GROUP ENGINEERING MANAGER, NEW TO 
THE ROLE SO I'M NOT USED TO IT YET. 
I KNOW MOST OF YOU IN MY PREVIOUS 
LIFE AS THE SOLUTION ARCHITECT, 
BUT NOW I'M THE REDMOND PLACE SUPPLY 
CHAIN MANUFACTURING TEAM. WE'RE 
HERE TO TALK ABOUT INTELLIGENT OPERATIONS. 
THIS IS INDEED YOUR LAST SESSION 
OF THE CONFERENCE, SO HOPEFULLY 
WE'LL -- YOU'RE SAVING THE BEST 
FOR LAST AND WE'RE GOING TO END 
YOUR CONFERENCE WITH A BIG BANG. 
THAT'S THE EXPECTATION. SO I HAVE 
MY COLLEAGUE HERE WITH ME. >> ARJIT 
BASU: HEY, GOOD AFTERNOON, I'M ARJIT, 
I'M A PM AND OUR TEAM OWNS THE INTELLIGENT 
OPERATIONS. IT WAS EARLIY CALLED 
CONNECTED MANUFACTURING, SO THEY'RE 
BOTH THE SAME IN CASE YOU HAVEN'T 
ENTERED THE WRONG ROOM SO CONNECTOR 
OPERATIONS AS WELL AS ENTERPRISE 
ASSET MANAGEMENT IS THE SESSION 
WE HAD EARLY MORNING , SO THESE 
AREAS. SO WHAT WE'LL TALK ABOUT 
TODAY AND WE'LL YOU -- GIVE YOU 
A WALK -THROUGH OF WHAT WE'VE DONE 
SO FAR OR INTELLIGENT OPERATIONS 
FOR FINANCE AND OPERATIONS. IT WAS 
KIND OF A LONG ASK WHEN WILL AX 
OR FINANCE AND OPERATIONS WORK WITH 
I. T. WE'LL SHARE SOME CUSTOMER 
REFERENCES AND STORIES WHICH WE'VE 
ALREADY DEPLOYED AT SOME OF OUR 
CUSTOMER SITES AND WE'LL GIVE YOU 
THE ROAD MAP OF THE OPPORTUNITIES 
FOR ENGAGEMENT. >> PAUL WU: ALL 
RIGHT. SO FIRST GIVE YOU THE OVERALL 
VISION AND HOW DOES EVERYTHING WORK 
AND I'LL DEFENSIVE DIVE ON THE TECHNICAL 
-- DEEP DIVE ON THE TECHNICAL SIDE 
LATER, THANK YOU. >> ARJIT BASU: 
THIS IS ONE SLIDE YOU'VE SEEN PRETTY 
MUCH AND I WANT TO SPEND A COUPLE 
SECONDS ON THIS BECAUSE THE [INAUDIBLE] 
ALSO VERY IMPORTANT RULE AND PHILOSOPHY 
OUT HERE BECAUSE AT THE END OF THE 
DAY WHAT WE ARE DOING WITH THIS 
CONNECTOR OPERATIONS IS WE ARE SENDING 
OUT DATA, WE ARE GETTING BACK DATA 
IN, WE ARE PROCESSING IT, ENRICHING 
IT AND THEN PUSHING IT BACK INSIDE 
FINANCE AND OPERATIONS TO GIVE INSIGHTFUL 
ACTIONS. SO THAT'S VERY, VERY IMPORTANT. 
SO WE HAVE BASICALLY THE DATA, YOU 
KNOW, THE INFORMATION FLOWING IN, 
AND THE DATA IS SUPPOSED TO GO OUT. 
SO FOR CUSTOMERS IT'S PRETTY STANDARD, 
YOU KNOW, INFORMATION GOES OUT OR 
PRODUCTS GO OUT, CUSTOMERS USE IT, 
THEY GIVE US FEEDBACK ON HOW WE 
ENGAGE CUSTOMERS. AND SIMILARLY 
FOR THE PRODUCT, THE PEOPLE, AND 
THE OPERATIONS. SO WE ARE GOING 
TO BE CONCERNED WITH THE OPTIMIZE 
OPERATIONS IN THIS SESSION AND TOUCHING 
UPON THE TRANSFORM PRODUCTS BECAUSE 
IN THE SUPPLY CHAIN AREAS IN FINANCE 
AND OPERATIONS WHERE WE BOTH BELONG, 
WE HAVE AN OVER VISION OF HOW DO 
YOU DIGITAL IZE FACTORY OF THE FUTURE 
CONCEPT, THAT'S A VERY COMMON TERM 
WHICH EVERYONE IS USING, EVERYONE 
WANTS TO BE THERE, SO FROM OUR SIDE 
WHAT ARE THE THINGS WE ARE GOING 
TO ENABLE IN THE PRODUCT NOW AND 
GOING FORWARD TO ENABLE OUR CUSTOMERS 
TO HAVE LITERALLY A FACTORY OF THE 
FUTURE VERSION OF IT. TRADITIONAL 
MANUFACTURING. VERY STANDARD, YOU 
KNOW, YOU HAVE YOUR LOGISTICS, YOUR 
RAW MATERIALS, EDUCATION SYSTEMS, 
FINISHED GOODS AND WAREHOUSE, YOU 
DO A LOT OF THINGS. WE HAVE CAPABILITIES 
IN THESE AREAS IN FINANCE AND OPERATIONS, 
BUT THERE ARE AREAS, OTHER WHAT 
TRADITIONAL MANUFACTURING SUPPLY 
CHAIN LACKS AS THE -- IS THE DIGITAL 
FEEDBACK LOOP. YOU KNOW, IN TODAY'S 
WORLD DATA IS THE NEW BUSINESS CURRENCY 
SO THIS DATA NEEDS TO FLOW IN AND 
WITH THIS JOURNEY THERE ARE A LOT 
OF AREAS WHERE A LOT OF DATA IS 
ACTUALLY FLOWING IN WITH IOT MACHINE 
LEARNING INTELLIGENCE AND IN TODAY'S 
WORLD A LOT OF THE DATA YOU USE 
COMES FROM OUT SIDE THE ORGANIZATION, 
AND HOW THIS DATA IS GOING TO GO 
AHEAD AND IMPACT YOUR SUPPLY CHAIN 
IS VERY, VERY IMPORTANT SO THINGS 
LIKE INBOUND AND OUTBOUND LOGISTICS, 
WAREHOUSING AND MANUFACTURING DISTRIBUTION 
SYSTEMS ARE THESE AREAS. SO MOVING 
OVER FROM OUR TRADITIONAL MANUFACTURING, 
WHAT WOULD IT FEEL LIKE YOU COULD 
NOW SEE THE FLOW OF INFORMATION 
ACROSS YOUR DEVICES, MACHINES, YOUR 
SHOP FLOOR, OKAY, WHAT WOULD HAPPEN 
IF YOU COULD MONITOR YOUR FLOOR 
REAL-TIME? AT EVERY LEVEL OF THE 
ORGANIZATION AND I MEAN EVERY LEVEL, 
RIGHT, FROM THE SHOP FLOOR TO THE 
TOP FLOOR, LIKE A VICE PRESIDENT 
SITTING CAN ACTUALLY VIEW NEAR REAL-TIME 
INFORMATION ON THE DASHBOARD, ON 
THE SCREEN. A PRODUCTION MANAGER 
CAN LITERALLY GO AHEAD AND SEE WHAT 
THE REAL-TIME INFORMATION IS AS 
WELL AS ANY QUALITY ANOMALIES THAT 
CAN IMPACT THE BUSINESS BECAUSE 
IOT IS NOT JUST ABOUT COLLECTING 
DATA BUT HOW TO MERGE THE DATA WITH 
A BUSINESS APPLICATION AND PROVIDE 
THE USERS SOME INSIGHTS AND ACTIONS. 
FOR EXAMPLE, IF A MACHINE SENDS 
ME A PARTOUT SIGNAL, JUST GETTING 
THAT SIGNAL AND COLLECTING IT AND 
DOING A SUB MENU MAX AVERAGE REALLY 
DOESN'T ALLOW A LOT OF VALUE. SOMEONE 
NEEDS TO TAKE THAT DATA AND THEN 
DO SOMETHING. IF YOU'RE GETTING 
A PARTOUT SIGNAL FROM THE MACHINE 
THE MACHINE WILL NEVER TELL YOU 
WHAT PRODUCT IT IS MAKING, WHO THE 
CUSTOMER IS, WHAT IS THE CYCLE TIME, 
ARE YOU DELAYED OR ARE YOU AHEAD. 
IF YOU ARE DELAYED, WHAT IS THE 
IMPACT. SO OUR OBJECTIVE OUT HERE 
IN THIS CONNECTOR OR INTELLIGENT 
OPERATIONS IS TO MAKE SENSE OUT 
OF THE DIGITAL DATA, THE TIME STAMP, 
THE BINARY DATA THAT'S COMING IN 
FROM THE MACHINES COLLECTED OVER 
IOT HUB, MERGING IT WITH THE BUSINESS 
DATA AND THEN GIVING USERS OF FINANCE 
AND OPERATIONS ACCESS TO IT SO THAT 
THEY CAN MAKE INTELLIGENT DECISIONS. 
NOW, THERE IS A LONG -- A VERY STRONG 
ROAD MAP WE HAVE AFTER THIS WHICH 
WE'LL SHARE DID YOU. BUT CONNECTING 
THE DIGITAL WORLD TO A SIGNAL IS 
THE HARD PART. SO ONCE YOU CONNECT 
A PHYSICAL MACHINE ON THE SHOP FLOOR 
WITH A RECORD [INAUDIBLE] WHICH 
MACHINE 1225 IN SOME WAREHOUSE LOCATION 
ONCE YOU HAVE THAT DONE, THEN, IT 
OPENS UP A LOT OF POSSIBILITIES. 
SO WHEN WE LOOK AT THE INTELLIGENT 
MANUFACTURING AS A WHOLE, TO ENABLE 
INTELLIGENT MANUFACTURING IS NOT 
JUST IOT WHICH HELPS BUT THERE ARE 
A LOT OF OTHER AREAS WHICH AS A 
WHOLE OUR SUPPLY CHAIN TEAM IS ACTUALLY 
WORKING ON. SO YOU WILL HAVE THINGS 
LIKE BUSINESS MODEL CHANGES. SO 
IN TODAY'S WORLD, PEOPLE ARE MOVING 
FROM TRADITIONAL SELLING TO MORE 
OF A PRODUCT AS A SERVICE KIND OF 
APPROACH. WHERE COMPANIES LIKE BMW 
AND OTHERS ARE ACTUALLY USING ALL 
OF THEIR CARS SO IT'S NOT JUST A 
SALES ENTRY GOES OUT, YOU STILL 
HAVE TO KEEP TRACK OF ENTRY BECAUSE 
IT'S MORE LIKE A REVENUE MODEL SO 
FINANCIALS HAVE WILL TO SUPPORT 
THAT, OUR SALES ORDER AND OUR SUPPLY 
CHAIN WILL HAVE TO SUPPORT THAT 
AS WELL AS ENSURE THAT WE HAVE TOTAL 
CONNECTIVITY TO THE GOODS AND SERVICES 
WHICH ARE OUT IN THE FIELD THAT 
ARE BEING USED SO WE CAN GET TELEMETRY 
DATA AND INCREASE OR IMPROVE THE 
KEY DATA CYCLES. A LOT OF MACHINES 
AS THE RISE OF THE MACHINES, WE 
HAVE TO ENABLE IN PROACTIVE MAINTENANCE. 
AND THAT'S ONE OF THE KEY AREAS 
WHICH WE HAVE INVESTED HEAVILY WITH 
AN IP ACQUISITION WHERE WE ARE GOING 
TO RELEASE A DYNAMICS 365 ASSET 
MANAGEMENT SOLUTIONS FOR THE BACK 
END OF AN ORGANIZATION. AND WITH 
THAT SOLUTION WE ARE GOING TO LINK 
IT UP WITH THE INTELLIGENT THINGS 
LIKE IOT SO AS TO ENABLE YOU TO 
DO PREDICT ABLE CAPABILITIES. THE 
MOST IMPORTANT THING OUT THERE IS 
THE FACTORY OF THE FUTURE CONCEPT. 
SO THAT IS HOW DO WE AUTOMATE WHAT'S 
ON THE SHOP FLOOR. IF YOU LOOK AT 
THINGS, SHOP FLOOR DATA, THE DATA 
THAT COMES OUT WHETHER THE MACHINES 
ARE CONNECTED OR NOT IS VERY, VERY 
SEPARATE FROM A BUSINESS APPLICATION. 
