Business Insights through Big Data

Transcription

1 Business Insights through Big Data PREDICTIVE ANALYTICS AND BUSINESS INSIGHTS 2014 PHILADELPHIA Gagan Saxena, VP & Principal Consultant Decision Management Solutions

2 Decision Management Solutions We help organizations plan, design, build and operate Decision Management Systems. Automate high-volume operational decisions using Big Data Analytics, Business Rules and Optimization Algorithms. 1

3 Agenda 1. Business Insight and Analytics 2. From Individual to Organizational Insights 3. What is Decision Management? 4. Decision Modeling 5. Insights in Context: Decision Transparency 2

4 Business Insight and Analytics 3

5 What is an Analytic Insight? A Predictive Analytic Model The Results of Data Mining An Optimization Model A Forecast An Estimate A Report A Visualization 4

6 The 4 Traps of Predictive Analytics 1. Magical Thinking: Plug-in Data, Reap Profits 2. Starting with the Boss: Focus on Strategic Decisions 3. Building Cottages, not Factories: Not building to Scale 4. Seeking Purified Data: Won t move until Data is Perfect 5

7 4 Steps to Analytics Success Be clear which decisions you are improving Understand decision context - how those decisions impact the business Decompose decisions to understand them Deploy analytical decisions to the systems and processes that need them 6

8 Decisions need Insights DECISIONS DASHBOARD Knowledge is available from various Sources Transactional Data Human Expertise Historical Aggregated Data External Data Analytical Models Automated Business Rules Different Technologies used for each Knowledge Source Formal methods are needed to describe Decisions, Information Sources and Knowledge Sources 7

9 Dashboards, Visualization & Mining DECISIONS DASHBOARD Models Other Knowledge Patterns DATA MINING DATA VISUALIZATION Data Data 8

10 Value for Decision Making Decisions with Limited Knowledge Human Expertise Transactional Data Historical Aggregated Data Analytical Models Automated Business Rules Effort required for Knowledge Extraction These two knowledge sources are not readily accessible LIMITATIONS (1) Hidden patterns in data and predictive insights not used (2) Standard decision patterns and activities are reinvented every time 9

11 From Individual Insights to Org Insights 10

12 Knowledge is Diffused in Large Orgs Trade-Offs Small Org Larger Org Experience, Training, Policies, QC, Approvals Patterns Predictions Learnt Rules Information Information System Coding Knowledge Knowledge DECISION DECISION ACTION ACTION 11

13 What is Changing Today? Trade-Offs Patterns Predictions Optimization Data Mining Predictive Analytics Learnt Rules Knowledge Information Business Rules Knowledge Big Data Information DECISION DECISION MANAGEMENT TECHNOLOGY ACTION 12

14 To Harness Big Data, Focus on Decisions Trade-Offs Patterns Predictions Optimization Learnt Rules Knowledge Information Data Mining Business Rules Knowledge Predictive Analytics Big Data Information DECISION DECISION ACTION DECISION MANAGEMENT TECHNOLOGY CONSIDER DECISION FIRST 13

15 Decision Management To-Do 14

16 Business Rules Predictive Analytics External Data Big Data 15

17 Delivering Decision Management Identify and Model Decisions Automate Decisions, Build Services Measure and Improve Decisions 16

18 Decision Management 17

19 What is Decision Management? Business Discipline Enhance Business Processes Enforce Business Rules Manage Uncertainty using Analytics Increase Transparency & Business Controls AND Technology Stack Business Rule Management Advanced Analytics Optimization Decision Analysis 18

20 Strategic Decisions Tactical Decisions Operational Decisions 19

21 Operational Decisions: Everywhere 20

22 Decisions deliver Customer Value 21

23 Decisions scale for Large Impact 22

24 Value Expert Decisions Manual Decisions Automated Decisions Complexity 23

25 Repeatable decisions Non-trivial decisions With a Measurable Business Impact That are Candidates for Automation 24

26 Decision Modeling 25

27 Need to Describe Decisions Accurately Information What is needed? Where does it come from? Knowledge How to make it? How to improve it? Precision Exactly how? Specificity without technical details Context Application Organization Business Goals 26

28 What is required to make a Decision? Guidelines, Policy documents Human Expertise Regulations Data describing the situation External reference data Predictive Analytic Models Data Mining Results The results of other Decisions 27

29 Decision Model and Notation (DMN) INDUSTRY STANDARD FROM OBJECT MANAGEMENT GROUP January

30 A Decisions Requirement Model Knowledge Decision Information 29

31 Manage Business Rules Ownership, volatility Documented sources Link to implementation Coherent rule groups 30

32 Decision Models balance Instinct, Analytics Analytic Instinct Policies and Regulations Too Analytic 31

33 Manage Automation Boundaries FIRST CANDIDATE FOR AUTOMATION 32

34 Decision Modeling Imperatives Agile Decision Requirements Build diagrams quickly, finding and reusing objects or importing existing information Connect Decisions, Processes, Systems, Orgs Put decisions into context, linking them to process, systems and organizations. Collaborate across silos Accessible from anywhere, a social powered and collaborative environment supports multiple perspectives Integrate with your Approach Define your own completeness levels and link to your BRMS, Analytics and Optimization 33

35 Insights in Context: Decision Transparency 34

36 Decision Models improve Transparency Links Action Uses a non-technical notation Model can be built by Business Analysts To Analytic 35

37 Target Decisions on KPIs Strategy defines KPIs KPIs measure operations Operational decisions affect KPIs The link between decisions and KPIs is critical 36

38 Build Confidence with Decision Context 37

39 Decision Models frame Collaboration Which Processes use this? Who decides this? Who determines how this is decided? 38

40 Decision Models capture Best Practices Document Best Practices Share models, Build Consensus Discuss Decision-making Approaches 39

41 Take Away Trade-Offs Learnt Rules Patterns Knowledge Predictions Information Decisions First Business Driven Initiative Deploy Enterprise Knowledge Experiment and Learn DECISION ACTION Much More At DecisionManagementSolutions.com 40