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Customer, Data Employee Trio

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The "trio": Customer Experience, Data-driven business and Employee empowerment.
This 2018 STKI summit presentation outlines the necessary "joined" journey to achieve customer experience transformation.

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Customer, Data Employee Trio

  1. 1. 1 Customer Engagement Data-Driven Business Employee Empowerment The Trio Initiative: Customer Data Employee
  2. 2. 2 Experience Is now more important than Product Customer
  3. 3. 3 Experience Is now more important than ProductPrice Customer
  4. 4. 4 Experience Is now more important than ProductPriceService Customer
  5. 5. 5 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 5 Experience Is now more important than ProductPriceServiceGoods Customer
  6. 6. 6 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 6 Experience Is now more important than ProductPriceServiceGoodsEverything Customer
  7. 7. 7 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 7 Experience everything. Customer
  8. 8. 8 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 8 But the bar keeps on getting raised higher and higher Customer
  9. 9. 9 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 9 Customers are constantly expecting more … and constantly disappointed Customer
  10. 10. 10 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 10 How do we master ever-changing expectations? It requires empathy and adaptability Organization’s value and processes Customer’s value and processes Customer
  11. 11. 11 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 11 Source:The Dip by Seth Godin But despite all efforts, CX quality has declined in 2017 Customer
  12. 12. 12 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 12 I can do this. But I can’t do it alone. Customer
  13. 13. 13 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 13 I can do this. But I can’t do it alone. Customer
  14. 14. 14 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 14 Customer Engagement Data-driven Business Employee Empowerment CMO HR CDO Data Officer
  15. 15. 15 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 15 Customer Engagement Initiative Destination Customer Maximum Customer LifetimeValue It has & always will be about maximizing CLTV & achieving growth Customer Engagement
  16. 16. 16 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 16 CMO / CXO / CCO CPO Privacy officer HR CIO CSO Service Officer CDO Digital Officer Customer Engagement Initiative Stakeholders Maximizing customer lifetime valueCustomer I Assure privacy & trust I manage Organizational design, engagement & commitment I Build the data platform; execute omni-channel strategy and manage digital operations I am part of Service and CX design; Manage omni-channel strategy I lead the digital transformation change I Build and maintain the customer data platform CDO Data Officer CEO I don’t only commit, I get involved set the tone for the org. I lead the CE Initiative
  17. 17. 17 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 17 CMOV1.0 Cost center CMOV2.0 Profit & Growth center 50% of CMOs are expected to lead CX initiatives Customer
  18. 18. 18 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 18 Marketing/CX budgets worldwide % of company revenue Source: Gartner 10% 2014-2015 11% 2015-2016 12% 2016-2017 11.3% 2017-2018 Why? Customer
  19. 19. 19 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 19 Marketing/CX budgets worldwide % of company revenue Source: Gartner 10% 2014-2015 11% 2015-2016 12% 2016-2017 11.3% 2017-2018 Now get results! Customer
  20. 20. 20 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 20 Marketing/CX Spend: 22% Technology People (employees + agencies) % of the marketing budget We bought all this technology Now let’s learn how to use it From using the right tools to using the tools right Customer
  21. 21. 21 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 21 MarTech State of Adoption - Worldwide vs. Israel Using Predictive Analytics Using Marketing Automation 10% 40% Source: STKI 2018 (refers to Israeli enterprises) Using Predictive Analytics Using Marketing Automation 30% 63% Source: emailmonday MA Statistics, 2017 Customer
  22. 22. 22 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 22 Source: Chiefmartec.com DO NOT examine technologies before defining your own needs CX technology is changing at the speed of light Customer
  23. 23. 23 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 23 Source: Chiefmartec.com DO NOT examine technologies before defining your own needs Customer
  24. 24. 24 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 24 1. Create your own architecture of needs 2. Identify assets & strength areas 3. Prioritize what’s missing 4. Map technologies you need on what you needCustomer
  25. 25. 25 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 25 1. Create your own architecture of needs 2. Identify assets & strength areas 3. Prioritize what’s missing 4. Map technologies you need on what you needCustomer
