ey big data report_low-res

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Becoming an analytics–driven organisation to create value
Becoming a true valuedriven
organisation
Our research shows that …
01 Value
In response to the research
findings, EY has developed our
big data capability framework.
This outlines the components
needed to support value-driven
decisions, including centralised
governance and technology
infrastructure. It also shows how
strategy and specific big data
functionality combine to support
value-based decision–making.
By proposing a best practice
model for big data, the big data
capability map helps big data
teams demonstrate the potential
for value creation among seniorlevel
managers, stakeholders,
customers, market observers
and regulators.
Why is the big data capability
framework critical
• All organisations will have to
address value and place bets to
win and survive in the current
market.
• The technology is developing at
an outstanding speed.
For example, in 2011 there were
approximately 100 marketing
science data analytics providers
whereas at the start of 2014
there were 1,000. This incredible
growth is set to continue.
• If you chase after the technology
without purpose, you will burn
lots of money and not know
where to focus.
• The framework helps you think
in a clear, prioritised and
structured manner about where
to place bets.
Internet
Strategy
(enable
corporate)
Strategy
(enable
operational)
Strategy
(big data
capability)
Fig 1. Big data capability framework
03 02
Prescriptive analytics – Automate the response
Predictive analytics – What can we do to optimise
Forecast – What if it continues
Statistical analysis - Why did it happen
Dashboards – Inform the right people
Drill down – When/where/who
Reporting – What happened
04 Governance
05 Security and regulatory compliance
Infrastructure (Hadoop etc)
Value
based
decisions
EPM
Human
performance
Leadership
Digital
Internal
data
We use value to anchor the big data strategy
01 02 03
04
05
Big data allows us to create and
protect value in ways that were not
possible before:
• We can now understand more
comprehensively what drives
customer, supplier and employee
behaviour.
• By focusing on the value drivers
that will have the greatest
impact, we can place our bets
appropriately.
• For example, if for a fast food
chain, one of the key value
drivers is restaurant location and
placement. Previously you would
have tracked footfall traffic by
physically fusing market surveys
and counts. Now you can track
mobile phone movement as well
as other sources to understand
where the best location is.
The value framework allows us to
be clear about the most important
decisions and focus the data
strategy around these decisions.
Frequently big data initiatives
are determined by what data is
available, i.e., it is technology–
driven. This can be turned around
by being clear what are the most
important decisions ensuring you
build a competitive advantage by
answering them.
The value framework enables us
to choose the appropriate type of
analytics for the challenge.
Do you need to know the next best
action, or do you need to know
why something is happening Do
you need to do this repeatedly or
is it a one off question By being
clear about the type of analytics
required, this will help focus on the
right tools, skillsets and solutions.
The main reason organisations
struggle with data quality is
because there is neither ownership
nor accountability for quality.
Many organisations are now
focusing their offering behind the
chief data officer and ensuring
that data is seen as an asset equal
to others.
The visible protection of data
is critical to retain customers,
employees and suppliers trust.
It is fundamental to have access
to this data, and not being able to
prove to these stakeholder groups
that you can protect their data
will place you at a competitive
disadvantage.
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