5 Critical Success Factors for Embedded Analytics
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The document discusses embedded analytics and five critical success factors for embedded analytics projects. It provides an overview of embedded analytics compared to traditional BI, discusses how embedded analytics can help overcome barriers to analytics adoption, and outlines use cases. It then details five critical success factors for embedded analytics: 1) tying analytics to strategic goals and planning, 2) focusing on information visibility, 3) ensuring better data access, 4) providing real-time value, and 5) maintaining constant visibility. The presentation concludes with a discussion of Information Builders' approach to embedded analytics.
5 Critical Success Factors for Embedded Analytics
- 1. Lyndsay Wise Research Director Enterprise Management Associates Twitter: @wiseanalytics Five Critical Success Factors for Embedded Analytics Jake Freivald VP of Product Marketing Information Builders Twitter: @jdfreivald
- 2. Todayās Speakers Slide 2 Ā© 2017 Enterprise Management Associates, Inc. Lyndsay Wise, Research Director Lyndsay Wise joined EMA in 2015 as Research Director for Business Intelligence (BI) and Data Warehousing, focusing on data integration, data governance, cloud technologies, data visualization, analytics, and collaboration. She has over 10 years experience in software research, BI consulting, and strategy development, specializing in software evaluation and best-fit solution selection. Jake Freivald, VP of Product Marketing In his position as Vice President of Product Marketing for Information Builders, Jake is responsible for strategic and product-level messaging, content creation for digital marketing, and related requirements for press and analyst relations. He graduated from Cornell University with a Bachelor of Science in Electrical Engineering in 1991.
- 3. Logistics for Todayās Webinar Slide 3 Ā© 2017 Enterprise Management Associates, Inc. An archived version of the event recording will be available at www.enterprisemanagement.com ā¢ Log questions in the chat panel located on the lower left-hand corner of your screen ā¢ Questions will be addressed during the Q&A session of the event QUESTIONS EVENT RECORDING A PDF of the speaker slides will be distributed to all attendees PDF SLIDES
- 4. Lyndsay Wise Research Director Enterprise Management Associates Twitter: @wiseanalytics Five Critical Success Factors for Embedded Analytics
- 5. Agenda A look at embedded analytics ā¢ How user expectations differ between traditional and embedded analytics ā¢ The barriers to adoption that embedded analytics can help overcome ā¢ How organizations can gain buy-in and sell the value to project stakeholders ā¢ Use cases and examples of operational and customer-focused embedded analytics ā¢ Technical requirements and differences of both operational and customer-focused embedded analytics 5 critical success factors ā¢ Tying embedded analytics to strategic business goals and planning ā¢ Focus on information visibility across the organization ā¢ Ensure better data access ā¢ Real-time value ā¢ Constant visibility Slide 5
- 7. Traditional Business Intelligence vs. Embedded Analytics Embedded Analytics Ease of use Broad deployment Intuitive self-service Supports agility Easy to reach customers Real-time operational access Slide 7 Ā© 2017 Enterprise Management Associates, Inc. Traditional Analytics Limited reach within organization Pre-defined analytics Information silos Longer times to delivery
- 8. Barriers To Analytics ā Solving Them Through Embedded Analytics Adoption Wide adoption remains hard ā depending on solution, self-service does not truly exist for most business users Data access is limited with data silos and lack of information sharing Difficult to create real-time data access Requires an understanding of where data comes from and how it interrelates Lack of trust ā can create invalid analytics or access to wrong data No barrier to access as analytics become a part of operational/transactional applications Predefined access takes out the guesswork Ability to stream analytics within applications Users donāt have to think to get information applicable to their line of business Assumption of trust ā developed to take into account business scenarios, rules, and processes Slide 8 Ā© 2017 Enterprise Management Associates, Inc.
- 9. Gaining Buy-In And Selling The Value To Project Stakeholders Slide 9 Ā© 2017 Enterprise Management Associates, Inc.
- 10. Use Cases Of Operational And Customer-Focused Embedded Analytics Slide 10 Ā© 2017 Enterprise Management Associates, Inc.
- 11. Technical requirements for embedded analytics ā¢ Level of integration ā portal versus white labeled within application ā¢ Security and privacy of data ā need to ensure that operational intelligence data reflects the access level of those who view it; customer-focused needs to provide customers with trust that their data is secure ā¢ Potential need for multi-tenancy for customer-focused embedded analytics ā¢ Level of embedded access ā URL to white labeling ā what type works best may differ based on use case Slide 11 Ā© 2017 Enterprise Management Associates, Inc.
- 12. 5 Critical Success Factors Slide 12
- 13. 1. Tying embedded analytics to strategic business goals and planning Slide 13 Ā© 2017 Enterprise Management Associates, Inc. Identify Strategic Goals Understand How Data Fits Develop A Data Driven Approach Tie Data To Business Initiatives Leverage Analytics For Constant Visibility
- 14. 1. Tying embedded analytics to strategic business goals and planning Slide 14 Ā© 2017 Enterprise Management Associates, Inc. What information and metrics are required to manage the process? How are data and business processes interrelated? What information is needed to manage business processes? What actions need to take place for deviations or missed targets? What information is tied to strategic business goals?
- 15. 2. Focus on information visibility across the organization Slide 15 Ā© 2017 Enterprise Management Associates, Inc.
- 16. 2. Address data silos Slide 16 Ā© 2017 Enterprise Management Associates, Inc.
