Here are my Top 10 posts for Intrapreneurs and those on their way:
1. The Rise of the Intrapreneur How to become an ‘Intrapreneur’? Why are Intrapreneurs needed? What is the difference to Entrepreneurship? – The future of innovation within large organizations lies within, if you know how to tap into it with intrapreneurship!
4. Starting an ERG as a strategic innovation engine! (part 3 of 3) While many companies demand creativity and innovation from their staff few companies seem to know how to make it work. – Is your organization among those hiring new staff all the time to innovate? The hire-to-innovate practice alone is not a sustainable strategy and backfires easily.
5. Innovation Strategy: Do you innovate or renovate? Not everything new is an innovation and some is more renovation than in innovation. Here is a framework that helps to distinguish an innovator from a renovator and works for entrepreneurs and intrapreneurs alike. It is important to understand which role to play and when; it all depends on what you need to achieve and what is critical to reach your goal!
6. How Intrapreneurs find executive sponsors Have you ever had a great idea and went to your manager for support but found they were just not interested in it? Nothing came out of it in the end, and you were disappointed? Perhaps, you just turned to the wrong sponsor for your project, a common mistake of intrapreneurs. Here are some thoughts on whom to turn for with ideas to make them happen within an organization.
8. Job description for an Executive Sponsor Executive sponsorship is an important prerequisite for the success of employee groups. The challenge is finding a great sponsor, so what should you look for? What would a job description for an executive sponsor look like? ‑ Here are some practical ideas that have worked.
9. Measure your company culture in real-time! It is difficult if not impossible to assess organizational culture directly. Instead, managers favor surveys to measuring organizational climate as a first step. However, surveys fall short in many ways and can lead to skewed results as input to managerial decision-making. Better than surveys is observing employee behavior with a meaningful metrics.
10. How to approach ‘metrics’? There is much truth in the saying that comes in many variations: “What gets measured gets managed”, “Everything that can be measured can also be managed” or even “What isn’t measured can’t be managed”. ‑ If you don’t measure progress or success, how would you know you reached the goal?
How to increase group intelligence for better decision-making – or why not to rely on a group of geniuses! New research breaks the ground to understand collaborative intelligence – but how to apply it to the workplace?
Better alone than in a team?
Think about this: What teams make the best decisions?
We all experienced it at some point: Even a group of the best and brightest people often ends up with poor decisions that do not do its individual member’s intelligence justice.
What goes wrong? How does a group of smart individuals, even geniuses, end up with poor decisions when they stick their heads together? What are they missing? Moreover, how can we avoid those obstacles to come to better decisions as a group?
Intelligence of individuals has been well studied for over a 100 years: A solid framework exists to measure the intelligence quotient (IQ). Individuals undergo a series of mental challenges under the premise that someone performing well in one task tends to perform well in most others too. Overall, the IQ is regarded as “a reliable predictor of a wide range of important life outcomes over a long span of time, including grades in school, success in many occupations, and even life expectancy,” as researchers put it.
Modern IQ tests consider an IQ close to 100 as average.
Does ‘Group Intelligence’ exist?
When we look at what it takes to make more intelligent decisions as a group than as individuals, the first question this raises is whether something like a measurable ‘group intelligence’ actually exists. If so, is it measurable and –perhaps‑ higher than the intelligence of its members?
Only recently, scientists took a deeper look at the intelligence of groups and made surprising findings. The joint team included MIT’s Tom Malone, whom we met previous in a post (“Collective Intelligence: The Genomics of Crowds”) as well as others from well-known academic institutions comprising the MIT, Carnegie Mellon, and Union College.
The researchers approached group intelligence following a similar systematic approach as the intelligence metrics for individuals. However, they linked group intelligence to performance as an endpoint, which makes their finding even more valuable for the workplace!
Outsmarting genius as a group
First, the researchers established that group intelligence in performance indeed exists and is measurable. They also found that the group’s intelligence does not add up to the sum of the intelligence of its individual members. In fact, the collective intelligence, or ‘c-factor’, shows only a weak correlation “with the average or maximum individual intelligence of group members” – this is remarkable finding! It means is that you cannot boost a group’s intelligence by composing or spiking the group with genius-level individuals!
Obviously, factors apply other than high individual IQ to increase the intelligence of the group.
The results from two studies consistently and overwhelmingly demonstrate that group intelligence outsmart individual intelligence – by far!
What it comes down to is that a high general intelligence is merely a measurable value in the lab but it does not also translate into a more successful life! An individual IQ above 135 or so can lead to quite the opposite (for reference, ‘genius’ starts at 140 on Terman’s classification). The higher IQ becomes rather a hindrance than an advantage in real life: a very high IQ tends to clutter and confuse a genius’ mind with more irrelevant options, which make it harder for them to see the most applicable one and come to a decision.
