Essential features of a scalable social innovation platform

The overall outlook and expectations towards social business software have changed dramatically over the last few years. Most enterprise decision makers have stopped questioning the value of social technology and are now more concerned with finding the right enterprise social platform that can support large communities within and beyond organizational boundaries. The trend is especially stronger in open innovation (or social innovation as I like to call it) communities. As a result, a number of existing players in innovation management have re-focused their product strategy to incorporate social elements. We are also seeing a large number of new idea management products entering the market at a rapid pace.

Although it seems that idea and innovation management tools have become a commodity, the reality is that most tools are limited to running campaign style idea collection leaving idea evaluation, filtering, and ranking in the hands of a small group of sponsors. This approach may be sufficient for some of the smaller ideation campaigns but does not scale very well when the community size and the number of ideation efforts go up. In order to be scalable, a social innovation platform must enable sponsors and community managers to:

• Clearly frame ideation objectives and engage the right audience for optimal results
• Manage online behavior of community members such that meaningful contributions are promoted and spamming/gaming attempts are minimized
• Ensure diversity of participation and connect the right set of collaborators belonging to the long tail
• Create an engaging experience that keeps users coming back
• Leverage the crowd to filter and rank ideas to minimize bias and management overhead
• Choose the right balance between crowd sourcing and top-down control

In this blog post I outline a core of set of features that must be present in a social innovation platform in order to effectively meet the needs listed above. Note that I focus only on advanced features that go beyond basic functionality such as idea posting, commenting, and voting.

Multi-tenant architecture and templates
Innovation efforts in large organizations involve multiple regions, lines of businesses, and ideation goals. We certainly recommend creating a global ideation site that allows the entire community to collaborate across organizational silos, however it is also necessary to create destinations visited by different population segments. The social innovation platform must allow sponsors to easily set up new communities and invite relevant sections of the user population for participation. Moreover it must allow innovation leaders to set up community templates with terminology, look and feel, evaluation and ranking mechanisms representing different ideation objectives and policies. Community templates significantly reduce the barrier to entry for new ideation sponsors; accelerates the learning curve and thereby minimizes effort required by the core innovation team to bring the new entrants up to speed.

User reputation
Innovation communities face two opposite types of problems: users posting too many ideas or an inactive community with too few ideas. The root cause in most cases is improper ideation framing. Some large communities, however, suffer from the former problem in spite of having a dedicated innovation team that clearly defines the goals. When the noise drowns out the substance, it makes it more difficult to make productive contributions and drives away serious users. Computing user reputation is an effective strategy to cope with this problem.

It is important to note that reputation is a reflection of quality of contribution not quantity. Some idea management tools use the term reputation to indicate activity level. Reputation rank should be determined not by how many times a user posts on the community, but how he community reacts to the user's online behavior and participation.

The reputation ranking of users has three implications for community management. First, displaying reputation on the leaderboard is a way of giving social recognition to your top contributors. It also creates a sense of competition, a great motivator for almost every kind of user. Second, the reputation score can be factored in idea ranking greatly improving relevance. Third, if reputation is tied to currency or points earned by users, it encourages users to be active in a meaningful way.

Reputation can also be used as a stick. The innovation platform must detect spammers and users who attempt to game the system. Reputation score for such users should be dropped to zero or a very low number thereby limiting their ability to get points and influencing idea ranking.

Game mechanics
The term game mechanics or "Gamification" is becoming quite popular in the context of social media discussions. This obviously does not translate to introducing Farmville to your community. That will probably result in having the "too few ideas" problem that I mentioned earlier. Gamification should really be about creating a fun, competitive environment for your innovation community that makes the site sticky in a positive manner. It should be designed in such a way that winning the game requires participants to align their behaviors with innovation objectives and strive to improve overall community health.

Gamification goes much beyond getting Foursquare badges (although that could definitely be part of it). It should include leaderboards that displays users by reputation, virtual wealth, and top innovators in addition to different types of idea rankings. Users should be able to acquire special powers that allows them to moderate content, view restricted areas or access functionality not available to other users. Mechanisms like idea markets and prediction markets are another example of constructive gamification. These mechanisms are not only a fun way of engaging the crowd, but they also enable sponsors to aggregate opinions of many and derive results that assist in decision making and making predictions.

Automated idea graduation
I recently heard a great quote about the value of crowdsourcing:

It's not difficult to find a needle in the haystack if you enlist the haystack to find it.

The point here is that it's a lot easier to find great ideas and solutions when you open up ideation challenges and problems to the entire community. I believe in going even further and enlisting the crowd in filtering and ranking of ideas in addition to initial suggestions. When you leave idea evaluation and ranking entirely in the hands of the sponsors, it is problematic in a couple ways. First, you really expose yourself to the biases shared by a small group of people. The HiPPO problem (highly paid persons opinion) is a corollary of this issue. Second, the innovation committee becomes a bottleneck in the innovation process as the number of ideas increase.

The innovation platform must support a way of filtering ideas in multiple stages. The number of stages and criteria associated at each stages can vary based on organizational culture and the type of ideation. We recommend a three-stage process that has worked well for most of our communities. The criteria for moving ideas forward in the initial stage should be fairly simple such as buzz, conversational levels, votes, etc. The second stage should raise the bar on simple metrics and add more in depth scrutiny (e.g. Multidimensional reviews, expert evaluations, etc.). The last stage should deploy a mechanism like idea markets that leads the users reveal their true preferences.

Idea and user recommendations
Every social innovation community I have examined demonstrates the long tail behavior in terms user activity levels as well as the number of users that collaborate on a single idea. There is typically a very small percentage of users that are extremely active and a few ideas that attract widespread attention. On the other hand a large number of users participate at a more moderate level and  there are many ideas that attract only a handful of collaborators. Interestingly, the ideation process is very democratic. Successful ideas don't just come from hyperactive users, many of them come from the long tail. As a result enabling collaborators to find each other on the long tail becomes crucial to success.

As the idea volume goes up, it becomes increasingly difficult for the long tail users to connect with like minded users and ideas that they have an interest in. In such cases, the innovation platform must make or recommend such connections based on user profiles, their participatory behavior, and social network analysis.The connections can be presented via a user-centric presentation of ideas and like-minded users. Alternatively recommendations can be pushed to the users via email notifications.

Shortening attention spans, multitasking, and the rise of Twitter

Number of theories abound regarding why Twitter has become so popular including this one that claims that it is because it is designed to have social intent. I started thinking about this and in particular thought about why I am not hooked on to Facebook but find Twitter useful. I came away with three reasons for Twitter's success: overabundance of information, shortening of attention spans, and the desire to create personal brands. Twitter thrives in this environment because it offers the most efficient way of discovering pertinent information via social curating.

The problem of information explosion predates the rise of the Internet in the consumer space; it just got worse with Internet's ubiquity and ease of access. A number of mechanisms have evolved in the Internet age to help improve information discovery as shown in the figure below. Note that the new mechanisms haven't replaced the older ones but simply expanded available modes of discovery.

Release of Netscape browser was the first sign of impending rise of the Internet. I remember getting excited about this cool new browser that was much better than Mosaic. Netscape was a great improvement over its predecessor but you pretty much had to type in the URL of a Web site until Yet Another Hierarchical Officious Oracle (Yahoo) came along and started "organizing" the Web into a hierarchy of categories. Now you could traverse the categories, find a topic of interest and browse available web sites pre-classified to be in that category. The next step in the evolution was Google with its PageRank based technology that was very effective in adding relevance to search. This provided a much better mechanism to find information in which "reputable" Web sites related to search keywords were listed at the top.

