Wu-Tang, the Long Tail and Data Culture
Lessons in data analytics that your business executives can learn from hip-hop music
I’d like to pose a question to you, dear reader. One that has been hotly debated by great thinkers and philosophers in countless barbers, bars and pubs for decades. Could the following quite possibly be the greatest rap lyric of all time?Shimmy shimmy ya shimmy yam shimmy yeh. I’ll give you a moment to ponder, as it is – undoubtedly – the most serious question you’ll be asked today.
Well perhaps not the most serious question. But should the question arise, you can weigh in on the discussion with data. At least you’ll be able to point to why Wu-Tang Clan (the group that created the above lyric) is the greatest collective of rap artists ever.
Clan in the Front
A few years ago, Matt Daniels, a digital brand strategist from New York, examined the number of unique words that 85 well-known rap artists used in their first 35,000 lyrics. Then using a bit of analytics and data visualization, he posted his results in an interactive graph. His finding? While there were a handful of individuals who used more, Wu Tang Clan, as a collective, used 5,895 unique lyrics. That’s significantly more than contemporary rappers such as Drake (3,522) and Kanye West (3,982).
Speaking of contemporary artists, popular music is getting dumber. According to more recent research, done by SeatSmart analyst Andrew Powell-Morse, you would only need a 2nd grade (Year 3) reading level to understand the vocabulary of today’s chart topping hits. This is down a full grade level over the past 10 years. Granted, reading level isn’t the only metric by which you can measure a song’s greatness. But when you compare today’s music to, say, Bob Dylan’s “All Along the Watchtower” (Year 11) or David Bowie’s “Space Oddity” (Year 13), you can start to see a clear difference in complexity not just of words, but of ideas as well.
Music and the Long Tail
So why am I sharing this? For one thing, it may give you a leg up in the argument with your kids about music being much better when you were young. An argument which has, by the way, been going on for centuries. (Heard circa 1839: “I won’t have you listening to that Franz Liszt garbage! He’s a bad influence on the youth.”).
For another thing, it’s important, from a business perspective to understand why this “dumbing down” of popular music is occurring. Though there are a number of contributing factors, one driver is the long tail effect. If you’re not familiar with the term, here’s a basic summary from Chris Anderson, the writer who coined the term:
The theory of the Long Tail is that our culture and economy is increasingly shifting away from a focus on a relatively small number of “hits” (mainstream products and markets) at the head of the demand curve and toward a huge number of niches in the tail. As the costs of production and distribution fall, especially online, there is now less need to lump products and consumers into one-size-fits-all containers. In an era without the constraints of physical shelf space and other bottlenecks of distribution, narrowly-targeted goods and services can be as economically attractive as mainstream fare
When talking about digital goods, such as music, those costs of distribution all but disappear. So as more people move toward these niches – sub-genres of music that appeal to unique and complex ideas and musical tastes – what’s left (i.e. the “hits”) take fewer risks, tackle simpler concepts, and resort to simpler language.
Cash Rules Everything Around Me
The business model laid-out in the long tail was introduced over a decade ago. And while much of what Anderson describes still holds true, the business environment in which the long tail exists has evolved significantly. Businesses have been able to achieve greater efficiencies with the rise in the digital economy, but those efficiencies have significantly reduced barriers to entry, thereby opening up their markets to greater competitive threats (exacerbated by the availability of highly scalable cloud-based services). Those efficiencies have also ramped-up consumer expectations of instant delivery.
On the customer-facing side, the long tail means a greater expectation of personalisation and customer intimacy. Being able to deliver on this expectation, though, is becoming increasingly complex as the channels through which this customer experience is delivered continue to expand from both a transactional (e.g., physical, web and mobile) and an engagement (e.g., face to face, call centre and social media) perspective.
And yet EBIDTA remains EBITDA. In other words, the fundamental measures of a company’s financial health haven’t shifted. For business executives, cash (flow) still rules everything around them. It’s just that the levers business decision-makers use to help steer their organisations, and the indicators they use to navigate their surroundings, continue to expand.
The Rise of Data Culture
With the rise of the digital economy comes data. Loads and loads of it. So not surprisingly, the key to unlocking the value of the levers in this economy is data analytics. In PWCs 2015 survey of CEOs, 84% of respondents indicated that data analytics was of high value to their organizations; this was second only to operational efficiency (at 88%) in organizational value. IDC has quantified that value, and found that UK companies taking advantage of their data have the potential to raise an additional £53B over companies that don’t.
The big challenge, however, is in understanding how to unlock the value of this data. Researchers from TDWI found that 46% of companies said they had inadequate staffing or skill level for big data analytics. A starker statistic: Gartner predicted that 85% of Fortune 500 companies wouldn’t be able to effectively exploit business analytics in 2015.
As they’re different studies, it’s difficult to make a direct comparison of the two. But they can provide some insight. It’s possible that this gap between adequate staffing needs and data exploitation can be attributed to a lack of data culture: the corporate mind-set that puts data-driven decision-making at the forefront.
Data Culture for Business Executives: It’s Bigger Than Hip Hop
If we can use and analyse data for fun questions like who’s the best musician, executives certainly should be able to do it for a better understanding of their business.
In Marketing it’s an analysis of buyer sentiment, potential for market penetration, or other key marketing decisions. In Finance it’s seeing linkages between departments more intelligent on topics such as pricing, worker productivity, inventory management, and predicting the broader or long-term value of changes in these areas.
To be fair, the kinds of data available, and therefore the kinds of questions we can ask of this data, are moving targets. That’s why Microsoft has developed the Data Culture Events series. Whether you’re an IT professional or a senior business executive, this series can help to empower your organisation to gain a competitive edge through data driven insight.
