innovations?!

12

Do external factors pertaining to the sponsoring organisations inhibit the

development of disruptive innovations?! 15

How could these crowdsourcing systems evolve in the future?! 19

Bibliography! 22

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Introduc)on

Some changes are so radical that they can mean the end of established things or systems.

These disruptions seem to emerge and change the whole landscape of the known world.

What is remarkable about this phenomenon is the fact that they seem to be unforeseeable

and non- influenceable.

Design thinking is a way of transforming things and systems. This approach to

solving problems was developed by design practitioners. In the last two decades this

practice has been so successful that it is competing shoulder to shoulder with established

consulting companies (Hyatt 2010). Its success has been ascribed by the coiners of the

term design thinking to a deep human-centredness of the practice and the resulting

products and services. This human-centredness has been described not only as the ability

to analyse and rationalise but also as the capacity to think intuitively, recognise patterns

and to construct ideas that have emotional meaning (Brown & Wyatt 2010). This design

thinking, as opposed to traditional consultancies, includes the human factor and all that it

means to be human in the value creation loop.

Crowdsourcing is one way to place the human factor at the front-end1 of the value

creation loop. It entails leveraging a large number of people to accomplish certain tasks by

using information and communication technology. On the one hand, the involvement of a

large crowd of people might increase the likelihood that those emotional human traits,

harnessed by design thinking and presumably neglected by other practices, are taken into

account.

On the other hand, according to the philosophical thoughts of Manuel de Landa in

War in the Age of Intelligent Machines, information-processing technology has allowed a

3

1 Front end is a generalised term borrowed from computer science that refers to the initial stage of a process.

In the context of innovation the front end is the stage at which input is collected in various forms from asource. This input is then funnelled down to a reduced set of options that is then implemented. In general theinput is processed and transformed to conform to specifications the back end can adopt and use. The frontend is an interface between the source and the back end


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high amount of interactivity. Resulting open networks used for collective decision-making

allow the machinic phylum2 to cross between many human beings (de Landa 1991, p.

291). Furthermore, de Landa posits, they allow for the creation of the Pandemonium, an

abstract machine concrete enough to allow the control of physical processes, but abstract

enough to allow the spontaneous emergence of order out of chaos (de Landa 1991, p.

291). These pandemoniac conditions seem to resemble those identified at the onset of

disruptive innovations. The beginning of the Internet is a good example of this state. On

one hand, the connection of computers was minimally organised through a common

language and, on the other hand, the usage and benefit of a network of talking

computers was not yet clear to anyone.

The combination of crowdsourcing as a form of open network, which places the

human at the centre of creative endeavours and De Landas surmise as described above

lead to the following assumption:

Organisations will be able to bring about disruptive innovations through the

deployment of crowdsourcing initiatives.

This assumption makes it worth exploring a few notions in the current literature and

discourses concerning collaboration, the role of ICT technology and the innovation new

types of collaboration can bring about. A discourse analysis of the statements the Occupy

Wallt Street movement has produced reveals that the current economic and political

system is not human centred and not based on social consensus. The movement

demands more self-determination and democracy. The discourse analysis has also shown

that these new behaviours might have their origins in the way humans interact with new

technologies and the higher connectivity it enables.

4

2 Manuel de Landa has borrowed this term from Gilles Deleuze to refer to the overall set of self-organizingprocesses in the universe. These include all processes in which a group of previously disconnected elementssuddenly reaches a critical point at which they begin to "cooperate" to form a higher level entity (de Landa,1991, p. 6 and 7)


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Scholars seem to agree that an undefined group of people collaborating off-line or

online can make better decisions than individuals. However, the expert voices are not clear

whether online collaboration can produce innovation. Three different approaches,

corporate strategy, technology & engineering and design thinking, have become common

practice to bring about this type of change. However, their effectiveness and the degree of

radicalness they can bring about is very much contested as well. The literature review also

reveals that there are no unambiguous and generally accepted definitions of innovation.

These discourses lead to the question of the disruptive innovations that online

collaboration has produced so far. Furthermore, it is worth investigating the possible

reasons for the results discovered as they might give an indication about how these

systems might evolve in the future.

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Whatisthedegreeofinnova)onthatan

onlinecommunityhasbroughtaboutforanorganisa)on?

This chapter discusses the current results of crowdsourcing initiatives. In a first step and

for the purpose of answering this very first question it is necessary to establish a common

understanding of the concepts involved. The main concepts to be defined are 'disruptive

innovation and 'crowdsourcing'3.

