big data and umg (art and science of management) dropbox

GZXR8 19:48 12/04/2015 MSIN101P: Art and Science of Management MSIN105P: Critical Analytical Thinking

UCL Management Science

Applications of big data and analytics for Universal Music Group

UCL Management Science and Innovation

Sebastian Sear


$15,000,000,000 $4,890,000,000

14,800,000 Figures taken from IFPI (International Federation of the Phonographic Industry) Music Report 20141 The Music Industry When people refer to the music industry, they are referring to the individuals and companies creating and/or selling music in order to make money. Music has a unique ability to unite people; with so many different genres, there seems to be a style of music for every taste. As a result, the industry exists on an enormous global scale and generates billions of dollars (US$) each year2. Resultant of the conception of internet-based music services and streaming services, such as iTunes, Soundcloud and Spotify, the industry has seen tremendous change3 since the start of the 21st Century – the main consequence being the increase of digital unit sales and the significant decline of analogue4 unit sales5. Combine this with the issue of illegal downloading (where consumers are able to download ‘free’ music causing labels and therefore artists to miss out on royalties) record labels are generating significantly less revenue from physical sales than at the start of the century; this is greatly reducing revenue and reducing the associated profit margins with producing a song:

1 http://www.billboard.com/biz/articles/news/global/5937645/ifpi-music-report-2014-global-recorded-

music-revenues-fall-4 2 http://www.billboard.com/biz/articles/news/global/5937645/ifpi-music-report-2014-global-recorded-

music-revenues-fall-4 3 Refer to section 1.3 of the appendices

4 Refer to section 1.1 of the appendices

5 http://money.cnn.com/2013/04/25/technology/itunes-music-decline/

Global Music Industry revenue in 2013

Music Industry revenue in the US in 2013

Number of units sold of the best-selling single of 2013


Source: Spotify6 Current state of Universal Music Group (UMG) UMG is currently the largest of the ‘big three’ major record labels7 turning over a revenue of €4.4 billion8 in 2010 and owning over 30 subsidiary labels including iconic labels such as: Decca, Def Jam Recordings and Island Records9. UMG is also itself a subsidiary company of Vivendi SA, a French multi-national mass media company based in Paris and operating globally10. UMG carries out many key activities, however the two most influential activities, the ones which can lead to multi-million dollar profits or losses and the ones which stand to change the most are: signing artists and developing artists. The key decisions associated with these activities are: who to sign, how to develop an artist and when to drop an artist. In response to the challenge of reduced revenue and diminishing profit margins UMG need to find a way to:

1. reduce their costs 2. increase the value of and revenue generated by their assets

Big data and analytics technology have the capacity to achieve these goals and to revamp the way in which UMG identifies opportunities. Refer to the Business Model Canvas found in section 2 of the appendices throughout this section. Impact of Big Data on the Music Industry and UMG There is currently a lot of speculation regarding the fate of the music industry and how it is going to change11. Despite the uncertainty, overall public perception of the music industry and its state is resoundingly positive12. Although the digital revolution so far has predominantly only brought about challenges for UMG, the astronomical amount of data being generated by internet-based services and digital technology (big data) is offering an opportunity for UMG.

600,000,000,000

Source: Datafloq, a big data platform13

6 http://www.spotifyartists.com/spotify-explained/


8 , http://www.vivendi.com/wp-content/uploads/2011/11/umg-investor-presentation-november-