When Web 2.0 arrived on the scene, we saw the emergence of folksonomies (tag clouds) and social bookmarking/tagging sites like Delicious, StumbleUpon, and Digg. These sites gently introduced Web readers to the notion of social curating when they started following bookmarks, posts, etc. created by people they trusted. Twitter perfected this art by providing the most efficient way of filtering information via social curating. Each Twitter user follows other users in the"circle of trust" that includes his friends, colleagues, and experts in the areas of interest. Resulting twitter feed then provides a much better way of finding interesting and useful content since it is either published or recommended by the people you trust.

Twitter is also very efficient in the way it gets information to you. Since the tweets are limited to 160 characters, it forces publishers to be succinct in their messages, a valuable gift for the recipients in the age of shortening attention spans. In general we are all getting used to and expecting instant gratification. Five day cricket test matches have for the most part been replaced by 20-20 games that last for about three hours; average movie lengths have been descending; younger generation talks in short bursts that almost sounds like an audio Twitter feed.

In a sense a Twitter feed is like the front page of a newspaper. The front page displays introductory portion of a number of news articles, most of the remaining article is on other pages. With Twitter, you get only the headlines and if you find that interesting, you click on a link that takes you to another place that shows you all the details.

The third reason for Twitter's popularity is that it is the most efficient way of advertising your personal brand. With Web 2.0 came a wave of new individuals that finally had the opportunity to create and maintain a personal brand. A number of now-famous individuals rode the blogging wave to make themselves into famous journalists, political analysts, critiques, reviewers, and advisers. The blogging revolution created a tournament (read more about the tournament behavior in Freakonomics) of information hawkers in which people compete to get rich in the information economy. Most competitors become part of the long tail and eventually stop playing. Some make it big and live on. From the information publishing viewpoint, Twitter  offers a very efficient mechanism to advertise your offering. It is also very effective since information consumers increasingly rely on these headlines to get to the content they ultimately want to see.

Although Twitter founders must be quite happy with its success, the underlying trends that make it popular are a bit disturbing. It's rise is accompanied by addiction to passive information consumption, shortening attention spans, and increased multitasking. Addiction to Twitter is probably best explained by the theory of unpredictable rewards (the same rationale that explains email addiction): you get rewarded with really interesting piece of information at a random frequency, so you keep reading hoping to find that next reward.

Twitter joins the crowded ranks of other competing sources of information like email, television, etc. that are fragmenting attention spans. These "distractions" coupled with the increased pace and complexity of modern life are forcing multi-tasking behavior and frequent context switching. My sense is that these conditions are seriously affecting the ability to focus on and adequately examine important tasks. Some of the research in this area cited in this New York Times article concludes that multi-taskers are worse at filtering out irrelevant information and switch tasks. You can even test yourself on these abilities here.

Since going back to stone ages is not a particularly good solution, the only option is to adapt to the new reality and find ways to minimize its impact on productivity. To that end I leave you with the following techniques I personally employ that allows me to be a player an not just a spectator:

• Shop when you need something, not when there is a sale - This works with information as well. Instead of continuous looking for information, I choose the most effective way of information retrieval that helps me with the job at hand.
• Play only during recess - I reserve my random explorations (twitter feed browsing, searches on innovation, etc.) for selected time periods
• Publish less - I am not on the frequent Twitter plan. For the most part, I try to tweet when I think it is of broad relevance to reduce information pollution.
• Avoid reciprocal follower-ship - I am a bit choosy about who to follow leaving me with relatively less number of tweets to browse through

A word from innovation professionals

I had never thought of myself as an "Innovation Professional" but I heard the term during the Process Driven Innovation conference I recently attended in Philadelphia and realized that I fall into that category or at least deal with that bunch every day. There was off course much more to learn besides the existence of aforementioned term. This was a small conference with around 50-60 people in attendance, very similar in size and scope to the one I attended a few months ago in Ibiza. Great thing about such smaller conferences is that they give you an opportunity to have in-depth exchange of ideas with people that are actively involved in innovation management (aka innovation professionals).

A lot of what I heard during the conference is common wisdom shared by the community. For example many speakers emphasized the need to have top down support, a continual communication strategy, obstacles created by the nay sayers, etc. I was on a panel that discussed such best practices along with Jon Bidwell (Chubb), Kevin Paylow (Halliburton), and Steve Fenessey (InnoCentive). I did have a few surprises and heard some interesting perspectives.

The Rise of "The Innovation Professional"
Innovation is undoubtedly the hottest buzzword these days. For example, you will find vastly increased number of people with the word "innovation" in their titles or job function if you search on Linked In today. That's great news, however, the innovation owners very often do not have the budget or the authority to implement ideas; that is the prerogative of the P&L owners. I have found this dichotomy very frustrating since it requires a dance between two different owners to achieve your innovation objectives.

My view was that innovation should really be a part of everyone's job function and we need to eliminate this dichotomy. Contrary to my belief, I heard overriding sentiment in the conference that the specialized innovation role is a must-have in an organization. This view sounds self-serving at first but as I heard people talk about their experiences I found an answer to this dilemma. No one was disputing the fact that every employee, customer, and partner should be part of the innovation process. They were simply pointing out that innovation teams are instrumental in orchestrating that process. They play a role very similar to the one played by brokers, advertisers, distributors in the free market economy.While everyone chips in with their ideas and sponsorships, innovation team administers the process, helps people present their ideas, and connects different players to optimize the process.

Have idea management tools become a commodity?
The speaker from 3M made a comment that the ideation tools have become a commodity. We certainly seem to hear about a new ideation tool every day that has a catchy interface and a cool slogen that claims to help you eliminate world hunger. I agree with this assertion if you limit the scope of idea management to idea collection, commenting, and voting. That has certainly been commoditized and almost all ideation tools would work very well for smaller communities with campaign style ideation. Unfortunately if you select a platform that is limited to this functionality only, it does not scale very well for large communities.

Innovation is not an event, it is an ongoing process. Making this process successful requires a combination of active community management, education, and the right tool set. Many routine tasks become major pain points as the community size increases. Spammers and users that try to game rankings and rewards becomes a bigger issue. Sponsors find it increasingly difficult to read each and every idea posted in the system. They need assistance in finding common themes and duplicate ideas. My feeling is that social innovation (or for that matter socializing any business process) is in it's infancy. Some of the tools in the market offer a far better alternative to older methods but there is still much to be learned. Until that happens, it is hard to imagine this space becoming commoditized.

Prelude to Idea Collection
Can Campbell Soups learn anything from Nike? Seems like the soups folks were inspired by the way Nike is improving customer loyalty by creating a Web site that provides fitness help. What does cat litter have in common with burn bandages? Both need absorbent material that removes odors. These are some examples of how businesses can innovate by observing other companies in acompletely different sector or products that seem unrelated but have solved analogous problems. Such strategies are crucial for a successful ideation process. In fact idea sourcing or collection itself is the easiest phase compared to what comes before (ideation framing and creative thinking methodologies) and after (evolution, evaluation, selection, and implementation).

Whirlpool presentation described another strategy to spawn creative thinking. Traditionally the decision to buy appliances is made by the woman of the house and appliances go either in the kitchen or the laundry room. When you present these observations, somewhat obvious questions that come to your mind are: why target only women? and what about other rooms in the house? This lead to the Gladiator brand that caters to men and focuses on solutions for organizing the clutter in the garage.

