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SWANonomics
The unexpected economics of Smart Water Networks

Haggai Scolnicov
Chief Technology Officer, TaKaDu

May 2012
TaKaDu in one slide



Sensor data    Event detection   Analyst action   Field repairs

•   12 utilities
•   Millions of sensor-days of data processed
•   Tens of thousands of actionable events reported
•   Thousands of invisible leaks detected

                                                                  2
Smart monitoring changes everything
New light on real conditions and existing processes
• Evidence on fault lifecycles
• System KPIs and where all the money goes



New opportunities to take action
• React before major failure – requires new tools
• Reprioritise across the utility, using new insight and data


                                                          3
Good news: smart monitoring drives
spending increase on field crews
 Less false alerts, greater accuracy
        More early warning

            More leakage fixed
            per field crew hour

         Point of diminishing returns is at
           much larger field workforce

                Save OPEX by hiring crews
           (Economic Level of Leakage changed!)

                                                  4
The five stages of new KPIs
Time to awareness of leaks was weeks, not days
(and users don’t always recognise leaks after getting the alert)
Sensor availability is 75%, not 90%
(and the 15% difference is misleading data, not just missing)

Denial: “That’s not leakage” or “you added up wrong”
Anger: “You’re ruining my report” or “so I should fire Joe”
Bargaining: “Can we call it something else? Split the difference?”
Depression: “So now we’re worse off than 5 years ago”
Acceptance: “Let’s start a new team or process for that”


                                                                     5
Better leakage reduction means
less Ml/day repaired
• Many leaks grow (gradually or suddenly)
• Fixing larger leaks may be a sign of inefficiency




                    April 7th   May 1st
                     1 l/s       4 l/s



                                                      6
The value of water loss reduction is
not (just) the cost of water loss reduced
     Lost water
                                        Damage and
   (production           Repairs
                                           fines
    distribution)

   Interruptions                           Asset
                    Water quality
     to service                          longevity

                                  Supply
               Public
                                capacity of
              relations
                                 network

                                                     7
And other shockers…
• That meter sample is worth 10¢ (or much more)
  Raw data costs money and creates value
• Leak detection least helpful during peak leakage
  Visible bursts are most urgent,
  and field location/repair may be a bottleneck
• Vast majority of leakage repairs are insignificant
  due to “random” targeting + location incentive
• OPEX can be “smart money”!
  SWAN services economy, from sensors to analytics
                                                   8
So is SWAN adoption very complex?
• First take the basic gains from each component
• The new facts were true before we knew them
• Opportunities to rethink established practices

Technology has already disrupted this industry:
    staying behind is a losing proposition



                                                  9

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The Surprising Economics of Smart Water Networks

  • 1. SWANonomics The unexpected economics of Smart Water Networks Haggai Scolnicov Chief Technology Officer, TaKaDu May 2012
  • 2. TaKaDu in one slide Sensor data Event detection Analyst action Field repairs • 12 utilities • Millions of sensor-days of data processed • Tens of thousands of actionable events reported • Thousands of invisible leaks detected 2
  • 3. Smart monitoring changes everything New light on real conditions and existing processes • Evidence on fault lifecycles • System KPIs and where all the money goes New opportunities to take action • React before major failure – requires new tools • Reprioritise across the utility, using new insight and data 3
  • 4. Good news: smart monitoring drives spending increase on field crews Less false alerts, greater accuracy More early warning More leakage fixed per field crew hour Point of diminishing returns is at much larger field workforce Save OPEX by hiring crews (Economic Level of Leakage changed!) 4
  • 5. The five stages of new KPIs Time to awareness of leaks was weeks, not days (and users don’t always recognise leaks after getting the alert) Sensor availability is 75%, not 90% (and the 15% difference is misleading data, not just missing) Denial: “That’s not leakage” or “you added up wrong” Anger: “You’re ruining my report” or “so I should fire Joe” Bargaining: “Can we call it something else? Split the difference?” Depression: “So now we’re worse off than 5 years ago” Acceptance: “Let’s start a new team or process for that” 5
  • 6. Better leakage reduction means less Ml/day repaired • Many leaks grow (gradually or suddenly) • Fixing larger leaks may be a sign of inefficiency April 7th May 1st 1 l/s 4 l/s 6
  • 7. The value of water loss reduction is not (just) the cost of water loss reduced Lost water Damage and (production  Repairs fines distribution) Interruptions Asset Water quality to service longevity Supply Public capacity of relations network 7
  • 8. And other shockers… • That meter sample is worth 10¢ (or much more) Raw data costs money and creates value • Leak detection least helpful during peak leakage Visible bursts are most urgent, and field location/repair may be a bottleneck • Vast majority of leakage repairs are insignificant due to “random” targeting + location incentive • OPEX can be “smart money”! SWAN services economy, from sensors to analytics 8
  • 9. So is SWAN adoption very complex? • First take the basic gains from each component • The new facts were true before we knew them • Opportunities to rethink established practices Technology has already disrupted this industry: staying behind is a losing proposition 9