Theconceptofinnova.on

Since there is no 'single or official or widely accepted definition' (Green, 2010) of the

term innovation, it is necessary to resort to a variety of different sources and synthesise

new definitions to check the validity of the assumption. For the term innovation the

following definition has been synthesised through the combination of different statements

from the current discourses: A new thing or system, which didnt exist before. It is neither a

solution to an existing problem (Green, 2010) nor the satisfaction of a current demand

(Briggs 2012), but it generates value by itself and is therefore adopted by a large number

of people over a certain period of time (Christensen, 1997).

This definition has been extended to include theories of innovation established by

Christensen in the Innovators dilemma4 in order to setup a definition for disruptive

innovation:

A disruptive innovation5 is a new thing or system, which didnt exist before. It is

neither a solution to an existingproblem nor the satisfaction of a current demand, but it

6

3 The present section does not pretend nor adhere to generally accepted definitions; it does not pretend toset conclusive definitions either. It merely tries to determine the scope and the boundaries of the meaningsfor further use in this research. Definitions established here will serve solely as a common platform forunderstanding and will not be conclusive.

4

In order to produce a more generally applicable definition of Christensen's findings the scope has beenbroadened by borrowing the terminology of 'deterritorialisation' and 'reterritorialisation' from Deleuze &Guattari; as well as 'actor' and 'things' from the Actor Network Theory.

5 The terms disruptive innovations and breakthrough innovations will be used in this paper indistinctively


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generates value by itself and is therefore adopted by a large number of people over a

certain period of time. This new thing or system is usually created by a deterritorialised

actor at the fringes of an established cultural6 network of actors and things, that is, at a

point where the forces of control and power are dampened, and possibly the conditions

tend to be chaotic. It is measured according to an unconventional set of values, attributes

and their performance trajectories. Established institutions of control and power refuse it

for its misalignment to the predominating set of values. Eventually this new thing or system

moves out of the current cultural circle and triggers the expansion of a new and formerly

non-existent network of actors and things and at some point reterritorialises by overtaking

the performance of the old value system; and thus inhibits continuity of the established

cultural network.

Image1|Courseofdisrup2veinnova2on

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6 The word cultural is used in this context in its widest sense to include all types of culturally linked people,so that not only corporate culture is included but also other types of cultural networks.


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Examples of disruptive innovations are steam technology, which led to the replacement of

sailing ships by steam-powered ships (De Landa 1991, p. 68). Or hydraulics technology,

which has led to the replacement of mechanical steam powered earthmoving equipment

(Christensen 1997, pp. 6176).

Theconceptofcrowdsourcing

Increased interaction through ICT technology has allowed online crowds to contribute to

several types of tasks. This type of mass contribution to a specific task has been identified

and subsumed under the term crowdsourcing by Jeff Howe (Howe, 2006).

Taking De Landas assumption in its broadest sense crowdsourcing could be

defined as self-organisation of an online crowd that collaborates for a shared goal. A

narrower definition, which fits the purpose of hierarchical organisations might be the

definition offered by Daren C. Brabham (no date) in Crowdsourcing:

Crowdsourcing is an online, distributed problem solving and production model.

Crowdsourcing blends open innovation7concepts with top-down, traditional

management structures so that crowdsourcing organizations can effectively tap the

collective intelligence of online communities for specific purposes.

There are many types of online platforms that generate crowdsourcing. They differ from

each other according to the design of the following components: initiative8,9, brief, sponsor,

crowd and interaction.

8

7 The expression open innovation has been coined by Henry Chesbrough in 2003 to describe a newresearch and development paradigm in which organisational boundaries become more permeable to outsideand inside knowledge flows and thus expedites possible innovation efforts within organisations.

8 In this paper the term initiative and challenge will be used indistinctively.

9 Daren C. Brabham (2011) distinguishes four types: the knowledge discovery and management approach(peertopatent.org), the broadcast search approach (innocentive.com, mathworks.com or topcoder.com), thepeer-vetted creative production approach (threadless.com), and distributed human intelligence tasking(mturk.com).


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Irrespective of the possible types of crowdsourcing, this paper will only examine the

approach that deals with creating and selecting creative ideas (Brabham, 2011, p. 6) and

where there are 'primarily...cooperative relationships among one another with a substantial

amount of technology sharing and deliberate spillovers' (Boudreau & Lakhani, 2009, p.

