WAYNE HEATHER: So
we spoke about, I guess, the never
normal anymore, which is taking place at the moment. And quite aptly
so, we were going to have Rich Clayton, a
vice president of business analytics. But unfortunately, last
night, his laptop got stolen. So what I've done is I've
asked Duncan Fitter, who is director of product strategy
for data analytics in Oracle, to join us. So Duncan's kind of
woken up this morning. He wasn't really expecting
to do a presentation. So welcome, Duncan. DUNCAN FITTER: Thank you. WAYNE HEATHER: So what
we're going to do today is we're going to chat about how
the next generation of growth industries are taking
over right now. They're led by companies that
are ready to tap into the shift to the virtual world,
digital commerce, how consumer
behavior has change. Duncan is going to help us
understand how you can better manage your finance,
HR, and operations, and better understand
those drivers that are presented to us within
Fusion Analytics Warehouse. So, Duncan, thank
you for joining us. I do appreciate you stepping in. SUBJECT: Adapting to change. WAYNE HEATHER: Exactly. So, Duncan, let's start
with the first question. Let me ask you
about your thoughts and how data and analytics drive
innovation within companies. DUNCAN FITTER: Innovation
takes a culture mostly curious, especially now with
volatility that we are seeing, finance and HR teams
need to be asking more challenging questions. But I think the
problem is too often people stop asking
those questions because they know how
hard it is to answer them. They don't have
access to the data. They don't have
access to the tools. They just kind of give up. But with a data-driven culture,
a well-informed data strategy, and an agile analytic
platform, I've seen some remarkable outcomes. One company I was
speaking to was able to identify millions
of dollars worth of savings through identifying
duplicate invoices. Another, True Blue,
identified four million in working capital
improvements in just 30 days. Synlait, who are
based in New Zealand, created a more diverse
and performant workforce by analyzing both recruitment
and performance data. So if you take this
approach and you put data at the center of
your organization, then that really can help
drive your strategy forward. And innovation isn't just
about product innovation. It's also about process
and operational innovation. And with connected
data, marketing can innovate the
customer experience. Finance can innovate
the business strategy and how they guide to business. Leaders can shorten
recruiting cycles to accelerate innovation. So having connected data
improves productivity across the
organization, allowing them to design better products,
modernize customer experience, and, ultimately,
also reduce costs. WAYNE HEATHER: Excellent. Thanks, Duncan. So another question, I
guess, getting and using the right data can be
a challenge, especially for large organizations. Why is that? DUNCAN FITTER: Well, sadly,
little data is in action today. Data is really at rest,
laying around in old systems, not being put to use. People can't get a hold
of it, in data silos. Or it's locked
tight and protected by some of the best
security in the world, so people can't get
their hands on it. It's also too
complex, this data. And too many
business leaders have kind of lost faith
in their ability to get their arms around
this data in order for them to make
not just daily, but quarterly and annual decisions. And also, in trying
to predict and trying to look into the future, looking
at that survey the poll survey that you just did and looking
at some research that HBR did, too many people rely on
intuition and gut instinct. The HBR research showed
that only 20% of executives say that they really have a
mature strategy in this space today. So whether you call
it monetization, industrialization,
or data driven, in terms of being a data
driven organization, the point we need to do is to
create value from that data. We have to automate
every piece of the puzzle so that we can acquire,
combine, and repeat that cycle with new data. We looked at this problem. And that's what TK
was talking about. We designed this solution,
the Fusion Analytics, to really try and address
some of these issues. So he talked about 1,500
metrics ready to go. In most deployments,
we've seen-- and I've been working
with some customers alive within about six weeks. And he talked
about it supporting dozens of use cases-- improving working capital,
monitoring inventory positions, managing spend, and
analyzing profitability. But what he was talking
about was really just the tip of the iceberg
because those dashboards, those metrics, that story
that he was painting is just the start
of the opportunity because it's extendable. It ships with a
factory-certified data model, KPIs metrics, but can be
extended beyond the Oracle data with non-Oracle data. So if you bring
this all together, if you make it
connected, you make it available to your
business people, you can very much provide
them with an agile analytics solution. WAYNE HEATHER: So I guess