  26. 26. 26 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 26 Define & Manage customer identities Define Value Design Value Deliver Value Optimize Most architectures of needs will look like this: Customer Identity Customer
  27. 27. 27 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 27 Customer Engagement Initiative Maximizing customer lifetime valueCustomer Customer Engagement
  28. 28. 28 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 28 28 Trek name: Manage customer identities Gather data From internal & external sources Define Customer ID Who are your customers?What do you need to know about them? Manage customer Identities Identify new segments & micro-segments
  29. 29. 29 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 29 Customer View 360 Customer data is: 1. Disconnected 2. Delayed 3. Inaccessible Customer
  30. 30. 30 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 30 CRM Data Partner Data Point-of-sale Data Web Data Mobile Data Call Center Data Device Data 3rd Party Data The Customer DataView is complex! Customer
  31. 31. 31 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 31 This drove the rise of CDPs Customer Data Platforms Sources: David Raab Customer
  32. 32. 32 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 32 What’s in a CDP? Source: Luma Source: David Raab Customer
  33. 33. 33 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 33 Customer
  34. 34. 34 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 34 2 years ago, we predicted consumers will re-gain control of their data: STKI Summit 2016 Source: Gigya survey 2017 - The state of consumer privacy and trust Customer
  35. 35. 35 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 35 GDPR (May 2018) is the EU’s attempt to put consumers back in control of their online data and compel businesses to keep that data safe Customer
  36. 36. 36 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 36 Which one are you? “GDPR is a huge headache” “GDPR is a creative opportunity” The last mile of personalization Customer
  37. 37. 37 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 37 Define & Manage customer identities Tag Mng. Systems GoogleTag Manager,Tealium Channel-related data Web, Mobile, chat, voice… Voice of the Customer Qualtrics, Nemala, OpinionLab Sensor/Location data Internal data gathering technologies: Transactional data CRM, Core systems… Social identity Mng. Gigya (SAP), Janrain DMP 2nd and 3rd party data Oracle – BlueKai, SF – Krux, eXalate… Social Listening Tracx, Buzzila, SF Radian6… External data gathering technologies: AdTech/Paid media data Data Warehouse Big Data Data Lake, HDFS,NoSQL DMP: Audience Data Oracle,Adobe, IDX, Exposebox EIM: Information Management Informatica, IBM… CIM: Customer Identity Management Gigys (SAP) DMP 1st party data Oracle BlueKai, Mapp, SF – Krux… Data Management technologies: CDPs (Customer Data Platforms) POS (Point of Sale) data
  38. 38. 38 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 38 Customer Engagement Employee Empowerment Data-driven Business This takes us to the Data Initiative CMO HR CDO Data Officer
  39. 39. 39 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 39 “Those who control the data, control the future. Not just of humanity, but the future of life itself.” -Yuval Noah Harari Data-driven Business Data
  40. 40. 40 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 40 The State of Data & Analytics (Forbes) 53% 25% 5% Already adopted big data analytics Rely on analytics for decision making Operationalize Insights We all want to be data-driven But 95%of us aren’t Data
  41. 41. 41 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 41 Data initiative destination Enable the organization to become data-driven on all initiatives Data Data Data-driven Business
  42. 42. 42 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 42 Data Initiative CDO: Data Officer CIO CAO:Analytics Officer DPO : Data Protection Officer Stakeholders: CMO & Other LoBs I build the platform and the access roads to it I accelerate analytics tools and methodologies I rely heavily on Data and operationalize insights I lead the “Data- Driven Business” Journey I assure privacy and regulations Data
  43. 43. 43 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 43 Data Initiative Enabling a Data-Driven businessData Data-driven Business
  44. 44. 44 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 44 Trek name: Plan data strategy Design a data architecture Set data principals Set a process for ideation & prioritization Align with constant technology changes
  45. 45. 45 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 45 ODS First, you need an architecture! And it should fit constantly changing needs Data
  46. 46. 46 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 46 DWs aren’t suitable for streaming data, real time analytics, large volumes of messy/complex data, ad hoc requirements. Data Lakes aren’t suitable for structured reporting, they lack maturity, sometimes security and integration. They require a lot of data preparation work. Data LakeDW Data
  47. 47. 47 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 47 The Logical DW Architecture Source: R20 Consultancy Data
