Increasing the Success of Business Analytics: Improving Requirements Determination? Ulrike Schultze, Cox School of Business, SMU

Motivation  New course prep: BA consulting project  Blueprinting a BA solution for brand management  Outline of project deliverables  Few conceptual tools for BA requirements determination  Reasons for BA project failure  Lack of adoption due to poorly understood requirements  Lack of user involvement  Insufficient communication b/w user and data scientist  Waterfall vs Agile

Why BA Projects Fail  analytics-projects-fail/ analytics-projects-fail/  Lack of Adoption by the Business Users – due to lack in involvement  most-business-intelligence-projects-fail-1.html most-business-intelligence-projects-fail-1.html  70-80% of BI projects fail (Gartner 2011)  Developers do not examine the business' own needs and the way they are evolving  agile is the answer  projects-can-fail/ projects-can-fail/  Lack of communication between data people and decision people resulting in wrong or flawed solutions

Project Scope Framework Approve Customer Credit Application Event ResultSubprocesses App sub- mitted Customer notified & Set up Case for Action Vision Metrics (of AS-IS)ActorsEnabling Mechanisms -Automated credit processing for small customers -Large customer apps handled in <2 days -1-4 hours applied time per application -7 days elapsed time per application -Process 150 apps per month; 10% growth per year -Loss of market share -Credit approval takes up to 2 weeks Complete Application Evaluate App Approve or Deny Inform Customer Set up Customer -Applicant -Sales Rep -Credit Rep -Credit Application -Credit Report -Notification Letter -Sales System

Tools for Requirements Determination  Swimlane diagram of AS-IS business process (e.g., brand management)  Strategy map of business area  Analysis of AS-IS Decisions  Objectives, metrics used, phase in analytical cycle, automated/manual, tools used, logic  Importance of decision (operational & strategic impact)  Performance of decision (speed, accuracy, …)  Identify decision opportunities for TO-BE (new decisions, access to better data, new BA applications)

Strategy Map (Balanced Scorecard) ROCE Customer Loyalty Customer Loyalty On-Time Delivery On-Time Delivery Process Cycle Time Process Cycle Time Process Quality Process Quality Employee Skills Employee Skills Financial Customer Internal/Business Process Learning and Growth Performance Drivers /Leading Measure Outcome/Lagging Measure

Prioritization Matrix

Enterprise Data Warehouse Bus Matrix Feasibility Analysis: Different colors designate existing vs new sources DatePolicy Holder Cove- rage Cover- ed Item AgentPolicyOnline Sear- ches Decision 1 xxxxxxx Decision 2 xxxx Decision 3 xxxx Data/Dimensions

Candidate BA Application List Rank App Name Short Descr Analytics Cycle Category Owner Biz Value Level of Effort App Type Data Elements Comments 1Dash- board Moni- tor 95Dash- board 2Data Minin g Cau- sality 85Algori- thm 3AlertsExcep -tions 97Alerts

Value Realization Grid Feasibility Potential Business Impact BAA4BAA3BAA2BAA1BAA5 BAA= Bus. Analytics Application

Specifications for Top Three BAA  Name, High-level description (who, what, when, how, why)  Criteria for Success  Application Details  Data (Sources and Elements) – but no tech or data architecture  Application Logic  Mock-up of Report

Final Deliverables: Implementation Plan & Business Case  TO-BE process flow (with new decisions and BA apps)  Stakeholder Analysis  Assessment of change readiness  Planning for resistance  GANTT chart to implement top three BA apps  Executive Summary: Making the Business Case