06:01
Faizan
Many people will tell you that it is all but impossible to move a company from focusing on one technology to another. How much harder must it be to do so when you also have to shift business models at the same time?
Undaunted, those are the kinds of challenges that today's business model innovators are taking on in switching both technologies and business models. Having a profound understanding of what needs to be done provides a core insight to guide those rapid shifts of focus.
When Tony L. White joined Perkin-Elmer (a so-so instrument maker) in 1995, he quickly shifted the company into a highly focused enterprise working on DNA sequencing. Even the corporate name was sold, along with most of the company's operations. By 1999, the company was comprised of two units with public stocks, one that made DNA sequencing machines (PE Biosystems) and the other its biggest customer (Celera Genomics), which led the race to finish decoding the human genome.
Pushed by Celera's progress, others bought more sequencing equipment. PE Biosystems' sales, profits, and value soared. Celera would sell its research to other companies to provide its on-going source of profitability.
With the human genome decoded and available for free from the U.S. government, how could Celera now earn a profit? The company quickly pivoted into taking the newly available genetic data and turning it into useful information for developing gene-based medicines. Under genetic problem-solving pioneer Craig Venter, Celera simulated how relevant genes and proteins will interact with potential drugs to predict effectiveness and side effects.
Similar to the race to decode the human genome, Celera was aided by protein-analyzing machines from Applied Biosystems. The new process operated much faster than the old technology, and offered the potential to locate many disease-causing proteins that would not be uncovered solely by looking at genes.
To gain a base of potential products to develop, the company acquired existing biotechnology firms at a time when the values of such stocks were often low and alternative funding was limited. The company aimed to improve the success odds in expensive clinical trials from 1 in 10 to as much as 1 in 3.
Undaunted, those are the kinds of challenges that today's business model innovators are taking on in switching both technologies and business models. Having a profound understanding of what needs to be done provides a core insight to guide those rapid shifts of focus.
When Tony L. White joined Perkin-Elmer (a so-so instrument maker) in 1995, he quickly shifted the company into a highly focused enterprise working on DNA sequencing. Even the corporate name was sold, along with most of the company's operations. By 1999, the company was comprised of two units with public stocks, one that made DNA sequencing machines (PE Biosystems) and the other its biggest customer (Celera Genomics), which led the race to finish decoding the human genome.
Pushed by Celera's progress, others bought more sequencing equipment. PE Biosystems' sales, profits, and value soared. Celera would sell its research to other companies to provide its on-going source of profitability.
With the human genome decoded and available for free from the U.S. government, how could Celera now earn a profit? The company quickly pivoted into taking the newly available genetic data and turning it into useful information for developing gene-based medicines. Under genetic problem-solving pioneer Craig Venter, Celera simulated how relevant genes and proteins will interact with potential drugs to predict effectiveness and side effects.
Similar to the race to decode the human genome, Celera was aided by protein-analyzing machines from Applied Biosystems. The new process operated much faster than the old technology, and offered the potential to locate many disease-causing proteins that would not be uncovered solely by looking at genes.
To gain a base of potential products to develop, the company acquired existing biotechnology firms at a time when the values of such stocks were often low and alternative funding was limited. The company aimed to improve the success odds in expensive clinical trials from 1 in 10 to as much as 1 in 3.
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