  48. 48. 48 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 48 How much data freedom is ok? Data Lake
  49. 49. 49 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 49 What is constantly changing? Technologies Your needs “This is my data architecture for the next 5 years” Data
  50. 50. 50 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 50 Trying to leverage common data technology architectures while knowing it is a moving targetData
  51. 51. 51 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 51 That’s why your perfect data innovation lab is in the cloud Data
  52. 52. 52 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 52 Plan data strategy: Players Aman (Eternity) Accenture B-Pro Biyond DataCube Deloitte Hilan-Nesspro KPMG MatrixBI Nogamy Taldor Yael Group (Actiview) And more… Data Architecture Planning Providers*: * Alphabetic order, not a ranking
  53. 53. 53 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 53 Trek name: BuildTrust Examine Anonymization Techniques Establish Data Gov. Organization & tools Protect data in context Implement data management processes
  54. 54. 54 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 54 Data Governance: one word – many meanings https://www.sas.com/content/dam/SAS/sv_se/doc/Presentation/sas-gdpr-seminar-30-november-jim-nielsen.pdf Data
  55. 55. 55 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 55 Many data-related roles and duties (“jobs”) Data
  56. 56. 56 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 56 Data Custodian DPO Data Protection Officer Data Steward Data Owner Data Registrar CDO Chief Data Officer Director of Information Flow CAO Analysis Officer Size of circle: STKI’s prediction for actually having this role in Israeli organizations Data
  57. 57. 57 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 57 Obstacles for Data Initiative Success Culture Data Literacy 70% 35% Data Skills 30% Dirty Data 45% Data
  58. 58. 58 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 58 Data “I love cleaning data” - Said no one, ever.
  59. 59. 59 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 59 But current DG level of maturity is very low! Source: Experian’s 2017 global data management benchmark report 18% 26% 39% 17% Data
  60. 60. 60 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 60 Source:https://www.slideshare.net/inforacer/impdata-gover Data regulations are kicking in The DPO reports to the highest management level of your organisation – ie board level. The DPO operates independently and is not dismissed or penalised for performing their task. Adequate resources are provided to enable DPOs to meet their GDPR obligations. https://ico.org.uk/for-organisations/guide-to-the-general-data-protection-regulation-gdpr/accountability-and-governance/data-protection-officers/ $“the U.S. are particularly well compensated, at $148,000 median” https://iapp.org/resources/article/2017-iapp-privacy-professionals-salary-survey-executive-summary/ Data
  61. 61. 61 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 61 New tools based on MLAI are helping with the tremendous difficult data management task (data lineage, data catalog, data dictionary, etc) Data
  62. 62. 62 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 62 Trek name: Build the data platform Deploy access roads to data sources Prepare data for analysis Build logical data platform Build physical data platform
  63. 63. 63 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 63 Data Ingestion Trends: nogatekeeper ▪ Real time (cdc, kafka) over batch (traditional ETL) ▪ Cloud integration ▪ Metadatatagging of data sets is more important Data
  64. 64. 64 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 64 • Transformation • Standardization • Quality Preparation in DW is done while ingestions by etl tools Preparation in data lake is done before analyses: Hence new category of tools “data preparations” Data warehouseData lake no gate keeper Data Logical preparation of Data: • Enhancement • Tagging
  65. 65. 65 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 65 Data
  66. 66. 66 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 66 Optimizing the performance of their company’s big data ecosystem ▪ Building data pipelines to collect data and move it into storage ▪ Preparing the data as part of an ETL or ELT process ▪ Stitching the data together with scripting languages; ▪ Working with the DBA to construct data stores; ▪ Ensuring the data is ready for use; ▪ Using frameworks and microservices to serve data. Who is doing all of the above? The Data engineer https://www.payscale.com/research/US/Job=Data_Engineer/Salary Data
  67. 67. 67 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 67 Data Lakes Virtual Data Warehouse Technologies & services for data platforms Physical data platform: Data Warehouse NoSQL Logical data platform: Data Preperation Data Preparation Tools Virtual DataWarehouse Providers:
  68. 68. 68 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 68 Customer Engagement Data-driven Business Employee Empowerment Now let’s go back to the CE Initiative CMO HR CDO Data Officer
  69. 69. 69 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 69 Customer Engagement Initiative Maximizing customer lifetime valueCustomer Customer Engagement