2011-final.pdf 9 http://www.universalmusic.com/company

10 http://www.vivendi.com/vivendi-en/



13 https://datafloq.com/read/big-data-enabled-spotify-change-music-industry/391

Number of bytes of data generated daily by Spotify users


If UMG is able to analyse, interpret and make use of more of the data available to them, relating to music consumption and music consumers, then UMG will be able to gain insight into how better to generate revenue in the industry. “The velocity, volume, and variety of data associated with music, listeners, and music influencers present a huge opportunity to extract meaningful insights that can deepen user customer engagement”14 The ‘future of the music industry is a two-way interaction’15 where consumers will be able to determine their level of engagement with music; consumers now have the option to ‘like’, ‘share’ and ‘follow’ artists, producers and songs. Making use of this new interaction doesn’t rely on accessing the data – this is not the issue, the trickier task is making sense of it all and making data-driven decisions which are in the best interests of UMG and its representative artists. Data is considered to be structured (easily organised and analysed) or unstructured (requires organisation before it can be analysed, interpreted and be of significant use). I have highlighted whether or not datasets are structured or unstructured. The data: Currently has access to: UMG currently has access to a large amount of data and is experimenting with a big data analytics tool called ‘Artist Portal’16. The tool is being used to make better informed decisions relating to marketing, promotion and investment. Currently UMG are making decisions based on small sets of data, primarily data relating to17:

1. online purchases (number of legal downloads from online databases) 2. physical purchases (number of CDs and analogue units sold) 3. ranking of singles and albums in the UK Top 40 chart, US Billboard chart

18(and other charts of equal prowess) 4. social-media buzz (related posts/ tweets on social media sites) 5. streaming19 (number of streams of a track or album) 6. airplay (time spent on the radio)

Needs access to: Although this is definitely a move in the right direction, to make more effective use of the data available and to further increase the revenue generated by label activity, UMG needs access to more datasets and increased access to specific information from the sets which they currently access:

14

Wilson Cheng, Co-founder of weeSPIN, (a social networking app connecting music consumers and allowing them to share their listening habits); http://venturebeat.com/2014/12/18/how-big-data-can-change-the-music-industry/ 15

Alexander Ljung, Co-founder of SoundCloud (an online music sharing service); http://motherboard.vice.com/read/the-future-of-the-music-industry-according-to-soundcloud 16

http://www.theaustralian.com.au/business/wall-street-journal/music-business-plays-to-big-datas-beat/story-fnay3ubk-1227156614023 17

http://www.theaustralian.com.au/business/wall-street-journal/music-business-plays-to-big-datas-beat/story-fnay3ubk-1227156614023 18

https://jeremy1.wordpress.com/2015/02/22/big-data-and-the-music-industry/ 19

Although data generated through streaming is in general unstructured, in this context it can be viewed as structured.


1. social media (Facebook, Twitter, Instagram) - likes, shares, followers, hash tags, messenger data (how much are

artists/songs being discussed) 2. streaming services (Spotify, Deezer)

- artist subscriptions, playlists, popularity of genres, location data (the areas, countries and regions where streaming of artists is taking place)

3. media sharing sites (YouTube, Vimeo, SoundCloud) - video views, likes, subscriptions, playlists, shares

4. music applications (Shazam, SoundHound) - songs being identified and frequency, location data

5. web page views (Wikipedia) - the frequency of visits to pages about artists, songs, albums, location

data There is clearly a focus on getting increased access to and better understanding unstructured data, rather than structured data, before UMG can progress further. Refer to section 3.2 of the appendices for discussion of useful data which isn’t easily accessible. Applications of Big Data and Analytics for UMG But what does understanding big data mean for UMG? As I identified earlier, two of UMG’s key activities are: signing and developing artists and it is these two activities which have the greatest potential to benefit from big data. Signing artists: Historically A&R departments and their talent scouts were responsible for selecting which artists to sign. Recognising talent was regarded as an art and decisions were based on human judgement and often came down to ‘gut instinct’: “Everything used to be based on a feeling...now we have the facts”20 Labels such as UMG are just starting to take in account big data in their decision-making processes; I suggest UMG take this further. Identifying artists with the potential to succeed is challenging in itself and the dynamic competition between labels means that time is of the essence when it comes to signing new artists. By using analytics to monitor data from: social media, streaming services, media sharing sites, music applications and web pages in real time, A&R departments will be able to make instant data-driven decisions, perhaps still based on gut instinct but also supported by vast amounts of data. UMG executives will also be able to see the logic behind their employees signing certain artists and be able to evaluate their performance as talent scouts.