70). Unlike other types of initiatives10, here the crowd is required to collaborate and funnel

down their inputs. Furthermore the only crowdsourcing purpose considered for the present

research will be the one in which the sponsor expressively intends to innovate irrespective

of the personal understanding of the term innovation.

Currentresultsofcrowdsourcingini.a.ves

A worldwide leading crowdsourcing company11 has provided a large amount of data

related to hundred and twenty three crowdsourcing initiatives carried out between late

2008 and late 2011. Each initiative has produced several ideas of which none, one or more

were awarded a prize by the sponsor and one idea received the highest amount of votes

by participants of the crowd. The best prized idea as well as the most voted idea of each

initiative have been weighted and ranked according to their degree of innovation and

disruptiveness12. This ranking has been developed by asking yes or no questions derived

from the definition of disruptive innovation established earlier. Possible marks range from

0 (lowest) to a maximum of 7 (highest). The average degree of innovation for the best-

prized ideas resulted in a mark of '2.9' and for the most voted ideas '3.8' out of a maximum

of 7 points. Although the most voted ideas have rated significantly higher than the best-

prized ones, both rates are rather low. A qualitative analysis of other cases support these

results. According to Aitamurto, Leiponen & Tee (2011) the results delivered by the crowd

9

10 Due to the irrelevance of these other types of crowdsourcing it is deemed unnecessary to explain them inmore depth.

11 The name of this company will remain undisclosed for confidentiality reasons, any related bibliographicalindications have been removed as well.

12 To simplify matters this degree will be called from here on innovation index.


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at an internal company challenge of Dell were 'regular customer feedback rather than

more elaborate or sophisticated business or innovation ideas. A content analysis of

several case studies published by the crowdsourcing company Brightidea reveals that the

results do show low levels breakthrough innovation as well.

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Whatcouldbethepossiblereasonsfortheresults

discovered?

From a global view the reason for these poor results can only be the following:

a. Disruptive innovations cannot actively be brought about, they happen without

the possibility to influence them.

b. Only individuals, as opposed to groups, can bring about disruptive innovations.

c. A group of people interacting online cannot produce disruptive innovations.

d. The design of the online crowdsourcing process is not sufficient to produce

disruptive innovations.

e. External factors related to the organisations initiating the crowdsourcing

challenges inhibit the development of disruptive innovations.

Candisrup.veinnova.onsbeac.velybroughtabout?

Most disruptive innovations come about by a paradigm shift in the way something is

understood and accepted by a larger community (Kuhn, 1962). There is no evidence that

any shift in paradigm has been realised with previous knowledge of the transformation

these shifts will cause, let alone planned and executed accordingly to the results wished

for. No conclusive answer can be given regarding point a) yet. But the elements and

circumstances that led to a paradigm shift can be studied and understood. Therefore it

stands to reason that by recreating similar conditions shifts in paradigm can be caused

deliberately.

Cangroups,asopposedtoindividuals,causedisrup.veinnova.ons?

Disruptive innovation is kicked off by an initial act of creativity, be it by an individual or by a

group. Nevertheless, current literature (Leadbeater, 2009; Johnson, 2011; Paulus &

Nijstad, 2003; Tapscott & Williams, 2008; Surowiecki, 2005) demonstrates that groups of

people perform better when it comes to decision-making and creativity.

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Canonlinecommuni.esproducedisrup.veinnova.ons?

According to Dennis & Williams (2003) there are two factors that foster and five that impair

creativity13. As opposed to offline groups, online groups only have one impairing factor and

this is social loafing14. But social loafing can only be present when individuals collaborating

in a group expect to be evaluated and monitored. And the expectation of being evaluated

and individually accountable is related to extrinsic motivation (Amabile, 1997). Extrinsic

motivations are most often detrimental to creativity (Amabile, 1996, cited in Hennessey,

2003, p. 197). The participants of the analysed crowdsourcing initiatives, however, engage

voluntarily through an open call, that is motivated intrinsically and therefore the negative

effects of social loafing should be minor or non-existent.

Isthedesignoftheonlinecrowdsourcingprocess

adequatetorealisedisrup.veinnova.ons?

A further reason that could explain the poor results is the design of the crowdsourcing

process. There are three dimensions to the crowdsourcing process. The first dimension is

the setting of the variables. The second is the design of the crowdsourcing tool and the

last one is how the crowdsourcing tool is deployed within the innovation process.

