Telefonica Sa · BME:TEF
Telefonica Sa — MWC 2022
44 slides from Telefonica Sa's conference presentation, Oct 5, 2022
Slide 1: Smart Buildings: There is no plan(et) B
SMART BUILDINGS There is no plan(et) B MWC 2022 Transformation is now
Slide 2: What is a Smart Building?
MWC 2022 What is a Smart Building? “Those buildings whose installations and systems enable centralized management and control, in order to maximize efficiency and sustainability while ensuring security as well as people’s safety and wellness.” 2
Slide 3: The path to Smart Buildings
MWC 2022 The path to Smart Buildings LEGACY BUILDING CONNECTED BUILDING SMART BUILDING • Independent • Manual integration of two • Integrated systems on a single platform. systems. or more systems. • Continuous learning, automatically responding and • Simple rules “If this then adapting to the chang
Slide 4: Some key facts
MWC 2022 Some key facts Buildings account for SDG #7 X2 36% Energy efficiency improvement rate of world energy consumption. 2030 4
Slide 5: Some key facts
MWC 2022 Some key facts Buildings generate SDG #7 39% 2030 of total greenhouse Accelerate gas emissions. Modern renewable share of total final energy consumption 2030.
Slide 6: Some key facts
MWC 2022 Some key facts Buildings need to be safe and comfortable, providing an optimal user experience. 89% Average time spent in buildings
Slide 7: Goals of Smart Buildings: People
MWC 2022 Goals of Smart Buildings People Ensure a healthy and safe environment Provide an excellent “phygital” user experience Minimize waiting times and avoid overcrowding
Slide 8: Goals of Smart Buildings: Efficiency
MWC 2022 Goals of Smart Buildings Efficiency Reduce operating costs, matching supply with demand. Anticipate and avoid potential issues. Optimize the use of each space.
Slide 9: Goals of Smart Buildings: Sustainability
MWC 2022 Goals of Smart Buildings Sustainability Minimize power, gas and water consumption. Incorporate renewable energy sources. Reduce carbon emissions, contributing to 2050 net-zero objective.
Slide 10: Goals of Smart Buildings: Security
MWC 2022 Goals of Smart Buildings Security Protect users and assets against any potential threat. Automate detection and response, minimizing impact. Use seamless technologies, not affecting user experience.
Slide 11: Our proposal for Smart Buildings: an integral solution
MWC 2022 Our proposal for Smart Buildings: an integral solution People Efficiency Sustainability Security Predictive Performance AI & Analytics Indoor Insights Demand planning Anomaly detection Maintenance benchmarking Platform Dashboard Alerts Recommendations BIM – Digital Twin Monitoring and BMS V
Slide 12: Our Smart Building platform
MWC 2022 Our Smart Building platform Centralized view of the building. Advanced analytics use cases. Alerts and recommendations. Dashboard + BIM digital twin. IoT BIG DATA DIGITAL TWIN 3D Model 3D Model Static data Dynamic data
Slide 13: Retail Analytics Project
Retail Analytics Project March 2nd 2022 La Torre Outlet Zaragoza 13
Slide 14: System based on data analytics and management to apply to retail
System based on data analytics and management to apply to retail Data Driven Decisions 14
Slide 15: Retail Analytics Project: Big Data and Analytics
Retail Analytics Project Description Big Data and Analytics Objective: Get the highest value of the generated data. Tool Architecture System based on Big Data and A.I., that captures a wide set of data to improve the retail performance. 15
Slide 16: Solution to improve all the retail areas
Retail Analytics Project Solution to improve all the retail areas: 16
Slide 17: Retail Analytics Project: Objectives and Result
T Retail Analytics Project _ | cocsussssseseese ce outlet Objectives Cuantitative Cualitative Result + Valuable information earned by BD and IA to optimize the Business Management and Performance 17
Slide 18: Visitor Capacity
Re tail Visitor Capacity An aly tic North zone Estimated occupancy 30’ Estimated occupancy 60’ Current 29% s 18% occupancy 9% South zone Central zone Pr Current occupancy 14,4% Estimated occupancy 30’ 24,5% Estimated occupancy 60’ 35,4% Current Estimated occupancy 30’ Estimated occupancy 60’ Food zo
Slide 19: Parking Capacity
Retail Analytics Project South Parking Current Estimated occupancy 60’ occupancy 10% 29% Parking Capacity Food Parking Leisure Parking Deco Parking Current Estimated Current occupancy occupancy Current occupancy Estimated occupancy 60’ Current occupancy 60’ occupancy 33% 82% 17% 9% 26,2% 61% Sports
Slide 20: Footfall
Re tail Footfall An Filters Initial date Final date aly Days of the week Time range tic Monday Tuesday Wednesday Thursday Morning Midday Afternoon Evening s Pr Global visits Average Visiting time oje Unique Visits Short Visits % ct Maximum influx Average Visits % Maximum influx Date Long Visits % 20
Slide 21: Footfall heat map: Tuesday
Re tail Footfall – heat map: Tuesday An aly tic s Pr oje ct 21
Slide 22: Footfall heat map: Saturday
Re tail Footfall – heat map: Saturday An aly tic s Pr oje ct 22
Slide 23: Business information: Turnover
