A Gartner analyst has recommended that IT leaders begin designing their algorithmic business models – both to capitalize on their potential for business differentiation and to mitigate the possible risks involved.
“The significant development and growth of smart machines is a major factor in the way algorithms have emerged from the shadows, and become more easily accessible to every organization,” Steve Prentice, VP and Gartner fellow, told attendees at the Gartner Enterprise Architecture Summit 2016.
“We can already see their impact in today’s world, but there is much work ahead to harness the opportunities and manage the challenges of algorithmic business.”
According to Prentice, while digital business is already transforming organizations, Gartner “confidently expects” algorithmic businesses to create even greater levels of disruption.
“Open algorithm marketplaces will rapidly create and incentivize an entire ecosystem of algorithm developers in the same way that app stores and mobile devices have changed software development,” he added.
Commenting on the importance of algorithms in today’s world, Rambus Fellow Dr. David G. Stork noted that Stephen Wolfram, pioneer computer scientist and physicist and developer of the computer language Mathematica, released an ambitious tome titled ‘A New Kind of Science’ in 2002.
“One of the premises addressed by the book was that science’s pre-occupation with the language of mathematics was, in a sense, a result of the historical ‘accident’ that mathematics arose before computers and the science of computing,” said Stork. “If the ancient Greeks and the pioneer physicists, chemists, and other scientists such as Isaac Newton and Antoine Lavoisier and innumerable others had had computers, the language they would have used to describe the natural world might have derived instead from computer science. That language is expressed in algorithms.”
As Stork explains, an algorithm is simply the abstract set of rules or procedures applied to solving some problem.
“Algorithms can address problems as simple as sorting or alphabetizing a list of names, or serving the most appropriate web page in a web search or even (in online dating sites) finding an appropriate mate. The same algorithm can be expressed in different computer languages,” he continued. “Both mathematics and algorithmics are universally expressive, in that they can describe any physical or other phenomenon, but some phenomena are more naturally described in one language than in another.”
For example, says Stork, it is much simpler to describe the shape of a cloud with an algorithm than by some extraordinarily complex mathematical equation. Conversely, it is more natural to describe the position of a swinging pendulum with mathematics than by a traditional algorithm.
Interested in learning more about algorithms? You can check out “Algorithms” by Robert Sedgewick and Kevin Wayne here, “Introduction to Algorithms” by Thomas H. Cormen and Charles E. Leiserson here and the “The Algorithm Design Manual” here.