Sengofthevariables

The following variables seem to have an influence on the outcome of any crowdsourcing

initiative:

The size of the crowd: According to Dennis & Williams (2003) groups withcomputerised support increase their creativity performance with increasing group

size.

12

13 According to Dennis & Williams (2003) the factors that improve creativity performance are synergy and

social facilitation, whereas factors that impair creativity performance are production blocking, social loafing,evaluation apprehension, cognitive interference and communication speed.

14 Social loafing is 'the tendency for individuals to expend less effort when working in a group than whenworking individually' (Dennis & Williams, 2003, p. 162)


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Diversity of the participants: It is widely accepted that diversity promotescreative and innovative outcomes (Koch, 2012; Page, 2008; Surowiecki, 2005;

Milliken, Bartel & Kurtzberg, 2003; Dennis & Williams, 2003). A relevant point

concerning the diversity of the crowd is the process of selection. The crowd can be

self-selecting through an open call or the member of the crowd can be selected by

invitation from a closed pool within the boundaries of the sponsors organisations.

This includes also current customers, who also belong to the wider network of the

sponsor.

Anonymity of the participants: Online creative collaboration offers the possibilityto engage anonymously. This might eliminate the possibility of evaluation

apprehension (Cooper, Gallupe, Pollard & Cadsby, 1998; Dennis & Valacich, 1993

cited in Dennis & Williams, 2003) and to help 'separate ideas from their contributor

so that criticism is more easily recognised as criticism of ideas, not of

people (Dennis & Williams, 2003, p. 173). Participants in the case of the analysed

data belong to an open pool and were able to engage anonymously.

Reward of initiatives: Research shows that intrinsic motivation enhances thecreativity performance of individuals and groups (Hennessey, 2003). In general

there are tangible and intangible motivations. The former is generated through

cash or material prizes. The latter are emotional. These include extrinsic

motivation, like the expectation of better overall performance, or intrinsic

motivation like peer-recognition.

Convergent interactivity: this is the system that stipulates how the many inputsof the crowd are being funnelled down. This variable was measured according to

the number of votes and comments given by the participants for each challenge.

Initial information: this is the brief given to the crowd which determines the taskand its goal. Briefs vary according to the degrees of specificity and the novelty

sought. For the present data these two degrees have been combined to measure

each challenge's brief in terms of its openness.

According to the present analysis of the delivered data it can be stated that the size of the

crowd as well as the openness of the brief plays a minor role in respect to the innovation

outcome. Unfortunately the effects of anonymity could not be measured in any way.

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On the contrary diversity could play a major role. Even though it can be assumed

that the diversity of the participants is higher than that of closed pools, the analysis of the

data demonstrates a lack of diversity concerning gender, language and country of origin.

The same can be stated from interactivity. In general, the overall level of

convergence was very low especially in terms of comments.

Furthermore the data delivered suggests that the prize money offered does not

represent an effective motivation. Evidence shows that participants might engage with

several identities to increase votes for their own ideas. It can be assumed that intrinsic

motivation would not trigger off this kind of behaviour and this suggests, in turn, that

participants might expect to win a prize money from the sponsor with higher votes from the

crowd. According to Harwood (2012) the real motivation is the possibility to have an

influence on a companys decisions and that this company actually listens. This motivation

is intrinsic and non-material.

Thedesignofthecrowdsourcingtool

The second dimension within the design of the crowdsourcing process is the design of the

tool itself in terms of software and conceptual framework around that software. Fayard &

Weeks (2011) have identified three design elements that could give answers to why

crowdsourcing tools perform so poorly in terms of disruptive innovation:

Concurrent streams & privacy: the possibility of engaging in concurrent streamsand the resulting ability to structure and direct cognitive focus is believed to be an

important reason for the improved performance of electronic groups (Dennis &

Williams, 2003). Fayard & Weeks (2011) also claim that online participants need to

be able to move from public group interactions, accessible to all, to private

conversations of subgroups or even dyads. None of the crowdsourcing platforms

studied offer the possibility to self-organise private subgroups.

Proximity: Fayard & Weeks (2011) argue that people meeting in a virtual spaceneed compelling reasons to start interacting online. They identify the following: a

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core group of participants to bootstrap interaction, easy access to shared spaces

and high awareness of others. According to qualitative research most

crowdsourcing tools fulfil all of these qualifications.

