Targeted conservation Data didn’t align historically We didn’t know where that data lived We’re working on that Learned this the hard way Spreadsheet is the system of record Real- time data Demand forecasting mentioned Staff ingenuity saved the day GIS linked to meters/accounts AI Documentation made a difference Customer portal in use Inherited legacy systems Scripts compensate for system gaps Data cleaning took forever Different staff gave different answers Interoperability Single source of truth We have AMI… but don’t use it yet Data gaps in history Dashboards pull from multiple systems Incremental progress beats perfect systems Had to write custom queries Manual process Someone laughs at their own system CWOL reporting done manually This isn’t perfect — but it works AMI + CIS finally integrated Data supports water budgets API limitations Vendor limits discovered late Defensible data Repeatable workflows It depends Siloed systems Data triggers customer messaging We paid to access our own data RFP changed after lessons learned Targeted conservation Data didn’t align historically We didn’t know where that data lived We’re working on that Learned this the hard way Spreadsheet is the system of record Real- time data Demand forecasting mentioned Staff ingenuity saved the day GIS linked to meters/accounts AI Documentation made a difference Customer portal in use Inherited legacy systems Scripts compensate for system gaps Data cleaning took forever Different staff gave different answers Interoperability Single source of truth We have AMI… but don’t use it yet Data gaps in history Dashboards pull from multiple systems Incremental progress beats perfect systems Had to write custom queries Manual process Someone laughs at their own system CWOL reporting done manually This isn’t perfect — but it works AMI + CIS finally integrated Data supports water budgets API limitations Vendor limits discovered late Defensible data Repeatable workflows It depends Siloed systems Data triggers customer messaging We paid to access our own data RFP changed after lessons learned
(Print) Use this randomly generated list as your call list when playing the game. There is no need to say the BINGO column name. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.
Targeted conservation
Data didn’t align historically
We didn’t know where that data lived
We’re working on that
Learned this the hard way
Spreadsheet is the system of record
Real-time data
Demand forecasting mentioned
Staff ingenuity saved the day
GIS linked to meters/accounts
AI
Documentation made a difference
Customer portal in use
Inherited legacy systems
Scripts compensate for system gaps
Data cleaning took forever
Different staff gave different answers
Interoperability
Single source of truth
We have AMI… but don’t use it yet
Data gaps in history
Dashboards pull from multiple systems
Incremental progress beats perfect systems
Had to write custom queries
Manual process
Someone laughs at their own system
CWOL reporting done manually
This isn’t perfect — but it works
AMI + CIS finally integrated
Data supports water budgets
API limitations
Vendor limits discovered late
Defensible data
Repeatable workflows
It depends
Siloed systems
Data triggers customer messaging
We paid to access our own data
RFP changed after lessons learned