In contrast, practical intelligence relates more to social savvy or ‘street smarts’ – a cunning and practical understanding that proves advantageous in the real world more than a high general IQ!
Here is the magic sauce!
Surprisingly, the strongest correlation of group intelligence is with three factors:
The average social sensitivity of the group members, i.e. “reading the mind in the eyes” of another person. There is something to be said for bringing together emotionally intelligent people.
Equality in the distribution of conversational turn-taking meaning an equal share of time to speak. Our society and businesses seem to favor smooth-talkers and attracted to extrovert and outspoken individuals that seem to signal competence, decisiveness, and determination.
Group intelligence, however, does not increase when there is a strong vocal leader, who dominates the discussion to push everyone in his or her direction. Be careful not to leave out the brilliance of individuals who may get steamrolled by the loud and dominating: introverts, in particular, are at a disadvantage. They are easily stuck in an extrovert world.
Given that the introvert/extrovert ratio in the USA is roughly 50/50 (according to the 1998 National Representative Sample), failing to include introverts effectively is a costly mistake, as it excludes their knowledge and valuable input to the decision making process ‑ and lowers the collective intelligence of the group. Introverts, for example, favor structured communication that plays to their strengths by allowing them to research and prepare; they need more time to express their refined response.
The proportion of females in the group composition; the more women the better. This appears to account largely to a higher social sensibility that women have over their male group members in general. However, all three factors have to come together, so building female-only teams does not do the charm either.
In a nutshell
When we bring it all together, what surprises me most is how little of this solid research has penetrated the workplace. Where employees and management teams make decisions, the survival of organizations is at stake and relies on leveraging the collective intelligence of the group effectively.
A myriad of practical applications for these findings come to mind. Here are just two examples:
Women still struggle to achieve gender equality in many organizations ‑ the amount of women in management positions is a widely used metrics that refers to the female proportion of the workforce. The common approach is to achieve this by ‘swinging the stick’ to establish and enforce quotas and leave it at that – Mission accomplished?!
Wouldn’t it be more compelling to offer the ‘sweet carrot’ of increasing group intelligence in leadership teams for better business results that includes leveraging the natural advantage of females?
Again, the female quota alone does not boost the group intelligence. We also need social sensitivity and equal shares of talking time. Thus, a flanking business application would go beyond how we compose teams based on gender. It considers social sensitivity measures and some structure to how we conduct group discussions or meetings to maximize the collective intelligence by including and engaging all participants. A challenge also for how we recruit, train, and evaluate our workforce.
Group intelligence beats individual brilliance – and businesses are willing to pay for the crowd’s wisdom in the social sphere. The MIT’s ‘genetic’ model allows combining social ‘genes’ to harness the collective intelligence of crowd wisdom successfully and sustainably, for example in scientific research or business/employee resource groups.
We use collective intelligence every day
Whenever we face a big decision, we turn to our friends, our family, or our confidants. We seek information, guidance, advice, confirmation, or an alternative perspective. No matter if we make a life decision (partnership, job, picking a school, etc.), a purchasing decision (house, car, mobile phone) or a less monumental decisions (which movie to watch, which restaurant to go to), we make our decision more confidently and feeling better informed after reaching out to our personal network.
What we do is tapping into the collective intelligence, knowledge, or wisdom of a crowd that we know and trust: we are ‘crowd sourcing’ on a small scale. We do this because we instinctively know that the focused collective intelligence is higher than the intelligence of individuals.
What is collective intelligence or the ‘wisdom of the crowd’?
Wikipedia, the iconic product of global collaboration and collective knowledge, brings it to the point:
“The wisdom of the crowd is the process of taking into account the collective opinion of a group of individuals rather than a single expert to answer a question. A large group’s aggregated answers to questions involving quantity estimation, general world knowledge, and spatial reasoning has generally been found to be as good as, and often better than, the answer given by any of the individuals within the group. An intuitive and often-cited explanation for this phenomenon is that there is idiosyncratic noise associated with each individual judgment, and taking the average over a large number of responses will go some way toward canceling the effect of this noise.”
Scaling up to a ‘crowd’
When we read a movie review and rating on Netflix or customer ratings of a product on Amazon, for example, we tap into a larger and anonymous crowd. On the other end, Netflix and Amazon know how they get people like you and I to deliver them free content (reviews, ratings) that runs their business.
So, let’s take this to a level where it really gets interesting for you! How can you get a crowd to do your work? How do you build a framework in which strangers work on your business problems and deliver quality result for free.