it's starting with the basics and then extending. So very good, thanks, Duncan. So I guess the next
question is that's great, but how can analytics help
businesses navigate disruption? DUNCAN FITTER:
Well, when people, when managers,
when business users when we all, even in
our personal lives, have data in uncertain
or unfamiliar situations, the more data we have,
the more insight we have, the more confidence we have
in the decisions that we make. If you think about
it, the pandemic has created an
enormous data deficit. How do we predict
the demand for pasta in Germany or in the UK, or
toilet paper across the globe? And the AI, when embedded
in analytics processes and platforms, can
power better decision making by scanning more
data, finding more outliers, and detecting patterns
faster than even our best analysts in our companies. And we call this
augmented analytics. It's really putting AI at the
center of your decision making. And it offers the potential
to substantially reduce the time to insight
and, thus, to action. And I've very much seen this
in action in the customers that I've been speaking to. WAYNE HEATHER: Fantastic. So, I guess, I kind
of thought about it the way you answered
that was almost not the digital translation,
as Peter mentioned early on in his presentation, but
a digital transformation, to truly embrace the power
of AI within your analytics to drive those insights. Great, Duncan. Another question for
you, how can companies better manage finance
and operations to better understand the
drivers of their business using Oracle Analytics? DUNCAN FITTER: Well,
most financial planners are built using the same
old drivers year after year. Very few finance teams are truly
embracing an augmented planning process, where they are
using AI as their co-pilot for creating predictive
models and for planning for the future. So rather than the accounting
forward approach to plans, an augmented
analytics solution can provide the necessary insights
on the correlations hiding in the data. And the finance team can, in
turn, draw their own conclusion on cause and effect. Of course, they must not confuse
causation with correlation. It's very much using
AI as a co-pilot. It's very much man and
machine, as Peter was talking. It's not about one or the other. It's about this idea
of augmented analytics. WAYNE HEATHER: Excellent. So one more
question, leaders are expected to make
more and more complex decisions now that there are
high expectations to explain and justify those decisions. Can you share some
practical advice on how analytics can
help with this dilemma? DUNCAN FITTER: Yeah. Decisions will continue to
come under scrutiny, especially as companies plan
for the recovery. I'm working with just
part of the picture won't work going forward. Real-time analytics
is here and now. Using and consuming all
that data is here and now. And we did 20
years of e-commerce in three months in the pandemic,
so waiting a month, a quarter, is a lifetime. So my number one advice, really,
is to use an agile methodology, develop an analytic
innovation sprint process. So for example,
we've created one for Fusion Analytics ERP, where
we offer 10 KPIs in 10 days to 10 users to prove the
point of agility and speed, to really put this knowledge
in the hands of business users. Getting 100% data quality
at speed is unrealistic. But getting access to the right
data to drive business outcomes and being connected to that
data is essential to success. WAYNE HEATHER: So I guess
don't let perfection inhibit innovation, right? Just move at an agile pace. What's the secret in getting
decision makers to balance intuition with insights
generated from machines, I guess getting
rid of that bias? DUNCAN FITTER: I
think it's trust. Now, as we talked about, AI
can automate many of the data discovery tasks. Decision makers need to ask
more challenging questions. And you kind of got to start to
trust some of these algorithms. But cognitive decisions,
using our own instincts, being supplemented by this AI-- we'll never be
replaced by machines. But they're going to sit idle
until decision makers really put them to work. So we've got to work together
with them and with this AI to drive better decisions,
and Fusion Analytics makes this possible. Beyond just the facts,
finance and operation leaders can get benefit to dozens
of embedded algorithms to find patterns in the data. So it's very much getting,
grasping this challenge and moving forward. WAYNE HEATHER: And I
guess, with the right data, how can those decisions
become easier? DUNCAN FITTER: If
I could get back to what TK was saying
about Fusion Analytics, it's ready to use
with over 250 KPIs, 1,500 metrics to personalize
to your job roles, to your responsibilities. There's no more DIY
or, as the Americans would say, Home Depot here. It's pre-built. It helps
you get moving and guiding the business very
much from day one. WAYNE HEATHER: Fantastic. Well, that's a great way
to think about it, Duncan. Thanks for joining us today,
especially sort of last minute, getting thrown under the
bus, really appreciate it.
