Presentation by James Dunning, CEO of Syrinix, at the SWAN 2012 Conference in Utrecht on the value of real-time data for the global water sector

1. Data‐Driven Value
James Dunning, Chief Executive
SWAN Forum Conference, Utrecht, May 2012
9th May, 2012

2. • The key to value realisation using smart water networks
is data
– data deployed to overcome the barriers to
adoption; and
d i d
– data deployed to realise value.
This presentation was delivered at the SWAN 2012 Conference, Utrecht, Netherlands in the Conference Session “Show Me the
Money” assessing the Return on Investment potential of smart network technology in the water sector. Notes have been added
in line with the presentation delivered on the day.

3. • Following the Hollywood theme of “Show Me the
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Money”, if “smart water networks” was a movie
character it would be the cool one in the room, slightly
maverick, a good haircut and top of the class on the
dance floor too.
• But despite that, it is also the case that
– barriers to the adoption of smart network
technologies remain pretty high; and
– that there’s no doubting many of technology
providers would love to “show the money” to
water utilities across the globe.
• But are those utilities ready? Are they listening?
• If the utilities are not yet listening, then smart water
network technology providers have a choice
choice…

4. • One option is to
– rail against the injustices of utilities not embracing
smart water technologies across the globe;
– challenge regulators to do more to support innovation;
or
– cajole water utilities to embrace this modern era
• Alternatively
– technology providers can try to understand better the
barriers the water utilities face
– they can work together, as shown by this SWAN 2012
Conference, i ensuring th t i2O’ progress i
C f in i that i2O’s in
Malaysia, the adoption by Thames Water of Syrinix’s
TrunkMinder technology, Takadu’s success in Portugal
are not individual successes but instead illustrative of
the general adoption of smart technologies.
• But how can that be done?
– by identifying and understanding barriers to adoption;
and
– overcoming those barriers by showing the power of
data at a macro‐ level an individual utility level and at
level,
a product level.

5. • At a macro level, there cannot be many who these days
dispute the multiple water‐related challenges bearing
down upon the industry and population at speed
– i th Middl E t and N th Af i populations
in the Middle East d North Africa l ti
have increased by 140% since 1970 whilst being
home to the top 16 water stressed nations
according to the Maplecroft Water Stress Index;
– at $1 per cubic metre, traditional water
productivity gains from the likes of desalination
are prohibitively expensive in a global economy
that rarely prices water accurately;
– non‐revenue water losses meanwhile remain
stubbornly high – at 38% in Sao Paolo and 40% in
Montreal to name but two, whilst by 2050 70% of
the world’s population are expected to live in
cities.

6. • There is also, of course, the report by the 2030 Water
Resources Group which identified
– that ignoring efficiency gains, global demand is
expected to increase from 4500 billion cubic
metres to 6900;
– that of a f
h f forecast 40% global supply d fi i or
l b l l deficit,
50% for a third of the population, business as
usual approaches will not get anywhere near
closing that gap.

7. • As evidence of this pending crisis being recognised, in
the SWAN survey from late last year 84% of respondents
rated real‐time monitoring as important and not just for
one or two reasons but across a broad spectrum of
measures.
measures
• But that survey does concede itself that it was in part
self‐selecting, that only those paying attention to smart
network management are likely to respond to a survey
about it.
• But that in itself highlights the challenge technology
providers in the smart water network sector face. Few
dispute the macro‐level challenges the sector faces but,
p g ,
at both individual utility and policy levels, barriers to
smart network adoption exist and it is the challenge for
smart water network technology providers to overcome
those barriers.
• But what are these barriers?

8. • As the 2030 Water Resources Group report identifies, a
lack of detailed data is no doubt part of the problem for
developing and developed economies alike.