A couple of presenters including the person from Campbell Soups described observation-focused ways of innovating. Both of these projects, however, involved a small number of people in the analysis of those observations. I think they will see much better results if they allowed a much larger number of people to examine those observations. In other words combining traditional methodologies with social innovation tools like Spigit would provide a huge benefit.

Miscellenous Tidbits

• Innovation is a Sale - Really? - Jean-Mark Frangos from British Telecom took the innovation professionalism to yet another level by casting his job function as making a sale. In this analogy, ideas are products, P&L owners are the customers, articulation and visualization are your sales tools. Now that's innovative
• Andrew Douglass from Rhodia illustrated how six-sigma techniques can be applied to the innovation process. Their existing process was resulting in a high failure rate for ideas that had passed the proof of concept stage. By examine the causes of failure and preparing a check list of criteria at the early stage reduced the failure rate substantially.
• Heard about the thank you program in IBM where employees can suggest gifts for other employees based on their personal experience. I thought this would be a good addition to Spigit's virtual economy

Social networks and Dunbar's number

In response to my earlier post about Metcalfe's Law, Lior Sion brought up another magic number that is frequently cited when it comes to the number of social relationships: Dunbar's Number. I remembered reading about this in Malcolm Gladwell's Tipping Point and it got me thinking about how it applies to online social networks.

To get started in my investigation, I looked up the Wikipedia article on Dunbar's number. The article describes the number as "a theoretical cognitive limit to the number of people with whom one can maintain stable social relationships". As I continued my search I found a better reference, Dunbar himself explaining how he arrived at this number in this video . According to Dunbar, the number of meaningful relationships a primate can maintain depends on the ratio of the size of neocortex (which exists only in mammals) to the overall brain size. You can compare this ratio and corresponding social unit size in different primates and arrive at a number of roughly 150 in humans. There are several examples of social units without a significant hierarchy that support this hypothesis including Goretex micro-businesses cited in Gladwell's book and Hutterite communes.

So how is this number related to online social communities? Apparently Dunbar is investigating this issue as reported in this article. The full report is due some time later this year. Not surprisingly he notes that even in case of people who have millions of "friends", the communication frequencies indicate that the number of meaningful connections is less than 150. I ran some numbers on Spigit's communities and I came away with the same conclusion. The chart below shows the total number of connections as a function of individual users for three community sizes: small (< 500), medium (< 5000) and large (> 5000). I cut off the long tail in order to clearly show the variation in the fat part (please note that no animals where harmed in this process).

The most conspicuous thing about the charts is the fact that the number of connections as a function of users seems to follow the power law. An interesting property of power law functions is that the natural log of frequencies (y values) varies linearly with log of x values. I did exactly that to the values shown in the first chart and plotted the resulting values in the chart below.

The top few highly connected users fail to live up to the power law expectations (Wikipedia article mentions similar deviations in other phenomena that otherwise follow power law), but the shape of the curve is quite close to being linear towards the end.

Looking at the first chart it is quite clear that the bulk of users have less than 150 connections but what about the highly talkative users that seem to have communicated over a thousand other individuals? The answer lies in the fact that none of these users maintained all these conversations simulteneously. Online communities differ significantly from  the social groups studied earlier in three inter-related respects:

1. Lower barrier to entry - Internet is highly efficient communication mechanism. It is incredibly easy to get virtual access to people that you have no prior knowledge of. 
2. Higher mobility - It is much easier to leave or join a social cluster compared to other social units where physical proximity plays a critical role.
3. Driven by Individual Goals - Online clusters form around a common interest or a goal that is initiated at the individual level not at the communal level. Offline social units form around a set of predefined common goals (e.g. Gore factory unit, HOAs, etc.). Social units (certainly within Spigit communities) in online communities are spawned by people who want to change the world around them.

These three factors contribute to a very dynamic set of social clusters that are formed around topics of interest, gain traction with a small group of users and are eventually replaced by other hot spots with a different membership. In fact looking under the covers, it was clear to me that even highly social users changed their group affiliations over a period of time. Even though they remained interested in communicating with a handful of individuals on a continuous basis, they communicated with different sets of people at different times. The chart shown below illustrates this point. It shows the communication pattern of some of the most connected users in highly successful Spigit communities. Each data point reflects the number of connections in a 30 day period. As you can see from the chart, that number is below 150 with the exception of one data point even though the total number connections over the entire period is above 1000 for some of these users.

So why is this analysis so interesting (other than satisfying one's academic curiosity)? Well, because it helps us evaluate the breadth of collaboration in an online community which is strongly correlated with diversity of participation.  The analysis presented here and in my last post about Metcalfe's law helps us set expectations in this regard. First, the number of interactions per user follows the power law even in the most successful communities. In general the best you can hope to achieve is to lift the long tail  part of the curve upwards. Second, whether it is due to cognitive or bandwidth limitations, the number of active communications in a short time frame that can be maintained by even the most active individuals seems to be below 150. As a result it is not realistic to judge the level of collaboration in terms of the total number of possible connections (n*(n-1)/2), but Dunbar's number seems to be an achievable ceiling for the most active users in your community.

Living up to Metcalf's law on social innovation communities

In my presentation last week at spigit's customer summit, I presented some statistics on spigit's social innovation communities including a comparison between actual connections established over a social network and the maximum possible connections - the basis for Metcalf's law (which is really not a law but we will continue the tradition for the time being). Given the warm reception from the audience at my explanation, I thought I will dig into this a little bit more. This blog post is the result of my investigation.

First let me set some context on Metcalfe's Law. Metcalfe, inventor of the Ethernet protocol, was originally talking about how the "value" of a network of compatibly communicating machines grows quadratically (not linearly). I found this post that shows a reproduction of his original slide. The basis for this assertion is the fact that in a network of "n" nodes, each node can communicate with n-1 nodes hence there are n*(n-1)/2 possible pair-wise connections on such a network. The value of a network is really in its power of establishing communication among its nodes. The number of possible connections is of the order O(n²) as n becomes large which leads to Metcalfe's law.

The mathematics works the same for any network so it is possible to apply the basic thought to other networks including human ones. If each person in an on-line community communicate with all other members, the total number of communication links will be of the order O(n²). Although this may be the ideal scenario, what's the reality like? I performed some analysis on Spigit communities to answer that question. The chart below shows the number of connections in the network plotted against the size of the social network. Three types of connections are plotted:

1. Conversational - Post-response connections between original poster of an idea, blog post, forum thread etc. and a commenter. Note that multiple exchange between two people count as one connection.
2. Conversations and Evaluations - In addition to conversations, this includes voting/rating interactions between two users
3. All connections - These include viewer-poster and linked-in style connections in addition to 1&2

This sanitized version of the graph does not show the numerical data but does depict the trends I observed in my analysis. The chart also shows a plot of linear and nlog(n) functions to give readers an idea about the order of change. Looking at the chart and the numbers behind it, it is clear that the number of conversational connections increases more or less linearly with the community size. The number of connections representing all interactions certainly did not grow at a quadratic rate but the fluctuations were too high to draw any meaningful conclusion. The linear variation in conversational connections is consistent with the long tail pattern of conversations found in all communities. There are a relatively fewer number of individuals who are extremely well connected, but the majority of users are part of the long tail and have a limited number of connections that is independent of the community size.