SO IT'S VERY INTERACTIVE SO SOMETHING 
HAPPENS ON THE SHOP FLOOR, SOMEONE 
HAS TO UPDATE IT. THOSE THINGS ARE 
NEVER IN SYNC IF YOU'RE LOOKING 
AT RAW MATERIALS BEING CONSUMED 
SOMEONE HAS TO MANUALLY GO AHEAD 
AND UPDATE ANY BUSINESS APPLICATION 
AND IT'S USUALLY DONE AT THE END 
OF THE SHIFT SO IF YOU HAVE A FOUR 
OR AN EIGHT-HOUR CHEF YOUR PHYSICAL 
INVENTORY ON THE SHOP FLOOR IS VERY 
DIFFERENT FROM WHAT YOU HAVE IN 
THE SYSTEM. SO [INAUDIBLE] PRODUCTION 
RUNS, IF YOU HAVE A MACHINE DOWN 
SCENARIO AND YOU WANT TO REPLAN, 
THIS DISCREPANCY IN INVENTORY CAUSES 
A LOT OF PROBLEM. AND IT'S USUALLY 
OFF. SO THESE ARE SOME OF THE CHALLENGES 
OR PROBLEMS WE ARE TRYING TO ADDRESS. 
WE'VE BEEN WORKING WITH A FEW HANDFUL 
OF CUSTOMERS IN OUR UNDERSTANDING 
OF THE SCENARIOS AND I'LL SHARE 
THE SCENARIOS WITH YOU AS WELL AS 
GIVE YOU A DEMO OF WHAT WE HAVE. 
GO AHEAD. NOW, FOR THE FACTORY OF 
THE FUTURE, WHAT WE ARE DOING, WE 
ARE LINING UP WITH FOUR KEY SCENARIOS 
OUT HERE. AND I'LL TALK ABOUT THE 
SCENARIOS IN THE NEXT SLIDE. BUT 
OUR OBJECTIVE IS TO ENABLE A COMPLETELY 
NEW MODEL SUPPORTED BY FINANCE AND 
OPERATIONS AS WELL AS THE AZURE 
IOT SUITE. INITIALLY WE WILL START 
OUT WITH IOT HUB BECAUSE WE ARE 
DEALING HERE WITH INDUSTRIAL MACHINERY 
AND EQUIPMENT. AND THEN LATER ON 
LOOK AT MODELS WHERE WE CAN LOOK 
INTO A IOT CENTRAL OR ANY OTHER 
KIND OF TECHNOLOGIES BUT INITIALLY 
WE WILL START WITH IOT HUB BECAUSE 
IT WILL GIVE US THE FLEXIBILITY 
AS WELL AS THE CAPABILITY OF [INAUDIBLE] 
INDUSTRIAL ORGANIZATION. SO INTELLIGENT 
OPERATIONS. SHOP FLOOR TO THE TOP 
FLOOR. NOW, THERE ARE SIX SCENARIOS 
WE ARE GOING TO LAND AND THIS WILL 
BASICALLY BE AS A SERVICE. SERVICE 
MEANS, MY COLLEAGUE PAUL WILL TALK 
MORE ABOUT THE ARCHITECTURE DETAILS 
ON HOW WE ARE DOING IT. SO THE SIX 
SCENARIOS WHICH WE ARE GOING TO 
LINE UP IS, FIRST ONE, NOTIFICATIONS 
FOR DELAYED PRODUCTION ORDERS. SO 
WHAT HAPPENS IS WHEN YOU ACTUALLY 
DO A PRODUCTION ORDER ON A JOB, 
YOU HAVE A QUANTITY, A THEORETICAL 
START TIME AND AN END TIME SO YOU 
CAN FIND OUT WHAT THE CYCLE TIME 
IS GOING TO BE LIKE. SO LET'S SAY 
YOU'RE SUPPOSED TO PRODUCE 400WITZ 
IN FOUR HOURS SO YOU KNOW THE THEORETICAL 
CYCLE TIME LIKE IT'S A A HUNDREDWITZ 
PER HOUR WHEN YOU RELEASE IT FOR 
MANUFACTURING ON THE SHOP FLOOR 
BECAUSE OF MICRO DOWN TIMES OR SHORTER 
USE OF INVENTORY, THE ACTUAL CYCLE 
TIME COMING IN VARIES WITH THE THEORETICAL 
CYCLE TIME. AND THE ACTUAL CYCLE 
TIME IS A SUMMATION OF THE PARTOUT 
SIGNAL WHICH YOUR MACHINE SENDS 
OUT AND YOU ACCUMULATED A PERIOD 
OF LET'S SAY 15 MINUTES AND THEN 
YOU CAN DO -- SO WHAT WE'RE ENABLING 
ABLING IS AT A REGULAR INTERVAL 
THE ACTUAL CYCLE TIME FROM THE SHOP 
FLOOR IS BEING NEAR REAL-TIME COMPARED 
WITH THE THEORETICAL CYCLE TIME 
AND IF THERE IS A DEVIATION, LET'S 
SAY, AND WHICH CAN BE CONFIGURED 
BY THE USER, LET'S SAY 10 DEVIATION 
OR 20, IT WILL AUTOMATICALLY SHOW 
A NOTIFICATION ONTO A WORKSPACE 
AND THEN RELATED ACTIONS ON THAT 
, WHICH WILL I WILL SHOW YOU , THAT 
THE -- SO THE PERSON CAN TAKE INTELLIGENT 
ACTIONS. NOW, FOR THIS CONNECTOR 
OPERATION WE ARE CONCERNING THREE 
PERSONAS, THE SHOP FLOOR WORKER, 
WHERE THE WORK WILL ONLY SEE WORK 
DONE ON THAT MACHINE AT THAT INSTANCE, 
THEY ARE NOT INTERESTED IN WHAT'S 
HAPPENING ON A DIFFERENT WORK CENTER. 
THE PRODUCTION MANAGER OR THE SHOP 
FLOOR SUPERVISOR WHO NEEDS TO HAVE 
AN OVERALL UNDERSTANDING ABOUT THAT 
SHIFT, THAT WAREHOUSE , OR THAT 
PLANT. AND THEN THERE IS THE VP 
OF OPERATIONS WHERE THEY ARE MORE 
INVOLVED OR INTERESTED IN OVER ALL 
EQUIPMENT EFFICIENCY. SO INITIALLY 
WHAT WE ARE DOING IS WE ARE FOCUSING 
ON THE SHOP FLOOR WORKER PERSONA 
AND THE PRODUCTION MANAGER PERSONA. 
SO FOR THE NOTIFICATION SERVICE 
FOR DELAYED ORDERS, WE WILL HAVE 
A NOTIFICATION FOR THE PRODUCTION 
MANAGER AS WELL AS RELATED ACTIONS 
BECAUSE IF THERE IS A DELAY IN PRODUCTION 
ORDER OCCURRING IN THE JOB IT'S 
GOING TO IMPACT ALL OTHER PRODUCTION 
SCHEDULES WHICH ARE THERE ON THE 
MACHINE SO WHAT IS THE CUSTOMER 
IMPACT IN TERMS OF VALUE BASS IOT 
JUST ONLY CANNOT GIVE YOU THE DATA, 
IT CANNOT TELL YOU WHAT THE CUSTOMER 
IMPACT IS. WE ARE HERE TO SOLVE 
THAT PROBLEM. THE SECOND SCENARIO, 
WHAT WE ARE GOING TO DO, AND BOTH 
THESE SCENARIOS HAVE ACTUALLY BEEN 
DEPLOYED AT ONE OF OUR PILOT CUSTOMERS. 
DISCRETE MANUFACTURING. AND, YOU 
KNOW, IT'S KIND OF WE'RE RUNNING 
WITH THEIR MACHINES. SO NOTIFICATION 
SERVICES FOR EQUIPMENT DOWN, SO 
TYPICALLY EQUIPMENT DOESN'T GO DOWN 
IT'S JUST THAT THE PRODUCTION HAS 
STOPPED BECAUSE OF MICRO DOWN TIME 
BECAUSE OF LET'S SAY RAW MATERIALS 
NOT BEING AVAILABLE AT THE ENTRY 
POINT, OR THE WORKER HAS FACED SOME 
QUALITY ISSUES OR THINGS LIKE THAT. 
SO THESE BASICALLY LIKE OUR PRODUCTION 
STOPS. NOW WHAT ALGORITHM WE HAVE 
HERE IS YOU CAN DEFINE IN THE SYSTEM, 
LIKE, HEY, IF THIS WORK CENTER DOES 
NOT PRODUCE A PARTOUT IN, SAY, 10 
MINUTES, IT MEANS THEY CAN ALERT 
TO ME SOMEONE NEEDS TO GO AND LOOK 
AT THAT SO WE CAN BYPASS OR FLIP 
OVER THE MICRO DOWN TIMES WHICH 
CAN HAPPEN FOR A MINUTE OR LESS 
THAN A MINUTE AND LOOK FOR AREAS 
IN WHICH A PRODUCTION MANAGER SHOULD 
GET INVOLVED IN. AND THIS IS ONE 
OF THE TOUCH POINTS WE ARE INTEGRATING 
IT WITH THE ASSET MAINTENANCE SOLUTION 
SO THAT A WORK HARDER OR A MAINTENANCE 
REQUEST CAN IMMEDIATELY BE GENERATED 
AND CREATE -- OR CREATED IN THE 
ASSET MANAGEMENT SOLUTION SO YOU 
CAN HAVE A TECHNICIAN LOOK AT THAT. 
AND THIS IS SOMETHING YOU CAN, YOU 
KNOW, HAVE AT A GLOBAL LEVEL OR 
AT AN INDIVIDUAL RESOURCE LEVEL. 
THE THIRD SCENARIO WE ARE DOING 
IS MAINLY FOR ONE CUSTOMER WHICH 
IS OUR PILOT CUSTOMER IN THE FOOD 
AND BEVERAGE INDUSTRY, IT'S QUALITY 
ANOMALIES. SO YOU HAVE A QUALITY 
BATCH ORDER AND YOU HAVE BATCH ATTRIBUTES 
WHERE YOU CAN DEFINE -- LET'S SAY 
YOU'RE MAKING FRIES, LIKE NORMAL 
FRENCH FRIES AND THINGS LIKE THAT 
AND YOU HAVE DEFINED QUALITY PARAMETERS 
LIKE MY SALT CONTENT IN THIS SHOULD 
NOT BE BETWEEN -- BETWEEN X AND 
Y, MOISTURE CONTENT SHOULD BE BETWEEN 
A AND B AND LET'S SAY THE COLOR 
SHOULD BE SOMETHING VALUE. OK. NOW, 
TYPICALLY WHAT HAPPENS IS THERE'S 
A QUALITY PERSON GOING THROUGH THE 
FRY LINE OR THE CHIP LINE, THEY 
TAKE A SAMPLE, TEST IT OUT AND THEN 
SAY, OKAY, THIS IS NOT GOOD, WE 
HAVE TO THROW THE ENTIRE BATCH AWAY. 
AND IT HAPPENS USUALLY LIKE EVERY 
COUPLE OF MINUTES TO MAYBE A HALF 
HOUR OR AN HOUR SO THERE'S A LOT 
OF WASTAGE. SO WHAT WE'RE DOING 
IS THIS CUSTOMER, THIS PILOT CUSTOMER, 
THEY HAVE TIED UP WITH AN OPTICAL 
SENSOR COMPANY WHICH IS SENDING 
LIVE DATA OF THE SALT AND MOISTURE 
CONTENT FROM THE FRIES. AND WE ARE 
REAL-TIME KIND OF COLLABORATING 
OR CHECKING THE DATA WITH FINANCE 
AND OPERATIONS BECAUSE THAT'S WHERE 
YOU SEND YOUR QUALITY ATTRIBUTES 
AND THE MINUTE IS IT GOES OUT OF 
ORDER IT WILL IMMEDIATELY FLAG A 
WARNING TO THE SHOP FLOOR WORKER 
AS WELL AS THE PRODUCTION MANAGER 
LIKE THERE'S SOMETHING WRONG SO 
ACTION CAN BE TAKEN IMMEDIATELY 
SO WE ARE LITERALLY REDUTYING THE 
VALUE OF CHECKING EVERY, YOU KNOW, 
LIKE 15 MINUTES OR 30 MINUTES DOWN 
TO LITERALLY SECOND, 30 SECONDS 
KIND OF TIME FRAME. SO THE WASTAGE 
WHAT YOU ARE PLANNING IS BASICALLY 
GETTING REDUCED DRASTICALLY. SO 
WE WILL BE EXPANDING THE QUALITY 
SCENARIOS TO DISCRETE AREAS AS WELL 
AND THINGS LIKE THAT. THE FOURTH 
SCENARIO WE ARE DOING IS INVENTORY 
OF DATA. AGAIN, THIS ONE WAS VERY 
SPECIFIC ABOUT THE DISCRETE MANUFACTURING. 
