Archive for the ‘Wisdom of crowd’ Category

Linkedin Skill Endorsements Gone Awry? Initial Review & Recommendations!

Wednesday, October 10th, 2012

As many of the active LinkedIn users are aware, LinkedIn’s latest feature – social endorsement of “Skills & Expertise” – is in later stage of its beta release and growing like rapid fire in the past few weeks. What’s interesting is LinkedIn brought social validation by your network to this feature they started testing since Feb of 2012 – a social proof for your skills and expertise.

After studying this feature for a few days, I decided to do few social experiments & surveys and my past few weeks of results have been nothing short of eye openers – with respect to user behaviors. While my data set is only limited to my own network, I am quite certain these results would be very akin to majority of LinkedIn users.

While most people endorse as a social convention – “you scratch my back and I scratch your back” – very much similar to how most of us used LinkedIn Recommendations, unlike LinkedIn “Recommendations”, skill endorsements can be removed any time you want after you endorse.

Similar to tweenage kids, I am already seeing immature behavior – where people endorse skills and delete the endorsements if you don’t endorse them back or if you don’t endorse them as many as they endorsed you.

Also, from a sheer value standpoint, an individual’s recommendation for you will always be more valuable than that individual’s endorsement, even though in the long run, # of credible endorsements speak a lot about you than recommendations.

Here are some of my thoughts and conclusions around this social experiment -

  • Reciprocity seems like an unspoken rule – This seems to be an overwhelming expectation – with my own direct experience as well as with people I spoke with regarding endorsements. Times when people solicit you to endorse them in return for their endorsements and other times they straight up harras you. This is very much akin to some of the spammers in the world of Twitter – You follow me and I will follow you.
  • When it comes to Endorsements, huge egos are at play – I have purposely ignored to see what would happen if I didn’t “endorse back” someone who deserves some endorsements. To my surprise, their original endorsements have been removed after few days! This is a big shocker for me.
  • Mutual friends & partiality in endorsements don’t get along – When you rate two peers inconsistently on skills they both pride themselves (like endorse Product manager to only one even though both of them are equally good and skilled at Product management), you start a pissing contest – most of the time without any straight confrontation.
  • That’s not a skill I am proud off – re-endorse me! – Thanks to LinkedIn’s auto recommendation of skills based on your profile, most of the people I spoke to were unhappy about some of the skills that were automatically chosen for them. I heard one person contemplating to contact all the people who endorsed him on a particular skill to re-endorse for some other more relevant skill. Another wished he could change the skill text without losing the endorsements for that skill.
So, how can LinkedIn make these endorsements more credible and experience less controversial/painful? While it is too soon to conclude where the crowd sourced endorsements could go for LinkedIn, here are some recommendations -
  • Endorsements are not same as Follow! – People should not be endorsing others and then remove them the next day. If they are not sure about endorsing someone, they should not endorse to begin with.
  • If you insist on leaving “undo” feature, then at least insist on getting rational feedback on why someone wants to undo their endorsement just a few days after they endorsed that person.
  • For Credibility, lets focus on Quality than Quantity- LinkedIn can make these endorsements more credibility by offering rich data around individual endorsements and individual motives behind endorsements. Such as  -
    • Displaying # of endorsements given vs # of endorsements got will give you some understanding of the value of endorsements.
    • Publish like an Endorsement Gradient that is calculated based on – # of endorsements given by those who did not get an endorsement vs # of endorsements given by those who got an endorsement.
    • Maybe an infographic about who (as in relationship – professional or personal) actually endorsed to learn why they endorsed – if all your endorsements are coming from your family members or close friends who never worked with you, then we know how valuable your endorsements are. 
    • Percentile the endorsements by skill or overall – When you crowd source people to endorse, some kind of percentile for individual skill endorsements or total endorsements – based on industry, education qualification, # of years of experience, etc – would be very useful.
  • Educate your users that endorsements are not social convention! – This is very important. When someone on the street says hello to you, you say hello back to them – that is social convention. Endorsements should not be social convention. Period! Educate your users with proper “coach marks” and alerts.
As per LinkedIn users, to create more credibility for your endorsements, stick to following principles -
  • Tell your endorsors to only endorse if they feel strongly about it. You do the same.
  • Tell your endorsors that you will not be reciprocating them back. Reiterate that endorsements should not fit social convention. If they try to obligate you, be polite and say that you don’t know enough about them on that particular skill to endorse.

As per endorsing me, take a wild guess!

@Vsistla

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Posted in Anthropology, Attention, Crowd Sourcing, Customers, Endorsements, Follow, Gamification, Influencer, Innovation, Linkedin, Motivators, Professional Connections, Psychology, Relationships, Social Capital, social networks, sociology, Twitter, User Behavior Data, Wisdom of crowd | No Comments »

How do Rewards & Costs Butt Heads With Altruism and Who Wins?

Friday, August 3rd, 2012

This post is not just for Social Entreprises but also for people who value relationships and those who want to put a value for relationships.

In the book Sway, authors talk about two parts of our brain that respond to altruism & material rewards and how both these parts can never work in sync and the part of the brain that gets excited about material rewards (Nucleus Accumbens)will trump the altruistic part (Posterior Superior Temporal Sulcus) IF these two forces ever butt each other.