  70. 70. 70 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 70 Define customer’s value Set KPIs to measure mutual value Map out Personas Define organization’s value For each persona Trek name: DefineValue (for organization and for customers)
  71. 71. 71 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 71 •‫בת‬ ‫אישה‬32 •‫שיווק‬ ‫מנהלת‬ •‫סרטים‬ ‫אוהבת‬ •‫מחברים‬ ‫המלצה‬ •‫יחסית‬ ‫יקר‬ •‫רועשת‬ ‫מוזיקה‬ ‫בחנות‬ •‫של‬ ‫פרסום‬ ‫מתחרה‬ •‫ונקייה‬ ‫יפה‬ ‫חנות‬ •‫מגולח‬ ‫לא‬ ‫מוכר‬
  72. 72. 72 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 72 •‫בת‬ ‫אישה‬32 •‫שיווק‬ ‫מנהלת‬ •‫סרטים‬ ‫אוהבת‬ •‫מחברים‬ ‫המלצה‬ •‫יחסית‬ ‫יקר‬ •‫רועשת‬ ‫מוזיקה‬ ‫בחנות‬ •‫של‬ ‫פרסום‬ ‫מתחרה‬ •‫ונקייה‬ ‫יפה‬ ‫חנות‬ •‫מגולח‬ ‫לא‬ ‫מוכר‬
  73. 73. 73 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 73 Value The going currency in the customer/company relationship. A mutual perception of appropriate derived value is the one and only condition to the continuation and fruition of the relationship.
  74. 74. 74 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 74
  75. 75. 75 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 75 Richard Thaler 2017 Nobel prize winner for economics
  76. 76. 76 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 76 Design Journeys By using co-creation & creative methodologies Trek name: DesignValue, craft amazing customer experiences Focus on a sub-journey & pilot it (“Entrance-Value-Exit” capsule) Create a mission team (per sub-journey) Analyze journey design & orchestration
  77. 77. 77 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 77 Excellent Consistent Precise Stands out In line Simple Made to fit Flexible
  78. 78. 78 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 78 The E.V.E. Framework
  79. 79. 79 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 79 Trek name: DeliverValue (activate journeys) Document journeys Set rules and triggers Orchestrate touchpoints across channels Automate journeys
  80. 80. 80 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 80
  81. 81. 81 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 81 81
  82. 82. 82 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 82
  83. 83. 83 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 83
  84. 84. 84 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 84 eCommerce platforms Hybbris, Magento, Nopcommerce Multi-channel messaging platforms Personalization Maxymizer (Oravle), Optimizely… Engagement Channels: - Voice - Web - Mobile - eMail - Social - Chat - Video - ChatBots - Social - AR/VR - Etc… Engagement & Gamification Walkme, GameEffective, PlayBuzz Content Marketing Kapost, Contently, Oracle, Taboola, Outbrain… Marketing automation Oracle,Adobe, Salesforce, SAS, IBM… Trek name: DeliverValue (activate journeys)
  85. 85. 85 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 85 Bots platforms and products in Israel
  86. 86. 86 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 86 Global leader Marketing Automation Platforms in Israel:
  87. 87. 87 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 87 The channel divide Source: Christine Moorman, CMO Survey 2017 Channel strategy is extracted from the CX strategy
  88. 88. 88 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 88 Source: chatbots.org (Thanks,Amit Kama!)
  89. 89. 89 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 89 89 Trek name: Optimize experiences & journeys Build a lab for experimentations Use growth hacking methods Analyze Customer journeys Analyze Customer journeys
  90. 90. 90 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 90
  91. 91. 91 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 91 Rise in the use of Analytics & Optimization
  92. 92. 92 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 92 OnlineTesting Oracle Maxymizer,Adobe, Optimizely Customer Experience Analytics SAS,Adobe, IBM, ClickFox Cross-channel Attribution Google Adometry,AOL-Convertro, VisualIQ Interaction analysis Glassbox, IBMTealeaf Campaign optimization SAS Optimize experiences & journeys Netcraft by Elad Optimization Service Providers: Customer Experience/ Journey Analytics
  93. 93. 93 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 93 From a semi-manual, batch process To an automated, real-time architecture
  94. 94. 94 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 94 Customer Engagement Technologies Outlook 2018-2022 Web analytics BI & Discovery Identity and Access Mng (CIAM) CDPs Journey Analytics Digital Analytics AI-powered journeys Optimization of journeys Marketing automation Multivariant testing Disparate channels Predictive Analytics Personalization (channel specific) Personalization of Journeys
  95. 95. 95 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 95 Obstacles for Customer Engagement Initiative Success Siloed organization Change Mng. Culture 80% 70% 40% Skills shortage 40% Literacy 25%
  96. 96. 96 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 96 At some point, your journey will reach a dead end. It will seem impossible to go on. The key to proceed will lie in the hands of your most important (and least expected) partner.