Re tail Business information Turnover An Filters aly Initial date Final date Days of the week Time range Monday Morning tic Tuesday Wednesday Thursday Retailer Midday Afternoon Evening s Pr oje Turnover Number of transactions Number of Transactions Average Transaction ct Average Spend per Visitor Av
Slide 24: Business information: Disaggregated Data
Re tail Business information An Disaggregated Data Business Performance Data aly tic Visits Unique Visits Visiting Time Turnover Density Average Spend Per Visit Average Units per Conversion Transaction Transaction Rate Value Number of Transactions Capture Rate s Fashion store 1 Fashion store 2 Pr Fa
Slide 25: Interrelation of metrics
Re tail Interrelation of metrics An Natural Scale Logarithmic Scale aly tic s Pr oje ct 2022-01 2022-02 2022-03 2022-04 2022-05 2022-06 2022-07 2022-08 2022-09 2022-10 2022-11 2022-12 Turnover Visits Conversion rate Visiting time 25
Slide 26: Interrelation of metrics
Re tail Interrelation of metrics An Natural Scale Logarithmic Scale aly tic s Pr oje ct 2022-01 2022-02 2022-03 2022-04 2022-05 2022-06 2022-07 2022-08 2022-09 2022-10 2022-11 2022-12 Turnover Visits Conversion rate Visiting time 26
Slide 27: Interrelation of metrics
Re tail Interrelation of metrics An Natural Scale Logarithmic Scale aly tic s Pr oje ct 2022-01 2022-02 2022-03 2022-04 2022-05 2022-06 2022-07 2022-08 2022-09 2022-10 2022-11 2022-12 Turnover Visits Conversion rate Visiting time 27
Slide 28: Consumer Profile and Behaviour
— Consumer Profile and Behaviour — & [| — la torre outlet Zaragoza Retail Analytics Project Consumer Profile and Behaviour + Age Range + Gender * Socioeconomic status + International * National / Spain * City — specific district Commercial interest Visit mix Customer journey Tracking Visit frequency
Slide 29: Consumer Profile and Behaviour: Origins
Re tail Consumer Profile and Behaviour An aly tic Origins Zaragoza city: 61% • International Zaragoza province: 16,5% s • National / Spain Spain: 17% • City – specific district Pr International: 4,5% oje ct 29
Slide 30: Consumer Profile - International Visitor
op Consumer Profile - International Visitor . k : Ve he 1
Slide 31: Consumer Profile: Forecasting
ep \| —- mer Profil oF la torre \ outlet yr oN 3 Zaragoza ‘ Forecasting —
Slide 32: Consumer Profile - City Visitor
— Consumer Profile and Behaviour — & || — la torre outlet Zaragoza Consumer Profile - City Visitor Delicias Casetas, Garrapinillos 7,09% Actur, Rabal y Rey Fernando 15,88% Casco Historico Me E 5,40% Miralbueno, , Oliver y Se slibok Valdefierro Salis 10,15% over Centro Sur, 5,33% Casablanca, Universi
Slide 33: Key Commercial Interest
Re tail An KEY COMMERCIAL INTEREST Saturday KEY COMMERCIAL INTEREST Tuesday aly tic Fashion: 28% Fashion: 25% s Sport: 24% Accesories: 5% Sport: 26% Accesories: 11% Pr Food & Leisure: 28% Home: 15% Food & Leisure: 15% Home: 23% oje ct Cons umer 33 Profil
Slide 34: Customer Journey
Retail Analytics Project Customer Journey 34
Slide 35: Customer Journey
Retail Analytics Project Customer Journey 35
Slide 36: Customer Journey
Retail Analytics Project Customer Journey 36
Slide 37: Forecasting: Descriptive Analysis
Re Forecasting tail • Business Performance • And marketing results over business indicators An Descriptive Analysis aly Total Visits Total Turnover Average Conversion Rate Fashion Turnover Sport Turnover Accessories Turnover Home Turnover Food Turnover Leisure Turnover tic s Pr oje ct 2022-01 2022-0
Slide 38: Forecasting: Predictive Analysis
Re Forecasting tail • Business Performance • And marketing results over business indicators An Predictive Analysis Applying advanced algorithims to know turnover category results, consumer behaviour and key retail metrics. aly tic s Pr oje ct 38
Slide 39: Forecasting: Predictive Analysis
Re Forecasting tail • Business Performance • And marketing results over business indicators An Predictive Analysis Applying advanced algorithims to know turnover category results, consumer behaviour and key retail metrics. aly tic s Pr oje ct 39
Slide 40: Forecasting: Predictive Analysis
Re Forecasting tail • Business Performance • And marketing results over business indicators An Predictive Analysis Applying advanced algorithims to know turnover category results, consumer behaviour and key retail metrics. aly tic s Pr oje ct 40
Slide 41: Forecasting: Predictive Analysis
Re Forecasting tail • Business Performance • And marketing results over business indicators An Predictive Analysis Applying advanced algorithims to know turnover category results, consumer behaviour and key retail metrics. aly tic s Pr oje ct 41
Slide 42: Key takeaways
MVC 2022 Key takeaways Smart Buildings are The combination of IoT and AI is Telefónica Tech offers an integral indispensable to achieve a key enabler for the solution for Smart Buildings focused the SDGs development of Smart Buildings on 4 pillars: people, efficiency, sustainability and security 42
Slide 43: Each new situation requires a new architecture
“Each new situation requires a new architecture” Jean Nouvel
Slide 44: Telefonica
Telefonica °3° Telefonica