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Polyphonic HMI: Mixing Music and Math Essay

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 loud 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. L. Background Company History The company introducing the new technology was Polyphonic HIM. Polyphonic was a subdivision of Group AI whose core competency was the use of artificial intelligence coupled with natural sciences to provide complex business solutions for their customers.

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They were a small company of approximately 50 people but had a wide portfolio of business interests that included energy, finance and business. In 2002 AI 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 HIM. Polyphonic team consisted of a relatively small number of staff members and scientists but had access to the La’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 lions of songs to isolate features like melody, tempo, pitch, rhythm, and cord progression. Initially the company decided to target the consumer market segment in which to introduce the technology. The concept was centered on a customer going into a big box music store not knowing which music to select or what genre they may like.

By entering some basic information the new technology could assist them in the selection of particular songs that met their particular set of criteria. Thus enhancing the consumer’s experience by getting them the music they wanted to hear and increasing sales for the retailers. By the time the product was ready to release there had been a sharp decline in music sales in the big box stores. (Figure 1) It was believed that this was due to several factors: first, increasing pressure from online competition and the ability to download music through the internet.

Second, the belief of the consumers that online music should be free. (Case Study Review) By redskin digital format. The New Product Faced with this Polyphonic and AI revisited the design intent of the technology and created a new program called Hit Song Science (HAS). The way HAS worked was it coked at the same information as the previous version but instead of looking for music with certain criteria entered by an individual consumer it looked at the similarities of songs that had made the “Top 40” hit list and the melody characteristics of each.

What the Polyphonic team found was that there were clusters each hit fell into and Polyphonic scientists felt that their system could accurately predict which songs would be hits and which ones would not, based on the analysis of HAS. After continued analysis and refinements in the program Polyphonic found that they could predict whether or not a song would be a hit with n 80% success rate. The calculations were made based on the weighted score found by HAS. If the songs weighted score was 7. Or greater there was a good probability that the song would be a hit. According to CEO Mike McCrea there were still limitations to HAS but if those limitations were taken into account the information provided could be useful in the selection off hit song. At the time the Polyphonic was ready go to market with HAS they had invested approximately $600,000 dollars on the development of Hit Song Science and found that they were running very low n capital investments.

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Because of this the management team had approximately $150,000 for marketing the product. II. Analysis In this section the case study will be broken down into segments that have been perceived as important and worth a closer review. 1) The first important piece of the case study deals with Group AI. Group AI had established itself as having a core competency of utilizing artificial intelligence (AY) and the natural sciences to solve complex business problems. AI saw potential use for a new technology in the music industry so they formed Polyphonic HIM.

When they formed Polyphonic AI brought in staff that were familiar with the music industry and the technology the initial program was designed for would assist consumers entering a music store in the selection of music that met certain criteria leading to greater customer satisfaction and higher sales. Looking at the available information Polyphonic should have seen that the market trend for sales from big box stores over previous decade had been in a sharp decline (Figure 1) and considered targeting a different market segment from the beginning.

Polyphonic either didn’t see the trend or Hough that it wouldn’t affect the release of the new technology. Because of the late discovery the product release had to be delayed, new applications for the technology searched out, and costly modifications made. By the time the new application was ready for release it had cost AI and Polyphonic $600,000 and reduced the marketing budget to almost nothing. 2) The next part of the case study I find interesting is the amount of time dedicated to explaining all of the aspects of the record industry and the amount of money spent on producing a single song.

What I didn’t see was an analysis of which level of adopter would most likely be interested in purchasing the new technology. Had they looked at this they may have seen that they may have wanted to focus the marketing campaign on the Innovators and Early Adopters and not a certain group segment such as artists or producers. 3) The next point I found had a budget of $150,000 to try to reach a target market. Having a usable product Polyphonic should have looked at other possible business applications for the technology and possible continued to market the initial version.

This could have given them a wider customer base and increased sales. However the problem with introducing a new technology into the market is they cannot accurately be analyzed. They may not have initially known where other opportunities were available but without making the information open to the public they would never know. 4) Another important piece I found with the case study is that when it came to the marketing plan, there was very little information on which type of strategies the marketing team actually used.

Although it did list several good questions it left the actual choices unanswered. Some of these questions would be what was the initial each head for the product? Why wasn’t the whole product marketed? Were the vertical and horizontal market segments considered? The entire marketing agenda was very vague. 5) Synthesis For over a decade the music industry had been seeing a decline in record sales but even with this decline in 2003 the market for music was valued at over $32 billion throughout the world.

The largest of these markets was in the US with approximately 39% of the sales . Figure 21st Century Music Retail Transformation and Global Music Sales Revenue With declining sales and the cost of producing an album ranging from a few housing dollars for an unknown artist to several million dollars for a well-known artist, coupled with only a 1 in 10 chance of success music producers and artist and repertoire (A&R) executives had the daunting task of selecting songs that had the potential of bringing in revenue to the company.

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At this point the music industry had used focus groups and surveys as research methods but these could run up to $10,000 dollars per song and were not very accurate. For the most part the industry had been making critical decisions based simply on Gut feelings and intuition. Polyphonic major decision was to choose which segment they would first introduce HAS. The choices being the producers, the A&R executives, the artists, or any group that perceivable could profit from the technology the most.

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Polyphonic HMI: Mixing Music and Math Essay
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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.

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2017-12-16 13:09:09
Polyphonic HMI: Mixing Music and Math Essay
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