20

Kimmo Valtanen, Marketing Director of Univeral Music Finland, http://www.theaustralian.com.au/business/wall-street-journal/music-business-plays-to-big-datas-beat/story-fnay3ubk-1227156614023


To be able to understand and give structure to unstructured data, UMG needs to make use of innovative music analytics software. I have identified two technology companies which UMG should consider accessing to make optimal use of big data:

1.) Music Xray21 - Refer to section 4.1 of the appendices 2.) Musicmetric22 – Refer to section 4.2 of the appendices

The implication of adopting this technology is that UMG can make better informed, quicker decisions regarding which artists to sign. This reduces the complexity and time involved sifting through a large selection of new artists which all appear to show promise. This means an increased likelihood of signing artists with great potential and with the right development, increased revenue from their successful hits.

Developing artists: Once an artist is signed, it is of the utmost importance that their career is taken in the correct path. UMG needs to know where to direct the majority of their marketing efforts, which gender and age groups to target, where they should advertise, where to tour, what image each artist should be conveying and most importantly, what type of music is in demand. The current strategy for artist development is based on data-driven decisions23 however, by increasing the scope and scale of data being taken into account when making these decisions, UMG can increase the impact and profitability of their artists. Adopting big data will not change the process of artist development, it will however allow UMG artist managers to base and support their decisions on an array of insight rather than being limited to the several datasets which they currently use. I have also identified two analytics tools which would allow UMG to gain better insight into artist performance, perception and demand (development):

1.) The Echo Nest24 – Refer to section 4.3 of the appendices

2.) Musicmetric – Refer to section 4.4 of the appendices The disposition effect in terms of psychology refers to ‘the tendency for investors to hold on to losing stocks for too long and sell winning stocks too soon’25. If an artist is no longer generating significant profit for UMG and analytics tools suggest their popularity is diminishing, UMG executives will have to make the decision as to whether investing more money into an artist is going to be beneficial or whether it makes more sense to drop them. By using analytics UMG can start to predict the future success of artists and lessen the disposition effect by better identifying which artists are unlikely to carry on trending or be in demand in the future.

21

https://www.musicxray.com/ 22

http://www.musicmetric.com/your-needs/dashboard/ 23

Mostly involving the structured data I identified above which UMG currently has access to. 24

http://the.echonest.com/ 25

http://www.investopedia.com/university/behavioral_finance/behavioral11.asp


Conclusion Recommendations: Vivendi has an estimated market cap of approximately €32.66 billion26 ($34.63 billion27). Apple Inc. has an estimated market cap of over $740.33 billion28. Spotify isn’t publically traded but has a value of approximately $5.7 billion29. The most promising music analytics start-ups have already been acquired by competing industry giant: Apple, and Spotify; UMG have already missed an opportunity to purchase some of the small, promising music analytics start-ups. However looking at the bigger picture, Vivendi and UMG still have the opportunity to take action. Vivendi/UMG: I recommend that UMG acquire Spotify. It is practical for Vivendi to make a bid for Spotify due to its valuation and size in comparison to Spotify. Successfully doing so would result in UMG gaining full access to Spotify’s masses of data30, streaming service and analytics tools (The Echo Nest analytical software, algorithms and API). The increased accuracy in identification of emerging talent and enhanced insight into how to develop artists successfully will allow UMG to cut their costs by:

- reducing the number of artists they sign which don’t go on to be successful - reducing the amount they invest in stagnating/failing artists - encouraging the earlier dropping of artists generating, and predicted to carry

on generating, losses - reducing the number of unsuccessful attempts to break into new markets

Revenue will increase due to: - increased number of successful artists, songs and albums (leading to

increased sales) - increased number of successful ventures into new countries and markets - increased effectiveness of targeted promoting and advertising

This combination of reduced costs and increased revenue will result in increased profit for UMG. The issue of course with this is that it is completely up to Spotify and CEO, Daniel Ek as to whether they accept the bid and consent to the acquisition. Alternatively UMG could attempt to acquire a smaller start-up company, such as Music Xray, however if UMG really wants to make an impact and dominate the market, I recommend pursuing the acquisition of Spotify. Refer to section 5.1 of the appendices for potential issues with analytics adoption.