SO WHAT HAPPENS IS WHEN YOU GET 
PARTOUT SIGNALS, SOMEONE HAS TO 
CREATE A REPORT OF FINISHED JOURNEY. 
NOW, WITH THIS SERVICE WE WILL BE 
ABLE TO TAKE THAT DATA, ACCUMULATE 
IT AND AUTOMATICALLY CREATE REPORT 
AS FINISHED JOURNALS IN THE SYSTEM 
SO THE WORKER OR THE MANAGER CAN 
REVIEW IT AND THEN POST IT. SO IT 
WILL STOP THE NEED FOR CREATING 
DRAFT JOURNALS MANUALLY , YOU KNOW, 
AT THE END OF THE SHIFT OR IN BETWEEN 
SHIFT NOW, WE ALSO TAKE CARE OF 
SERIAL IZATION SO IF YOU ARE PART 
OUT IF YOUR PRODUCTS HAVE SERIAL 
NUMBER CONTROL ON THEM AND THE IP 
SENSOR OR SOME SENSOR CAN GIVE US 
THE DATA WE WILL BE ABLE TO SPLIT 
UP THE LINES QUALITY ONE IS THE 
SEWELL NUMBER AND POPULATE THE JOURNAL 
FOR YOU INITIALLY WE WANTED TO GO 
AHEAD AND AUTO POSE THE JOURNAL 
BUT SOME OF THE FEEDBACK WE GOT 
WAS JUST CREATE IT SOMEONE WILL 
POST IT UP. BUT THE MAIN OBJECTIVE 
IS REDUCE THE TIME SO THAT THE INVENTORY 
ON THE SHOP FLOOR CAN BE UPDATED 
IN THE SYSTEM. THE IOT SIGNALS ARE 
COMING AND WE'LL EXPLAIN A LITTLE 
BIT MORE ON THE ARCHITECTURE ON 
WHAT WE'RE DOING AND HOW WE ARE 
DOING IT SO THAT YOUR INVENTORY 
JOURNALS CAN ACTUALLY GET UPDAT 
ED NEAR REAL-TIME. ASSET MAINTENANCE, 
THERE ARE TWO SCENARIOS WHICH WE 
ARE RELATING. SO THE FIRST SCENARIO 
IS WHENEVER YOU HAVE A MACHINE DOWN 
OR ANY KIND OF EVENT, WE WILL HAVE 
A CONFIGURABLE SETUP WHICH WILL 
ALLOW YOU TO CREATE A MAINTENANCE 
REQUEST OR A WORK ORDER ON THE ASSET 
MANAGEMENT MODULE. IF YOU HAVE THE 
ASSET MANAGEMENT MODULE FOR 365 
IN OCTOBER THE PIECE WILL BE ABLE 
TO ACCESS ASSET MAINTENANCE AND 
AUTOMATICALLY REQUEST REQUEST FOR 
YOU WHICH, THEN, CAN BE ROUTED BY 
THE SCHEDULER OR TECHNICIAN. GOING 
FORWARD THE SCENARIOS FOR OTHER 
ASSET MAINTENANCE ARE MORE ABOUT 
PREVENTING MAINTENANCE. SO WHEN 
YOU'RE DOING PREVENTIVE OR CONDITION-BASED 
MAINTENANCE, WE HAVE SOMETHING CALLED 
ASSET COUNTERS. SO COUNTERS ARE 
SOMETHING THAT YOU WANT TO MEASURE 
ON THE ASSET LET'S SAY AN ELEVATOR, 
LIKE HOW MANY TIMES IT HAS GONE 
UP AND DOWN BEFORE IT'S DUE FOR 
MAINTENANCE. OR LET'S SAY A VEHICLE, 
LIKE AFTER 10, 000 MILES, SO MILES 
IS A COUNTER, YOU NEED SERVICE A 
AFTER 20, 000 MILES YOU NEED SERVICE 
B. SO TODAY THESE COUNTERS HAVE 
TO BE MANUALLY INPUTTED INTO THE 
SYSTEM. BUT WITH THIS CAPABILITY 
GOING FORWARD, WE WILL BE ABLE TO 
TIE THOSE COUNTERS WITH THE DATA 
FROM THE SHOP FLOOR SO THEY CAN 
BE UPDATED ON AN AUTOMATIC BASIS 
SO FOR EXAMPLE LIKE IF YOU HAVE 
A VEHICLE AND YOU HAVE THAT VEHICLE 
CONNECTED AND THE DATA SENT TO AZURE 
HUB WE SHOULD BE ABLE TO UPDATE 
THE DATA AND UPDATE IT LIKE EVERY 
15 MINUTES ON WHAT THE TOTAL MILEAGE 
IS. IF YOU HAVE A MACHINE AND IT'S 
PRODUCING, OR A CONVEYOR BELT THAT 
REQUIRES MAINTENANCE AFTER EVERY 
1, 000 HOURS, WE SHOULD BE ABLE 
TO PULL OUT THE TIME IT'S IN USE, 
A PREVENTIVE MAINTENANCE SCHEDULE 
CAN BE AUTOMATICALLY BE GENERATED. 
THESE ARE IMPORTANT THINGS WE'RE 
INVESTING IN AND NOW WITH ALL THE 
DATA THAT'S GOING TO COME IN FROM 
THE IOT WORLD THERE'S SOME PART 
OF THE DATA WHICH WE'LL PUSH INTO 
A DATA [INAUDIBLE] SO YOU CAN RUN 
YOUR OWN ANALYTICS PLUS WE'LL GIVE 
YOU OUR ANALYTICS, PAUL WILL GIVE 
YOU MORE ON WHAT WE HAVE PLANNED 
BECAUSE WE'RE TALKING ABOUT BIG 
DATA, INDUSTRIAL MACHINES THAT HAVE 
300 SENSORS AND THEY'RE SENDING 
DATA EVERY ONE SECOND. SO WE DON'T 
USE ALL THE DATA BECAUSE IT DOESN'T 
HAVE A BUSINESS IMPACT SO WE ONLY 
EXTRACT THE DATA WHICH HAS A BUSINESS 
IMPACT LIKE QUALITY PARAMETERS, 
GOOD QUANTITY, BAD QUANTITY KIND 
OF SCENARIOS, THE REST LIKE SPINDLE, 
RPM AND ALL THAT STUFF AS OF NOW 
WE DON'T USE IT BUT WE'RE GOING 
AHEAD AND PUSH IT INTO STORAGE LOCATION 
WHERE YOU CAN SPIN OUT YOUR OWN 
ANALYTICS AND BI AND AS WE MOVE 
FORWARD WE'LL START USING IT BECAUSE 
IOT -- I MEAN THE DATA RETENTION 
IS SEVEN DAYS BEFORE YOU NEED TO 
MOVE IT OUT. THE LAST SCENARIO, 
AGAIN, IS RELATED TO EQUIPMENT HEALTH 
AND MACHINE HEALTH. IT'S VERY SIMPLE 
TO EQUIPMENT EFFICIENCY BUT THIS 
IS MORE ON THE LONG-TERM. SO HOW 
DO YOU MEASURE THE EQUIPMENT HEALTH 
OR THE HEARTBEAT THAT THE MACHINE 
IS ON AND THINGS LIKE THAT AND WHAT 
IS THE DIGITAL HEALTH OF THE MACHINE. 
SO USING THESE COUNTERS AND THE 
IOT TOUCH ONES, IF YOUR MACHINE 
IS CONNECTED AND THE DATA IS SENT 
VIA A GATEWAY INTO A IOT HUB WE 
WILL BE ABLE TO TAKE THAT DATA AND 
BE ABLE TO DEFINE ARCHITECTURES 
ON HOW YOU SAY THE EQUIPMENT IS 
HEALTHY OR NOT. AND ALL OF THIS 
REQUIRES THE VERY BASIC THING IS 
CONNECTING YOUR IOT SENSOR DATA 
TO LITERALLY MACHINE DATA. THAT'S 
VERY, VERY IMPORTANT. SO WHAT I 
WILL DO IS THE ARCHITECTURE PART 
IS IMPORTANT TO UNDERSTAND. SO I'LL 
ASK MY COLLEAGUE PAUL TO EXPLAIN 
IT TO YOU WHAT IS THE ARCHITECTURE, 
HOW WE ARE GOING AHEAD WITH IT, 
WHAT ARE THE CAPABILITIES, AND, 
YOU KNOW, ANY QUESTIONS WE CAN TAKE 
AFTER THAT PAUL? >> PAUL WU: ALL 
RIGHT. THANKS, ARJIT. ALL RIGHT. 
SO THAT WAS A REALLY GOOD INTRODUCTION. 
SO I SEE A COUPLE HEADS NODDING 
HERE AND THERE SO I'M NOT SURE IF 
THAT'S NODDING 6 APPROVAL, ACKNOWLEDGMENT, 
OR MAYBE NODDING FROM LUNCH. [LAUGHTER] 
SO BEFORE I GO INTO THE ARCHITECTURE, 
LET'S DO A FUN EXERCISE. SO EVERYBODY 
PLEASE PUT YOUR HANDS UP. ALL RIGHT. 
COOL. SO FOR THOSE OF YOU, I WANT 
-- KEEP YOUR HANDS UP IF YOU CURRENTLY 
ARE COMPLEMENTING OR PLAN TO COMPLEMENT 
F&O MANUFACTURING PRODUCTION, ASSESSMENT 
MANAGEMENT TYPE OF SCENARIOS. KEEP 
YOUR HANDS UP. OK. THANK YOU. VERY 
GOOD, VERY GOOD. >> ARJIT BASU: 
YOU'RE IN THE RIGHT ROOM, RIGHT 
SESSION. [LAUGHTER] >> PAUL WU: 
QUESTION NUMBER TWO, PLEASE, GIVE 
IT UP. FOR THOSE OF YOU WHO ARE 
INTERESTED IN IMPLEMENTING IOT SENSOR-BASED 
INTELLIGENCE SCENARIOS, PLEASE KEEP 
YOUR HANDS UP. YEAH, THAT WAS A 
TRICK QUESTION. IF YOU PUT YOUR 
HANDS DOWN, YOU'RE NOT SUPPOSED 
TO BE HERE. OK, GOOD. NOW, DO YOU 
CURRENTLY OWN OR PLAN TO OWN A STRENGTH 
ANALYTICS PIPELINE? OOH, THAT WAS 
-- >> ARJIT BASU: THAT'S GOOD, WE 
GOT OUR ANSWER. >> PAUL WU: THAT'S 
PRETTY EXPECTED. SO LET ME INTERPRET 
THAT QUESTION A LITTLE BIT. YEAH, 
SO IN ORDER TO DO ALL THESE -- THAT'S 
A GOOD TIME TO JUST -- >> ARJIT 
BASU: GO INTO THE ARCHITECTURE. 
>> PAUL WU: LET'S BRING THE WHOLE 
THING. THERE WE GO. NO SUSPENSE. 
BEFORE I GET INTO THE DETAIL, I 
NEED TO GIVE A BIG DISCLAIMER. THIS 
IS STILL IN PUBLIC PREVIEW. WE'RE 
STILL -- PRIVATE PREVIEW, YEAH THANK 
YOU. IN PRIVATE PREVIEW. THE GOAL 
IS TO WORK WITH A COUPLE OF THE 
CUSTOMERS, WELL, WE ACTUALLY HAVE 
-- BEEN WORKING WITH TWO CUSTOMERS 
TODAY. THE MOST OF THE STUFF THAT 
WE SHOW, JAMES [INAUDIBLE] WAS LIVE 
IN PRODUCTION WITH LITTON, ARE WE 
GOING TO SHOW LIVE SCREEN SHOTS? 
>> ARJIT BASU: NO, I'LL SHOW YOU 
WHAT IT IS. >> PAUL WU: PERFECT, 
PERFECT. BUT A LOT OF THESE ARCHITECTURE 
COMPONENTS WHICH I'LL GET INTO, 
IT'S STILL, YOU KNOW, UP TO OUR 
INTERPRETATION AND UP TO MODIFICATION. 
