Polyphonic HMI: Mixing Music and Math (Case Study Review)
Polyphonic HMI: Mixing Music and Math
(Case Review)
Abstract
This paper is an analysis of a case study originally conducted by the Harvard Business School in August of 2005 and is based on the challenges of introducing a new technology into a market place that for decades been based on “gut feelings and intuition”. The new technology was initially designed to assist consumers in music stores find music that met a certain criteria. Later this was changed because of a sharp decline in music sales. The new revision of the technology was designed to assist music producers, record companies, and artists in the selection of music that could be successful. Faced with a very small marketing budget the challenge of the marketing team was to decide what marketing plan would give the best results.
I. Background
Company History
The company introducing the new technology was Polyphonic HMI. Polyphonic was a subdivision of Grupo AIA whose core competency was the use of artificial intelligence coupled with natural sciences to provide complex business solutions for their customers. They were a small company of approximately 50 people but had a wide portfolio of business interests that included energy, finance and ebusiness.
In 2002 AIA decided to venture into the world of entertainment and introduce their tools into the industry. They did this by forming a new company called Polyphonic HMI. Polyphonic’s team consisted of a relatively small number of staff members and scientists but had access to the AIA’s data and scientist staff and was given an annual operating budget of around $500,000.
The product being introduced was based on the science of analyzing music by its mathematical characteristics. The new technology named Music Recommendation System and used a database compiled of millions of songs to isolate features like melody, tempo, pitch, rhythm, and cord progression. [1]
Initially the company decided to target the consumer market segment in which to
(Case Review)
Abstract
This paper is an analysis of a case study originally conducted by the Harvard Business School in August of 2005 and is based on the challenges of introducing a new technology into a market place that for decades been based on “gut feelings and intuition”. The new technology was initially designed to assist consumers in music stores find music that met a certain criteria. Later this was changed because of a sharp decline in music sales. The new revision of the technology was designed to assist music producers, record companies, and artists in the selection of music that could be successful. Faced with a very small marketing budget the challenge of the marketing team was to decide what marketing plan would give the best results.
I. Background
Company History
The company introducing the new technology was Polyphonic HMI. Polyphonic was a subdivision of Grupo AIA whose core competency was the use of artificial intelligence coupled with natural sciences to provide complex business solutions for their customers. They were a small company of approximately 50 people but had a wide portfolio of business interests that included energy, finance and ebusiness.
In 2002 AIA decided to venture into the world of entertainment and introduce their tools into the industry. They did this by forming a new company called Polyphonic HMI. Polyphonic’s team consisted of a relatively small number of staff members and scientists but had access to the AIA’s data and scientist staff and was given an annual operating budget of around $500,000.
The product being introduced was based on the science of analyzing music by its mathematical characteristics. The new technology named Music Recommendation System and used a database compiled of millions of songs to isolate features like melody, tempo, pitch, rhythm, and cord progression. [1]
Initially the company decided to target the consumer market segment in which to