Genetics of Collective Intelligence
MIT professor Tom Malone dissects the mechanics of collective intelligence in his groundbreaking article (MIT Sloan Review, April 2010). The MIT Center for Collective Intelligence researched to understand this matter better and identified a number of building blocks or ‘genes’ than need to come together to engage and tap into the ‘wisdom of crowds’ successfully and sustainably.
Since these ‘genomic combinations’ are not random at all, we can also combine genes to build a collective intelligence system. Depending on what it is that you want to achieve, the genes can be combined to a model that suits your specific purpose. This is ‘social genomics’ made easy, and you don’t need a biology major! 🙂
Interestingly, this social genomics can be used independently for social projects you have in mind but also in relation to Employee or Business Resource Groups (ERG/ERG). – The common link lays in the organizational design that is similar to the generic BRG/ERG business model discussed previously. Thus, collective intelligence systems need to address the same questions as a business model:
Strategy or the goal: whatneeds to be accomplished?
Staffing or the people: whodoes the work? Are specific individuals doing the work or is there collaboration within a more or less anonymous crowd?
Structure and Processes or howto organize and conduct the work? How is the product created, and how are decisions made?
Rewards or whydo they do it? What are the incentives, what is the measure for success?
Motivation is Key
It is crucial to get the motivation right, i.e. why people engage and continue to come back to contribute more to the cause or project. It comes down to finding the basic drivers for human motivation. This explains why people invest much of their time and resources to crowd sourcing.
The famous $1million Netflix Prize was a 5-year open competition for the best collaborative filtering algorithm to predict user ratings for films, based on previous ratings. The winner had to improve Netflix’s algorithm by 10%. The million-dollar reward in 2006 gives a flavor of just how valuable the crowd’s wisdom is for a company! In contrast to common belief, money is not always the driver. If it was, how do you explain the popular virtual ‘farming’ on Facebook, for example, where players pay hard cash for virtual goods?
In the more clandestine intelligence community, recruiting individual operatives plays to four motivational drivers: Money, Ideology, Conscience, and Ego (easy to remember as ‘MICE’).
The drivers for attracting collective intelligence are a bit different, as Tom Malone found out. Nonetheless, there are parallels: He calls the key motivators Money, Love, and Glory.
Everyone knows Wikipedia, arguably the best-known social collaboration and crowd-sourcing project thriving from an intellectual competition over Love and Glory, no monetary incentives involved for the authors.
How powerful Glory and Honor are we see also in areas away from the mainstream where you may not expect to find crowd-sourcing and gamification: in scientific research. The following two impactful examples reflect successful implementations for large crowds collaborating and competing to solve scientific problems:
Seth Cooper’s AIDS research challenge on the “FoldIt” online platform challenged players to find the best way of folding a specific protein. We will not dive into the science behind it and its medical significance; here are the details for those who are interested to dig deeper: MedCrunch Interview with Seth Cooper at TEDMED 2012. For our purpose, we establish that a relevant scientific problem in AIDS research, which remained unsolved within the scientific community for a decade, took the crowd 10 days to solve!
You may find it surprising that there was has no monetary incentive involved whatsoever – yet FoldIt attracted over 60,000 players(!) from around the world. The winner of the AIDS-related challenge was later recognized and honored at the 2012 TEDMED. It was not a Nobel-prize laureate from an Ivy-League institution but a laboratory assistant from Britain – who, well, enjoys folding proteins and collaborating on the puzzle with think-alike from other countries. This is the power of Love and Glory!
Another example is the ongoing “Predicting a Biological Response” on Kaggle.com, a geeky online platform for people who like developing descriptive models. My friend and colleague David Thompson of Boehringer Ingelheim (a major yet privately held bio-pharmaceutical company) designed this scientific competition to compete for the best bio-response model for a given data set of scientific relevance.
The challenge offers a $10,000 prize for the winning model and lesser amounts for the models coming in second and third. The monetary award together with a time limit of three months helps to speed up the process and keep up the competitive pressure. Last time I checked, 467 teams competed and have already submitted 4,300 entries with another month to go. The quality of the model is summarized in a single number (‘log loss’), so competitors can compare their results directly and immediately, the same quantifier determines the winner.
Note that the Kaggle participation is not driven by the monetary incentive primarily; otherwise, the number of participants should correspond directly with the amount of money offered for a particular challenge, which is not the case. Thus, participants are in it more for the challenge and fun than for the cash. (If you are a participant and disagree, please correct me if I am wrong!!) On the other hand, don’t underestimate the business value of the gamification of science either: another ongoing competition in Kaggle offers a serious $3million reward!
The bottom line
Social collaboration, crowd-sourcing, and collective intelligence all rely and depend on humans collaborating to make things happen. What holds true in the real world seems to hold true also in the virtual world: the magic formula is all in the genes…