A lot of people continue to be
mystified by Big Data, what it is, and why it's suddenly become such a 'hot
topic' for businesses across all sectors globally? When clients ask about
hiring in this area, it's clear there is a lack of clarity on the talent
profile, the location of skills and how they can identify and attract the best
90% of digital data is unstructure
evident is that demand for skills in this area is rapidly on the rise. To
understand the origins of this pressure it would be useful to start with some
context, a quick and basic explanation of Big Data and why it presents both an
urgent challenge and huge opportunity for organisations.
At a very
simple level, Big Data can be defined as a vast collection of data that is
uncategorised and not easily searchable. In the last few years there has been
what is commonly referred to as a 'data explosion': a sudden rise in available
data caused by the rapid increase in data sources from media and communication
outlets, social media and crucially machines, with the advent of IoT and smart
devices. In effect, this has created vast lakes of information, much of which
is generated in real-time, meaning it's not just the volume of data, but also
the speed at which the data is generated, variety of sources and the unverified
accuracy that create the unique characteristics of Big Data.
additional complexity that 90% of digital data is unstructured and it's easy to
understand why this makes an unprecedented challenge for organisations. In
essence they are now sitting on vast quantities of rich, potentially powerful,
yet invisible information.
The role of the data science/ big data
function is to create value from Big Data through the application of highly
advanced technologies and scientific methodologies.
Telematics insurance ……monitoring real-time behaviour allows the
insurer to assess risk and create bespoke pricing and products accordingly.
So what is the value to organisations?
Big Data Analytics is
changing our world: in healthcare it's helping us predict disease patterns and
find cures, in science it's helping us make new discoveries and in security
it's helping the police predict crime patterns and analyse criminal
In business it's allowing for faster, better and more
qualified decision making: you'll hear talk in the corporates about
transformation to a more 'information centric' culture and the more analytics
driven businesses in technology and telecommunications going one step further,
with the Chief Data Officer (CDO) or Head of Data Analytics being positioned
as the top strategic role within the organisation. An interesting use of Big
Data analytics is to create new products and services for customers. A good
example of this is telematics insurance (also known as black box insurance),
whether that be a sensory device in a car, the home or your pet, monitoring
real-time behaviour allows the insurer to assess risk and create bespoke
pricing and products accordingly.
The opportunity Big Data presents to
deepen the customer relationship through providing personalised advice and
products to customers is significant. Showing value to customers through an
enhanced customer experience is the key to reversing the 'switch to save'
behaviour we have seen across all sectors in the last few years.
Enhanced customer experience is the key to reversing the 'switch
to save' behaviour.
Cost reduction is also key. Insight driven
approaches can transform a huge range of organisations' operational processes
to bring immediate benefit. Within utility companies, where, with the advent
of smart homes and the IoT, almost every aspect of the network will be
visible, companies can get a comprehensive view on when and how customers are
using devices across their network, for example, kettles being switched on in
the X factor ad break, meaning demand planning models can be much more
Issues can also be detected before the customer has even
noticed and organisations can have them pre-emptively resolved, equating to
greater efficiency, fewer fines and complaints, thereby giving a more seamless
So what are the skills
and experiences required to bring value to the Big Data challenge? Broadly
speaking, senior roles in this space can be broken down into three categories;
1. Lead Data Scientists, 2. Big Data Analytics leadership roles, and 3. Chief
Data Officers. The latter being a broader leadership role that is relatively
new in concept and one we have seen rapid uptake of by organisations in recent
The common theme between the roles is the level of intellect and
qualifications that is required to truly excel in this area is significant, in
fact it's pretty much akin to that of a Rocket Scientist! As a bare minimum
organisations who are building serious analytics capabilities will need a Data
Scientist with either a PhD in Artificial Intelligence, Computer Science or a
Mathematics and Science subject, which involves working with novel
methodologies to interpret complex data sets.
explosion and upsurge in digital usage is putting huge pressure on talent
supply: the existing pool of talent globally is far from adequately meeting
Whilst candidates in this space tend to have 'off the scale'
IQs, recruiting individuals with strong EQs as well tends to be the biggest
challenge. The fact remains that individuals with extremely strong analytical,
mathematical and scientific capabilities can often be lacking in emotional
intelligence. In the field of Big Data, having a healthy balance of both is
required at leadership level: the IQ to create the value out of the data and
the EQ to translate the key messages effectively to the business, thus having
the ability to present a compelling story and the actionable insights to make
the value meaningful.