It is evident from the chart that there is a significant variation in the connectivity utilization between different communities. When I examined the dynamics within more successful communities (in terms of user connections), I found three key factors:

1. Well-defined innovation process -  All successful communities have a very well defined process consisting of idea sourcing, evaluation, and selection. The process is well publicized and executed as promised.
2. Incentives - Most communities have fine-grained incentives for encouraging broader participation in addition to allocating funding for implementing selected ideas. The incentives range from tangible items like gift cards to recognition by leadership to purely monetary rewards corresponding to the play money earned in Spigit's virtual economy.
3. Emphasis on "social" - Some of the well connected communities emphasize social interactions by promoting blogging, open exchange of thoughts on discussion forums, and (now) traditional collaboration over wikis. Innovation is embedded within this larger context.

It is interesting to note that not every successful community incorporated all three factors. Also in general increased connectivity did not necessarily lead to a better result in terms of number of quality ideas that get selected for implementation. That is strongly correlated only to the first two factors. Conversely in some communities,  organizational culture inhibited people from freely collaborating on proposed ideas, but the outcome has been significantly better compared to traditional processes due to support from the executive team and strong innovation process management. This is an important point to consider when setting up enterprise communities. Whereas communication within consumer-oriented social networks is very often an end in itself, for enterprise communities communication is a means to an end. For spigit communities, the goal is the selection and implementation of ideas that provide business value and achieving that requires channeling community interactions to that end.

It's also worth mentioning a few patterns that I thought I would see but didn't. I didn't find any correlation between different business sectors and network connectivity nor did I find more interactions within communities that had higher percentage of knowledge workers. There was C-level involvement in a couple of cases but in many communities the innovation effort was lead by an internal champion who was passionate about making the innovation effort successful. Finally the size of the community didn't seem to have much effect on the networking pattern even though it did have an effect on the number of participants that posted on the innovation site.

Designing idea markets for social innovation communities

Cisco's I-Prize competition hosted by Spigit concluded recently. I thoroughly enjoyed seeing lots of interesting ideas coming through and the amount of collaboration that followed. From Cisco's viewpoint the great success story was the billion dollar idea that was selected at the end of the competition. For me, the most successful outcome was the fact that our idea market worked! The idea selected by Cisco had the maximum amount of investment in the market and the overall ranking matched up very well with the internal evaluation process.

I am a big proponent of deploying Idea Markets within social innovation communities. Some of our key clients have made that core to their idea ranking and selection process and have seen excellent results in terms of the quality of ideas that bubble up to the top. In this blog post I explain the main concept behind idea markets, how to use them in practice and why I think they work better than some of the other techniques for ranking and rating ideas.

Role of Idea Markets in Social Innovation
One of the core features a social innovation platform is its ability to leverage the crowd for evaluation and ranking of ideas. There are many ideation tools that attempt to do this based on simple voting measures. In the simplest case, ranking is done based on popularity, the idea with the most "Thumbs Up" votes wins. This approach is appealing for its simplicity but is prone to gaming. The gaming behavior can be significantly reduced by introducing user reputation in idea ranking computation. Instead of simply counting up votes or ratio of positive to negative votes (approval rating), ranking can be computed as a reputation weighted average of votes. We have seen this work very well in ideation communities especially in the initial stage of the idea lifecycle. The approach still has its limitations. Very often frivolous ideas (e.g. 20% raise for all employees) get to the top even though there is no chance of them getting accepted for implementation. Voting is almost too easy to perform. On the positive side this leads to greater participation, on the negative side it promotes careless or even worse cliquish voting behaviors.

Idea markets, if designed in the right way, can overcome these shortcomings. Spigit uses its virtual economy as a basis for an incremental reward system for users. Idea market is one of the most interesting aspects of this economy. We usually introduce idea trading after filtering out the noise via conventional means. Idea market is then used to determine idea ranking in the final stage. The market is set up in such a way that users see a pay-off on their investment only if the idea gets selected. When the currency is tied to a reward system, users are motivated to invest only in those ideas with a higher chance of getting implemented. As a result idea markets more effectively suppress adverse behaviors like gaming, careless selections, voted-for-my-friend, etc.

Market Design Principles
Simplicity
Idea Markets work well only if the markets are thick and diverse. Simplicity of the investment model is probably the most critical factor that determines participation levels. For example, "short selling" may be understood very well by Wall Street traders, but is quite confusing for the average user and will most likely inhibit participation.

Incentives Tied to Success Potential
The ultimate objective of running idea markets is to recognize the best ideas based on the crowd's input. The "stock" price of an idea determines the ranking and therefore must be tied directly to its potential for success. Correspondingly the payoff model must incent users to invest in ideas based on their eventual chance of success and suppress day trading and cliquish behaviors that work against the main goal of identifying promising ideas.

Early Investment equals Bigger ROI
The design should provide better rewards to those who invest early and should decrease as the idea gets more popular. In general this encourages users to spread out there investments in many ideas and inhibits "jumping on the band wagon" behavior.

Embedded Collaboration
While prediction market traders are investing in outcomes they cannot control, idea markets are about trading in ideas that can be greatly enhanced or be allowed to fail fast based on inputs from market participants. Idea markets therefore should provide users the ability to express their views, suggest modifications, and supply additional information.


Independent Idea Selection
Idea markets should have an independent mechanism for selecting successful ideas and should reward investors in those ideas. Without independent verification, markets are much more prone to gaming since being on the top of the stock market fully guarantees a reward. Many users then choose to invest for guaranteed rewards albeit for a lesser amount.

Idea Market Models
The main concept behind idea markets is simple. Market participants are given play money when they join. They may earn more money by posting ideas, voting, commenting, etc. The market administrator allows participants to invest their money in some or all ideas posted on the system. The "stock" price (although it is not visible to the user in the variation that I like) of an idea goes up with the number of investors and/or amount of investment. I have seen and experimented with three different idea markets that implement the basic concept described in the last paragraph. These are described below.

Stock Markets with Continuous Double Auction
Traditionally idea markets have simulated real world financial markets to a large extent. Each idea is traded as a stock market instrument. Ideas typically open at a fixed price (typically $10 with idea price varying from $1-$99). The markets run using the Continuous Double Auction (CDA) mechanism in which traders place bids and asks at a certain price and share quantity. The system executes a trade when it finds a bid at an equal or higher price than an ask. Markets either allow short selling or award a fixed number shares to all traders in order to inject liquidity in the market. The final closing price is based either on the last executed trade or more often Volume Weighted Average Price (VWAP) over the last few days preceeding the close. Users are awarded prizes based on their portfolio value

Stock Markets with a Automated MarketMaker
I have seen automated market maker implementations in prediction markets but not within idea markets except the one offered by Spigit.  We have used the stock market paradigm combined with a system market maker on Spigit platform with a fair amount of success.  In this model, the market maker sets the idea price based on the level of investment and number of investors in that idea relative to all other ideas in the market place. Users trade with the market maker when they want to buy or sell shares in an idea.

Investment-Based Market
In this market implementation, users bet or invest money in ideas they like. They don't buy or sell stock, but simply indicate the amount of money they want to invest in an idea. A user can adjust their investment at any time before an idea is closed. Users that invest in successful ideas make profit on their investment. The virtual ROI is conveyed to the user at the time of the investment. Early investments often yield higher profits and changing investments does not yield any profits.

Market Comparison
We have deployed all three types of market for our clients. The collaborative aspect can be embedded in all three models. An independent mechanism for selecting successful ideas can be established for all models as well. The models do differ with respect to the other three considerations that I have laid out earlier.

The stock market like models are hard to understand for most users outside of the financial sector and companies with highly educated workforce. Some companies do prefer the stock market paradigm due to the fun factor they bring in. They both reward early investors but encourage more active users in purely profit-seeking transactions that go against their own evaluation of ideas.

