Louise Maynard-Atem: Taking an Agile Approach to Data and Analytics Success

Louise Maynard-Atem, Data Insights Lead at GBG, shares her tips on
implementing agile methodology to drive innovation in the wake of
the pandemic

Born in the realm of software development, agile methodology has
been growing in popularity across a wide range of business
functions in recent years.


In this week’s episode of the Business of Data Podcast, Louise
Maynard-Atem, Data Insights Lead at identity verification,
location intelligence and fraud prevention company GBG argues
that an iterative, collaborative approach to data and analytics
will help to drive innovation and demonstrate business value as
we emerge from the pandemic.


“[Agile] helps us innovate faster. It helps us to surface the
problem quicker and utilize data more effectively,” says
Maynard-Atem. “But it wasn't until we really had to put agility
into practice quickly, because necessity meant that we had to,
that we realized the importance of it.”
The Pandemic Highlighted the Importance of Business Agility

If there’s one thing we’ve learned in the last 12 months, it’s
that you never know when you might need to transform the way your
business operates.


“Agility really is king. It’s king because you never know when
you are going to have to make a pivot, make changes to your
business model, make changes to your ways of working and make
changes to what you're doing with data,” says Maynard-Atem. “It’s
taken the global pandemic, I suppose, to really bring the need
for agility into clear focus.”


The advantages of rapid action in a turbulent market have
highlighted the advantages of agile thinking to business leaders.


“I think it wasn't until we had to put agility into practice
quickly, because necessity meant that we had to, that we realized
the importance of it,” says Maynard-Atem.
Driving Innovation with Agile Methodology

However, as things begin to settle, Maynard-Atem says that agile
thinking and, more specifically, agile methodology, will drive
innovation in data and analytics.


I think innovation, agile thinking and agile practices go
hand-in-hand because innovation is ultimately [about] trying to
do something new,” says Maynard-Atem.


She continues: “We want to make sure that we're not just taking a
waterfall approach. We're taking small incremental steps and
pulling in the feedback loops – and that’s ultimately what agile
teaches you.”


However, for organizations used to long development cycles and
multi-year digital transformation initiatives, the fast-paced
iterative nature of agile can seem like an unlikely partner.


“It seems as though a lot of organizations feel like they're
under pressure to deliver a big transformation program, but I
don't think that's the best way to deliver in terms of data and
analytics,” says Maynard-Atem. “And certainly not from an agile
perspective.”


Instead, Maynard-Atem recommends looking for manageable,
well-defined experiments to test hypotheses, and pulling in
feedback loops.


“It's just breaking it down to those manageable chunks and being
really specific about what each experiment is going to deliver,
what that value means, and then how [you will define] success,”
she says.
Key findings


Agility was a critical success factor for businesses
during the pandemic. As companies rapidly pivoted
their operations, the ability to think and act quickly was a
key differentiator.


Agile methodology empowers innovation.
Experimentation and rapid iterations are the hallmarks of both
innovative thinking and agile methodology.


Break down large initiatives into manageable
chunks. By looking for the smallest experiment
possible you can demonstrate value more quickly.