Meant to raise questions and serving as a learning opportunity for graduate students in academic program around the globe, this case study lifts the corporate curtain a bit to show how innovation through intrapreneuring really happens and decision points along the way.
The newly appointed director of Innovation Management & Strategy at Boehringer Ingelheim, a German-based multinational pharmaceutical company, is finding his way forward in his firm’s new, first-of-its-kind role, which is central to the company’s growth rejuvenation strategy. His job has a threefold mandate: to build internal networks, to establish internal structures and to leverage internal ideas. His biggest challenge, however, may be transforming the organization’s DNA. The blockbuster business model that has characterized the company for decades is no longer appropriate. Instead, the firm needs to develop healthcare products available to end users over the counter. This shift in strategy requires innovative changes in distribution, delivery and customer focus. To accomplish this goal, he needs to institutionalize innovation so that it becomes sustainable. But in doing so, he must also identify the metrics for assessing progress. The case provides an opportunity for students to step into the shoes of an innovation leader, to develop an innovation roadmap for the organization in the face of uncertainty and to understand how to engage in innovation leadership at various levels of a global enterprise.
This case has two key objectives. First, this case provides students an opportunity to grapple with the difficult decisions associated with innovation in an uncertain environment. Second, this case highlights that anyone has the ability to cultivate an entrepreneurial mindset and to lead innovation. The case divides the attributes of an innovation leader into five components: observing, questioning, experimenting, networking and associating. It shows the real-life experiences of a manager doing seemingly routine activities, who evolved into a leader who transformed the DNA of a global enterprise. The case also provides a template of the tasks, responsibilities and value-added changes as an individual moves progressively within an enterprise from an operations manager to a senior manager to an innovation leader. This case can be used either toward the beginning or toward the end of any course that addresses innovation and creative thinking in a large organization. At the beginning of a course, it illustrates the challenges of acting in the face of uncertainty in a large organization. At the end of a course, the case provides an opportunity for students to apply what they have learned about innovation, entrepreneurial thinking and innovation leadership.
The increasing diversity of employees at the workplace led to employees gathering along affinity dimensions like birds-of-a-feather to form networking groups within organizations. The next step goes beyond affinity and establishes employee resource groups (ERGs) strategically as a business resource and powerful driver for measurable business impact and strategic innovation bottom-up.
Let’s start with what it takes to found a successful ERG on a high level and then drill down to real-life examples and practical advice. What you cannot go without is a strategy that creates a business need before you drum up people, which creates a buzz!
While many companiesdemand 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.
Strategic innovation hands-on: Who hasn’t heard of successful organizations that pride their innovation culture? But the real question is what successful innovators do differently to sharpen their innovative edge over and over again – and how your organization can get there!
What every new employee resource group (ERG) requires most are people: the life-blood for ideas and activities! But how do you reach out to employees, help them understand the value of the ERG and get them involved to engage actively?
What do Generation Y (GenY) oriented Employee Resource Groups (ERG) share with the military? – More than you expect! A constant supply of active members is the life-blood for any ERG to put plans to action and prevent established activists from burning out. The U.S. Army faces a similar challenge every year: how to attract and recruit the youngest adult generation? Next-generation ERGs listen up: Let the U.S. Army work for you and learn some practical lessons!
It’s a long list to describe Generation Y with a commonly unfavorable preconception. This youngest generation at the workworkplacern after 1980, also called Millennial) is said to be: lazy, impatient, needy, entitled, taking up too much of my time, expecting work to be fun, seeking instant gratifications, hop from company to company, want promotions right away, give their opinion all the time and so on. But is it really that easy to characterize a new generation?Don’t miss my Top 10 Innovation posts and Top 10 posts for Intrapreneurs!
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…