Technology acquisitions, never rare occurrences, still attract a great deal of attention, speculation and column inches. Maybe this is driven by the huge sums of money involved or the sometimes unclear motives behind them, but more often than not it is quite simply because we are trying to understand exactly what products or solutions the acquired company is going to develop.
This was the case recently when two technology giants made acquisitions that got industry tongues wagging. Salesforce’s mega acquisition of Tableau Software was heralded (in some quarters) as a game-changing case of the number-one CRM vendor buying the number-one business intelligence (BI) and analytics vendor – exciting stuff. Coming hot-on-the-heels of Google’s acquisition of Looker, these are particularly interesting developments for those of us interested in how data is being used globally and how both Google and Salesforce’s (among others’) strong pursuit of the BI and analytics market is going to impact the way data is used in future.
I am as excited as anyone to find out what the outputs of the combined forces of these tech companies will come up with, but I am also concerned that if we do not do better as an industry at getting some of the basics right, we will risk squandering these opportunities – something we can simply not afford to do.
Data – a huge opportunity
Few people would dispute that data is a huge opportunity right now. The way in which it is collected, stored and (more importantly) used can have a huge impact on how an organisation operates. The issue we face now is not that business leaders need to be persuaded of the value of data, but that expertise in how they should go about using it is in such dangerously short supply. This means that they are highly unlikely to be able to effectively use this most valuable asset, even if they have appetite to do so.
In the rush to benefit from the data revolution, I have noticed a strong and understandable trend for companies to look for tools to help them. This trend is, in turn, met by tech companies trying to meet this need by building tools designed to help them achieve their objective of unlocking the value of their data. In a similar vein, tech giants are attempting to consolidate solutions along the full data pipeline in order to offer a completely outsourced data model. The idea being that business intelligence software can put data analytics into the hands of front-line staff rather than trained IT and data science professionals. All of which, on paper, makes real sense.
As a result, when companies, like Google and Salesforce, buy such tools and the companies that built them, they are rewarded with increased valuations and the kind of money-cannot-buy buzz that gets industry-watchers and investors really excited. What could be the problem with that?
Where are the experts?
There is, of course, nothing wrong with the way in which the industry is responding to a real need to boost organisational data analytics. Buying Tableau is all part of Salesforce’s plan to join Google, Amazon and Microsoft in offering cloud-based data graphics tools. This competition is not a bad thing. Far from it. Healthy competition has been the lifeblood of so much progress in the tech industry for many years and I truly believe that this could be similarly positive. There is, however, a critical success factor missing in all this. People.
As many of us know, we are currently facing a huge and growing data science skills gap. One recent report has suggested there are about 300,000 AI professionals worldwide, but millions of roles available. The competitive salaries and benefits packages that data scientists can command (the average salary of a data scientist in London is over £50,000 according to Glassdoor) and massive increase in the requirement for AI talent indicates that supply is not even coming close to meeting demand.
This is the problem we are facing and it is not a problem that can be solved by the creation of more tools and tech solutions. The fundamental issue of what organisations can do with their data is still going to be a challenge as long as we lack skilled, well-trained people to operate these tools. Do those working in this field really understand the scientific process behind the BI tools they will be using? Are they able to fully grasp the significance of the outputs or the risks and biases associated with the models? When it comes to leveraging the power of data, organisations cannot be expected to get the right answers from their data if they are not asking the right questions. This requires real skill. Skills that are currently lacking from many organisations and are not going to be filled any time soon.
My concern is that a lot of industry trends in this field are really just window dressing designed to give the impression that progress is being made and something is being done when the reality is far more complex and great deal more concerning.
A positive first step
These technology-led solutions and products are often, however, the first step in an organisations’ journey towards being more data-driven. Developments like these do increase desire and commitment within organisations to invest more in talent and to develop long-term data strategies. This can only be a good thing.
Ultimately, we need to be doing more to address the ever widening skills gap, on a global level, as there is simply no short-cut to having data science professionals embedded in your organisation. Companies are already suffering from a serious shortage of these crucial skills and with data-driven innovations accelerating so rapidly, we could soon find ourselves with an almost insurmountable gap, completely lacking in the skilled people we need to power future growth. Alongside this deep expertise, we also need better educated managers and business executives to ensure data is analysed and acted upon swiftly and impactfully.