Permission: the former authors also claim that online participants need to beencouraged by management. A crowdsourcing project is usually initiated and

promoted by management, which in turn means that they implicitly give permission

for participation.

Deploymentofthecrowdsourcingtoolwithintheinnova.onprocess

Two things become apparent when organisations deploy crowdsourcing projects. Firstly, it

is used as a tool only for sourcing ideas. So far, no information has indicated that the

crowdsourcing tool is being used for exploration of a problem, gaining insights into human

behaviour, or experimentation with conceptual prototypes. Secondly, these projects are

usually one-off events. With some exceptions (Koch, 2012) and according to the available

data, no sponsor has engaged more than once to launch reiterative challenges in order to

allow for a concept to develop. These two facts seem to indicate that the sponsors follow a

linear, milestone-based process, and this could be one of the reasons why the results

show a low degree of innovation.

Doexternalfactorspertainingtothesponsoringorganisa.onsinhibit

thedevelopmentofdisrup.veinnova.ons?

The innovation index from ideas generated through the analysed crowdsourcing platform

is rather low. This applies to the ideas that the crowd has selected through a convergent

process as reflected by the most voted ideas. However, the ideas selected by the sponsor

(best-prized ideas) had an even lower innovation index. Many organisations limit their

crowds to people from within certain boundaries related to their organisations. This seems

not to be the only problem, however, since, in most analysed challenges, the crowd was

not from within the organisations boundaries.

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Qualitative and quantitative research of crowdsourcing projects have shown that the

reasons lie in:

Strict orientation to profit and risk

Inclusion of distorting elements into the process of innovation

Inflexibility of pre-established structures

Lack of knowledge about innovation and sociological phenomena

Organisations engage with a crowdsourcing tool at the beginning of the challenge by

setting up the brief and stating their intentions; and by selecting ideas during or at the end

of the convergence process. An analysis of the briefs has shown that the sponsors have

mainly three reasons for initiating crowdsourcing challenges:

1. Creative ideas for internal or external marketing purposes

2. Improvements or incremental innovations for something already existing

3. Revolutionary things or systems that do not exist yet

For all three reasons sponsors appear to be searching for innovations but only for

the last one they expressively state to be searching for revolutionary things or systems that

do not exist yet. But, although they appear to be searching for this last reason, the ideas

that could lead to such a disruptive innovation are dismissed by the sponsor.

For the sponsors the process of prizing ideas is closely connected to certain evaluation

criteria. These have been expressively stated in many of the briefs and are used to funnel

down complying ideas. These evaluation criteria are usually the following:

1. Originality and novelty

2. Usefulness

3. Feasibility and ease of implementation

4. Effectiveness and expectation of widespread impact

5. Promptness

6. Cost of implementation

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7. Alignment with a set of organisationally related values like fitting with brand, for

example

All of these evaluation criteria, except the first one, confine the divergent possibilities to

certain boundaries, which lie in the immediate neighbourhood of possible things and

systems. These boundaries are related to functionality, reliability (Martin, 2009) and

viability (time and money). Some sponsors make the boundary itself the target of the

crowdsourcing project when they mention financial targets like profit or cost savings

(Healey, 2012). These boundaries originate from a profit and risk oriented mindedness that

avoid that members of the crowd can focus on the only two evaluation criteria relevant to

(future) consumers: originality and novelty.

Qualitative research has exposed that one of the motivations to engage with

crowdsourcing for employees is because they believe that this participation will have a

positive impact on their personal performance evaluation process. This evaluation could

prove to be distorting because it refers to the relationship between employees and

superiors and is not related to the innovative goals of the crowdsourcing project.

Furthermore, there is a tendency of pre-established connections and structures to

become inflexible. One example which demonstrates the reductionist view and the rigidity

of structures is a crowdsourcing initiative performed for an energy company (Harwood,

2012). Usually, the cost of energy consumption becomes cheaper the more you consume.

Customers and members of the participating crowd decided that this relationship between

cost and energy consumption should be reversed; that is, the more energy is consumed

the more expensive it should become. The management decided that this was not

possible because it was too complicated to change the billing and invoicing systems. This

indicates an inflexible relationship between humans and systems in the form of machines,

software and processes.

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Finally the low compliance between the most voted and the best-prized ideas

makes apparent that the organisations way of gaining knowledge is reductionist. They do

not take into account the synergistic properties of an ecosystem, which emerges as a

result of people interacting with each other (De Landa, 1994).