THE REASON -- GETTING BACK TO THE 
LAST QUESTION I ASKED, WE -- THE 
QUESTION I NEED TO ANSWER IS DO 
YOU CURRENTLY OWN A SET OF THINGS 
LIKE THERE'S MULTIPLE COMPONENTS 
INVOLVED IN BUILDING A STREAMLINED 
ANALYTICS PLATFORM RIGHT, SENSE 
OR NEEDS TO BE PUMPED INTO SOMETHING, 
MOST LIKELY IOT HUB. THAT'S ONE 
COMPONENT AND ONCE IT LANDS IN AN 
IOT HUB TYPICALLY ONLY THE SENSORY 
DATA ITSELF DOES NOT MAKE A LOT 
OF SINCE, RIGHT, IT'S A WHOLE BUNCH 
OF NUMBERS, YOU NEED TO PARSE THEM 
OR YOU NEED TO ENRICH THEM WITH 
DATA COMING FROM ERP, RIGHT, THAT'S 
WHERE WE COME IN. AFTER THE DATA 
IS COMBINED ALL INTO THE IOT HUB, 
THEN, YOU PUT STREAM ANALYTICS PLATFORM 
ON TOP OF IT TO DO AGGREGATION OR 
RULE -BASED CALCULATION TO DERIVE 
INSIGHTS INTO THE CURRENT BATCH 
WINDOW YOU'RE LOOKING AT OR AGGREGATION 
OF THE CURRENT BATCH WINDOW INTO 
SOMETIME IN THE PAST THAT'S HOW 
IT GOES. AFTER THE STREAM ANALYTICS 
GOES THE RESULT OF WHICH WE'RE GOING 
TO PAINT IT BACK TO F&O AS INSIGHTS 
EITHER AS AN ALERT OR AS SOME SORT 
OF ACTION THE END USER CAN PERFORM. 
KNOWING THE END-TO-END STORY THIS 
IS PRETTY MUCH WHAT THIS PICTURE 
IS DESCRIBING SO WE'RE GETTING SENSORY 
DATA FROM ALL THE MACHINE RESIST 
REAL LIFE, REAL WORLD, PUMPING OUGHT 
THE DATA INTO IOT HUB, IN OUR CASE 
THE AZURE IOT HUB, YOU CAN HAVE 
AN ON PREMISE HUB OR ANOTHER HUB 
INTO A DIFFERENT CLOUD I DON'T KNOW, 
WHO HAS AWS HUB? GOOD. THAT WAS 
ALSO A TRICK QUESTION. [LAUGHTER] 
>> PAUL WU: SERIOUSLY, WHO HAS IOT 
HUB TODAY? >> ARJIT BASU: OK. >> 
PAUL WU: OK. WHO HAS STREAM ANALYTICS 
PLATFORM LIKE AZURE STREAM ANALYTICS 
TODAY? OK, THE SAME GROUP. YEAH. 
OK, COOL. SO YOU NOTICE THIS BIG 
KIND OF BOX, CIRCLE HERE AROUND 
THE COMPONENTS FOR SHIPPING? THE 
INTELLIGENT OPERATIONS SERVICE IS 
REALLY THE MEAT OF WHAT MY ENGINEERING 
TEAM IS WORKING ON, RIGHT? REMEMBER, 
THIS PROBLEM IS REALLY A DATA ENRICHMENT 
PROBLEM WE'RE TRYING TO SOLVE. BECAUSE 
IT'S SENSORY DATA BY ITSELF MOST 
OF THE TIME DOES NOT GIVE YOU ALL 
THE INSIGHTS YOU WOULD NEED. THE 
SIZZLE -- THE PART THAT SIZZLE IS 
WE ARE ABLE TO IOT SENSORY DATA 
LIKE I JUST DESCRIBED. >> ARJIT 
BASU: THIS IS A COMPLETELY NEW SERVICE 
WHICH WE ARE GOING TO RELEASE FIRST 
AND THIS, THE MAGIC SAUCE AS PAUL 
MENTIONED IS HOW DO YOU MAKE THE 
SENSORY DATA COMING OUT FROM THIS 
INSTANCE, ACTUALLY, FROM CUSTOMER 
X FOR THIS PRODUCT AND IT'S SUPPOSED 
TO BE DELIVERED ON THIS DATE, SO 
THAT'S THE SECRET SAUCE, THAT'S 
BASICALLY THE BREAD AND BUTTER, 
THE FOUNDATION AL ELEMENTS OF CONNECTING 
MULTI-PIECES OF DATA. >> PAUL WU: 
YES. I'M SURE FOR THOSE WHO ALREADY 
OWN IOT HUB OR DOING STREAM ANALYTICS 
IT'S EXACTLY THE SAME CHALLENGES 
AND PROBLEMS YOU GUYS ARE TRYING 
TO SOLVE AS WELL ON YOUR OWN. SO 
OUR GOAL IS TO MAKE THAT PART EASY 
SO THE REST OF YOU TO PLAN TO IMPLEMENT 
THE SAME DON'T HAVE TO GO THROUGH 
THE SAME EXACT CHALLENGES AND PROBLEM-SOLVING 
PROCESS THESE GUYS MIGHT HAVE WENT 
THROUGH. SO WE'RE SHIPPING THAT 
BIG BOX, I CAN GET INTO A LITTLE 
MORE DETAILS INTO EXACTLY WHAT'S 
INSIDE THAT BIG BOX BUT IN TERMS 
OF ALL THE SCENARIOS WE'RE BUILDING, 
YOU'LL SEE THESE LITTLE BLACK BOXES 
OVER HERE ON THE OTHER SIDE, IT'S 
MAPS TO THE SIX SCENARIOS THAT ARJIT 
JUST WALKED US THROUGH. >> ARJIT 
BASU: THESE SCENARIOS CAN BE DEPLOYED 
EITHER INDIVIDUALLY OR ALL TOGETHER. 
SO WE'VE KIND OF COMPARTMENTAL IZED 
THEM SO YOU SAY I ONLY NEED THE 
DELAYED SCENARIO, RIGHT NOW I'M 
READY TO DO THE OTHERS, YOU CAN 
HAVE THE ABILITY TO GO AHEAD AND 
DEPLOY INDIVIDUAL SCENARIOS AS WELL. 
>> PAUL WU: CORRECT. I'D SAY IN 
THE NEXT SLIDE WE'LL GET INTO FUTURE 
PLANS, SO ON AND SO FORTH BUT FROM 
AN ARCHITECTURE PERSPECTIVE, WHO'S 
HEARD OF THE LAMBDA ARCHITECTURE 
IT'S THE SAME GUYS WHO HAD THEIR 
HANDS UP WHO OWNS IOT. ANY SORT 
OF STREAM ANALYTICS, THERE'S ALWAYS 
TWO PATHS, RIGHT, THE HOT PATHS 
AND KIND OF THE COLD PATH. THE HOT 
PATH IS FOR I WANT ACT, I WANT TO 
BE ALERTED IN REAL-TIME OR NEAR 
REAL-TIME FASHION, FOR EXAMPLE. 
IF MY MACHINE IT DOWN, IF MY PRESSURE 
ON HIGH HYDRAULICS IS LEAKING I 
NEED TO BE ALERTED RIGHT AWAY, BECAUSE 
I NEED TO SEND A MAINTENANCE WORKER 
RIGHT AWAY TO GO WORK ON IT. BUT 
THEN THERE ARE CERTAIN HEURISTICS 
AND INSIGHTS YOU CAN DERIVE ONLY 
FROM MARGE AMOUNTS OF HISTORICAL 
DATA AND THOSE DATA ARE CALLED THE 
BATCH PROCESSING, THAT'S MORE OF 
A COLD PATH SCENARIO. FOR THIS PHASE 
-- ALL THE SCENARIOS WE'VE BEEN 
TALKING ABOUT SO FAR MOSTLY FOCUSES 
ON THE HOT PATH WHERE WE STREAM 
LARGE AMOUNTS OF INFORMATION AND 
WE ARE DOING REAL-TIME ANALYTICS 
WITH A STREAM ANALYTICS PLATFORM 
, RIGHT? AND THEN THE POST-PROCESSING 
OF THAT WILL COME IN PHASE TWO. 
SO FOR EXAMPLE FOR ASSET MANAGEMENT, 
THE PREDICTIVE MAINTENANCE, RIGHT, 
INSTEAD OF ME JUST DOING VERY DUMB 
SCHEDULING EVERY THREE WEEKS LET 
ME DO A MAINTENANCE SO REPREVENT 
A PROBLEM FROM HAPPENING, WE CAN 
LOOK AT HISTORICAL DATA AND HAVE 
A REALLY EFFICIENT MAINTENANCE SCHEDULE 
THAT KEEP OUR MACHINE UP AND RUNNING, 
SO ON AND SO FORTH. SO LET ME DIVE 
A LITTLE BIT MORE INTO EXACTLY WHAT'S 
IN THAT MAGICAL BOX I'VE BEEN TALKING 
ABOUT. SO ESSENTIALLY WHAT THAT 
MAGICAL BOX IS, WE'RE TAKING DATA 
OUT OF F&O, COMBINING IT WITH THE 
DATA COMING FROM THE SENSOR, SO 
THAT'S ONE SERVICE THAT WE HAVE, 
CURRENTLY HAVE HOSTING. ANOTHER 
SERVICE WE HAVE HOSTING IS THE NOTIFICATION 
OF WHAT WE CALL THE NOTIFICATION 
SERVICE. THE PURPOSE OF THE NOTIFICATION 
SERVICE IS BRING THE RESULT OF THE 
STREAM ANALYTICS BACK TO F&O SO 
THAT WE CAN SURFACE THE INSIGHTS 
IN THE CONTEXT OF F&O AND SO THAT 
YOU CAN ACT ON IT. >> ARJIT BASU: 
THIS IS VERY IMPORTANT TO UNDERSTAND 
BECAUSE YOU MIGHT HAVE THE QUESTION 
IN THE BACK OF YOUR MIND HOW THIS 
IS GOING TO PLUMMET THE SYSTEM PERFORMANCE 
BECAUSE YOU'RE DEALING WITH A LOT 
OF DATA. ONE OF THE DESIGN DECISION 
WERE TO MOVE THE PROCESSING AND 
THE RULE-MAPPING OUTSIDE OF F&O. 
SO WHAT WE ARE DOING IS WHENEVER 
YOU'RE DOING AN EVENT LIKE STARTING 
A PRODUCTION ORDER OR THINGS LIKE 
THAT WE'RE SENDING A PAYLOAD OF 
REFERENCE DATA OUT SIDE F&O AND 
THE DATA FROM THE SENSORS WHICH 
IS COMING, WE ARE PROCESSING IT 
COMPLETELY OUT SIDE F&O. SO THAT 
HUGE TERABYTES OF DATA THAT MIGHT 
HAVE HUNDRED MACHINES THAT ARE SENDING 
IT'S COMPLETELY OPERATED ON BY THE 
INTELLIGENT OPERATIONS SERVICE, 
IT DOES NOT GO AHEAD AND HIT F&O. 
ONLY WHEN AN EXCEPTION HAPPENS, 
A BUSINESS EXCEPTION HAPPENS, WE 
ARE ONLY SENDING BACK THE RESULT 
INSIDE F&O. EVEN -- I'LL SHOW YOU 
THE PRODUCT WE HAVE A STREAMING 
GRAPH, THE DATA FROM THE GRAPH IS 
ALSO COMING OUT FROM OUTSIDE F&O. 
FOR EXAMPLE IN ONE OF OUR VISUALS, 
AND I'LL SHOW YOU, WE HAVE THE PARTOUT 
SIGNAL -- LET'S SAY YOU HAVE A PRODUCTION 
ORDER THAT RUNS FOR EIGHT HOURS. 
AT THE END OF THE DAY YOU WANT TO 
ACTUALLY SEE THE TREND OF
TIME SENSE 
LOSS PARTOUT WHICH IS A KEY METRIC 
FOR A LOT OF PEOPLE WE HAVE THE 
CAPABILITY RIGHT NOW TO SHOW THAT 
ENTIRE EIGHT HOURS TREND INSIDE 
F&O AND THAT MEANS BASICALLY YOU 
HAVE TO SOMEWHERE GET THAT DATA 
INTO A GRAPH AND SHOW YOU ARE DOING 
IT COMPLETELY OUTSIDE F&O. SO IN 
TERMS OF PERFORMANCE CAPABILITY 
WE ARE ONLY MANAGING EXCEPTION INSIDE 
F&O, REST, EVERYTHING IS BEING PROCESSED 
BY THIS SERVICE WHICH SITS OUTSIDE 
FINANCE AND OPERATIONS. >> PAUL 
WU: CORRECT. >> ARJIT BASU: THIS WILL 
GIVE YOU SCALABILITY, THIS WILL 
GIVE YOU PERFORMANCE AS WELL AS 
ALL THE OTHER GOODNESS OF THE MICRO 
SERVICES ARCHITECTURE. >> PAUL WU: 
EXACTLY, EXACTLY. NOW, THE COMPUTE 
AGAINST WHICH WE'RE DOING STREAM 
ANALYTICS THAT ARJIT JUST MENTIONED, 
THAT ENGINE, IT'S -- TODAY WE'RE 
PLANNING TO USE AZURE DATA BREAKS. 