English: Reward system Français : Structures c...

English: Reward system Français : Structures cérébrales constituant le système de récompense. (Photo credit: Wikipedia)

This is a very important concept to grapple with for most of the social entrepreneurs and social entreprises. In fact every social entreprise should clearly understand these forces before they instrument their product features, incentives & rewards.

Here is the most interesting thing – these conclusions are also consistent with non social entreprises and other conventional “do gooder” type; I have conducted my own experiments to validate that many of the following -

For example,

  • Sometimes, no reward is better than some reward – In general not putting a price or reward for someone’s good actions and intensions is better than putting some price/reward in place. This has impacted my own ability to contribute at the best of my abilities in some of the personal projects I was involved in the past few years. This becomes a big issue when the reward you are given is much lesser than what your time and attention is worth. Of course, we tend to rationalize (that darn Nucleus Accumbens) as soon as someone puts a price on your deeds. It is very important for individuals to clearly understand the inherent motivations behind “do gooders”. Those inherent motivations dictate their reactions to the rewards.
  • When you reward, don’t expect – In general, when you reward someone for their good deeds especially when they are doing that without any contingencies or expectations, you should not have any expectations from them especially after you reward them. Most of the time, as soon as someone rewards for your actions, they also start to set expectations on your ability to do future good deeds. This becomes a viscous cycle.
  • Rewards and incentives are a tricky beast - Most people focus on “how much” they can reward for someone’s good deeds and to a lesser extent on “what”; I feel “how” the reward is defined, delivered, acknowledged and so forth is as important as how much and what the reward is. Inherently each of us are motivated by many aspects in life when we help others. You cannot define all of us with a few broad strokes. More about this in the next bullet.
  • Good deeds/intensions come in all kinds of instruments- Some take “time” and other’s write a check and others donate what they don’t need. Some do physical labor, and some help on strategy and others be there for you in need. Some make the very important introduction, while others “like” or “retweet” your message. While not all of these are same, one cannot ignore the value of each of these actions. So, when your social entreprise is only accounting for a “check” then you are leaving lot of opportunity untapped.
  • People who give in all kinds of instruments are as myriad as what motivates them to do – Just the way people contribute for “social good” in various instruments, people’s individual expectations (if they have any) also vary. So, taking into account all those aspects in your models is very critical. For example, someone who is motivated by being the “charitable” leader board responds to “gamification” compared to someone else who want to be anonymous.   
  • First give before you expect – I spend umpteen hours with many early stage startups to coach, share, learn and collaborate – without anything on paper. I strongly believe we give before we expect or take. That is how we create “value” for people around us. The more value we create for people around us, the more valuable we become. I see many Social Entreprises experimenting with interesting “charity” models – where you give something for charity for getting something back in return. Some times what you get in return for your charitable contribution is its just bragging rights and some times its lot more tangible. Different people respond to these models differently. So, it is critical social entreprises take into account all those nuances into account before they structure their charitable models.

This blog post is motivated by – the book Sway by Brafman brothers, Robyn Scott from OneLeap, Ali Ansari Professor & ex-Chairman of Engineers Without Borders, interactions with various angel investors from The Unreasonable Institute, and my own experimentations with various early stage startups and entrepreneurs.

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Posted in Altruism, Charity, Crowd, Crowd Sourcing, Good Society, Incentives, Influencer, Innovation, Motivations, Motivators, Neocortex, Personas, Psychology, Reputation, Rewards, Social Capital, Social Entreprise, Wisdom of crowd | 3 Comments »

Wisdom of Crowds & Stock Market – Motivator Analysis!

Tuesday, June 14th, 2011
The Wisdom of Crowds

Image via Wikipedia

When Space Shuttle Challenger burst into flames quarter century back, it took 21 minutes for the stock market to dump shares of all the suppliers to the shuttle and Morton Thiokol stock took the biggest hit by the end of the day. All the investors – amateur and pros have dumped Morton Thiokol stock within that trading day but it took months for the investigators to conclude the same. Crowd knew it before the experts could figure out – way ahead.

Enter Wisdom of Crowds!

Wisdom of Crowd is one of the most counter intuitive concepts out there. I revisited this problem when Leigh Drogen (@LDrogen) pitched me his super awesome startup - Estimize – to disrupt sell side research for publicly traded firms.

Just because Morton Thiokol stock took a hit doesn’t mean that all the individuals who avoided to buy its shares are smart or well informed. Chances are many of the traders might have “followed the leader” or in some cases the trend. After all that is the wisdom of the crowd!

We start to question the wisdom of crowd when we pay close attention to each of the individuals in a crowd. The argument goes like – if majority of participants in a sample are not smart enough to make the right decision, even with few smart well informed individuals the average outcome of the crowd decision can be skewed by the “not so smart” lot. This argument assumes that average members of the group do not get influenced by their surrounding in making their decisions such as why is everyone selling this stock, why is there is a trading halt on the stock, etc. Such arguments are based on the individual merits and do not take into account individual decision making acumen regardless of their domain knowledge or Intellectual Quotient (IQ).

