C* Summit 2013: Data Driven Retail: How One Mega-Retailer Drove Down Energy Costs Across 7,000 stores by David Leimbrock
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How do you keep up with the velocity and variety of data streaming in from all the smart devices that run the physical environments of 7,000+ stores? What about getting analytics that tell you exactly where energy waste is happening in real-time? In this talk, Riptide IO, describes their blueprint for collecting, organizing and deriving real-time operational intelligence from smart devices such as lighting, HVAC, sensors and more. Learn how this retailer gained a dramatic boost to their sustainability program, and solved some of the major bottlenecks in managing countless devices across thousands of stores.
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C* Summit 2013: Data Driven Retail: How One Mega-Retailer Drove Down Energy Costs Across 7,000 stores by David Leimbrock
- 1. DATA-DRIVEN RETAIL #CASSANDRA13 CASSANDRASUMMIT2013 HOW ONE MEGA-RETAILER IS DRIVING DOWN ENERGY COSTS 22% ACROSS 8,000 STORES
- 2. { A B O U T U S } SMART DEVICE MANAGEME NT FOR VERY LARGE ENTERPRIS OUR PARTNER #CASSANDRA13 CASSANDRASUMMIT2013
- 3. MARKET TRENDS GOAL: 20% LESS ENERGY CHALLENGES OUR APPROACH VALUE DELIVERED 1 2 3 4 5 DATA-DRIVEN RETAIL { W H AT W E W I L L C O V E R } “Experts often possess more data than judgment.” Colin Powell #CASSANDRA13 CASSANDRASUMMIT2013
- 4. 1 MARKET TRENDS #CASSANDRA13 CASSANDRASUMMIT2013
- 5. 2 EXPLOSION OF SMART DEVICES 3 BIG DATA ECONOMICS 1 LEAN & GREEN BUSINESS THREE MARKET TRENDS { D R I V I N G D E M A N D } CASSANDRASUMMIT2013 #CASSANDRA13
- 7. BRICK & MORTOR CHALLENGES R E TA I L BRICK & MORTAR RETAILERS FACE INTENSE COST PRESSURE CASSANDRASUMMIT2013 #CASSANDRA13
- 8. BEING “GREEN” IS DRIVING NEW BEHAVIOR & DATA REQUIREMENTS CASSANDRASUMMIT2013 #CASSANDRA13
- 10. ON THE ROOF (~600PTS) DEVIC E DATA FROM THE LIGHTING (~600PTS) FROM THE METERS (~400PTS) FROM REFRIGERATION (~200PTS) CASSANDRASUMMIT2013
- 11. ENERGY SPEND: SPREAD ACROSS HUNDREDS OF DEVICES TYPICAL ENERGY USE IN RETAIL LIGHTING HVAC MISC #CASSANDRA13
- 13. Metering, HVAC, Lighting Controllers Temperature, sensor readings 15 min. intervals 15 DEVICES 1,800 DATA POINTS ~58M PER HOUR VOLUME ACROSS 8,071 STORES Define “time series”: a sequence of data points, measured typically at successive points in time, spaced at uniform time intervals. CASSANDRASUMMIT2013 #CASSANDRA13
- 14. 2 GOAL: 20% LESS ENERGY #CASSANDRA13
- 16. INITIAL SUCCESS – THEN,…. 0 500 1000 1500 2000 2500 3000 3500 2010 2011 2012 Number of Stores Online Number of Stores Online SAVINGS PERFORMANCE PROBLEMS DRIFT { A D D I N G 5 0 + S T O R E S P E R W E E K } CASSANDRASUMMIT2013 #CASSANDRA13
- 17. APPLICATION SILOS Vendor A Store-‐X Vendor D Vendor C Vendor B Store-‐X Store-‐X Store-‐X Store-‐X Store-‐X Store-‐X Store-‐X Store-‐X Store-‐X Store-‐X Store-‐X Even within same vendor architecture, multiple servers Required, with limited data sharing capabilities. { M U LT I - V E N D O R E N V I R O N M E N T } CASSANDRASUMMIT2013 #CASSANDRA13
- 18. 4 HOW WE SOLVED IT #CASSANDRA13
- 19. DASHBOARDS EXECUTIVE ENERGYBUILDING OPERATIONS § Financial § Environmental § Equipment Status § Alerts & Alarms § Policy § Performance § ConsumpKon § Usage Profile BRIGHTWORKS DATA MANAGEMENT LAYER VERTICAL APPLICATIONS RIPTIDE IO & 3RD PARTY § AFDD § ADR § Building Management § CriKcal Systems Monitoring § Dynamic Pricing § Safety & Security § Work Order Management DEVICE INTEGRATION PLATFORM PROPOSED SOLUTION CASSANDRASUMMIT2013 #CASSANDRA13
- 20. Solution optimized for time-series. Performance at scale. Broad language support. Fault tolerance. Commercial support & healthy community; not overly specialized. TECHNICAL CONSIDERATIONS 1 2 3 4 5 6 Keen on executing – avoid analysis paralysis. CASSANDRASUMMIT2013 #CASSANDRA13
- 21. EVALUATION RESULTS 1 6 12 18 24 30 36 Months of Data Reads Writes CASSANDRASUMMIT2013
- 22. NEW ARCHITECTURE B R I G H T W O R K S C L U S T E R P O W E R E D B Y C A S S A N D R A CASSANDRA BrightWorks Applications Weather Utility Data Stores Stores Stores Vendor Siloes Vendor Siloes CASSANDRASUMMIT2013
- 26. OPERATIONAL INPROVEMENTS { B O N U S : M O R E T H A N J U S T E N E R G Y S AV I N G S } TROUBLESHO OTING TOOL FOR THE FIELD GLOBAL REAL ESTATE VIEW FOR EXECUTIVES IMPROVED WORK FLOW FAULT DETECTION NEXT CASSANDRASUMMIT2013 #CASSANDRA13
- 27. Reliable high performance data store. RE: data modeling perspective, pay more attention to CQL3. Datastax security features – additional layers is a good thing. Happy with decision to pre-compute as much as possible. KEY TAKE AWAYS 1 2 3 4 5 Data extract & validate rules; slow & with inevitable surprises. CASSANDRASUMMIT2013 #CASSANDRA13
- 29. Dave Leimbrock Phone: +1 805 588 4580 Email: dleimbro@riptideio.com t twitter.com/dleimbro CONTACT ME #CASSANDRA13 CASSANDRASUMMIT2013