I DON'T KNOW IF YOU GUYS HAVE HEARD 
OF AZURE DATABRICKS, YES? IT'S ESSENTIALLY 
AZURE VERSION OF A PARTY SPARK. 
THAT'S A WELL-KNOWN PLATFORM, A 
VERY HEALTHY ECOSYSTEM AROUND IT 
, PERFORMS REALLY WELL. SCALES REALLY, 
REALLY WELL. SO THAT'S THE MAGIC 
COMPUTE INSIDE OF THAT BOX. FOR 
SCENARIOS LIKE MACHINE DOWN, DELAYED 
ORDERS, ANOMALY DETECTION, WE'RE 
USING AZURE DATABRICKS TO DO THE 
STREAM PROCESSING. >> ARJIT BASU: 
YEAH, AND ANOTHER INTERESTING THING 
IS WHEN YOU SET UP, I'LL SHOW YOU 
AGAIN THIS , RULES YOU DEFINE, WHEN 
-- WHERE YOU DEFINE A MACHINE DOWN 
THRESHOLD, WHERE DO YOU DEFINE THE 
QUALITY ARCHITECTURES? -- METRICS, 
THOSE THINGS ARE NOW INSIDE F&O. 
SO WHEN YOU'RE CONFIGURING FINANCE 
AND OPERATIONS, YOU WILL BE ABLE 
TO DEFINE, LIKE FOR MACHINE 1225, 
IF I DON'T GET A PARTOUT FOR 10 
MINUTES, SEND ME AN ALERT, FOR A 
DIFFERENT MACHINE IT'S DIFFERENT, 
FOR ROUTES AND THRESHOLD SETTINGS, 
THE SETTINGS ARE ALL INSIDE F&O, 
VERY STANDARD, WE ARE NOT CHANGING 
ANY OF THE EXISTING THINGS, WE'VE 
ADDED JUST BASIC ATTRIBUTES SO THE 
FAMILIARITY WITH THE MODULE DOES 
NOT CHANGE. IT'S VERY, VERY IMPORTANT 
TO UNDERSTAND THAT. AND THAT IS 
THE DATA WE SEND OUT TO BE MAPPED 
WITH FINANCE AND OPERATIONS IN AZURE 
IOT. >> PAUL WU: YEP. OK, YEAH, 
SO THAT KIND OF CONCLUDES THE ARCHITECTURE. 
LITTLE ASTERISK HERE IN TERMS OF 
WHAT EXACTLY WE'RE GOING TO SHIP 
BY -- SO IF YOU LOOK AT OUR OCTOBER 
WAVE TWO 2019 RELEASE, IOT INTELLIGENT, 
INTELLIGENT IOT IS PART OF THAT. 
'CAUSE WE HAD DIFFERENT NAMES BEFORE 
THAT. SO WE NEED TO MAKE SURE WE'RE 
SAYING THE RIGHT THINGS THERE. IOT 
INTELLIGENT, INTELLIGENT IOT IS 
PART OF THE FALL RELEASE. THE DOUBLE 
ASTERISK THERE, IT SAYS EXTENSIBILITY 
PLAN POST-GA. EXTENSIBILITY MEANS 
WE'RE GOING TO SHIP ALL THE SCENARIOS 
ARJIT HAS MENTIONED OUT OF THE BOX, 
RIGHT, YOU'RE NOT -- ALL YOU HAVE 
TO DO IS OWN THIS AZURE IOT HUB, 
RIGHT? THAT ACTUALLY SITS INTO THE 
CUSTOMER SUBSCRIPTION. NOW, WE'RE 
GOING TO HIDE ALL THE COMPLEXITY 
OF BUILDING, DEPLOY AZURE INDY CAR 
CLUSTER, MANAGING THE JOB, DEPLOYMENT 
OF A JOB, ALL THAT AWAY FROM YOU 
GUYS, WE'RE GOING TO ABSTRACT THE 
HEAVY LIFTING OF BRINGING ERB DATA 
OUT, MESH IT UP WITH IOT DATA AND 
ALSO PUTTING DATA BACK, RIGHT, WE'RE 
GOING TO HIDE ALL THAT COMPLEXITY 
BEHIND THE SCENES. THE FACT THAT 
WE'RE HIDING ALL THESE FLEX 'TIS 
MAKES EXTENSION EXTENSIBILITY STORY 
A LITTLE HARDER FOR US TO DESIGN, 
RIGHT, SO WE'RE IN THE PROCESS OF 
THINKING ON TOP OF THE SAAS OFFERING 
WE'RE GIVING YOU THE TEMPERATURESBILITY 
STORY. SO FOR THE PARTNERS IN THE 
ROOM REST ASSURED WE DON'T PLAN 
TO HAVE A VERY CLOSED SYSTEM ON 
TOP OF WHICH YOU GUYS CAN'T CUSTOM 
IZED, THIS ABSOLUTELY WILL HAVE 
A EXTENSIBILITY STORY, IT'S JUST 
PHASE ONE, WE'RE NOT GOING TO HAVE 
EXTENSIBILITY STORY RIGHT NOW, WE'LL 
SHIP WITH OUT-OF-THE-BOX SCENARIOS 
AND PHASE TWO, CHARLOTTELY AFTER 
THAT WE'LL HAVE EXTENSIBILITY STORY. 
>> ARJIT BASU: AND WE WILL BE DEPENDENT 
ON A LOT OF [INAUDIBLE] ON OUR PARTNERS 
IN THE FIELD BECAUSE THERE ARE SO 
MANY DISCRETE PROCESSING SCENARIOS 
WHICH CAN BE AUTOMATED WE'LL SHIP 
SOME TEMPLATE SCENARIOS OUT OF THE 
BOX AND THEN WE WILL WORK WITH OUR 
PATTERNS ISVS AND EXPERTS IN THE 
FIELD IN THE EXTENSIBILITY STORY 
SO YOU CAN HAVE SOMETHING VERY SPECIFIC 
FOR CHEMICALS OR VERY SPECIFIC FOR 
FOOD AND BEVERAGE SO THAT'S THE 
ULTIMATE GOAL. >> PAUL WU: THAT'S 
CORRECT. ARJIT, BACK TO YOU. >> 
ARJIT BASU: SO ENOUGH TALK. I THINK 
WE'VE KIND OF BORED YOU GUYS, LET 
SEE IT IN ACTION. SO THIS IS STANDARD 
F&O, I JUST REFRESHED IT JUST IN 
CASE IT DIED, A STANDARD OUT OF 
THE BOX MARKET. THE WI-FI? OK. IS 
HE WHAT WE'RE DOING IS WE HAVE SOME 
BASIC SETUP. SO FIRST OF ALL, IF 
I GO INTO PRODUCTION CONTROL PARAMETERS 
AND, AGAIN, THE UI WILL CHANGE BECAUSE 
THIS IS A PRIVATE PRE VIEW, THE 
NAME, TAXONOMY AND ALL THAT SO WE 
HAVE A NEW TAB CALLED CONNECTOR 
MANUFACTURING, WE CHANGED THAT AND 
HERE WE HAVE A GLOBAL THRESHOLD 
FOR MACHINE DOWN. SO I'LL WALK YOU 
THROUGH SOME OF THE BASIC SETUP 
STUFF. IN THE RESOURCES, SO IF I 
EXPAND THAT AND I -- LET'S SAY, 
MACHINES, IT SHOULD HAVE SOME -- 
HERE. SO HERE WE ALSO, THIS WILL 
BE ENABLED, SO THIS IS A DOWN TIME 
FOR A SPECIFIC MACHINE. BECAUSE 
BASED ON YOUR MACHINE'S AGE YOU 
MIGHT HAVE DIFFERENT DOWN TIME THRESHOLD 
SCENARIOS. AND THEN THERE ARE OTHER 
SETUPS WHICH ARE VERY SPECIFIC TO 
A ROUTE BECAUSE AND AS WELL AS THE 
QUALITY ATTRIBUTES AND STUFF. SO 
THE SETUP WILL BE VERY, VERY SIMILAR 
TO THE SYSTEM. NOW WHAT WE'LL ALSO 
DO OUT HERE IS THIS IS THE PRODUCTION 
WORKSPACE. EVERYONE'S SEEING IT, 
YOU'VE USED IT, PROBABLY GOT BORED 
WITH IT BUT WHAT WE'RE GOING TO 
DO IS WE HAVE ANOTHER TAB OUT HERE, 
SO ONCE YOU'VE ENABLED THE SERVICE, 
IT'S CALLED NOTIFICATIONS PRE VIEW, 
WE PROBABLY WILL HAVE A BETTER NAME 
FOR THAT ONCE WE MOVE TOWARD AVAILABILITY, 
WHAT THIS DOES -- THIS IS GOING 
TO BE AN EXPERIENCE FOR THE PRODUCTION 
MANAGER, OKAY, THE SHOP FLOOR WORKER 
EXPERIENCE IS DIFFERENT. THEY'LL 
START FROM THE JOB CAR TON AND THEN 
MOVE FORWARD. SO THE PRODUCTION 
MANAGER WILL HAVE THIS ENABLED AND 
ONCE THEY CLICK ON IT, BEFORE I, 
YOU KNOW, MOVE IT, THIS IS THE PLACE 
WHERE THE NOTIFICATIONS ARE GOING 
TO COME, THE EXCEPTION NOTIFICATION 
S ARE IOT HUB AND RELATED TO YOUR 
MACHINE'S ANNUAL PRODUCTION ORDER. 
AND FROM THEE MODIFICATIONS YOU'RE 
GOING TO DEEP DIVE TO A DETAILED 
SCREEN WHERE AS A PRODUCTION MANAGER 
YOU CAN FILTER WHAT RESOURCE GROUPS 
YOU HAVE, VERY STANDARD. IF I CLICK 
ON THIS THIS IS BASICALLY THE NOTIFICATION 
SCREEN. I WILL CLICK ON SHOW DETAILS. 
NOW, IF I CLICK ON SHOW DETAILS 
IT'S GOING TO TAKE ME TO ANOTHER 
SCREEN WHERE HERE ON THE LEFT-HAND 
SIDE -- AND I HAVE SIMILAR RELATED 
MACHINES RUNNING IN THE BACKGROUND, 
OBVIOUSLY, YOU KNOW, OUR TEAM DOESN'T 
HAVE THE BUDGET TO BUILD A MULTI- 
MILLION DOLLAR MACHINE, BUT THESE 
ARE THE MODIFICATIONS THAT YOU WILL 
SEE FOR MACHINE DOWN AND ORDER DELAY 
COMING IN DIRECTLY FROM IOT HUB. 
SO IF I LOOK AT THIS JOB SOMETHING 
RUNNING ON 1221 IS DELAYED YOU WILL 
NOT ONLY SEE THE DELAY ALERT BUT 
YOU WILL BE ABLE TO SEE ACTION AND 
RELATED INFORMATION. SO THE RELATED 
INFORMATION IS HOW MUCH WAS EXPECTED 
AND HOW MUCH YOU'VE COMPLETED, VERY, 
VERY IMPORTANT. THIS ORDER IS FOR 
WHICH CUSTOMER , WHEN IS THE DELIVERY 
DATE AND WE CAN ADD MORE DETAILS 
BECAUSE THIS IS STILL FLUID. BECAUSE 
THE MAGIC IS, JUST BY GETTING A 
PARTOUT SIGNAL, I'M ABLE TO CORRELATE 
IT TO WHICH PRODUCTION ORDER IS 
RUNNING BECAUSE A IOT OR A MACHINE 
WILL NEVER GIVE YOU THE PRODUCTION 
ORDER, THE CUSTOMER ORDER AND THINGS 
LIKE THAT. NO, THE BEAUTY IS IF 
YOU'VE SEEN THIS GRAPH WHILE I WAS 
SPEAKING, THIS IS KIND OF UPDATES 
EVERY 15 SECONDS. THIS BASICALLY 
GIVES YOU A TIME- SENSE LOSS PARTOUT. 