The pure investment-based model is simple to understand for most people. The only way to earn profit is to bet on the right idea and the ROI diminishes as the idea gets more popular with investors. We have successfully used this model for Cisco I-Prize and some of the internal communities. That's certainly my preference but would love to hear your thoughts!

Building trust within social innovation ecosystem

I recently sat in the kick-off meeting of one of the biggest roll outs of Spigit's social innovation platform. As we started exploring goals and needs of different working groups, one of the group leads started talking about an issue that comes up very frequently: lack of interest/buy-in from middle management. As I listened to his experiences, it occurred to me that we spend a lot of time talking about what motivates the "crowd" but seldom discuss how to best involve other parts of the social innovation ecosystem and build trust within the ecosystem for effective collaboration.

For a social innovation effort to be successful, it must be engineered to build trust among key stakeholders (depicted in the figure below). The key to building trust is to prove that the system "works" and mitigate fears (even though some times they are either irrational or selfish). Anyone starting a purpose-built community must conduct stakeholder analysis and design technical and social elements of the system accordingly. Once you establish trust, you can build upon it by offering appropriate incentives for meaningful participation. Since the topic of incentives has already gained a lot of attention, this blog post mainly focuses on strategies to allay stakeholder fears and creating proof points that demonstrate that social innovation works.

The Champion
We almost always work with a "Champion" in the client organization in the beginning of a Spigit deployment. The champion is passionate about making social innovation work in his or her organization and in general NOT a sponsor with the budget or the authority to implement selected ideas. In most cases, the champion is really a team of people responsible for bottom-up innovation. The champion's goal is to successfully deploy innovation platform that provides real value to all other stakeholders. Her fear off course is the possibility of conducting a failed experiment that generates little traction from the target community and does not produce results expected by the business leadership. The needs and fears of the champion are really about addressing the same for all other stakeholders and satisfying them requires implementing approaches described in the rest of this blog post.

Upper Management
When it comes to senior leadership, there are three important concerns that need to be addressed: IP and licensing issues, leakage of confidential information and the risk of allowing participating employees/customers to air dirty laundry in public. All of these concerns are valid but it is important to recognize situations where the benefits outweigh the risks and prove it to the leadership. The biggest proof point is increasing number of companies, both large and small, that have engaged in collaborative innovation both inside and outside organizational boundaries. Companies like P&G (Connect + Develop), Shell (Game Changer) have started open innovation programs that invite ideas from public at large. They have successfully co-created products in a semi-open (collaborative aspect is missing from these sites) environment. Customer feedback and suggestion sites maintained by Dell and Starbucks have demonstrated the benefits of social innovation (albeit at an incremental level).

To address confidentiality and information leakage possibilities, there needs to be clear strategy both at the technology level and community governance policies. At the technology level, the social innovation platform must be proven in terms of network, storage, and application level security. The governance policies must be encoded in the form of information monitoring and access control rules protecting sensitive information. The concern about negative input can be addressed by recognizing that if users don't do it on the designated site, they will do it some place else (which is much harder to monitor and control). It also helps to convey to the community members that being able to share information is a privilege (e.g. Facebook makes this clear to their employees when they share information in an open forum) and explaining the rule of proper conduct. 

To prove the benefits of social innovation, it crucial to understand how the top leadership views innovation. My personal viewpoint is that innovation is any change that makes a difference in your lives. Most leaders however think "game changing" when they hear the word "innovation". In my experience, focusing purely on game changing innovation is often frustrating since these ideas are very hard to come by, take relatively longer time for evaluation and years to implement. The best practice is to allow multi-level innovation efforts to co-exist and set expectations matching the degree of abstraction in each case. In any event, the champion should focus on the following to build trust among senior leadership:

• Pick the right scope and focus area that is consistent with the strategic direction defined by the leadership
• Create a frame of reference by articulating the vision, expected outcomes, and time frames
• Convey intermediate milestones and achievements in a concise and quantitative manner
• Provide feedback regarding softer metrics that convey improvements in customer satisfaction, employee morale, etc.

Middle Management
Middle management (MM)  is mainly responsible for execution of the policies set by the top level leadership and therefore is far more interested in efficiently running day-to-day operations of the organization. This puts them inherently at odds with innovation, especially breakthrough innovation. In many organizations, it is far easier for MM to take no action than engage in something novel that may subsequently fail.  In general I have seen three things that MM is scared of: 1. Destabilizing existing processes by introducing a change 2. Loss of control over business operations 3. Loss of productivity due to employees spending time on non-essential work (i.e. innovation).

Given MM's focus on managing the daily grind, it is clearly important to frame innovation efforts around incremental improvements such as process efficiencies, cost cutting measures, etc. Selecting a well defined problem with a high likelihood of finding an answer within a short time span will go a long way towards getting MM interested and bought into the new paradigm. Such an effort can be accompanied by a number of strategies that will increase MM involvement and trust:

• Create an example- People learn to trust something new if there is a precedent. You can create a precedent by finding an MM lead user that is willing to try open innovation, has a problem that needs a fix, and has the budget to fund the solution. Socialize the results of the first campaign so that they are widely known and other managers feel more comfortable following it.
• Templatize Sponsor Experience - Use the first campaign experience to create a cookie cutter solution for others to follow. Many times managers are unwilling to participate due to the perception of high overhead and lack of well-defined procedure. We have done this many times and have had great success with this approach.
• Limit "unproductive" time - Enable access to the platform for a restricted amount of time. This can be done by physically restricting access (especially in case of retail clients) or by making the software accessible for a limited amount of time
• Subordinate pressure - Enlist the help of people who work for MM in proving the impact of social innovation on employee morale. This can be done in a positive way. For example I have seen very appreciative employee emails grateful for the fact that the company is listening to them. Such communication must be encouraged and propagated to MM. MM can also be made aware of the employee desire for active participation in company operations. The sense of frustration in this regard can be used to signal the need to change.

 R&D Gurus/Subject Matter Experts
Traditionally this class of employees bore the sole responsibility for all innovation in large organizations, especially knowledge intensive sectors like pharmaceutical and technology. Broadening the scope of innovation to include rank & file employees in the organization obviously poses a threat to this hierarchy. As a result R&D stakeholders are fearful of losing control (from the technical standpoint) and authority to direct innovation activities. They are concerned with preserving confidentiality of intellectual property and dilution of decision making responsibilities in areas that require deep domain knowledge and expertise. Senior R&D technologists are also reluctant to participate in a democratic process and spend time in "marketing" their idea to the masses.

R&D stakeholders have a legitimate concern when it comes to innovations that do require technical depth and experience. For example, I was involved in a prediction market exercise conducted at a pharmaceutical company focused around FDA approvals, efficacy of certain molecules, etc. Clearly, expressing opinions about such matters or innovating at that level requires proper training, education, and experience in pharama. Some the concerns may not have as much merit, e.g., getting a consumer focused idea evaluated from a diverse set of users in terms of its usability, value, implementation difficulties is clearly valuable.

Some of the strategies to gain trust of R&D stakeholders are:

• Make it clear that there is an alternate avenue to transform ideas to innovation in the good old way. Ideas deemed to have merit by the traditional decision makers can be fast forwarded bypassing the social vetting process.
• Highlight importance of the role and contributions of SME's within innovation communities by use of appropriate badges, assigned reputations, and visually separating SME provided content.
• Make SME approvals part of you idea graduation process as well as idea selection process to minimize the fear of loss of control

The Crowd
The only way to gain trust of "The Crowd" is to treat them the same way Southwest Airlines handles their customer complaints: provide a constructive response and close the loop for each idea posted on the community site. This does not mean that each person must be personally contacted by the team managing social innovation. It simply means that the ideators must clearly understand the decision making process that follows his/her post and the rationale behind selection or rejection of the idea.