In summary, although there are significant costs associated with acquiring Spotify and integrating analytics into the daily activities of UMG, UMG should view this as a long-term investment with massive potential for the near future.

26

http://www.bloomberg.com/quote/VIV:FP 27

http://www.xe.com/currencyconverter/convert/?Amount=32660000000&From=EUR&To=USD 28

http://www.bloomberg.com/quote/AAPL:US 29

http://www.billboard.com/articles/6458093/spotify-5-billion-valuation 30

https://datafloq.com/read/big-data-enabled-spotify-change-music-industry/391

Word count (excluding titles, references and headings): 2013 (2000±10%)


Appendices

1. The Music Industry 1.1 Analogue refers to physical units; when we discuss the music industry this means CDs, vinyl records, tapes and anything else which exists in the physical world and stores music. Digital refers to anything online or in the digital world – downloads from the iTunes store and other units of music which only exist in the digital world. 1.2 A record label is a brand or trademark affiliated with the marketing of music products and services and is often also responsible for publishing, distribution, manufacture and enforcement of copyright legislation. Record labels are split into three main categories:

1. Major – one of the three industry giants. 2. Subsidiary/Sub-label – a smaller label owned by a major label; the label

will often have the freedom to choose who they sign and how to spend money, but the revenue generated still belongs to the major label, their budget is determined by the major label and the major label gets final say in all decisions.

3. Independent (Indie) – labels which are not considered to be under the control of or associated with one of the ‘big three’

Up until recently, four major record labels: Universal Music Group (UMG), Sony BMG, EMI Group and Warner Music Group (collectively referred to as the ‘big four’), were responsible for the vast majority of music production. In 2013 EMI merged with Virgin, a subsidiary label of UMG, to become Virgin EMI Records, therefore now EMI is considered to be a part of UMG. We now refer to the ‘big three’, which is the grouping of: UMG, Sony and Warner. Why choose UMG? The music industry is an area I am passionate about and is the industry I intend to go into after completing my degree. Having grown up with the ‘digital revolution’ I was already aware of some of the significant changes that have taken place within the music industry and with the relatively recent conception of social media, it seemed logical to look at the potential application of big data and analytics for the music industry. In order to take a look at the general “chatter” surrounding the music industry I generated a network of articles/blogs using the search query: “music industry”:


The initial chaos was rather daunting so I reiterated my search and changed my query to: "music industry" AND "record label" OR "big four record labels" AND Sony AND "Universal Music Group" AND Warner AND Virgin OR "Virgin EMI". I then filtered out all the clusters relating to less than 1% of the total article count (46 clusters) but still the leftover network was still too complex to easily interpret the trending topics regarding the music industry. I therefore selected only the top 10 clusters and filtered the others out:


To further reduce the complexity, reduce the scale and focus in on only the bigger trending topics, I filtered out any articles/blogs with a news rank greater than 3:

This simpler network made it easier for me to see the span of the top 10 clusters and I chose to look at UMG as it seemed to be mentioned more frequently than its main two competitors: Warner and Sony. 1.3 I isolated one of the clusters – ‘Crash of the music industry’ from the network above:


This was the fourth biggest cluster generated by my reiterated query and is evidence of the uncertain fate and massive changes the music industry is and has been experiencing. Some of the headlines that stand out are:

- ‘Think you know the music industry? Think again’ - ‘Kesha Opens Up About ‘Unrealistic’ And ‘Dangerous’ Music Industry...’ - ‘The Music Industry in 1998: The Titanic Right Before It Hit the Iceberg’ - ‘Music Industry sees delayed benefits’

2. Current state of Universal Music Group (UMG) 2.1 The digital revolution refers to the ‘advancement of technology from analog electronic and mechanical devices to the digital technology available today. The era started to during the 1980s and is ongoing...the Digital Revolution is sometimes also called the Third Industrial Revolution’31. Specifically regarding the music industry, the phrase refers to the mass shift from analogue units (CD, Vinyll records, tapes etc.) to digital-based music, such as iTunes and Spotify, which is resulting in the significant decrease in sales of singles and albums from record labels. Business Model Canvas (BMC) UMG is currently responsible for a vast array of products including: singles, albums, merchandise, music videos, compositions/songs, concerts and digital media (the content and downloadable content found on the UMG website and the websites of UMG’s sub-labels and the artists UMG represent). UMG has many value propositions, the key ones being: variety, quality and trend. The products offered by UMG vary greatly in genre and style, music released is of the industry standard and the material being released tends be trending – this doesn’t mean all material is mainstream and will be found in the charts, it simply means it has an audience with a large enough following to justify continued output of music of the associated style. Products and value propositions are delivered to four key customer segments: private consumers, streaming services, broadcasters and licensed venues. Private consumers purchase physical units of music or download music through the internet for personal use and enjoyment but not for commercial gain. Streaming services pay to allow subscribers to access music belonging to UMG; these services pay royalties to UMG (who then pays their artists) based on how frequently UMG property is streamed. TV and Radio broadcasting companies also pay royalties to UMG for use of their material on the TV and radio. Venues, such as clubs, bars and pubs, are able to purchase a PPL (Phonographic Performance Ltd.) license, allowing them to play copyrighted music to the public - UMG takes a cut of the licensing fee. The profit made by UMG is their revenue minus their costs. UMG generates revenue via its revenue streams which include: singles, albums, merchandise, intellectual material (compositions and lyrics), advertising and product endorsement, concerts, royalties and licensing fees. UMG’s costs relate to: recording, manufacturing, royalties, promotion and distribution. Taking into account the respective costs associated with a song, the profit margin of a song or album can be calculated by deducting the associated costs from the revenue generated by song/album sales.

31

http://www.techopedia.com/definition/23371/digital-revolution


3. Impact of Big Data on the Music Industry and UMG 3.1 I returned to my very first search query: “music industry” and removed all filters. I then limited my network to 10,000 articles within the last 5 years and aggregated the network by cluster and size by the article count in each cluster. I then coloured my clusters by sentiment and set green to be ‘positive’, grey to be ‘neutral’ and ‘red’ to be negative. The network identified that 54% of articles were positive, 37% were neutral and only 9% were negative. This network demonstrates the generally positive public perception of the music industry, despite massive change and uncertainty:

The link between big data and the music industry: As part of my initial research, I generated an articles/blogs network using the query: “music industry” AND “big data”. Although I set the time span to the last 10 years, Quid only found articles dating back to 2013. As you can see, three prominent clusters are evident:


These clusters are: ‘Cloud Computing’, ‘Zero Marginal Cost Phenomena’ and ‘Big Data Analysis and New Business Models’. I zoomed in and isolated the small, hidden cluster ‘Universal Music Uk’: I reviewed these articles and from here I went on to extensively research the potential applications of big data for the UMG and the music industry. I also plotted a timeline to see how the cross-over between big data and the music industry was being covered in the news. I was able to identify a key change: March 2015, where big data and the music industry were discussed together frequently. The change was that Sony BMG, one of the ‘big three’ and one of UMG’s two key competitors, signed a big deal with Alibaba relating to how Sony distributes their music via the internet.