AND THIS IS STREAMING DATA WHICH 
IS COMING LIVE FROM A CACHE WHICH 
IS BEING FED FROM IOT HUB. SO THIS 
IS A VERY KEY METRIC WHICH A PRODUCTION 
MANAGER WOULD LIKE TO SEE IS THE 
FREQUENCY BECAUSE YOU REALLY DON'T 
WANT TO GET A NOTIFICATION, YOU 
WANT TO UNDERSTAND TREND. BECAUSE 
IF YOU'RE GETTING DELAYS OR ALERTS 
OR NOTIFICATION EVERY HOUR YOU HAVE 
A BIGGER PROBLEM IN HAND. SO THIS 
IS THE PART WE ARE SHOWING. YOU 
ALSO HAVE THE OPTION TO SEE THE 
LAST ONE HOUR. YOU HAVE THE OPTION 
TO SEE THE LAST THREE HOURS. AND 
WE ARE ADDING FEATURES TO A CONCEPT 
OF A SHIFT LEVEL SO YOU CAN SEE 
THAT. YOU HAVE THE OPTION TO TAKE 
AND DRILL DOWN INTO A VERY SPECIFIC 
SOMETHING [INAUDIBLE]. YOU CAN FIND 
OUT AS A PRODUCTION MANAGER A SPECIFIC 
TIME, WHAT WAS THE PARTOUT, SO YOU 
HAVE THE FLEXIBILITY OF LOOKING 
AT THE ENTIRE DURATION OF THE PRODUCTION 
ORDER AS WELL AS THE TREND. SO I 
JUST RESET IT. NOW, FOR THIS MACHINE, 
I'LL JUST CHANGE THIS, THIS IS ALSO 
GOING TO GIVE YOU THE IMPACTED ORDERS 
WHICH ARE SCHEDULED ON THAT WORK 
CENTER. SO WE'VE CURRENTLY DONE 
IT AT THE 36-HOUR LEVEL BUT WE'LL 
MAKE IT PARLIAMENT TERRIZED SO AS 
A CONFIGURABLE LEVEL YOU CAN DEFINE 
IT HERE FOR THE NEXT -- MY TIME 
FRAME IS SIX HOURS OR 24 HOURS, 
SHOW ME ALL THE ORDERS. IF MY MACHINE 
WAS SUPPOSED TO FINISH PRODUCTION 
LIKE 12:00 AND IT'S GOING ON TILL 
TWOSK SHOW ME THE ORDERS THAT ARE 
BEING IMPACTED. SO RIGHT FROM THIS 
SCREEN I HAVE THE OPTION TO REPRIORITIZE 
THEM, CHANGE THE PRIORITY, I CAN 
RE ASSIGN THEM, VIEW THE PROGRESS 
, AND EVEN LOOK AT GANTT CHARTS. 
SO THE DASHBOARD FOR THE PRODUCTION 
MANAGER IS BASICALLY SEEING THE 
NOTIFICATIONS, AND THIS IS A STOP 
PRODUCTION DELAYED ORDERS. SO WE 
ALSO HAVE NOTIFICATIONS FOR QUALITY 
SCENARIOS. AND RIGHT NOW WE HAVE 
A CREATE WORK ORDER WHICH IS MANUAL 
BUT GOING FORWARD, FOR SCENARIOS 
LIKE THIS, YOU WILL BE ABLE TO GO 
AHEAD AND AUTOMATICALLY CREATE MAINTENANCE 
REQUESTS OR WORK ORDERS FOR DIFFERENT 
SCENARIOS. SO WE WILL MAKE THAT 
CONFIGURABLE. SO THIS IS LITERALLY 
BASICALLY SHOP FLOOR TO THE TOP 
FLOOR. WHERE THE SCREEN IS VERY 
SIMPLE. IT'S VERY FAMILIAR, WORKSPACE 
WHICH A PRODUCTION MANAGER USES 
IN F&O BUT IT'S NOW ENRICHED WITH 
SENSOR DATA AND ALERTS AND TRIGGERS 
SO THAT YOU HAVE MUCH MORE INTELLIGENT 
INSIGHT. SO IT'S JUST NOT A DUMB 
NOTIFICATION, IT'S LIKE ERROR CODE, 
CONTACT YOUR ADMINISTRATOR THESE 
ARE ACTIONABLE NOTIFICATIONS WHICH 
WE ARE GOING TO DRIVE. AND GOING 
FORWARD, WE'LL HAVE A CONFIGURED 
WAY YOU CAN DEFINE THE SCREEN AS 
WELL. SOMETHING NOT THERE PREVIOUSLY 
IN F&O. SO THIS IS BASICALLY THE 
DASHBOARD WHICH THE PRODUCTION MANAGER 
SHOULD BE ABLE TO SEE. NOW, THE 
COOL PART IS -- OBVIOUSLY, YOU GET 
NOTIFICATIONS , SOMEONE HAS TO ACT 
ON THAT OTHERWISE, YOU KNOW, YOU 
NEED TO TAKE THEM OFF YOUR QUEUE. 
SO WHAT DO YOU DO? HERE WHAT WE 
HAVE HERE IS WE HAVE A CLOSE OPTION, 
SO THAT WHEN YOU HAVE -- AND WE 
WILL HAVE AN OPTION CALLED REACTIVITY 
ELEVATE AND SNOOZE AS WE MOVE ALONG. 
SO AS A PRODUCTION MANAGER, YOU 
SEE SOMETHING, YOU'VE CREATED A 
WORK ORDER OR THE MECHANIC HAS GONE 
IN AND LOOKED AT IT, YOU CAN LITERALLY 
GO HERE AND YOU CAN CLOSE A NOTIFICATION. 
WE WILL HAVE A REASON CODE HERE 
AS TO WHY THIS WAS CLOSED OR WHY 
THE PROBLEM WAS ADDRESSED, AND I 
JUST SAY NO. AND HERE IN THE CLOSE 
NOTIFICATION, WE WILL HAVE A LOG 
OF ALL THE NOTIFICATION THAT CAME 
WITHIN A SPECIFIC JOB, LIKE A PRODUCTION 
ORDER, WHAT WERE THE ACTIONS THAT 
WERE TAKEN, WHO WAS IT TAKEN BY 
AND WHAT WAS THE DURATION. SO YOU 
CAN LITERALLY GET OVERALL EQUIPMENT 
EFFICIENCY NEAR REAL-TIME. SO YOUR 
MACHINE ON TIME BECOMES NEAR REAL-TIME 
AND YOU'LL BE ABLE TO LEVERAGE THIS 
DATA TO COME UP WITH ANALYTICS LITERALLY 
DURING A PRODUCTION ORDER RUN AND 
THEN USE IT FOR ANY OTHER KIND OF 
APPROACHES. WE WILL ALSO LINK THIS 
NOTIFICATION SCREEN WITH MICROSOFT 
FLOW SO THAT'S NOT ONLY THAT YOU 
HAVE TO LOG INTO F&O TO SEE THIS 
SCREEN. SO WITH THE LEVERAGING BUSINESS 
EVENTS AND MICROSOFT FLOW TEMPLATES, 
YOU WILL BE ABLE TO REDIRECT THESE 
NOTIFICATIONS INTO A MOBILE DEVICE, 
E-MAIL, OR ANY CONNECTOR THAT BASICALLY 
MICROSOFT FLOW SUPPORTS SO THAT 
YOU HAVE THE RIGHT INFORMATION WITH 
THE RIGHT SORT OF ERROR CODES AND 
MACHINE DATA TO THE CONCERNED PERSON 
EVEN IF THEY ARE PHYSICALLY PRESENT 
IN OFFICE OR NOT. SO THIS IS BASICALLY 
WHAT'S -- WE HAVE BEEN WORKING ON 
FOR THE LAST COUPLE OF MONTHS, ON 
BRINGING THE FIRST KIND OF SHOP 
FLOOR TO THE TOP FLOOR SCENARIO 
WHERE WITHIN F&O WE WANT TO ENRICH 
THE EXPERIENCE GOING FORWARD. NOW, 
COMING BACK, SO THIS IS THE FIRST 
PART. WHAT DO WE PLAN TO DO MOVING 
AHEAD? SO DEFINITELY WE WILL HAVE 
THE GENERAL AVAILABILITY AND PUBLIC 
PREVIEW OF THIS, WE ALREADY HAVE 
TWO CUSTOMERS, WE HAVE A COUPLE 
OF CUSTOMERS WHO ARE IN THE PIPELINE. 
IF ANY OF YOU WHO ARE INTERESTED 
IN PILOTING IT JUST LET PAUL OR 
MYSELF KNOW OR DROP US AN E-MAIL 
WE CAN MEET YOU OUTSIDE THIS. SO 
ABSOLUTELY HAPPY TO WORK ON WITH 
THIS WITH YOU GUYS. SO INDUSTRY 
SCENARIOS, SO WE WILL BE WORKING 
WITH MAD ISVS EXTENDING THESE PACKAGES 
LIKE THESE BLOCKS. WE WILL HAVE 
AN ON-BOARDING, EXPERIENCE, BECAUSE 
UNDER THE COVER THERE'S A LOT OF 
WORK. SO SUPPOSE YOU ARE A CUSTOMER, 
WE HAVE TO CONNECT TO YOUR IOT HUB, 
CONNECT TO YOUR ANALYTICS, THERE'S 
PROBABLY A HUNDRED THINGS WE DO 
UNDER THE COVER, WE DON'T WANT YOU 
TO DO THAT AS PAUL SAID, WE WANT 
YOU TO WALK THROUGH LIKE A FIVE-BY-FIVE 
EXPERIENCE. SO WE WILL BE FOCUSING 
ON [INAUDIBLE] PROCESS DISCRETE 
ENDING SO IF YOU WOULD LIKE TO GET 
IN TOUCH, ABSOLUTELY PLEASE E-MAIL 
US. EXTENSIBILITY, AS PAUL MENTIONED 
, AFTER GENERAL ABILITY , TO ENABLE 
ISV OR PARTNER KIND OF ENGAGEMENT, 
WE HAVE TO DO THE EXTENSIBILITY. 
SO EXTENSIBILITY IN TERMS OF SERVICE, 
EXTENSIBILITY IN TERMS OF THE F&O 
COMPONENT AS WELL AS AVAILABILITY 
OF THE SPECIFIC SERVICES LIKE AN 
APP SOURCE OR ANY OTHER AREAS SO 
EXTENSIBILITY ARE THE SCENARIO SOMETHING 
WE'LL BE WORKING ON. THIRD ONE IS 
THE END-TO-END EXPERIENCE WE'LL 
BE LIGHTING UP A LOT OF SCENARIOS 
IN ASSET MAINTENANCE. THE KEY ONE 
IS PREDICTIVE MAINTENANCE. SO PREDICT 
ONCE WE HAVE THE SENSOR DATA AND 
ALL THAT STUFF COMING IN AND DUMPING 
INTO A DATA, WE WILL BE ABLE TO 
11 POWER AI AND AZURE ON TOP OF 
THAT DATA AND PUSH AUTOMATIC WORK 
ORDERS INSIDE F&O AND THIS WILL 
BE DONE USING THE DATA PIPELINE 
BECAUSE THE REAL CHALLENGE IS IDENTIFYING 
A SENSOR ON A MACHINE, WHAT MACHINE 
IT IS SO WE'RE SOLVING THAT DIFFICULT 
PART SO THAT YOU DON'T HAVE TO. 
THE CONNECTED EXPERIENCE WILL BE 
RICHER. WE'LL BE LOOKING AT WORKING 
WITH IOT CENTRAL IN SOME POINT OF 
TIME WE'LL BE LOOKING AT EDGE DEVICES. 