In general I would suggest following this simple recipe: document the business process behind innovation life-cycle, execute the process as documented, and provide closure by telling them periodically (or at the end in case of a time-bound ideation campaign) about the end results. A well designed innovation platform like Spigit will decentralize and automate the task of providing individual feedback to the ideator. Augment this process by periodically publishing key metrics related to ideas (e.g. total ideas received, under implementation, innovations that began their life on the system, etc.) and participants (highly reputed members, successful innovators, implementation teams, etc.).

You can have your cake and eat it too

I am currently in the middle of reading "The Black Swan" by Nassim Nicholos Taleb. The author talks about how a few unpredictable high impact events that underlie our lives. Just when you are convinced of the unpredictable nature of life, he advises not to stop predicting! Off course it all makes sense when he elaborates further and asks to continue forming opinion about future events that will affect your personal life on a smaller scale but avoiding unnecessary dependence on large impact predictions based on economic and social theoretic models.

This got me thinking (I know, always a bad sign...) about some other things that seem contradictory at first but seem to make sense once you delve deeper. Why is this important? Every pithy saying that I have ever heard makes sense only within a certain context and we can learn far more by examining the "flip" side and understanding how seemingly opposite viewpoints can co-exist.

You must have heard about Perfection being the enemy of Good Enough. If you haven't, just ask the folks who preach product strategy. Contrast this with my personal favorite advise to my kids: Almost Done is Not Done. Clearly achieving perfection is impossible for us mortals in quite a few cases; which means you have to be pragmatic in your decision making and not wait until eternity before you disclose your work to others. At the same time, you cannot make that an excuse to be sloppy or start watching Hannah Montana when your homework is almost done.

Being proactive is considered a good trait. In fact that is a crucial factor behind the success enjoyed by Spigit. We have built the leading social innovation product that pioneered several new concepts that now define this market. A lot of that success can be attributed to our proactive efforts. I built the product by combining my past experience with my intuition about what might work. In more scientific terms, I kept making S*** up and some of it stuck. When I look back at my experience in the last three years, it strikes me that equal share of our success came from reacting quickly and effectively to contingencies. It is certainly not good idea to be reactionary, but it is great to be opportunistic (something my co-founder really excels in). In fact that's a key message of the book "The Black Swan". You cannot really predict the next Black Swan event , but you have to be ready to take advantage of one when it happens.

The following stanza in Bhagavad Gita captures it's essence (at least according to me)

कर्मण्येवाधिकारस्ते मा फलेषु कदाचन।

मा कर्मफलहेतुर्भूर्मा ते सङ्गोस्त्वऽकर्मणि॥

Here's a loose translation: You have the right to your actions, but never to its result. Don't be attached to the fruits of your labor but at the same time don't let that detachment lead you to inaction.

Does that mean you should not have goals, stop being ambitious, cease to strive for excellence? What happened to "keeping your eye on the prize"? Even if you ignore or disagree with the deeper message about "detachment", there is still something to be said about focusing on execution without getting distracted by visions of glory that might follow. If a basketball player focuses completely on making that last second shot that will win the championship, he is more likely make it than if he is already thinking about the post-win celebration. A football receiver must first concentrate on catching the ball before he sprints to the end zone (that just about completes my quota of sports analogies for this year).

I will leave you with one last thought before I let you escape this prison of co-existing contradictions. Please remember that you can have your cake and eat it too, but you cannot eat your cake and have it too!

Acknowledgment: Cartoon illustrated by Milind Ranade who happens to be a good cook in addition to being a filmmaker and a cartoonist.

Reputation on social innovation systems: how and why

I introduced the notion of user reputation within the context of social innovation platform via spigit's idea management system about three years ago. Judging by the growing list of competitors that are incorporating reputation in their products, its utility has certainly been validated beyond doubt. In this blog post I want to spend some time on the central idea behind the reputation score and why it is such a critical aspect of a social innovation environment.

What is Reputation Score?
Within a "purpose-built community", reputation score is an number representing the "quality" of user contributions measured against the stated purpose of that community.

I want to stress a few points here. First it should reflect the "quality" of contributions not the "quantity". I have talked to quite a few people and seen implementations that confuse reputation with "virtual currency" or "points". Although we have found a high correlation between active users and high reputation scores in practice, the score must not be computed based on the contribution volume.

The second point is that it should take into account how user is performing with respect to the community goal. For innovation communities this obviously relates to the quality of ideas suggested by a user. The figure below (grossly over-simplified but hopefully gets the point across) shows four factors that can potentially influence the reputation score:

1. Peer Feedback - This perhaps is the most important factor influencing reputation. Peer feedback can be positive or negative. Depending on sponsor's preference, one can include purely social interactions such as making a connection or providing a testimonial, or take into account goal-driven interaction such as voting patterns or topical conversations.
2. Achievements - User accomplishments in the context of the community goal is also an important factor. In social innovation system, it can be tied to the quality of ideas posted by a user as reflected by the stage advancement or acceptance ratio.
   
3. Predictive Ability - At Spigit, we preach the value of involving the community, not just for idea collection, but for collaborative evaluation and selection of ideas. An individual's ability to spot good ideas early in their life-cycle is very important function of the system and therefore should be considered in reputation score calculations.
4. Designated Status - This is similar to the notion of designating certain Web sites as "trusted" in certain web page ranking algorithms. Organizations always have certain individuals that have an "off-line reputation". Even if this does not automatically assign a higher score to a person, it can be factored in to control the degree of influence the person has on reputation of other users s/he interacts with.

Finally, the reputation score is really not a single number. Reputation scores can be attached to different segments of user contributions such as pre-defined categories, tags, ontological subjects, etc.

Putting Reputation Score to Use
Reputation score has three important uses. First it is a tool for bubbling up community leaders. Second, it can be leveraged to manage online behavior of community members, both positively and negatively. Third, it helps add relevance to idea ranking and reduces effect of gaming/clique behaviors.

Identify Emergent Leaders
A well designed Enterprise 2.0 platform must help in recognizing good ideas and good people. Reputation scores help identify "natural" leaders in the community as opposed to the "designated" leaders identified based on their position within the organization. Users that earn high reputation provide direct value via their knowledgeable contributions. They can also become part of community governance process. Community sponsors can rely on such users to channel user input in the right direction and spreading the word about new initiatives and ideas.

Reputation as a positive motivator
I discussed different types of motivations in another blog post. Reputation scores can be used as a powerful motivator directly and indirectly. Depending on the culture of the organization, being on the reputation leaderboard can be a source of peer recognition and bring out individual competition. We have seen this happen in communities that have a high percentage of knowledge workers. Some of Spigit's customers are also making this a basis for recognition by the leadership.

Inhibit spamming/gaming behaviors
This is one of the less known and less understood use of reputation score. A good reputation system should have the ability to detect behaviors that add little value to the community and correspond to spam-like content or deliberate attempts at gaming the system. For internal facing communities, such behaviors are rare (less than 0.5% of total user population). I have seen some external communities where the spam has drowned out legitimate content. These "bad apples" (as I fondly call them within Spigit platform) have to be detected and their reputation score and points need to be adjusted accordingly.

