ShortCut: Data Analytics Transformation | Page 2

solutions into their day-to-day routines
as expected. There may also be underestimated
internal resistance: employees
show a lack of buy-in often caused by an
alienation from the new solution or an
overriding fear of job losses to technology.
And finally, a lack of resources can
pose a challenge. This might mean that
there aren’t sufficient employees able to
conduct DA use cases, handle the applications
or understand how to find value
from the outcomes generated.
Changing mindset and structure
It’s clear from these eight challenges that
success in DA not only requires applying
fancy mathematical and stochastical
methods and developing high-level
solutions. More importantly, it’s about
adopting the right mindset and to build
up adequate structures which require a
dedicated DA operating model.
The operating model introduces and embeds
DA into current organizational structures
by defining the collaboration model
(functions and responsibilities, DA unit set
up (if applicable), internal/external cooperations,
key process definition, the governance
(legal framework, guidelines, committees
and KPIs) as well as the required data
and technological infrastructure and the
necessary skills and capabilities within the
organization to apply DA successfully.
But none of that will have any impact if
the management and staff can’t see value
NATURALLY BORN DATAISTS
Almost all companies are working
on DA initiatives, but some are
leveraging it better than others. Internet
companies and startups, in
particular, have largely already undergone
digitalization – and therefore
have the agility to apply DA far
better. But it is the financial institutions,
telecommunications, insurance
and healthcare companies
of this world that are the naturally
born data analyzers and AI users.
These benefit from the resources
and vast existing datasets to gain
the most from DA.
in what DA can add – to their specific
roles as well as to the wider organization.
This needs to be done by intelligent communication
and change management
formats to either educate, motivate or
activate the organization as well as by
piloting and implementing use cases
successfully in each and every part of the
organization.
But to achieve this, all business units –
across both the innovation and operational
environments – must be aligned to the
same strategic goals. Senior management
lending their full commitment to DA initiatives
will help to support this.
KEY SIGNPOSTS ON THE WAY TO
DATA ANALYTICS TRANSFORMATION
An example of this is BBVA Data &
Analytics’s smart data service ‘Urban
Discovery’. The DA arm of Spanish
banking group BBVA predicts
regional economic indices using
aggregated and anonymous data
from bank card transactions. This
data analytics tool identifies the
most popular tourist and residential
areas, or areas with the highest
number of, e.g. young shoppers.
BBVA uses these insights to advise
touristic and retail business clients
in the selection of investment areas
for building up new shops or hotels. 2
Become a data-driven company
DA can bring great benefits to a company.
But as said, it’s not a tool that just needs to
be implemented – it completely changes
the way we work. Because of that, there
are many separate challenges to overcome
when becoming a data-driven company.
With a deep understanding of the DA ecosystem,
sophisticated project management
skills and a proven track record in
transformation management, goetzpartners
works with clients to achieve DA best
practice and unleash its full power.
THE AUTHORS
ALIGN THE MANAGEMENT
DO THE RIGHT THINGS
STEFAN HOMANN
Partner, goetzpartners
INVOLVE THE IT
SPEAK ABOUT IT
BUILD UP GOVERNANCE
COLLABORATE
EDUCATE THE EMPLOYEES
DR. ALEXANDER QUACK-GROBECKER
Partner, goetzpartners
2) BBVA Data Analytics and CARTO present Urban Discovery, BBVA 2017: https://bbvaopen4u.com/en/actualidad/bbva-data-analytics-and-carto-present-urban-discovery-study-commercial-activity-madrid
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