WE WILL BE LOOKING AT INTEROPERABILITY 
WITH THE AZURE DIGITAL TWIN SO AS 
TO ENABLE A MUCH RICHER SEAMLESS 
EXPERIENCE IN THE IOT WORLD AND 
INDUSTRIAL IOT AND LAST ONE INSIDE 
INTELLIGENT AND AS PART MENTIONED 
WE WILL BE TAKING A LOT OF THIS 
DATA WHICH WE WILL HAVE AND WE'LL 
PUT IT INTO A DATA LAKE OR SOME 
STORAGE WHICH WE WILL BE GIVING 
ACCESS TO YOU BECAUSE WE DON'T WANT 
TO CREATE ALL THE REPORTS IN ANALYTICS, 
THEY'RE ABSOLUTELY INDEPENDENT OF 
EVERY CUSTOMER. SO YOU WILL BE ABLE 
TO GO AHEAD AND KIND OF MAKE YOUR 
OWN CHARTS , GRAPHS, AND RICH ANALYTIC 
SCENARIOS USING THAT DATA. SO SOME 
OF THESE BASIC SCENARIOS , THE AREAS, 
BIG INVESTMENT AREAS ARE SOMETHING 
WHICH WE ARE GOING DO WORK ON. WE'D 
LOVE TO HEAR BACK FROM YOU AND ALSO 
LOOK AT OPPORTUNITIES WHERE WE CAN 
WORK TOGETHER. BUT I THINK FROM 
FIRST OF ITS KIND WHERE OUR TEAM'S 
BEEN WORKING VERY HARD TO LIGHT 
UP THE BASIC SCENARIO OF MOOSHING 
DOWN, SO IOT SENSOR INTO DYNAMICS 
365 F&O. SO WE HAVE 15 MINUTES LEFT, 
LAST SESSION, I'D LIKE TO OPEN IT 
UP FOR ANY Q&A AND PROBABLY GIVE 
YOU SOME TIME BACK. YES. SO I THINK 
THE LADY WAS FIRST. YES. >> QUESTION 
[INAUDIBLE] >> PAUL WU: THE QUESTION 
IS WHAT'S THE TIME FRAME FOR PUBLIC 
J. SO RIGHT NOW IT'S OCTOBER. SO 
THE WAVE TWO 2019 RELEASE. >> PAUL 
WU: THE PLAN IS WE'RE GOING TO DO 
A CONTROLLED PUBLIC PREVIEW. >> 
ARJIT BASU: CONTROLLED PUBLIC PREVIEW 
[INAUDIBLE] WE DON'T HAVE THE ON-BOARDING 
EXPERIENCE BUILT IN SO OUR ENGINEERING 
TEAMS WILL WORK WITH A HANDFUL OF 
CUSTOMERS WHO ARE READY TO DO THE 
PUBLIC PREVIEW SO WE'LL KEEP IT 
CONTROLLED BUT ABSOLUTELY GET IN 
TOUCH WITH US AND WE'LL HAVE NOTIFICATIONS 
AND ANNOUNCEMENTS MORE ON THESE 
AND THEN WE'RE LOOKING AT A GA DATE 
IN OCTOBER. >> PAUL WU: YEP, GA 
DATE IS OCTOBER. >> ARJIT BASU: 
YEAH. >> [QUESTION INAUDIBLE] >> 
ARJIT BASU: GOOD QUESTION. THE QUESTION 
IS THAT BLUE BOX, IS IT STILL GOING 
TO BE A BLACK BOX FOREVER OR ARE 
WE GOING TO OPEN IT UP. SO AS PAUL 
MENTIONED, FOR THIS YEAR, OCTOBER 
IN A COUPLE OF MONTHS WE WILL KEEP 
IT AS A BLACK BOX. >> PAUL WU: YES. 
>> ARJIT BASU: BUT WE HAVE TO ENABLE 
THE EXTENSIBILITY AND THE STORY 
LIKE EXPOSE APIs AND STUFF BECAUSE 
IT'S A SERVICE SO THAT'S DEFINITELY 
IN THE ROAD MAP BUT NOT BEFORE OCTOBER. 
>> PAUL WU: AND JUST TO ADD TO THAT 
THE SCENARIO IS NOT SO SIMPLE, OH, 
I'VE GOT MY SENSOR, I'VE GOT MY 
GATEWAY SENSOR, PUMP IT INTO IOT 
HUB AND CALL IT GOOD BECAUSE HARDWARE 
VENDORS DON'T GIVE YOU THAT TELEMETRY 
INFORMATION, YOU DON'T HAVE ACCESS 
TO THE SENSORY DATA. THEY PART THOSE 
TELEMETRY DATA IN THEIR OWN CLOUD. 
SOMETIMES WE'RE ACTUALLY TALKING 
TO API, RIGHT, SO THESE ARE GOING 
TO BE THE LEARNINGS THAT WE'LL BE 
GATHERING AND GETTING IN THE NEXT 
COUPLE OF MONTHS BY WORKING WITH 
SOME OF YOU GUYS. >> ARJIT BASU: 
YEAH, AND ALSO LIKE WHEN YOU'RE 
GETTING DATA INTO THE IOT HUB WE 
NEED TO HAVE IT IN A STANDARD FORMAT 
SO WE CAN DO THE MAPPING SO WE'RE 
WORKING ON THAT TO GET A STANDARDIZATION. 
DOES THAT ANSWER YOUR QUESTION? 
>> YES, THANK YOU. >> [QUESTION 
INAUDIBLE] >> ARJIT BASU: YES, WE 
WILL -- WE WILL -- SO WE WILL GIVE 
-- I MEAN I INTERCHANGED -- THE 
QUESTION IS WHEN I DO PREDICTIVE 
MAINTENANCE AND, YOU KNOW, IN THE 
NEAR FUTURE AND WE CREATE A WORK 
ORDER, IS IT ONLY THAT IT'S GOING 
TO BE A WORK ORDER BUT CAN IT BE 
A MAINTENANCE REQUEST AS WELL? SO 
THE ANSWER IS WE'RE GOING TO HAVE 
AN OPERATING TO CONFIGURE THAT YOURSELF. 
SO IF IT'S A WORK ORDER, DO IT. 
IF IT'S A MAINTENANCE REQUEST AND 
WHAT TYPE OF MAINTENANCE REQUEST 
IT IS, SO IT CAN BE ROUTED TO THAT 
WAY. SO WE WILL GIVE A CONFIGURATION 
OPTION. >> PAUL WU: YEAH, IT WILL 
BE CONFIGURABLE. >> [QUESTION INAUDIBLE] 
>> ARJIT BASU: CORRECT. >> PAUL 
WU: CORRECT. >> ARJIT BASU: CORRECT. 
>> PAUL WU: YES. >> ARJIT BASU: 
WE WILL MAKE IT TO KNOW FIGURABLE. 
>> [QUESTION INAUDIBLE] >> PAUL 
WU: THE WAY IT'S ARCHITECTED TODAY, 
THE CUSTOMER HAS OWNER SHIP OF THE 
IOT HUB. >> ARJIT BASU: YEAH, IF 
YOU GIVE ME AN IOT HUB WHICH IS 
YOUR CUSTOMER STUFF, WE'LL BE ABLE 
TO WORK WITH IT. NOW, FOR THE BILLING 
PART, HOWEVER, SO THAT'S SOMETHING 
WE WILL LOOK AFTER OCTOBER, IF YOU 
ARE DOING WORK ON THAT CUSTOMER 
STUFF AND WE LINK IT UP WITH THE 
ASSET MANAGEMENT AND WE [INAUDIBLE] 
RIGHT NOW WHAT WE HAVE TODAY IS 
THE CUSTOMER-OWNED IOT HUB. WE JUST 
TELL YOU OR WE WILL TELL YOU DURING 
THE ON-BOARDING PROCESS THAT SIGN 
INTO AZURE, WE WILL SUCK UP ALL 
THE AZURE IOT HUBS YOU HAVE YOU 
CAN SELECT ONE OR MORE IOT HUB BECAUSE 
YOU MIGHT HAVE MANY AND THEN IT'S 
GOING TO GO AHEAD AND FILL IN THE 
DEVICES CATALOG, LIKE THE NODE ID 
AND THE APPLICATION ID DIRECTLY 
FROM THE SPECIFIC IOT HUB. >> PAUL 
WU: MARCO, I THINK -- ARJIT GOOD 
POINT BUT I THINK YOUR QUESTION 
IS HOW DO YOU BUILD NEW SCENARIOS 
ON TOP OF DATA, NOT ONLY ENRICHED 
WITH F&O ERP BUT ALSO FROM THIRD-PARTY 
APPLICATIONS, IS THAT WHERE YOU 
WERE GOING, RIGHT? SO, YEAH, TODAY 
THE WAY IT'S BEING ARCHITECTURED, 
WE'RE ONLY GOING TO WORK WITH OUR 
OUT-OF-BOX FIVE OR SIX SCENARIOS 
THAT ARJIT HAS LISTED BUT HOWEVER 
BECAUSE THE OWNERSHIP OF THE HUB 
REALLY BELONGS TO THE CUSTOMER. 
THERE'S NOTHING PREVENTING THE CUSTOMER 
TO SAY, YEAH, YOU KNOW WHAT, I'M 
GOING TO USE MY OWN INDY CAR CLUSTER, 
BECAUSE I OWN A IOT HUB I CAN CONNECT 
TO MY IOT HUB STREAM AND I CAN PUMP 
TO OTHER CONNECTIONS, I CAN DO MY 
OWN STREAM ANALYTICS. THAT'S NOTHING 
PREVENTING YOU OR OTHER CUSTOMERS 
FROM DOING THAT TODAY. ALL WE'RE 
SAYING IS FOR THE CUSTOMER WHO SAYS 
I DON'T HAVE A BIG IOT TEAM, I DON'T 
WANT TO GET MY GUYS TO MANAGE A 
WHOLE BUNCH OF INDY CAR CLUSTERS, 
I DON'T WANT THEM TO LEARN PISON 
OR SCALA I WANT OUT-OF-BOX EXPERIENCE, 
FIVE-MINUTE EXPERIENCE LAY DOWN 
MY MACHINE ORDER. THIS IS WHAT WE'RE 
TARGETING TODAY. >> ARJIT BASU: 
WE START SIMPLE AND THEN OPEN IT 
UP WITH EXTENSIBILITY AND SCENARIOS 
AND DIE EMPLOYABLE PACKAGES AND 
ALL THAT, LIKE BUNDLES LIKE BUSINESS 
EXPERIENCE AFTER THE GA. >> PAUL 
WU: NOTHING PREVENTING YOU FROM 
DOING THE SAME BECAUSE YOU OWN THE 
HUB. >> ARJIT BASU: YES. >> [QUESTION 
INAUDIBLE] >> ARJIT BASU: YES, SO 
THE DATA PIPELINE -- THE QUESTION 
IS IF YOU WANT TO GET EXTERNAL DATA 
IN AND CAN WE PLUG THAT BACK INTO 
F&O FOR ALERTS LIKE AUTOMATIC PALETTE 
CREATION AND STUFF LIKE THAT, YES, 
THE ARCHITECTURE WE ARE DESIGNING 
ON IS BASICALLY -- TODAY WE ARE 
MAPPING IOT DATA WITH F&O DATA. 
NOTHING WILL STOP YOU FROM GETTING 
A TARGET DATA INTO THE MAPPING AND 
THEN PUSHING BACK EXCEPTIONS AND 
LETTERS. YES, MARCO. >> [QUESTION 
INAUDIBLE] >> ARJIT BASU: YES, SO 
I'M SURE THERE WILL BE BUT NONE 
OF US WORRY ABOUT THAT. [LAUGHTER] 
>> PAUL WU: THAT'S A VERY GOOD QUESTION. 
I'D BE LYING IF I DIDN'T PREDICT 
SOMEBODY WOULD ASK THAT QUESTION 
BUT -- >> ARJIT BASU: THERE WILL 
BE SOMETHING DEFINITELY. WE JUST 
DON'T LOOK CURRENTLY WHAT THE MODEL 
IS, LIKE WHERE OUR MARKETING AND 
PRODUCT MARKETING TEAM AND FINANCE 
WORK. >> PAUL WU: THE GOOD NEWS 
IS HERE THE ENGINEERING TEAM IS 
MOVING FASTER THAN THE MARKETING 
TEAM IN THIS CASE. >> ARJIT BASU: 
FOR A CHANGE. [LAUGHTER] YEAH. ANY 
QUESTIONS? >> WHAT YOU DESCRIBED 
IN THE IOT HUB SOUNDED TO ME LIKE 
A FULL- BLOWN DATA [INAUDIBLE] DIRECT 
[INAUDIBLE] THAT YOU'RE GOING TO 
REPLACE HONEYWELL AND THOSE DATA 
HISTORIANS? >> ARJIT BASU: NO, NO. 
>> PAUL WU: NO. SO THE IOT HUB IS 
BASICALLY A HUB THAT GATHERS IOT 
TEAM INFORMATION. THREE GUARANTEES. 
SO IN TERMS OF GUARANTEED DELIVERY, 
RIGHT, SEND ONLY ONCE, AT LEAST 
ONCE, AT MOST ONCE GUARANTEED DELIVERY 
OF ANY SENSORY DATA COMING FROM 
ON PREM SENSORY. IT DOES NOT PROVIDE 
A PERMANENT STORAGE OF THAT INFORMATION. 