For example, members in a crowd making decisions based on their friends, other experts, trend/sentiment, could actually tilt the average towards the right decision. So, one could generate more accurate results if members of the sample know what the previous members have chosen and their reasoning behind their decision.
What’s more important?  The individual member’s IQ/domain knowledge or their individual motivations?

I would argue that their motivations are as important as individual’s domain expertise/IQ in a crowd assessment.

Of course the above argument assumes that individuals in a group always make rational decisions and all the true individual motivations are apparent to the rest of the group members. That is a very big assumption but in a very controlled experiment or system, one could turn such assumptions (at least some) into reality.

For example, if we take a sample of traders in stock market – their individual motivations to estimate future stock price is based on following -

(note am only talking about motivations)

  • Do they already have a position in that particular stock?
  • Is that long or short position?
  • If neither, what is their incentive to make an accurate assessment?
  • What information do they have and how they can benefit from that information versus other members in the group, and so forth.

* If motivations are aligned, group’s decisions have lowest variance. That doesn’t necessarily mean that it would lead to most accurate decisions.

Each of the group members have their own individual motivations. Aligning the group’s motivations would get you results that are much closer – and with right motivations, average estimate could be accurate or close to accuracy. For example, traders in Morton Thiokol stock all had the similar motivations – to make money and avoid loss. Traders who own the stock want to reduce their losses and the traders who don’t own the stock want to put their money to work somewhere else. Of course some of the traders got into the stock assuming it is a bargain and hoped to make a quick buck the very next day.

* If individual motivations are apparent to the rest of the group members, rest of the group might make rational decisions.

If individual motivations are apparent to other members of the group, individuals can make the most rational decision – but depending on the individual motivations, someone of the members might not make their true drivers apparent with the rest of the group. Such behavior is the pulse of Stock market – since a trader needs another trader to sell off the losing stock and sellers need to conceal their true motivators to buyers of the stock.

For example if traders who are already in Morton Thiokol stock are trying to reduce their losses by selling, other traders who might be aware of such motivations decide not be on the other side of such trade.

Individual motivations dictate their individual actions which will ultimately impact the crowd sentiment about the assessment.

What are the types of motivations within the members of a group?

At a broad level there are group motivations as well as individual/more dispersed motivations.

Individual Motivators -

Within individual motivations, there are at least five types -

  • Vanity (intangible benefits) -

    An individual could be motivated by vanity of being accurate and correct in crowd experiments. Such intangible motivations could be provided by the system in which such experiments are conducted such as leaderboards, badges, points and so forth. Even if the system doesn’t provide intangible benefits, building a consistent and successful pedigree would also result in future intangible perks and that could become a motivator for some of the individuals.

  • Tangible Benefits -

    Group experiments and crowd sourcing when tied with tangible benefits could become major motivators for individuals. For example, in case of Jellybean Jar, if the instructor promises to give the entire Jellybean jar to the individual or individuals with most accurate estimate, the quality of estimates will be much higher. Of course, it would help to know the demographic of the individuals to assess the impact of such motivators – for example – the older you are, the less you are interested in winning a Jellybean jar; you might not care for it if you are diabetic or don’t have children; etc – in short – knowing what such tangible motivators mean to the individuals within the group might help rest of the group members in making informed decisions.

  • Could careless -

    As I was saying in the previous point, motivators should mean sometime to the members of the group to have act on them. For example if the motivators are not attractive enough, the members in the group might not respond to them. So it is as important to know what motivates individuals but also the impact of motivators on individuals to understand the crowd and its decisions.

  • Pain versus Profit -

    Not all motivators are equal. For example, if a system offers rewards for most accurate estimates the impact of such motivators is far different than when a system punishes the individuals for inaccurate estimates. Also, individuals respond differently in systems that reward accuracy and punishes inaccuracy versus systems that only reward accuracy and doesn’t punish inaccuracies.

  • Good denizen -

    While hard to find, there are always members in a group who are just passionate to make rational decisions without any external motivators.

In case of stock market and traders, knowing about individual motivators and the impact of those motivators on individuals will help the system assess the crowd estimates and hence present the data in a most informed manner to rest of the users of the system.

Group Motivators -

Now if we move on to group motivations, if groups of individuals are pitted against other groups, and the group’s actions are tied to tangible benefits, “co-operative” and “collaborative” thinking will produce accurate assessments from the group.

Ideally any system or platform that taps into wisdom of crowd should make sure that individual motivators should not counter group motivators lest all motivators will cancel out the group actions.

PS: I limited this blog post to motivators within wisdom of crowd. I will try to address other aspects of wisdom of crowd in future blogs.

Opinions expressed are my own ….

@Vsistla

Ps 2: I have not read book Wisdom of Crowds by James Surowiecki – so, this blog is not a reflection of that book.

Ps 3: I have not done any scientific analysis or research in any of the thoughts – open to debate and suggestions on these thoughts.

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Posted in Analytics, Attention, Business Intelligence, Competition, Crowd, Crowd Sourcing, Information Age, Innovation, Motivations, Stockmarket, Trading, Twitter, Wisdom of crowd | No Comments »