How To Manage A Business

Transcription

1 Big Data, Analytics & FM: From Lady GaGa to Workplace Management Nancy Johnson Sanquist, IFMA Fellow, AIA Associate Manhattan Software, a Trimble Company

2 Data to Information to Knowledge to Wisdom

3 Agenda Introduction to NJS and Trimble Navigation Introduction to Big Data and Analytics Case Studies from Lady GaGa to Workplace Future of Big Data and Analytics for FM and RE

4 Manhattan Functional Spectrum Market Planning Supply and Demand Planning Capital Asset Planning Financial Management Acquisitions & Disposals Lease Management Project Management Sustainability Space Planning & Management Operations & Maintenance Asset Management Space Scheduling ERP ERP ERP ERP CAFM IWMS Manhattan Real Estate Life Cycle Fin Systems Lease Admin. GIS Excel CAP PAM Projects SRS CAD O&M AMS Reserve Specialist Systems / Point Solutions 4 World Leading Real Estate & Facilities Management Software

5 5 World Leading Real Estate & Facilities Management Software

6 Gartner IWMS Magic Quadrant World Leading Real Estate & Facilities Management Software

7 Lifecycle solutions Re-engineering levers: Provide real-time information for key stakeholders Connect field (actual) to the office (plan) Enable measurement of on-site progress to overall plan Streamline and integrate workflow processes Exchange data from construction phase to operate and manage phase Optimize building portfolio with analytics CONCEPT ENGINEERING & DESIGN ESTIMATING PROJECT PLANNING CONSTRUCT OPERATE

8 Folie 7 7 We should consistently use plan, design, build,operate Ragnar Wessman; 8 This workflow picture is consistent with other Trimble material (AG etc). Ragnar Wessman; 9 The text is too specific and does not work for all customer groups, I think. Ragnar Wessman;

9 The RE Life-Cycle

10 Trimble

11 My Analytics Background Thomas Davenport John Serri 3.

12 It s all about the data

13 The Accelerating Pace of Innovation!!! Google(1999) Pre Industrial ~750 years Industrial Period/Post War Space Age ~200 years Early Information Age Mainframe PC ~20 years Trends: SaaS Mobility / APPS / Devices Big Data / Analytics Information Explosion! Exponential Volumes, New Connections, More sources 1990 Internet, DNA, E commerce Smart Phones ~20 years 2010 Information Revolution Phase 3? ~ Last 3 years 2014

14 Nexus of Forces (Gartner) Internet of Everything Information: Big Data & Analytics Increase performance and innovation VIRTUAL PHYSICAL Mobile Devices Places + Reduce costs Assets Sustainable, Resilient, Agile, Schedulable

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16 Mobility

17 Goodbye to my guts tell me.

18 Big Data & Analytics

19 Welcome BIG DATA and ANALYTICS The Sexiest Job in the 21 st c.

20 Definition Using new technologies and methods to manipulate unprecedented amounts of data to provide more timely, precise, insightful and predictive information for business decisions and actions Robert Morrison Lead Faculty IIA Co-Author with Tom Davenport Analytics at Work

21 + Visual, Variable, Veracity

22 Analytics 1.0

23 Analytics 2.0

24 In this changing world

25 The Queen of the Data Scientists: Lady GaGa Deep data mining has hit the music business Meet Troy Carter of AtomFactory who created the concept of Little Monsters Mined the 31m Twitter & 51m Facebook followers & ticket sales for big data Created more targeted social media platform and cut out middle men

26 Big Data Disrupts Disaster Relief

27 Data and Analytics Questions

28 Are you asking the right questions?

29 and are you asking the questions right?

30 Are you getting the right answers?

31 are you ready for the next development? Data Curator We are all now data scientists

32 Analytics 3.0

33 Less well-known queen Meet Dr. Pamela Peele, CAO of Univ. of Pittsburgh s Medical Center Background in gaming, economics and healthcare Fired existing financial analysts and created big data and analytics centralized organization (federated model) Created a knowledge factory with team of epidemiologists, physicians, physicists & math. Plant foreman is industrial engineer Most important member of team: JOURNALIST

34 Federated Model for Enterprise Analytics

35 No Mickey Mouse Analytics Meet Mark Shafer, SVP of Revenue & Profit Management; head of Disney s data army 120 analysts (30 w/phds) for business big data analysis in federated model Able to take analytics work done in the cruise industry and apply it to a Broadway dynamic pricing model Top grossing show due to secret algorithm

36 The Quantified Workplace

37 It s all about the DATA Buildings: HVAC, Electrical and Mechanical Systems Performance for BMS Badging, RFID, Video, Security LAN/WIFI usage/position location Utilization/presence Sensors Operations & maintenance BIM data Wellness TCO People: Movement/location Interactions/behaviour Health & wellness Performance Economic: Real time pricing Real time supply and demand Market data Site location analysis