- 17. 3. Ensure better data access ā¢ Making sure data is consolidated only provides value if it is available to users in the way they require ā¢ Looking at self-service in a way that meets needs of user groups ā¢ Information needs to be easy to get to ā both in terms of self-service and visibility/transparency based on who needs what information ā¢ Embedded provides this type of capability providing embedded is delivered with these considerations in mind Slide 17 Ā© 2017 Enterprise Management Associates, Inc.
- 18. 3. A little about self-service Slide 18 Ā© 2017 Enterprise Management Associates, Inc.
- 19. 4. Real-time value ā¢ Latency has always been an issue for companies ā¢ Embedded analytics provide real-time access and give users instant access to data/analytics ā¢ Historic reports only provide part of the picture for trends or planning but not for operational analytics or efficiencies ā¢ Operational BI enables constant business visibility to what is happening within specific processes ā¢ Organizations cannot wait until after the fact to get the visibility into operations they need Slide 19 Ā© 2017 Enterprise Management Associates, Inc.
- 20. 5. Constant visibility ā¢ Real time access leads to constant visibility ā¢ Organizations understand what is happening as it is happening and can become more proactive. ā¢ Identify potential risks more proactively ā¢ Take action when issues occur ā¢ Evaluate factors of performance Slide 20 Ā© 2017 Enterprise Management Associates, Inc.
- 21. 5. Real-time for embedded BI Slide 21 Ā© 2017 Enterprise Management Associates, Inc.
- 22. Takeaways Slide 22 Ā© 2014 Enterprise Management Associates, Inc. ā¢ Embedded BI can enhance a broader analytics program and provide operational insights ā¢ Organizations need to align their business strategy with their data access ā¢ Evaluate the type of embedded analytics that work best by targeting the level of self-service access ā¢ Identify the latency required to meet business needs ā¢ Leverage embedded analytics to increase overall information visibility
- 23. Embedded BI and Analytics The Information Builders Approach 23 Jake Freivald VP, Product Marketing
- 24. Better Data. Better Analytics. Information Builders
- 25. 25 Data Quality Data Governance Master Data Management Integrity Integration Batch ETL Real-Time ESB ApplicationsLegacy Systems Relational/Cubes Big Data Columnar/In Memory Unstructured Social Media Web Services Trading PartnersIoT Hadoop-Based BI Portal Embedded InfoAppsā¢ Mobile Natural Language/ Narrative BI Data Discovery Reporting Dashboards High-Performance Data Store Intelligence Location Analytics Casting and Archiving In-Document Analytics SearchPredictive Analytics Sentiment and Word Analytics Performance Management Social Hot Bad Feedback Write-Back
- 26. 26 Data Quality Data Governance Master Data Management Integrity Integration Batch ETL Real-Time ESB ApplicationsLegacy Systems Relational/Cubes Big Data Columnar/In Memory Unstructured Social Media Web Services Trading PartnersIoT Hadoop-Based BI Portal Embedded InfoAppsā¢ Mobile Natural Language/ Narrative BI Data Discovery Reporting Dashboards High-Performance Data Store Intelligence Location Analytics Casting and Archiving In-Document Analytics SearchPredictive Analytics Sentiment and Word Analytics Performance Management Social Hot Bad Feedback Write-Back
- 27. IT Developers Management Operational Workers Business Partners Customers Tools for business users & IT Self-Service for Everyone Business Analysts App Studio InfoAssist+ Data Discovery Predictive Analytics Social Intelligence Search Location Intelligence Reporting Dashboards Generate & Deploy Insights Social Hot Bad Feedback
- 28. IT Developers Management Operational Workers Business Partners Customers Tools for business users & IT ā InfoAppsā¢ for non-technical users Self-Service for Everyone InfoAppsā¢ Dashboards & Scorecards Governed Self- service Reporting Mobile InfoApps E-Statements Data Discovery InfoApps Predictive InfoApps Search & Social Analytic InfoApps Operationalize Insights & Monetize Data Business Analysts App Studio InfoAssist+ Data Discovery Predictive Analytics Social Intelligence Search Location Intelligence Reporting Dashboards Generate & Deploy Insights Social Hot Bad Feedback
- 29. Embedded BI For Commercial Portals 168/286 JSR-compliant portlets/webparts For Custom Portals and SaaS-style Apps a. iFrame āMashupā Style ā simplest b. RESTful Web Service API ā maximum control and flexibility For Resellers, Partners, and On-Premises Apps Deliver a fully customized and styled BI service within or alongside an on-premises application 29 Some technical details
- 30. Information Builders understands the economics of the SaaS business. They were able to come up with a pricing structure that works for both of us. Alan Rich Chief Executive Officer WebFOCUS at Chrome River 30 Software Provider Makes SaaS Offering Shine With BI Challenge: Integrate a robust reporting solution that supports RIAs in a lightweight, web-based deployment model. Establish flexible pricing to complement a subscription-based SaaS model. Strategy: Create parameterized reports that leverage a multitenant security model, and augment these reports with a flexible ad hoc environment. Results: Expense reporting now includes flexible inquiry and analysis tools that provide visibility into spending patterns by office, department, practice group, user, client, and other variables. Computer Services, Customer Since 2009
- 31. WebFOCUS at Chrome River 31 SaaS Application Create Expense Report Chrome River Servers Review/ Approve Reports Reimbursement Deposit Accounts Payable Client Billing Client Invoices Data exportsData imports Clients / Matters Daily FX Rates Cash Advances Credit card Transactions Scanned Receipts Phone Entries Computer Services, Customer Since 2009
- 32. Donāt Take Our Word For It 32
- 33. Additional Resources 33 Videos What is Embedded BI and its requirements? Other information Fact sheet Recent blog post Customer story Paycor embeds WebFOCUS into their HR application White paper Making a Case for Embedded Business Intelligence