Location of skills
The data explosion and
upsurge in digital usage is putting huge pressure on talent supply: the
existing pool of talent globally is far from adequately meeting demand.
The UK has suffered from a traditionally low concentration of technical and
analytical skills. With many organisations favouring outsourcing offshore as a
quick fix solution to the skills deficit, we have seen a lack of investment
and intent to home grow these skills. Whilst there is a small pool of high
quality talent, competition for the best people remains fierce.
concentration of skills has had a number of consequences across the talent
landscape for senior leadership roles. Firstly, the creation of artificially
high salaries; candidates with limited experience and lacking in well-rounded
business skills are often over promoted into roles and attracted by the
'highest bidder' into senior positions, essentially putting middle-senior
level managers into Director level roles and enjoying executive packages.
Secondly, candidates are headhunted frequently and as such the candidate
market has become highly transient, with senior candidates often unable to
evidence having delivered sustainable transformation before moving on to
Critical mass of talent can,
unsurprisingly, be found in the digital goldmine of the US West Coast or
On a global level the critical mass of talent can,
unsurprisingly, be found in the digital goldmine of the US West Coast or India,
a long established hub of technical outsourcing. However, even with the
concentration of good talent in both locations, skill shortages are still
projected. A recent McKinsey report in the US forecasts a shortage of 180K Data
Scientists and 1.5m analysts and managers by 2018. In India skill supply is
actually limiting growth; not only are they continuing to deal with the sharp
rise in outsourcing demand but are also battling an internal digital explosion
whereby internet and mobile phone use is increasing at an unprecedented
So what can organisations do to
attract these skills? In the short to medium term it's clear that any
organisation that's serious about attracting top tier talent, needs to take a
truly global approach to their search. In addition, being prepared to relocate
individuals and 'buyout' elements of their existing package is also key;
ultimately organisations who have managed to attract the best talent are now
working hard to retain it and when going into battle for such skills,
businesses need to be armed with the appropriate weapons to win. As well as
hefty packages, significant LTIP buy-outs running from £300K - £800K are not
uncommon when we're dealing with premium talent in this space.
addition to having the right financial incentives, the right armoury in this
case also includes the 'intellectual challenge'; a strong articulation of the
complexities and nuances of the data landscape and how this relates to the
role accountabilities. This is critical in motivating candidates who
ultimately are motivated to break through new boundaries and navigate
previously uncharted waters in the field.
In terms of long term
solutions, 'home-grown' talent through interventions in academia is becoming a
popular solution to help grow and secure a strong pipeline of talent. Whilst
academia has become a popular sourcing ground for corporates looking to
strengthen their data leadership population, foremost technology and telco
organisations are now starting to sponsor talented graduates through their
postgraduate qualifications in order to attract and secure the best and
brightest talent for the future.
Therefore, to get ahead in the future
businesses firstly need to acknowledge and own the problem but more
importantly must put in place interventions now in order to stem the
deficiency of skills later on. This isn't an issue that can be solved purely by
buying in talent right now just to address immediate business issues, the
problem must be looked at over the longer-term as well. Not just programmes of
acquisition but grass roots programmes of development through universities and
colleges, after all Big Data won't go away and exploited correctly, will in
fact become the life blood of many organisations.
We live in a world full of data, in fact full of Big Data, but data is only
useful once analysed, interpreted and delivered in an easily digestible form.
No matter which sector we work in, success seems to follow whomever keeps
informed and ahead of changing demands. Businesses need to put themselves in
that position, by using Big Data to derive the next trend, create the next
'thing' or deliver the next product or service innovation. Whatever that might
be in the future it needs real people to capture, analyse and make sense of
the data that's hitting us from all manner of sources at an alarming and ever
increasing rate. Without investing in the right talent now businesses will
only ever be challengers in their respective markets.