3.2 Not easily accessible: A lot of the data of interest to the music industry is accessible. Some datasets are open and can be accessed by anyone, such as chart data from the UK Top 40, and some require purchasing the rights to. There are however, some useful datasets which would prove very tricky for UMG to fully and extensively access:

1. illegal downloads (number of illegal downloads, location data) The people running these illegal download and sharing services and their users want to remain anonymous in order to avoid prosecution. There is also the issue of volume. Due to the great number of illegal download services, it would prove very difficult to monitor/access them all, and if easily identifiable in the first place they would be shut down. 4. Applications of Big Data and Analytics for UMG How I identified promising music analytics companies: I started by performing a company search on Quid using the query: music OR “music industry” AND “big data” AND analytic AND software AND algorithm. This generated a diverse network of 2395 companies: After zooming in and exploring the clusters, I identified the two clusters relating to the music industry, which I was interested in: ‘playlists / radio stations / music service / djs’ (media platforms and services) and ‘predictive analytics / predictive /


recommender / hadoop’ (predictive analytics). I then isolated these two clusters and explored the remaining 195 companies: From here I identified three companies connecting the clusters which I named: media platforms and services and predictive analytics:


Unfortunately the companies aren’t specifically related to the music industry and music services, but rather related to the telecoms, TV, connected devices and intelligent: systems markets: I then focused in even further to only look at the predictive analytics cluster:


I explored the remaining 31 companies and identified Semetric Limited and its child company: Musicmetric. After further research I came to the conclusion that acquiring Semetric would have been very beneficial to UMG, however due to Apple’s recent acquisition of the company it would prove very difficult to gain access to Musicmetric’s ‘dashboard’ data analytics tools.

I looked at some of the ‘neighbor’ companies surrounding Semetric Ltd. in the sub-clusters - nothing of great significance specifically relating to the music industry and predictive analytics stood out. Separate from Quid, I then went on to research what other companies are out there that perform similar functions to Semetric’s Musicmetric. I drafted a shortlist of companies that I thought were interesting:

1.) weeSpin32 - allows people to listen to music together in real-time. 2.) Tunecore33 - is a distribution service that focuses on getting artists heard. 3.) Music Xray34 - connects artists, fans and industry professionals to the

music they are looking for. 4.) Next Big Sound35 - a data analytics company which has focused on

public social data relating to artists in the music industry. 5.) Musicmetric36 - an analytics tool which analyses a large variety of big,

unstructured datasets and offers insights into the music industry. 6.) The Echo Nest37 - a big data analytics company which has created a

platform/API used by over 400 music applications.