Incentives DO work, monetary rewards may not!

You think incentives don't work? Here's the proof to the contrary.

1. Assume that an action A is an incentive
2. "A" by definition must "incite" users to perform the right type of action (check the definition in the dictionary)
3. Incentives DO work
4. QED

Alright I will stop being facetious and come to the point before you decide to boycott my blog entirely. I am always amused when people argue for or against "incentives and rewards". Incentives, by definition, must work, monetary rewards may not. The overwhelming feedback 400+ enterprise communities on Spigit platform is that you have to actively motivate community members to contribute. In other words, community members need different types of incentives to participate frequently and meaningfully. Monetary rewards work in certain contexts and promote behaviors that support the ideation process.

The central issue is not so much if (monetary) rewards work, but what you should be doing as a community manager to motivate the crowd. There are three dimensions to this problem: the motivational stimuli, personality types, and the context for ideation. Let's start with some answers to the fundamental question of what motivates people.



What motivates people to contribute on an innovation network?

Autonomy
Some individuals have the intrinsic desire to be creative and continuously strive to improve and innovate. Although a rare commodity, such people do exist and are at the core of every successful organization. As long as you don't create impediments in their work, this group does not really need outside motivating influences. They are happy to contribute as long as their ideas are seeing the light of the day and they get the freedom to be at the heart of the implementation process.

Recognition By Leadership
Organizational leaders are ultimately responsible for creating a culture that values innovation. Recognition from the leadership in such an environment is a great motivating factor for the community members. Recognition can certainly be demonstrated by public celebration of individual accomplishments but personal communication will work even better.

Recognition By Peers
Human beings are social creatures. Most of us seek and enjoy attention from people around us at home and in the workplace. If organizations create a culture that values innovation and make creative accomplishments widely known, it would provide a great motivation to contributing citizens.

Monetary Rewards
Money may not buy happiness but certainly helps achieve it in most cases. Effectiveness of money as a motivator depends on the relative worth of the award and how it correlates with achievements. Multiple strategies are possible ranging from fixed awards for being in the top list of contributors to awards that are roughly proportional to the ultimate value of the innovation.

Competition
Competition is a great motivator for people, something that is often ignored as an incentive that boosts participation. Competition can happen at individual level as well as a group level. Highlighting top leaders in terms of their virtual wealth or reputation is a way of encouraging individual competition. Aggregating ideation and collaboration statistics at geographic location, divisions, job functions, departments, etc. can spur a group level competition.

Personality Types on Innovation Networks
The second factor in solving the incentive puzzle is different types of personalities that contribute to the innovation process. I have observed the following types on Spigit's innovation networks.

• Ideators - Users with original ideas. Note that "ideators" may not necessarily "innovators" in the sense that people with great incites or novel solutions may not carry the idea through to working innovations. That typically happens via collaboration among many personality types.
• Co-Creators - Individuals that collaborate to improve upon the original idea. Dynamic team formulation is a must for any social innovation environment. In fact an idea will not achieve enough escape velocity without a team that evangelizes it and explores feasible ways of implementing that idea.
• Mavens (term I borrowed from "The Tipping Point") - Every organization has people who are experienced or simply curious enough. These individuals have amassed considerable knowledge that can be very useful to ideators and co-creators. Leveraging maven contribution requires making them aware of ideas in their sphere of expertise and motivating them to share their knowledge with the rest of the community.
• Connectors - Making the right connections between ideas and people becomes very important within large communities facing the "long tail" problem. There are a few individuals within any social network that frequently communicate with a broad range of community members and therefore provide a natural mechanism for bringing together ideators, co-creators and mavens.
• Cheerleaders - Community members that provide positive feedback and encouragement to other users. Whether cheerleaders need to motivated is debatable. Cheerleading in excess can become spam that detracts collaborators from central topic of conversation. On the other hand, I have observed that they keep the dialog going in many cases and motivate users that may be somewhat reluctant to share their ideas and viewpoints in an open forum.

Ideation Context
The innovation context is shaped by a number of factors but two stand out the most: the ideation framing and community composition. In general we advocate creating an always-on ideation environment that offers multiple ways in which the ideation is framed:

• Continuous Open Innovation - This model can either provide a completely open forum for blue ocean thinking or provide a gentle direction by spelling out broad strategic objectives. In general this type of community should be encouraged to submit horizon 2 or horizon 3 ideas. This format is too inefficient for incremental innovation.
• Innovation Themes - Theme-based ideation can provide a focus and lightweight direction for open innovation forums. In fact we encourage Spigit clients to introduce themes that change periodically in order to create a dynamic environment for ideation.
• Ideation Campaigns - Companies often engage a segment or all of their business community members in ideation campaigns that run anywhere from a few weeks to few months timeframe. The ideation campaigns are focused events that either invite innovative solutions to a well defined problem or ideas for incremental improvements leading to new product features, process efficiencies, or cost savings.

Community composition is the second important aspect of ideation context. In pharmaceutical and tech companies, the community tends to have a much higher percentage of knowledge workers due to the nature of their business. On the other hand, retail sector companies are at the other extreme. Retail industry also has a highly transient, younger workforce that has significant seasonal variation.

So how do I choose the right incentive?
The right incentive, or I should say the right mix of incentives, depends on the particular combination of personality types and contextual parameters described earlier. I have observed that in more sophisticated domains with high percentage of knowledge workers, peer recognition and individual competitive element work very well for co-creators, mavens, and connectors. If a community runs a focused campaign/competition, members expect some type of monetary reward at completion especially in external facing communities. Smaller monetary rewards tend to work for less sophisticated domains. In this case, care has to be taken to highlight and reward quality contributors otherwise the reward scheme often leads to a lot of spam.

You can certainly perform analysis on the type of innovation network you are managing and characterize it in terms of personality type and contextual elements. This will give you a starting point for setting up a mix of incentives that should work for that combination. Ultimately there is no substitute for actively monitoring the effects of your incentive schemes and changing the mix that yields the right motivation for each type of person in your community.

World Innovation Convention 2010, Ibiza, Spain

I had fairly interesting three days participating in the World Innovation Convention in Ibiza, Spain. In the beginning I thought it was too small a gathering, but it turned out to be a blessing. I had a chance to discuss many innovation related issues at depth with attendees from Nokia, Thomson Reuters, Microsoft, and Shell among others.

The first day began with a keynote by Prof. Deschamps in which he drilled down into the concept of "innovation leadership". Some of the interesting points that came out of that were:

* Innovation leaders do not necessarily have to be innovator themselves
* Two different styles of leadership, more creative exploratory front end leaders and execution oriented backend leaders that will get your innovation faster to the market
* Enemies of successful innovation - arrogance, complacency, greed (now the last one is quite interesting!)
He touched upon the notion of top down and bottom up styles of innovation. In his view radical innovations that change business models would have to be done top-down whereas incremental innovation is suitable for bottom-up innovation. My view is a little different. I think any type of innovation, there has to be synergy between the gathering of ideas whether they come from the leadership or from the average Joe and the leadership team that ultimately makes final decisions. So a radical, business model changing idea could come from a grass root, open ended innovation exercise in a truly bottom up manner. The difference would be in the scale and the leadership level at which it will get evaluated, selected, and implemented.

I gave my ending keynote on the second day. I mainly talked about the idea of democratizing innovation, why there is a surge in companies wanting to do this, strategies for executing this bottom-up approaches, and some observations about how companies go about doing this. The message was to move away from insular innovation to a more transparent and open model.