38 The Digital Workplace

39 Internet of Things

40 BIM Big Data

41 People in the Workplace

42 NEW DEVELOPER, NEW WELLNESS STANDARD for ALL WORKPLACES

43 Why does FM & RE care?

44 The Digital Worker From Basement Bob To Data Darrell

45 Data Scientist for FM Sara H. Steinbauer, PMP Managing Director of Information Services at NELSON Focused on delivering technical expertise, industry knowledge and information solutions to drive high performance portfolios Big data and analytics specialties include: BIM in FM for As-Built Lifecycle Management Digital Visualization Services & Revit Content Creation Data Analytics and Visualization Solutions supporting service delivery excellence

46 Sara H. Steinbauer, DL I data Data gives me the power to make better decisions and take action with confidence.

47 Meet another RE Analyst Vita Kan Data Manager, Global Real Estate, Motorola Solutions Inc. 18 years in software development, systems engineering and solutions architecture. 4 years with Motorola Solutions Real Estate team focusing on real estate data management tools, software solutions and data analytics. Analytics Philosophy: More data available to more people at a faster pace became a norm for business landscape. Ability to make strategic business decisions with confidence comes with quality data, effective processes, and smart platform.

48 Aspects of Data Analysis Renewal 10 Disposit 3 Relocat 1 Acquisit Expiration 5 Renew 7 Disposit 6 Internal 1 Transactions and lease costs 15 Operating costs and utility trends Compl eted Transactions Facility Management Strategic Planning Occupancy Planning Portfolio analysis 0 Space and Occupancy metrics

49 Location Analytics

50 Capital Asset Planning

51 Mobile Intelligence Site Viewer Benefits Untethered access Full security Real time Information Flexible interrogation Seamless move from reports to updates

52 Interactive Visualization CAD based Interrogation Benefits Graphical Insights Flexible Queries Layers of Information

53 Supply & Demand Analysis

54 Interactive Visualization GIS based Interrogation Benefits Graphical Insights Flexible Queries Layers of Information

55 Utilization Analysis

56 Energy Analysis

57 RE & Workplace Analytics Insight by Building, Region, City Actions Improved Performance Against Benchmarks Real time measurements of Facility Usage Occupant Feedback on Facility By Building, City. Region TCO trends and comparisons Reactive and Preventative Trends Reduce TCO in Building Improve User Satisfaction Improve Maintenance Programs Reduce Response Time Improve Sustainability Challenges Unavailability of Data Talent Data completeness and Quality Lack of Standards Voluminous Information Large Solution Space Sources Sensors Benchmarking Services Help Desk OA&M System Utilities FEMA Weather Twitter, Facebook, Google TCO, Sustainability Occupancy Insights TCO Forecasts/ Targets Sustainability Forecast and Targets Solutions 56

58 RE & Workplace Analytics

59 What does analytics mean to Sara & Vita? Facility Management Projects Management Optimize with confidence Occupancy Planning Lease Administration Vendor Management Strategic Planning Communications Report with confidence Data Completeness: Know your buildings and costs Plan with confidence Forecast with confidence Data Analysis: Know your occupancy and vacancy, allocate cost based on SFT, manage lease events Data based decisions: Know your poor and strong performers, utilize market trends and what if scenarios, understand company trends and growth opportunities Data based strategy: Know your metrics and benchmarks, make strategic decisions to optimize utilization and cost, streamline mergers and acquisitions,

60 Future of Analytics for FM/RE

61 FM: Third Wave of BIM BIM Transformation from a Multi-dimensional Model to the Business Database for Building Assets

62 Project Tango

63 Project Tango

64 FM and Urban Analytics Urban FM Share: Smart Cities Population Use: Smart Workplaces Workforce Operate: Smart Assets Operations

65 City of Antwerp: event facilities Selection & reservation services for all citizens and organizations Approx 1000 facilities Public, enterprise, private Resilience planning

66 Neighborhood Analytics

67 Quantified Community

68 Network Analysis

69 Street Analytics

70 Transportation Analytics

71 People Analytics Person of Interest TV Show

72 Digital & Physical Workplace

73 Who defines workplace analytics? Who controls it? Who owns it? Space Organization Work Practice SPACE Finance Technology Workplace Strategist FM Data CRE HR IT

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75 Building Analytics 3.0

76 Next Steps Today Start Thinking about what to do in your organization Monday Morning November 24 - Inventory existing and potential sources of Big Data relevant to your real estate and FM activities Next 90 Days - Establish a data scientist tiger team to consult with the C-level and business units on Big Data and advanced analytics opportunities - Identify at least one analytic idea from outside our industry to adopt and adapt Next 12 Months - Refocus investments and resources away from traditional reporting and toward diagnostic, predictive and prescriptive analytics - Establish methods for quantifying information s potential and accurate value to the business

77 Dankeshon!!!