9. • But the barriers go beyond that.
• Cost is certainly often cited as a barrier though it is noticeable how
quickly money can be found when pressure mounts as shown by
some of the measures being taken in the UK now a drought has
been announced.
• Understandably, other barriers include
– “if it ain’t broke why fix it?”
– “it would cost a fortune to collect all that data and we
wouldn’t use it anyway, we don’t have the time”
• Ignoring the role of innovation, of data deployment all around
them, others query if there really is a need noting that flooding a
house is acceptable once or twice though a third time is probably
unacceptable particularly if with sewage.
• Another example of a barrier to smart water network technology
adoption is “we’ve got 100 men out looking for leaks every day” .
Though it is unclear what that means in terms of effectiveness it
nonetheless sounds like action is being taken, so relieving pressure.
• Perhaps the most important barrier is that there is not always the
detailed understanding of the costs of events. Whilst it is known
that a burst may have necessitated the payment of £x million in
compensation there is less clarity about the related costs due to
increased call centre volumes, management time in rerouting
supplies, dealing with the press, managing the emergency response
teams etc.

10. • As seen by that, there is a gap
– at a macro‐level it is understood that water is an
increasingly precious resource and that the
pressures on supply are already increasing and are
going to keep increasing;
– but at a micro‐level, is “smart network
management” seen as even having a major role in
alleviating those pressures?
• Certainly it can have a major role and certainly progress
is being made. Equally certainly, however, there remains
a long way to go.
• The consequent challenge is to bridge that gap and the
way to do that is through data.

11. • In May 2011, the McKinsey Global Institute published a
detailed report on the potential of “big data” and its
findings were quite illuminating
– by their calculations, retailers could increase
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operating margins by 60% by mining data
comprehensively (imagine that applied to the
water sector);
– European Governments could save $100bn in
administration.
administration
• There are millions of sensors already deployed, with the
number increasing by 30% per year.
• But what are the practical benefits of smart
technologies? What are the real‐time real life benefits
to encourage water utilities to take a substantial step
forward and embrace smart network applications?

12. • An immediate benefit is transparency – in the public
sector, McKinsey found that some are spending up to
20% of their time looking for data.

13. • Data also allows empirical evidence to be displaced by
more rigorous assessment, for direction not to be driven
by the opinion of the highest paid person in the room,
the HiPPO, but instead by analytics and statistical
assessments; for innovation to based not on a hunch or
a suspicion but on a foundation of hard facts.
• Data also allows for automation to be applied in place of
human decision making, be that in automatically
spraying de‐icer on a bridge when the temperature
drops or, as with our TrunkMinder technology,
automatically detecting and locating leaks on major
pipelines to the nearest meter.
• In the oil sector, as an illustration of what is possible,
using real‐time data to manage oil fields remotely has
led to a 25% reduction in operating and maintenance
waste.

14. • Data also facilitates operational benefits, for example by
allowing staff to be better mapped to events, by directly
relating operations to variable costs such as energy ‐
activities that are dependent on real‐time data.
• In California and elsewhere a significant amount of the
lf d l h f f h
energy used, one estimate is well above 10%, is spent on
moving water around the State. Consequently the
savings suggested by using smart water network
technologies are not savings at the edges but substantial
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savings at the heart of utility operations.

15. • The following examples provide instances of direct
impact on utilities in terms of the potential role of data
and smart water networks
– 60% of insurance claims for water utilities relate
to water loss;
– when a trunk main b
h k burst on Oxford Street in
f d
London it cost Thames Water over £4m; and
– when a trunk main burst in the North of England,
the relevant water utility was at once a YouTube
sensation and at once found its branding and
image under considerable pressure.