To conclude, these findings suggest that here could be other important reasons for

the low innovation degree ascertained at the beginning of this chapter.

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Howcouldthesecrowdsourcingsystemsevolveinthefuture?

In conclusion, it can be stated that, so far, crowdsourcing has not produced disruptive

innovations. However, crowdsourcing does have the potential and the ability to bring about

disruptive innovations. Johnson (2011) states that most innovations in history, especially in

recent history, have been generated through a network and in a non-commercial

environment. The philosopher Pierre Levy (2012) argues that a crowd can solve existing

problems 'but for disruptive innovations you need to pose new problems' and that 'we still

don't have collective intelligence systems or organisations able to help crowds to pose new

problems' (Levy, 2012). This answer refers to the inability to produce such disruptive

innovations because of the lack of the right tools or systems, not because of the intrinsic

inability of crowdsourcing to do so.

The innovation index from ideas generated through the analysed crowdsourcing

platform is very low. This applies to the ideas that the crowd has selected through a

convergent process as reflected by the most voted ideas. If this is true, it can be claimed

that the reasons lie mainly in a lack of diversity of the crowd and its low level of

interactivity.

A higher level of diversity could be achieved through larger crowd size, but other

systems could be conceivable through a semi-self-selected process with systems that

inhibit a concentration on certain features and with additional voluntaries that bring in more

divergent influences.

With regard to interactivity, the tools need probably to be redesigned to encourage a

higher amount of interaction in the form of comments between the participants. It would

probably be worth designing and experimenting with multi-layered systems both

horizontally to allow the crowd to interact more with each other before starting to give final

judgments in the form of votes and vertically to allow for the creation of concurrent sub-

streams. The systems would also need a mechanism that avoids the duplication of ideas.

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So far, crowdsourcing tools have been used to form a component of a very linear,

milestone based innovation process. It would be worth experimenting with a

crowdsourcing tool that resembles a design thinking approach. It is helpful to think of the

crowd as a team of designers, who, rather than being asked to simply deliver ideas to a

brief, are asked to become involved within the overlapping spaces of inspiration, ideation

and implementation (Brown & Wyatt, 2010, p. 33). This would require a shift in the way

crowdsourcing is approached. On the one hand, a major integration of the crowd and the

sponsor from the beginning of the process until the final implementation would be needed.

On the other hand, this approach would require the crowd to switch from being idea

deliverer to explorative researcher or interpreter (Verganti, 2009). The crowd would

become not only the object but also the subject of research. For that to happen, the

crowdsourcing system would need to allow for errors (Johnson, 2011) and loop backs in a

more institutionalised form. Prototyping and testing of ideas would require that the crowd

be involved until the end of the process and in reiterative steps with the possibility of

changing the crowds for each reiterative step.

In relation to design thinking, crowdsourcing could also be used from a much

broader perspective to gain insights about the behaviour of human beings and the

emergent properties that evolve through interaction. These new insights, in turn, could

lead to disruptive innovations.

Most importantly, however, is that organisations choose a different approach in their

search for disruptive innovations through crowdsourcing. In a first step it would be

conducive to avoid using crowds that are related to the sponsoring organisation.

Furthermore the constraints and rules within a brief and by which ideas are selected

should be, neither too narrow or rigid, nor too abstract or loose (Brown & Wyatt 2010; De

Landa & Davis, 1992). Brown (2009) claims that the constraints given in a brief need to be

balanced. The analysed briefs reveal that the constraints given to the crowd were either

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too constraining or too open. In most cases, the prize went to ideas that were very specific

and elaborate. High task specificity indicates that the sponsor is looking for a solution for a

precisely formulated problem (Piller & Walcher 2006, p. 310). However, they need to allow

for the crowd to pose new problems by giving constraints which are more relevant to

people and more compatible with the nature of a disruptive innovation. It is not possible to

assess the functionality, reliability and viability of future things and systems, which do not

exist yet and for which there is no demand. The answers will be rather abstract,

unelaborated and unspecified and demand a broad and long-term view.

A right approach for companies could be creating skunkworks in which the

perceived corporate risk is kept low. These skunkworks could have more experimental

character by including the divergent features of crowdsourcing with crowds completely

alien to the sponsor.

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crowdsourcing a pandemonium for disruptive innovation

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