In 2006 Nike and Apple showed that new combinations of existing technique can result in useful and lucrative products when they launched the Nike+iPod sportskit. Basically it is an iPod connected to a pair of jogging shoes and it gives the user information like distance travelled and calories burned via the earphones and the display.
This intersection has now turned into an arena of competition as Samsung and Adidas present the result of their cooperation - the miCoach. It is more or less the same concept but the device used is a mobile phone instead of a music player. It includes a heart-rate monitor, a shoe sensor and a Webworkout journal that keeps track of workouts.
Read more about technical details and a comparison between the products in this Washington Post article.
/Kristian Ribberström
Optimization Modeling and the Modern Supply Chain (Another example of linking seemingly disparate atrtributes to achieve a collective outcome).
Overview
There have been numerous studies and reports on the various methods (i.e. Monte Carlo) used in determining supply chain optimization.
I would have to say that my preferred method has been to use the heuristic approach under an agent-based model in which the unique operating attributes of each stakeholder is understood separately before a collective outcome is identified and achieved.
It is this latter “twist” if you can call it that, that has enabled the optimization process to extend beyond the limitations of executional boundaries referred to in a May 2007 article that appeared in Supply Chain Digest titled Supply Chain Optimization versus Simulation. Specifically the author’s assertion that “Mathematical” optimality is not used, and is not required or likely even feasible. Optimization almost always takes at least some minutes to process (and in some cases hours), and hence isn’t generally usable in an execution environment.”
With partial funding from the Government of Canada’s Scientific Research and Experimental Development (SR&ED) Program, I developed a theory that I refer to as “strand commonality” in which disparate and seemingly unrelated data streams can be linked through the use of advanced algorithms to produce a “positive or beneficial” collective outcome.
It is really quite fascinating in that production models have consistently produced the correct results in terms of real-world applicability approximately 98.2% of the time.
It gets really interesting when you introduce multiple tier factors that include intangible elements such as the value of technician certification versus x number of years of practical experience.
The key starting point is to recognize that the term supply chain is a misnomer in that it implies a sequential order of events (in the spirit of your question, a non-deterministic set of algorithms which aligns with the equation-based modeling used by most software vendors).
In reality however we operate in a world in which synchronization between diverse (and now global) stakeholders have to exchange and quantify disparate data on a real-time basis, and therefore the term supply practice would be a more appropriate description.
Once again, when you recognize this elemental difference you will then take the first steps towards building an effective and meaningful optimization model.
And as indicated in a column I wrote titled How Not to Abandon your e-Procurement Initiative (http://www.summitconnects.com/Articles_Columns/PDF_Documents/w09_6_07.pdf), this methodology extends to the collaborative imperative of identifying and understanding the diverse requirements of different stakeholders. Or what Simone Weil referred to as "unified totality," which is the recognition that each need to a degree enables, enriches and participates with all other needs.
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This, of course has stirred some discussion; some argue that it should be forbidden while others mean that this is the same inevitable development that we see in so many other sports.
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