We heard a series of presentations, mainly by employees leading innovation in their companies in some capacity. Some described efforts that started at the top (e.g. Amanda West, Chief Innovation Officer of Thomson talked about their incubation program), some were about individuals leading the charge via specific projects and initiatives (Ron Exner from Kraft Foods talked about innovations in packaging and the process of taking those innovations from R&D to production).

Open Innovation
Companies are increasingly keen on collaborating with other companies as well as individuals outside the company. The main reason for collaboration with other companies is to take advantage of their respective core competencies to quickly bring new products to the market. P&G's collaboration with Dunkin Donuts is a good example of this where P&G combined their expertize in supermarket distribution channels with the unique brand of coffee produced by Dunkin Donuts. Coke's collaboration with illi on coffee products is another.

Collaboration with customers or individual innovators is often done to support incremental product improvements, but some time also done to create new products based on innovative ideas suggested by customers or individual innovators. Customer feedback sites like Dell's IdeaStorm are a well known example of the former. Martin Ertl from Bombardier talked about co-creating railroad technologies (e.g. improved car designs) via customer competitions which also fits within the first category. P&G's "Connect + Develop" and Shell's "Game Changer" initiative illustrated the later. Micheal Ruggier from Shell gave a good example of an innovation that results via such collaboration: a device for measuring 3-phase flows created by applying body scanning technology found in medical devices.

Internal Innovation
A number of speakers (Philips, Kraft Foods, BASF, Thomson Reuters) talked about traditional innovation processes that originate and managed in a top-down manner. Most of these were in industry segments that rely on complex technologies to create value and therefore inherently rely on subject matter experts to create and deliver innovations. Most companies have a system of evaluating emerging trends and inferring key strategic innovation areas that should become the focus for their R&D efforts. Coke, for example, identifies the "Need States" and pairs that with demographic factors to get insights into unmet market needs as well as drive product marketing.

Surprisingly there was relatively little discussion on employee-driven innovation except in two cases. Hannes Erler from Swarovski gave a very good overview of their innovation process. Swarovski creates upwards of 1300 products every year and benefits tremendously from suggestions posted on their on-line idea management system. Novartis presentation mentioned "Innovation Oscars" but did not provide much detail.

Going Green
Green technology was definitely a hot topic. Prof. Markku Wilenius talked about Kondratieff cycles as measured by 10 year yield on S&P 500. The current downturn is unique in the extent to which it is affecting the entire world. The major challenge in coming out of this economic cycle would be the balancing act between increased human demand for resource consumption and lowering ecological impact of future development. It was interesting to hear technologies developed in this direction including oil spill containment, eco-friendly cars, and electronic printing technologies.

Innovation Measurements
I heard a few interesting thoughts about measuring results of innovation process. Shell's Game Changer program converts roughly 1% of submitted ideas into working products. Dr. Martin Curley mentioned that success rate of innovation is 5% although the source of this information was not clear. Bombardier presented an interesting way of characterizing the value of socializing innovations. He provided statistics on the "value" provided by users participating in their YouRail contest. He computed that value based on the money the company would have spent to have their employees engage in a similar collaborative innovation effort. The calculation was done by mapping hours spent on the competition sites, page views, and number of designs produced by the community.

Are you smarter than a sixth grader?

I recently finished coaching a team of middle-schoolers competing in the Odyssey of the Mind (OM) tournament. My team was working on building a set of balsa wood columns designed to maximize supported load given a set of weight and distribution constraints.
The unique feature of the OM competition is its emphasis on letting kids solve the chosen problem completely on their own. A coach is not allowed to make any decisions for the team, nor is he allowed to offer preferences or direct solutions to the problem. This makes coaching extremely frustrating at times (Three points in space defines a plane, so if introduce a fourth point that makes the system unstable. Can't you see it?). On the positive side, I looked at the whole process as a lab experiment about how humans (well ok a bunch of sixth graders - pretty close) collaborate to solve an open ended problem subject to time, resource, and monetary constraints.

As expected I observed plenty of things that could have been improved upon, but I also saw a few "best practices" that can be followed when grown ups like me and you are collaborating within a social network. I am posting some of my observations as a question to the readers. Unfortunately you don't win million dollars if you have all the right answers. On the bright side, if you fail you get to post a comment on this blog that says "My name is [insert your name here] and I am not smarter than a sixth grader!


Are you employing the right information aggregation mechanisms?
My team had to select five members out a total of seven to compete in the "sponteneous" section of the competition. I am not sure about the rationale behind forcing the team to select a sub-group in this manner but I am guessing they do it to test the collaboration spirit. For us it proved to be a daunting task given different combinations of personal preferences, desires, gender conflicts, etc. Ultimately the team decided on a voting model that involved each kid writing in five names for three possible variations of the sponteneous problem. After everyone cast their ballots, we simply selected the top five vote getters in each of the three possible variations of the problem. Amazingly, the team collectively seemed to have made a better choice than most of the team selections proposed by each team member individually.

Selecting the right aggregation model is crucial to the success of collaboration communities. In general the end goal of these models is creating a ranking of competing entities such as people, ideas, outcomes, best practices, etc. Spigit offers a number of aggregation mechanisms including:

• Polls - very simple mechanism for analyzing crowd preferences
• Prediction Markets - determine likelihood of future outcomes
• Idea Markets - Allows users to invest virtual money on ideas and in the process ranks ideas according to their potential
• Automated Graduations - Engages the crowd in idea filtering by aggregating information about buzz, voting, reviews, team memberships, etc.

Is your community composed of a diverse, independent-minded individuals?
Our OM team required different kinds of talents to be successful. Some team members were good at column designs, some were good at building, and some were good at writing and acting. It also turned out that the roles and contributions changed as we went along. Initially boys on the team were keen on building and the girls were engaged in writing/acting aspect of the problem. These roles and interests changed over a period of time as the kids discovered some hidden talents that they didn't know they had.

The evolution of the OM team is fairly representative of what we see in the 400+ communities that are supported on the Spigit platform. When you expose the ideation process to a large number of participants with diverse skill sets and experiences, it greatly speeds up the innovation process. If implemented correctly, individual biases tend to cancel out. Community members are quick to point out flaws based on their experience and jump in to greatly enhance the idea's potential. In some cases, we have seen bad ideas turned into very good possibilities when users suggest a different use case for the same basic concept. Great ideas are often suggested by users that happen to be interested in areas out of their "designated" expertise or users who are close to the customer.

Are you encouraging an open ended exploration of the solution/idea space?

When our team started tackeling the column design problem, I explained the physics behind column building process. I talked about truss designs, different types of forces, failure modes, etc. The kids did take some hints from that explanation, but very quickly started experimenting with different design possibilities. It wasn't quite the linear process one adopts in solving text book problems. They created 50+ column models that included different cross-sections, truss patterns, laminations, etc. The team then tested more promising ones and ultimately selected a design that was best in terms of the supported weight and stability.

This exploration strategy reminded me very much of the way bees decide on the best source of nector as described in James Surawieki's "The Wisdom of Crowds" book. The most exciting thing about social innovation is how the crowd can collectively break the mold and come up with ground breaking ideas and solutions via taking random walks through the solution space. Traditional R&D centric approach tends to perform poorly in this area. Tools like spigit offer communication efficiencies that scale very well and enable this approach. In conjuction it is important to encourage open ended thinking. Radical ideas may be adversely reviewed by the peer network, but sponsors should be careful not shutting down those ideas before the owner has a chance to prove the critiques wrong.