16. • As relevantly, OFWAT, the UK regulator, has made it clear that it
will be placing an increasing focus on real‐time data ‐ a move that
other regulators are likely to follow. As a result, simply seeking
approval for CapEx will no longer be acceptable ‐ detailed data
substantiation will be expected and even required.
• In the USA too, hundreds of millions of dollars of investment are
required in the drinking water infrastructure but where should the
utilities begin with that and, if it is not affordable, as is the case for
many economies at the moment, what can be deferred and what
cannot be?
• If utilities do not know the answers to those questions, if they do
not have the data, and if, rather than replacing pipelines, the
utilities are not monitoring their critical pipelines on an informed
basis with technology like TrunkMinder – in that case all that
remains is guesswork and an example of “what you can’t measure
what can t
you can’t manage”.
• Meanwhile, when major corporates like Nestle and Coca Cola are
investing in water efficiency around the world and when water
scarcity is rising up the public consciousness, basing major decisions
on a paucity of df data will b increasingly unacceptable.
ll be l bl

17. • But that is not to say there are no practical examples yet
either – far from it.
– in Mission Springs California, reservoir controls
are being automated with consequent reductions
in
i energy use and id increases i reliability;
in li bilit
– the Siemens wastewater plant in Warsaw allows
all plant information to be viewed from a central
control room ‐ how many utilities actually have
that level of information visibility?
– in Atlanta, USA, automated data‐driven
technology has contributed to a 13% reduction in
consumption despite a 28% population growth;
and
– at Thames Water software is being used to
Water,
converge telemetry data, historic rainfall
information and weather forecasts to provide 6
hour ahead projections allowing systems to be
drained down ahead of surges and pumping to be
aligned with within d energy cost variations.
li d ith ithi day t i ti

18. • Also with Syrinix’s TrunkMinder technology deployed on larger diameter
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water pipelines
– utilities can receive automated leak detection and location to
within 1 metre – with immediate automated alerts when a leak is
found;
– utilities can receive fully automated burst alerts within seconds of
a burst occurring rather when the next 15 minute wake up cycle
starts on a more basic burst alert system;
utilities can receive real‐time information every second of every
day….that you can access real‐time or on an historic basis.
• From a desk, a car, out in the field, anywhere with a web connection, it is
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possible to log on to the system and see for a pair of installed TrunkMinder
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units the real‐time pressure, the real‐time flow and the location of any tiny
leaks.
• Imagine that ‐ information at ones fingertips, realising the benefits
highlighted by McKinsey, making utility operation more efficient real‐time
and opening the door to
and opening the door to
– fact‐based optimisation;
– fact‐based issue identification; and
– fact‐based decision making.
• But, whilst McKinsey might therefore give Syrinix a big tick. whilst Syrinix
can provide that information on a real time and historic basis, the
can provide that information on a real‐time and historic basis the
challenge posed by utilities remains “show me the money”.

19. • “Wont it be very expensive….surely nothing can beat
that old stalwart…the mahogany listening stick?” is a
claim often made in respect of deploying smart network
technology.
• In response to that, Syrinix has, in respect of
TrunkMinder, used an external consultant to interview a
number of utilities as well as using externally available
data.
data
• In doing so, consideration has been given to the actual
costs of TrunkMinder equipment on an entire network
basis and applying a variety of scenarios of leaks and
bursts, as well as taking into account installation costs
and the alternatives of physical surveys and leak
location teams.

20. • The data substantiated result of that analysis is clear
namely that applying TrunkMinder in critical locations
has a payback period of less than three years and that is
before account is taken of the impact of lowered
insurance premiums, the benefit of real‐time data for
regulatory negotiations and the savings achievable
through energy‐use optimisation.
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• Indeed even extending TrunkMinder technology across
an entire network, encompassing non‐critical trunk
mains too, the expectation is that the payback period
will not be significantly higher given those additional
benefits.

21. • As has been seen then, barriers remain to deploying smart
network technologies, barriers that are certainty
understandable but which are also surmountable.
• In summary
– the importance of water as a precious asset is
increasingly recognised at a macro‐level;
– at a utility‐level, benefits are achievable in terms of
automation, transparency, innovation and operational
benefits;
– at a product‐specific level, using Syrinix’s own
TrunkMinder technology as an example, the benefits
are again clear not on a “we would say that” basis but
on the basis of substantiated externally derived data.
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• So the message to water utilities about embracing smart
network technology is consequently clear ‐ give technology
providers the opportunity and they will indeed show you the
money.
money