  97. 97. 97 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 97 You can’t spell HERO without HR Sorry, did we say “HR”? we meant CHRO: Chief Human Relations Officer
  98. 98. 98 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 98 Customer Engagement Data-driven Business Employee Empowerment CMO HR CDO Data Officer
  99. 99. 99 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 99 Employee Empowerment Initiative Destination Maximize employees lifetime value for the future organization CHRO Employee Empowerment
  100. 100. 10 0 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 100 Skills shortage Siloed organizations Low engagement Un-coordinated efforts >90% of organizations feel they’re unprepared for the future. Why? Agile Not agile Wrong culture
  101. 101. 10 1 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 101 Change the way we Engage Change the way we Measure Performance Change the way we Hire Change the way we Learn Change the way we Operate Change the way we Communicate CHROs To-Do’s in an employee-driven market:
  102. 102. 10 2 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 102 Change the way we Engage Change the way we Measure Performance Change the way we Hire Change the way we Learn Change the way we Operate Change the way we Communicate CHROs To-Do’s in an employee-driven market:
  103. 103. 10 3 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 103 Employee Empowerment Initiative Employee Empowerment
  104. 104. 10 4 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 104 Trek name: Build the People Platform Collect employee data Create an employee data platform Unify HR &Talent processes
  105. 105. 10 5 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 105 People PlatformTechnology Players Talent Mng. & HRMS Suites
  106. 106. 10 6 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 106 Align goals Set KPIs to measure performance Understand organization goals Understand employee goals Organizational and employees Trek name: Align with organization goals
  107. 107. 10 7 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 107 Managing change will be one of HR’s most important roles
  108. 108. 10 8 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 108 108 Trek name: Optimize decisions based on data Develop hypothesis Gather missing data Invest in managers data literacy Develop & validate analytic models Grow HR-specific analytic skills
  109. 109. 10 9 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 109 People Analytics 8% Believe their organizations are excellent in it Believe using people analytics is important
  110. 110. 11 0 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 110 Look familiar? HROs – be CMOs. Source: LinkedInTalent Solutions
  111. 111. 11 1 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 111 Look familiar? HROs – be CMOs. Source: LinkedInTalent Solutions
  112. 112. 11 2 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 112 Matrix + Matrix BI Opisoft (SQlink) iProsis (for SAP SF) Hilan-Ness Technology providers for people data-driven decisions People Analytics service providers: Oracle HCM SAP Successfactors People Analytics technology providers:
  113. 113. 11 3 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 113 88% believe that building the organization of the future is very important. Only 11% understand how. - Deloitte Human CapitalTrends report 2017
  114. 114. 11 4 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 114 Source: Deloitte University Press HROs will design the future organization
  115. 115. 11 5 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 115 Agile Organizational Design Source: Josh Bersin, Deloitte Built for Efficiency Built for Agility
  116. 116. 11 6 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 116 CX is a long-term thing
  117. 117. 11 7 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 117 Quick wins can be dangerous Long-Term Growth … If they throw you off the road
  118. 118. 11 8 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 118 Let’s remember how we started this journey:
  119. 119. 11 9 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 119 What is at the end of the trio-initiative journey?
  120. 120. 12 0 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 120
  121. 121. 12 1 Copyright@STKI_2018 Do not remove source or attribution from any slide or graph 121 Einat Shimoni Einat@stki.info 054 70 000 24 121 Pini Cohen Pini@stki.info 054 70 000 23 Yoav Pridor Yoav@pridor.com 052 80 006 00

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