With EY's confirmation that growth in big data deals is running at an annual rate close to 30% coming hot on the heels of Microsoft’s $26 billion purchase of LinkedIn, the summer has seen intensification of the global dash-for-data. Underlining this increased emphasis on data-driven deals is the fact that data has firmly established itself as the primary commodity to be mined in the 21st Century. Data driven transactions are likely to define dealmaking for a generation – this in turn pose questions for business leaders and the legal and accounting community alike.
Every tap on a smart phone, every turn of a road in a connected car: it is all logged, analysed and wherever possible monetised. The new ways in which data is captured and considered, and the extent to which we have accepted this as part of our everyday lives, would have been unthinkable ten years ago. Even five years ago. But the collective willingness of the world’s population to grant access to their data is revolutionising society and the corporations and institutions that serve it.
Harnessing the power of this unending stream of data is now the top priority for many businesses, be they global conglomerates or rapidly growing start-ups. But deciding to acquire data is in many ways the straightforward part – negotiating and papering a deal which protects that value and then unlocking the inherent value in a potential treasure trove of information is much more difficult to achieve.
Deriving meaningful insight from largely unstructured data sets is incredibly challenging. It is particularly so for organisations that have only recently become attuned to the idea that the information they hold about their customers is probably more valuable than the goods and services they currently sell to them.
Some industries have been quicker to respond to the opportunity data presents than others. Take the advertising and retail sectors, both of which have developed increasingly sophisticated targeting and profiling techniques over many years; we are now seeing these ideas being translated to other sectors.
The growth of cloud computing means that in the financial services market a startup can build retail-focussed algorithmic trading platforms in ways that simply would not have been economically viable just a few years ago.
While data-driven deals are undoubtedly attractive and potentially transformative for many organisations, the pitfalls and potential obstacles standing in the way of long-term success are considerable.
Effectively pricing the true value of data is hard enough for those immersed in the sector – for ‘data newbies’ it is likely to be much tougher.
The discounted cash flow models that are the mainstay of the ‘old economy’ are much less effective in a digital world where true value is determined by the level of insight that one can derive from any given data pool.
And when it comes to papering the deal how do you address the question of value and its impact on price.
There is also the risk that seemingly valuable data can turn out to be utterly worthless. Given that algorithms are ultimately programmed by fallible humans, who is legally to blame in such a situation? It is difficult enough to establish legal protections against tangible assets which turn out to be worthless or "damaged goods".
Indemnity or warranty protections for useless algorithms raise new questions with the additional challenge that its resulting loss will be regarded by lawyers as speculative and difficult or impossible to recover.
The issue of ownership, which is less binary than one might initially think, also has to be rigorously considered. Who actually owns the data being acquired is often far from certain, as are the appropriate consents to process that data in accordance with applicable law. There is even a genuine legal question as to whether data can truly be owned in the same way as other assets.
As an increasing number of data-driven deals are announced in the coming years, access to data, and the robustness of the controls that regulate this data, will be heavily scrutinised. For example, who bears liability if in the course of negotiations or shortly after a deal it turns out there has been a cyber-attack and that proprietary data is put up for sale on the dark web?
The dash for data will also place an increased burden on the respective regulatory and competition authorities reviewing and evaluating such deals. The European Authorities have made great strides coming to terms with the evolving landscape but questions remain including whether competition law will be applied to data and analytics in the same way as it has been applied to physical goods and services.
Given the pro-digital economy stance taken by the European Commission it is possible that in time, the existing competition law framework could be deployed to data and analytics in the same way as it has to software and bundling.
Finally, there is the issue of individual consent. Just because a firm acquires data, does it automatically mean that it has the appropriate consent to analyse the information in any manner it wants? The answer is no: as individuals we typically grant consent to our data for specific reasons and to specific parties, which might ultimately render an acquisition redundant or irrelevant.
But while the opportunities are clear, significant threats exist. And in the digital dash-for-data everything is up for grabs.