>> ARJIT BASU: CORRECT. THE IOT 
HUB CAN ONLY STORE DATA FOR SEVEN 
DAYS, OKAY, AND THEN IT HAS TO BE 
MOVED OUT. THE BEAUTY OF IF YOU 
LOOK AT HISTORIAN, MASSIVE DATA, 
PUMPING IN DATA. IOT HUB IS BIDIRECTIONAL 
TODAY, IOT HUB CAN DO CLOUD-TO-DEVICE 
AND DEVICE-TO-CLOUD COMMUNICATION 
SECURELY AND DO OTHER COMPLEX STUFF 
LIKE THAT AND INTERACT WITH YOUR 
EDGE DEVICES AND AZURE SPHERE AND 
STUFF LIKE THAT SO THAT'S WHY WE'VE 
TAKEN IOT HUB AND TO THE DOWNSTREAM 
OF IOT HUB, THE GATEWAY AND THE 
OPC CONNECTORS AND SERVERS AND ULTIMATELY 
THE P LCS AND THE SENSORS, WE'RE 
COMPLETELY TRANSPARENT OF THAT. 
YOU ARE TREE TO -- FREE TO ADOPT 
WHATEVER ARCHITECTURE YOU HAVE AS 
LONG AS YOU GET THE DATA -- YOU 
CAN USE ICONNICS, OPC GATEWAY, DOESN'T 
MATTER, WE HAVE COMPLETELY TRANSPARENT. 
AS LONG AS YOU GIVE IT IN A SPECIFIC 
FORMAT WHICH CONFORMS TO A STANDARD 
JSON FILE WHICH WE WORK HAND-ON-HAND 
WITH OUR CUSTOMERS SO WILDCAT TAKE 
THAT DATA IN AND CAN CONFIGURE, 
WE ARE GOOD. >> PAUL WU: YEP, YEP,, IOT 
HUB IS NOTHING BUT A -- IT ACTUALLY 
IS AN AZURE EVENT HUB UNDERNEATH 
THE HOOD. >> ARJIT BASU: YEAH, SO 
THAT'S RESPONSIBLE FOR DATA [INAUDIBLE] 
AND DISTRIBUTION, PLUS DEVICE -TO-CLOUD, 
CLOUD-TO-DEVICE , FAILOVER AND A 
WHOLE BUNCH OF THINGS, IT'S NOT 
MEANT TO REPLACE -- IT WILL ONLY 
STORE DATA SEVEN DAYS MAX BEFORE 
YOU HAVE TO MOVE IT TO A BLOB OR 
DATA LAKE OR ANYTHING LIKE THAT 
WHAT WE'RE DOING IS TAKING THE DATA 
FROM THE IOT HUB, INJECTING BUSINESS 
DATA. THAT'S VERY IMPORTANT. SIGNAL 
OF PARTOUT COMES RIGHT NOW AT THIS 
TIME STAMP I SHOULD BE ABLE TO TELL 
HERE THIS IS PROVIDING THIS WIDGET 
WHICH IS THIS CUSTOMER AND THIS 
IS THE JOB ORDER AND THIS WAS SUPPOSED 
TO START FROM A TO B AND RUNNING 
ON THIS RESOURCE, SO WE CAN [INAUDIBLE] 
THE ENTIRE LIFE CYCLE OF THAT BINARY 
SIGNAL THAT COMES IN FROM THE MACHINE, 
INCLUDING FINDING OUT WHAT MACHINE 
IT IS, BECAUSE, YOU KNOW , THE SENSOR, 
IF I WERE A LITTLE BIT TECHNICAL, 
SENSOR WILL NOT GIVE YOU THE MACHINE 
MODEL -- IT WILL JUST GIVE YOU AN 
OLD ID AND APPLICATION ID AND JUST 
BY LOOKING AT IT YOU WILL HAVE NO 
CLUE AS TO WHICH SOURCE THIS IS 
IN F&O. WE'RE DOING THE HEAVY LIFTING 
FOR YOU, MAPPING, CONFIGURATION, 
WHAT WE NEED IS SCENARIOS AND SUPPORT. 
>> PAUL WU: YES. >> [QUESTION INAUDIBLE] 
>> ARJIT BASU: YES, SO THE QUESTION 
IS CAN IT BE INTEGRATED WITH A TOOLING 
SERVICE. SO IF I TAKE A STEP BACK, 
THIS IS THE DATA PIPELINE, WHAT 
WE DISCOVERED, IT HELPS YOU CONNECT 
SENSOR SIGNALS TO F&O. FOR THE FIRST 
SCENARIO, WHAT WE ARE DOING IS WE 
ARE TAKING THOSE SENSOR SIGNALS 
FROM MACHINE AND CONNECTING IT TO 
F&O SOURCE. IF I EXPAND YOUR SCENARIO, 
IF YOU ARE TOOLING EQUIPMENT CAN 
GIVE ME DATA OF TOOL USAGE IN A 
SPECIFIC JSON FORMAT THE DATA PIPELINE 
CAN MAP IT NOW WITH NOT A MACHINE, 
BUT MAYBE AN ITEM WHICH MIGHT BE 
A CONSUMABLE TOOL AND THEN PASS 
ON THE INFORMATION BECAUSE THAT'S 
VERY SIMILAR WHAT WE ARE GOING TO 
DO WITH ASSET MAINTENANCE IS I CAN 
HAVE AN ASSET WITH COUNTERS AND 
THOSE COUNTERS CAN COME IN FROM 
A CAR ENGINE. DOESN'T MATTER. WHAT 
THIS DATA PIPELINE IS GOING TO DO 
IS TAKE AN IOT SIGNAL, A SPECIFIC 
TAG AND A TIME STAMP AND LINK IT 
WITH AN ASSET OR A DIGITAL RECORD 
INSIDE F&O. >> PAUL WU: LET ME ASK 
JUST A CLARIFICATION QUESTION, WHEN 
YOU SAY TOOLING, ARE YOU REFERRING 
TO LIKE THE END-TO-END MANAGEMENT 
AND MAINTENANCE OF THE IOT PIPELINE? 
LIKE THE TELEMETRY -- SO FOR EXAMPLE 
SEEING'S THIS IS BLACK BOX IOT TO 
YOU GUYS SO COMING TO WORK TODAY 
I'M EXPECTING TO SEE THAT CURVE 
LINE, INSTEAD OF SEEING A CURVED 
LINE I SEE A STRAIGHT LINE. LIKE 
WHAT HAPPENED WHERE DO I GO DO DEBUG, 
IS THAT WHAT YOU'RE TALKING ABOUT 
OR -- >> [QUESTION INAUDIBLE] >> 
PAUL WU: YEAH, YEAH, YEAH THAT'S 
A GOOD QUESTION. LIKE WE SAID THE 
PLAN RIGHT NOW IS FOR US TO ASSISTIVE 
THE WHOLE THING AS A SAAS OFFERING. 
WE'RE RESPONSIBLE FOR PROVIDING 
THE SLA FOR THE SERVICE, IF IT'S 
DOWN IT'S AN ICM TICKET TO US. JUST 
LIKE WHEN YOUR F&O IS DOWN, YOU 
SEND US AN ICM TICKET. >> ARJIT 
BASU: BUT THAT'S ALSO A VERY GOOD 
POTENTIAL FOR AN ISC OR PARTNER 
BECAUSE THEY DON'T WORRY ABOUT THE 
PLUM BEING UNDERNEATH IT IT'S JUST 
TAKING DATA FROM IOT HUB MAPPING 
IT WITH MAYBE A DIFFERENT ENTITY 
INSIDE F&O AND THEN UPDATING COUNTERS 
OR THINGS LIKE THAT. BECAUSE WE'VE 
KIND OF KEPT IT VERY LOOSELY COUPLED 
BECAUSE WE WANT TO USE THE PIPELINE, 
THE CONNECTIVITY OF THE REAL WORLD, 
THE DIGITAL AND THE PHYSICAL PIPELINE 
MAPPING FOR USABILITY. OK. ANY OTHER 
QUESTIONS? THERE IT IS. >> [QUESTION 
INAUDIBLE] >> ARJIT BASU: GO AHEAD. 
>> PAUL WU: SO THERE'S ACTUALLY 
MULTIPLE ASPECTS TO THAT QUESTION. 
NUMBER ONE IS -- >> ARJIT BASU: 
I'LL REPEAT THE QUESTION. >> PAUL 
WU: YEAH. THE QUESTION IS HOW DO 
I MAKE SURE THE IOT SENSORY DATA 
THAT I HAVE CORRECTLY MAPPED TO, 
SAY FOR EXAMPLE THE WORK ORDER I 
HAVE IN MY SYSTEM? THERE'S ACTUALLY 
MULTIPLE ASPECTS TO THAT. ONE IS 
THE MAPPING, ONE IS -- >> ARJIT 
BASU: SENSING. >> PAUL WU: YEAH, 
SEQUENCING. WHAT IF THE DATA WAS 
ANY STREAM ANALYTICS, I'M ALWAYS 
LOOKING AT THE CURRENT TUMBLING 
WINDOW, WHAT IF AT THAT TIME I RECEIVED 
AN EVENT THAT ACTUALLY TOOK PLACE 
IN THE PAST, RIGHT, HOW DO I -- 
DO I AGGREGATE IT AGAINST MY CURRENT 
WINDOW OR AGGREGATE IT AGAINST A 
WINDOW THAT ACTUALLY HAPPENED IN 
THE PAST? THESE TYPE OF FUNDAMENTAL 
GUARANTEED DELIVERY AND TUMBLING 
WINDOW TYPE OF SCENARIOS -- >> ARJIT 
BASU: THIS IS GOING TO TAKE CARE 
OF THAT. >> PAUL WU: HANDLE THESE 
STREAM ANALYTICS PLATFORM WHICH 
IS A GOOD THING. GOING BACK TO HOW 
DO I MAKE SURE THINGS OVER HERE 
IS MAPPED PROPERLY TO MY WORK ORDER, 
THAT'S EXACTLY WHERE THE MAGIC THAT 
WE DO. WE'RE MINING OUT THE INFORMATION 
COMING FROM THE IOT SENSORY AND 
TYING THAT BACK TO -- BASICALLY 
DOING OUR ON-BOARDING EXPERIENCE 
WE'RE GOING TO HAVE A MAPPING EXERCISE 
BETWEEN THE NODES YOU'RE HAVING, 
THE AUTOMATED DATA YOU HAVE WORK 
ORDER AND MACHINES TO CERTAIN PARTS 
THAT WILL COME FROM THE SENSOR. 
AS LONG AS YOU MAP THESE PROBABLY 
IT GUARANTEES DOWN STREAM WHEN WE 
DO THE STREAM ANALYTICS THESE ARE 
GETTING MAPPED PROPERLY. >> [QUESTION 
INAUDIBLE] >> ARJIT BASU: WE CAN 
ONLY GUARANTEE IF -- SO -- YEAH. 
SO BASICALLY HOW IT WORKS IS TODAY 
WHEN YOU -- IT'S ALL [INAUDIBLE]. 
SO WHEN YOU GO TO A PRODUCTION ORDER 
AND YOU CLICK ON START, SOMEONE 
HAS TO CLICK THE START BUTTON. IT'S 
EXACTLY AT THAT TIME WE TAKE CERTAIN 
PAYLOAD AND THEN WE PUSH IT OUTSIDE. 
AND THEN WHEN YOU FINISH STOP ON 
THE PRODUCTION ORDER, WE ALSO SEND 
ANOTHER STOP EVENT WHICH IS OUTSIDE 
F&O. SO AS LONG AS THE PEOPLE WHO 
ARE ACTUALLY DOING THEIR WORK IN 
F&O DO IT IN THE RIGHT WAY, WE'LL 
DO IT PLUS, WE'LL HAVE ALSO OTHER 
SCENARIOS, IF SOMEONE FORGETS TO 
EVEN STOP THE PRODUCTION ORDER AND 
ALL THAT STUFF SO WE ARE BUDGETING 
EDGE SCENARIOS FOR THAT TO SHOW 
THAT YOU HAVE THE RELIABLE DATA, 
BUT, AGAIN, I CAN'T GIVE YOU A HUNDRED 
PERCENT GUARANTEE BUT WE ARE TRYING 
IT ON TWO OF OUR CUSTOMERS PLUS 
A FEW MORE AND WE ARE GOING TO BUILD 
ON THE RELIABILITY AND STUFF LIKE 
THAT. >> PAUL WU: WE DO HAVE THE 
JOB ID AND START AND END TIME OF 
A PRODUCTION ORDER OR A WORK ORDER 
, THAT'S HOW WE CORRELATE. TIME 
STAMP-BASED ESSENTIALLY. >> ARJIT 
BASU: BECAUSE IF YOU WANT TO DO 
IT, WE DON'T WANT PARTNERS AND CUSTOMERS 
SPEND DOING HEAVY LIFTING IT'S NOT 
THEIR SCHOOL BOARD, SO WE'RE GOING 
TO DO THAT FOR -- JOB, SO WE'RE 
GOING TO DO THAT FOR YOU. >> PAUL 
