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5 Critical Success Factors for Embedded Analytics

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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
Transcript

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

Today’s Speakers

Slide 2 © 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.

Logistics for Today’s Webinar

Slide 3 © 2017 Enterprise Management Associates, Inc.

An archived version of the event recording will be

available at www.enterprisemanagement.com

• Log questions in the chat panel located on the lower

left-hand corner of your screen

• 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

Lyndsay Wise

Research Director

Enterprise Management Associates

Twitter: @wiseanalytics

Five Critical Success Factors

for Embedded Analytics

Agenda

A look at embedded analytics

• How user expectations differ between traditional and embedded analytics

• The barriers to adoption that embedded analytics can help overcome

• How organizations can gain buy-in and sell the value to project stakeholders

• Use cases and examples of operational and customer-focused embedded analytics

• Technical requirements and differences of both operational and customer-focused

embedded analytics

5 critical success factors

• Tying embedded analytics to strategic business goals and planning

• Focus on information visibility across the organization

• Ensure better data access

• Real-time value

• Constant visibilitySlide 5

Why Embedded Analytics?

Slide 6

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 © 2017 Enterprise Management Associates, Inc.

Traditional Analytics

Limited reach within organization

Pre-defined analytics

Information silos

Longer times to delivery

Barriers To Analytics – Solving Them Through Embedded

Analytics Adoption

Wide adoption remains hard – 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 – 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 don’t have to think to get information

applicable to their line of business

Assumption of trust – developed to take into

account business scenarios, rules, and

processes

Slide 8 © 2017 Enterprise Management Associates, Inc.

Gaining Buy-In And Selling The Value To Project

Stakeholders

Slide 9 © 2017 Enterprise Management Associates, Inc.

Use Cases Of Operational And Customer-Focused

Embedded Analytics

Slide 10 © 2017 Enterprise Management Associates, Inc.

Technical requirements for embedded analytics

• Level of integration – portal versus white

labeled within application

• Security and privacy of data – 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

• Potential need for multi-tenancy for

customer-focused embedded analytics

• Level of embedded access – URL to white

labeling – what type works best may differ

based on use caseSlide 11 © 2017 Enterprise Management Associates, Inc.

5 Critical Success Factors

Slide 12

1. Tying embedded analytics to strategic business goals

and planning

Slide 13 © 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

1. Tying embedded analytics to strategic business goals

and planning

Slide 14 © 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?

2. Focus on information visibility across the organization

Slide 15 © 2017 Enterprise Management Associates, Inc.

2. Address data silos

Slide 16 © 2017 Enterprise Management Associates, Inc.

3. Ensure better data access

• Making sure data is consolidated only

provides value if it is available to users in

the way they require

• Looking at self-service in a way that

meets needs of user groups

• Information needs to be easy to get to –

both in terms of self-service and

visibility/transparency based on who

needs what information

• Embedded provides this type of capability

providing embedded is delivered with

these considerations in mindSlide 17 © 2017 Enterprise Management Associates, Inc.

3. A little about self-service

Slide 18 © 2017 Enterprise Management Associates, Inc.

4. Real-time value

• Latency has always been an issue for companies

• Embedded analytics provide real-time access and give users

instant access to data/analytics

• Historic reports only provide part of the picture for trends or

planning but not for operational analytics or efficiencies

• Operational BI enables constant business visibility to what is

happening within specific processes

• Organizations cannot wait until after the fact to get the

visibility into operations they need

Slide 19 © 2017 Enterprise Management Associates, Inc.

5. Constant visibility

• Real time access leads to

constant visibility

• Organizations understand what is

happening as it is happening and

can become more proactive.

• Identify potential risks more

proactively

• Take action when issues occur

• Evaluate factors of performance

Slide 20 © 2017 Enterprise Management Associates, Inc.

5. Real-time for embedded BI

Slide 21 © 2017 Enterprise Management Associates, Inc.

Takeaways

Slide 22 © 2014 Enterprise Management Associates, Inc.

• Embedded BI can enhance a broader analytics program and

provide operational insights

• Organizations need to align their business strategy with their data

access

• Evaluate the type of embedded analytics that work best by targeting

the level of self-service access

• Identify the latency required to meet business needs

• Leverage embedded analytics to increase overall information

visibility

Embedded BI and AnalyticsThe Information Builders Approach

23

Jake FreivaldVP, Product Marketing

Better Data. Better Analytics.Information Builders

25

Grouped by sections

Data Quality

Data Governance

Master DataManagement

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 InfoApps™ Mobile

Natural Language/Narrative BI

Data Discovery Reporting Dashboards

High-PerformanceData Store

Intelligence

Location Analytics

Casting and Archiving

In-DocumentAnalytics

SearchPredictive Analytics

Sentiment and Word Analytics

Performance Management

SocialHot

BadFeedback

Write-Back

26

Grouped by sections

Data Quality

Data Governance

Master DataManagement

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 InfoApps™ Mobile

Natural Language/Narrative BI

Data Discovery Reporting Dashboards

High-PerformanceData Store

Intelligence

Location Analytics

Casting and Archiving

In-DocumentAnalytics

SearchPredictive Analytics

Sentiment and Word Analytics

Performance Management

SocialHot

BadFeedback

Write-Back

IT Developers Management Operational Workers Business Partners Customers

Tools for business users & ITSelf-Service for Everyone

Business Analysts

App Studio InfoAssist+

DataDiscovery

PredictiveAnalytics

SocialIntelligence

Search

LocationIntelligence

Reporting

Dashboards

Generate & Deploy Insights

SocialHot

BadFeedback

IT Developers Management Operational Workers Business Partners Customers

Tools for business users & IT – InfoApps™ for non-technical usersSelf-Service for Everyone

InfoApps™

Dashboards & Scorecards

Governed Self-service Reporting

Mobile InfoAppsE-Statements

Data Discovery InfoApps

Predictive InfoApps Search & Social Analytic InfoApps

Operationalize Insights & Monetize Data

Business Analysts

App Studio InfoAssist+

DataDiscovery

PredictiveAnalytics

SocialIntelligence

Search

LocationIntelligence

Reporting

Dashboards

Generate & Deploy Insights

SocialHot

BadFeedback

Embedded BI

For Commercial Portals

168/286 JSR-compliant portlets/webparts

For Custom Portals and SaaS-style Apps

a. iFrame “Mashup” Style – simplest

b. RESTful Web Service API – 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

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

WebFOCUS at Chrome River

31

SaaS Application

CreateExpenseReport

ChromeRiver

Servers

Review/ApproveReports

ReimbursementDeposit

AccountsPayable

ClientBilling

ClientInvoices

Data exportsData imports

Clients /Matters

DailyFX Rates

CashAdvances

Credit cardTransactions

ScannedReceipts

PhoneEntries

Computer Services, Customer Since 2009

Don’t Take Our Word For It

32


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