Anglian Water provide water
and water recycling
services across East Anglia
and Hartlepool for over
six million customers.
Anglian Water's key
purpose is to bring social
and environmental
prosperity across the region
as part of our 'Love
Every Drop' commitment.
'Love Every Drop' is around
recognizing just how precious
our water supply is.
The first piece of the
puzzle for us has been
building a data store
large enough to handle
these kind of volumes of data.
The storage point solution really starts
about two years ago.
We had that storm named
The Beast from the East.
During that time, we were
set up as a small team
to do a quick reactive piece of work
to understand how the water levels
within the reservoirs are behaving.
The main problems that we had was really
around a extraction of data.
The main sort of objective
was make it easy,
scalable and repeatable.
Our solution was based solely
on the Microsoft platform,
in particular, the Azure Data Lake
as well as all the additional
attributes of that,
things like ADF pipelines and et cetera,
which was really the main crux
and a process and engine of our solution.
We need to understand how
the consumer uses water,
and when the consumer
uses water, we need to
know how that's going to
affect the storage point.
And when the storage point
is affected, we need to know
if that's going to cause
a problem where we need
to make changes at the
water treatment work.
For us, Azure was key,
and we use Azure Databricks,
and that has honestly
changed the way we work.
There was no way that
a human would be able
to look through that much data
and determine if there was a problem.
In this case, it was a problem
that only could be solved by AI.
The AI capability was an
integral part of this solution.
And what we wanted to do was to understand
what that flow data was doing,
and to be able to understand
the behaviours of the
reservoirs at any given point
and to be able to combine
that alongside weather data
we're pulling across from meteomatics.
Over the last two years,
we've been trialing our
smart metering program.
We've been able to deliver a 11% reduction
in demand across the
households within these areas
through identifying customer-side leaks
and also through behaviour
change by customers
being able to understand
how much water they use
and also giving them better control
of ways that they can save water at home.
It offers us the ability to understand how
our customers use water and hence,
the best advice to give our customers
as to how they could save water.
As we scale up our smart metering program
we need a platform like
Azure that is scalable,
high performing, and also
ensures that we've got the level
of security around our customer data,
but also provides us the insights,
the level of information
that we need as a business
to inform our decision-making.