32

http://www.weespin.com/ 33

http://www.tunecore.com/index/what_is_tunecore 34

https://www.musicxray.com/ 35

https://www.nextbigsound.com/about#wrap 36


http://the.echonest.com/


I then evaluated which companies were most established, had the greatest potential and offered predictive analytics specifically related to signing and developing artists and allowed for easy integration into UMG’s current signing and development processes. I concluded that Music Xray, Musicmetric and The Echo Nest were key companies for UMG to look at. 4.1 Music Xray38 – is an analytics tool based on a two-way interaction. It takes material of a certain style or genre and analyses its “DNA” - the composition and combination of sound waves (sine, triangle, square etc.). Artists looking to get signed upload their content to the site, Music Xray then runs their analytics software and analyse the make-up of the audio; Music Xray then connects industry professionals and fans with new, up-and-coming music that suits their interests and tastes. 4.2 Musicmetric39 – is an analytics tool which looks at location data, the data generated by social media, streaming services, media sharing sites, as well as the physical and digital sales of music, in order to provide demographics relating to songs and artists. One can see how many fans an artist has at a given time, where an artist/song is most popular, social media activity, torrent activity and file-sharing and mentions of material in the news in real-time. The most important two functions of the tool is that one can view an artists’ ‘fan rank’, which gives a general overview of how their popularity is changing and secondly, the ability to add databases to the service. Musicmetric has its own extensive database but offers the ability to add third party data, which means the possibilities for the expansion and development of insights is great. Semetric (Musicmetric’s parent company) was recently purchased by Apple Inc. for an estimated $50 million40; this suggests a merger between UMG and Apple. Vivendi SA could consider merging with Apple, thus accessing Musicmetric and its parent company: Semetric. Semetric specialise in big data analytics for most media related industries, including: music, television, film, eBook and gaming41. Vivendi operates on a global scale and one of UMG’s major fellow subsidiary companies is a TV and film company: Canal+ Group, which operates 15 smaller TV and film companies. Semetric’s big data analytics technology could then be applied to the Canal+ Group and used in a similar way to Musicmetric to generate diagnostics and insights regarding the success of TV programs and film channels. This issue with this is that Apple is a much larger corporation, with a much larger valuation than Vivendi so if a merger was to go through, Vivendi would undoubtedly lose a significant amount of control over their assets and would have to share the majority of their profits. In reality a merger is very unlikely; the more likely case is that Apple would make a bid to acquire UMG. In any case, in my opinion regarding a merger, I believe that the disadvantages would greatly outweigh the advantages. It would not be advisable for Vivendi to let Apple acquire UMG either, seeing as UMG is one of Vivendi’s most valuable assets. 38

https://www.Music Xray.com/ 39


http://www.valuewalk.com/2015/01/apple-inc-buys-semetric-music-analytics-startup/ 41

http://www.semetric.com/


4.3 The Echo Nest42 – is arguably the market leader in music analytics technology. Its software and API (Application Programming Interface) are used within 432 music applications. The Echo Nest also has an in-depth, analytical understanding of over 3 million artists and 36 million songs43. The Echo Nest was recently acquired by Spotify44, hence if UMG intend to use it analytics software they should consider an acquisition or a merger with Spotify. 4.4 Musicmetric – the demographics provided by Musicmetric and the identification of trending artists isn’t only useful from the perspective of signing artists. Using Musicmetric UMG could also better identify which countries and areas to focus their promotional efforts, for what reasons artists are coming up in the news, which types of music they are releasing are in demand, the scale of demand and where there is demand for certain artists and genres of music. 5. Conclusion 5.1 Potential issues: Employee reaction of adoption of analytics tools: Artist selection will always involve some degree of human influence as an algorithm can’t predict human nature and reaction with 100% accuracy. Music is a subjective topic; whether a song succeeds or not will always be subject to uncertainty and be somewhat dependent on current socio-economic factors. Analytics will be used as an aid rather than as a replacement for skilled talent scouts, hence its adoption shouldn’t be perceived negatively as a threat, but rather positively as a tool for making UMG employees’ decisions easier and more informed. Cost of analytics adoption: The cost of acquiring Spotify is likely to lie in the region of $6-8.5 billion45, as Daniel Ek is unlikely to sell Spotify for its current valuation of 5.7 billion given its potential and dominance in the streaming market. The music analytics industry is valued at approximately 1.8 billion pounds a year46. Based purely on these figures, if UMG are able to integrate analytics into their operations and become market leaders in music analytics, they may start seeing a return on their investment in 4-6 years, depending on how saturated the market becomes. Image sources Front cover:

- http://defdavyne.com/2014/09/26/contract/ - http://www.dailymail.co.uk/news/article-2307239/Universal-Music-security-guard-I-fired-blowing-whistle-

rock-stars-drug-taking.html - http://sleekmoney.com/vivendi-receives-neutral-rating-from-nomura-vivef/155983/

42



http://techcrunch.com/2014/03/06/spotify-acquires-the-echo-nest/ 45

http://www.billboard.com/articles/6458093/spotify-5-billion-valuation 46

http://www.theguardian.com/technology/2014/apr/09/music-analytics-is-helping-the-music-industry-see-into-the-future

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