What do Adele and big data have in common?
Adele has been all over the news recently for smashing record sales with her new album 25. Three million Americans and 800,000 Brits stormed the stores in the first week for a physical copy of her album. The latest figures state that sales are set to surpass five million copies sold in the U.S. by the end of its third week on sale.
Whilst these figures are impressive, the real success story is Adele’s battle against the ticket touts and resellers using a number of tricks (and of course big data analytics).
Firstly, fans had to pre-register just to have the opportunity to buy tickets. This might sound a bit extreme or a bit of a ‘turn off’ however 500,000 fans registered at adele.com for just the chance to purchase tickets. This provided the first wave of data.
Secondly, using big data analytic processes, Adele’s Team were able to catch more than 18,000 ‘known or likely touts’ from the process. More than 15,000 of them were based in the UK/EU and were struck off before they even had a chance to buy tickets.
However, a few tickets still slipped through the net, approximately 1.9%, which in comparison to the 20% industry standard is incredible in itself. As the ‘first wave’ of Adele tickets ended up on secondary ticketing sites including Stubhub, Viagogo, GetMeIn! and Seatwave – the Adele Team still had some tricks up their sleeves.
The Consumer Rights Act 2015 introduced earlier this year, carried new laws restricting the resale of tickets to live events in the UK. It warns secondary ticketing operators they must make information known to the buyer, which ‘as far as applicable’, should include ‘the number, letter or other distinguishing mark of the seat’. Where this instruction is being followed by resale sites it offers a gold opportunity to strike back. The purchase is cancelled by Songkick and the identified seat is made available to genuine fans. So far, over 100 tickets have been cancelled this way.
This all sounds incredible and as a fellow festivaler, this is music to my ears. But with my cynical hat on, it does raise a lot of questions around privacy and technical infallibility.
Big data analytics – just because you can do something, should you?
The term ‘Big data’ has been making headlines for a number of years and ‘Big data analytics’ has be hailed as the holy grail for organisations and marketers to deliver tailor made offerings to their customers by uncovering spending patterns, identify purchasing correlations and highlight insightful titbits, which are readily collected as we navigate away through the cyber universe. This might not sound too bad; however a number of industry leaders are raising concerns, primarily:
- Privacy breaches and personal embarrassments – Target’s pregnancy marketing campaign has made headlines recently
- Anonymity could become impossible – with so much data, correlations will happen and it will be obvious who’s who
- Data masking could be defeated to reveal personal information – cyber security is always a hot topic
- Few (if any) legal protections exist for the involved individuals
- Big data analytics are not 100% accurate – it is still an interpretation
- Unethical actions based on interpretations are likely to happen
- Discrimination as organisations have access to data that they may not be legally allowed to ask for on their own, but can be accessed legally through the IoT or analytics
- Big data will probably exist forever – when do call time on holding personal records?
- Concerns for e-discovery and adhering to relevant litigation
- Potential to make patents and copyrights irrelevant as patent office’s struggle to sift through data to verify the originality of a person’s claim.
In the case of Adele’s ticket system, there could have been a number of honest individuals who were trying to register for tickets, but were deemed ‘untrustworthy’ due to the criteria set. Moreover, the resale of the tickets could be down to purely honest reasons, where a person has bought the ticket and then can no longer go (however most ticket sellers are happy to refund or ‘buy’ the ticket back from you at face value). Without knowing the full extent of the analytics tools used, it would be presumptuous of me to assume too much and draw finite conclusions.
Big data analytics hold great promise for inspiring significant innovations, improving upon all sectors of organisations, and bringing true benefit to individuals. However, organisations that choose to open this Pandora’s box must ensure that the associated privacy and information security impacts are fully mapped out before they actually put analytics into use. This is particularly important when you consider the use of big data analytics by Government bodies.
HMRC loves to Connect big data
In 2010, HMRC brought in the Connect software platform which trawls through billions of items of data from over 30 sources in its hunt for underpaid tax – and it's about to have access to even more information as data is shared with 60 other countries.
HMRC has a crack team of over 150 data analysts that utilise modelling techniques to identify a particular type of taxpayer or business sector where anomalies are common. Once identified, a dedicated ‘taskforce’ is established to focus on this hot spot. These taskforces draw on the expertise of multiple teams from across HMRC including special investigations, local compliance and criminal investigation units for targeting specific sectors and locations where there is a high risk of tax evasion. The taskforces uses the Connect software to help uncover business areas where tax evasion is common place as well as to target specific businesses.
In September 2016, Connect's powers will extend when HMRC is given access to files held by banks and other financial firms based in British overseas territories, such as the Channel Islands. From 2017 Connect goes truly global with access to data in a further 60 countries. The scale of this big data analytics program sounds unbelievable and the potential is astounding. The numbers of investigations initiated by Connect are growing - £3bn extra in tax has been collected so far.
But many have their doubts. Not only is there a possibility that some of the data could be erroneous or incomplete – triggering unwelcome tax investigations or worse, possible prosecutions – but there are also fears about security. Sources currently include public sector records – such as the Land Registry or DVLA, as well as a growing number of private businesses and trade associations.
Connect routinely looks at credit card transactions, car data and activities on Internet marketplaces like Ebay or Gumtree to identify ‘suspiciously high levels of activity’, indicating income that needs to be declared.In some cases, Connect is used to trawl social media profiles to identify evidence of spending, travel and other undeclared assets. Although still rare, the success of Connect trials indicates that social media will play an increasingly important part in the evidence gathering process.
But where will HMRC draw the digital line when looking for tax evaders and what big data should be off limits when looking at innocent individuals personal circumstances?
I am sure this debate will rage for years, however I refer back to the title of this section - just because you can do something, should you?
For further information, please contact Jason Mitchell or your local MHA MacIntyre Hudson tax advisor.
Alternatively, join the conversation at our MHA MacIntyre Hudson Tech Sector LinkedIn Group.