Innovation and Execution. On February 28th, Boston University's MS-MBA Association and Consulting club hosted a dynamic panel of speakers during the BU Symposium event. The panel was enthusiastically moderated by Erik Molander, Innovation & Strategy Lecturer at BU.
The session was introduced with Chris Meyer's, CEO Monitor Talent, perspective on the future of management. Like bacteria, companies will succeed by adapting with the environment and self organizing. Greg Collier seconded the notion that innovation will come from diverse sources, stating Wikipedia's as an example where restriction failed and an environment of deregulation ultimately succeeded. In a contrasting view, Bobby Ray Harris noted the importance of having a small team driving decision making during a large implementation to avoid chaos and ensure timely delivery.
Could it be that different stages of the product/service delivery process require unique approaches? As we move our way down the development and installation funnel can we consider authority as moving from decentralized to centralized? What other factors are at play?
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I've thought about this issue before and concluded that the level of collaboration is directly related to the amount of money that a company is seeking. Every company (or effort) in my opinion adheres to the following two strategies in a complementary manner, meaning that more focus on one implies less focus on the other, and you can't do both at 100%:
ReplyDelete1) The strategy is to make as much money as possible
2) The strategy is to innovate as much as possible
The way a project effort distributes its strategy amongst these two principles is largely dependent upon the nature of its value proposition.
An open source software project is unique in that startup costs are minimal. Most of this is due to the fact that the distribution of information to all the team members is trivial since the "product" is electronic, making collaboration very easy. Furthermore, each participant only needs a computer and and Internet connection and can participate in the process at his/her convenience. This means that there is very little risk to the participants if the project were to fail. This low risk allows software projects to focus on innovation rather than money making.
If you consider a pharmaceutical project, like the development of a drug, you'll find the characteristics of the process are completely different. Startup costs are tremendous, and participating in the project is a substantial commitment, making it a high risk endeavor. The implications, then, are that a successful outcome must include compensating the participants for this risk, and as a result, such projects are predominantly profit driven.
Health and Crowdsourcing
ReplyDeletehttp://www.xconomy.com/seattle/2009/03/02/harnessing-the-crowd-to-make-better-drugs-mercks-stephen-friend-nails-down-5m-to-propel-biology-into-open-source-era/
To me, the idea described in this article is incredibly exciting. Many organizations have begun to exploit the talent and knowledge that exists outside of our 'physical' and 'social' spheres/networks. How many better decisions could be made with a standardized information about genes? That is the question Friend hopes to answer and he believes that quite a bit can be gained. I tend to agree based on the experience of innovation on the Internet.
Thoughts?
The article describes:
"If Merck’s Stephen Friend gets his way, about five years from now, he will have ushered in a new era in which biologists work together to make drugs that are better than any company can today inside its walls."
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"Sage is built on the premise that vast networks of genes get perturbed, or thrown off-kilter, in complex diseases like cancer, diabetes, and obesity. Scientists can’t just pick one faulty gene or protein and make a magic bullet to shut it down. But what if researchers around the world capturing genomic profiles on patients could get all of their data to talk to each other through a free, open database? A researcher in Seattle looking at how all 35,000 genes in breast cancer patients are dialed on or off at a certain stage of illness might be able to make critical comparisons by stacking results up against a deeper and broader data pool that integrates clinical, genetic, and other molecular data from peers in, say, San Francisco, New Haven, CT, or anywhere else.
Besides helping scientists aim higher, this will make medicine more transparent than ever, Friend says. Physicians from around the world could look at genetic profiles from their patients, match it up with the Sage database, and then prescribe the medicine most likely to work, Friend says. The FDA could look for insight into the proper balance between the risk and benefit of a drug. Health insurers could look at drugs for certain patients that have the greatest likelihood of success, and pay for ones that work. Drug companies could use the database to weed out treatments that are bound to fail or cause side effects for patients with certain genetic profiles, potentially saving years of wasted effort and hundreds of millions of dollars.
“We see this becoming like the Google of biological science. It will be such an informative platform, you won’t be able to make decisions without it,” Schadt says. He adds: “We want this to be like the Internet. Nobody owns it.”"