New Path To Value Fall

8/7/2019 New Path To Value Fall

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New Path To Value FallNew Path To Value Fall

Deebika.S

RameshKumar

Mishaal Hamza

Absin.P.Abraham

MohanDoss


2/27

AGENDAAGENDA

y EXECUTIVE SUMMARY

y KEY FINDINGS

y

ANALYTICS THE DIFFERENTIATORy RECOMMENDATIONS

y SETTING UP FOR SUCCESS

y

THE SURVEY


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EXECUTIVE SUMMARYEXECUTIVE SUMMARY

y Smartest organizations are already capitalizing

on increased information richness and analytics

to gain competitive advantage.

y Top performers view analytics as a differentiatory Data not the obstacle Lack of understanding

& Lack of management bandwidth

y Where is the focus ? Historical reporting

replaced with emerging approaches.

y The five critical recommendations.


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RECOMMENDATIONSRECOMMENDATIONS

y Focus on the biggest opportunities first

y Start with questions, not data.

y Embed insights to drive action

y Keep existing capabilities while adding new

ones

y Build the analytics foundation according to an

information agenda


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KEY FINDINGSKEY FINDINGS

y Knowing what happened and why it happened areno longer adequate

y Improvement of information and analytics was a toppriority 50%

y Significant pressure to adopt advanced informationand analytics approaches - >20%

y Innovating to achieve competitive differentiation asa top business challenge 60%

y Organization has more data than it can useeffectively 60%

y Analytics should be closely linked to strategy


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ANALYTICSANALYTICS THETHE

DIFFERENTIATORDIFFERENTIATORy Business information and analytics differentiatestop players within their industry

y Analytics to guide future strategies and twice as

likely to use insights to guide day-to-dayoperations

y The correlation between performance and

analytics-driven management has important

implications to organizations whether they areseeking growth, efficiency or competitive

differentiation


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ANALYTICAL CAPABILITYANALYTICAL CAPABILITY

y Aspirational: These organizations are the farthest

from achieving their desired analytical goals.

y Experienced: Experienced organizations are

developing better ways to effectively collect,

incorporate and act on analytics so they can begin to

optimize their organizations.

y Transformed: These organizations have substantial

experience using analytics across a broad range of

functions.

y Common Practice : organizations tend to wait until

they have gained some experience before they apply

analytics to growth objectives


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DATA NOT THE OBSTACLEDATA NOT THE OBSTACLE

y Lack of understanding of how to use analytics to

improve the business 40%

y Management bandwidth due to competing

priorities- >33.33%y Concern with data quality or ineffective data

governance 20%

y Best Buy Case Example- Analytics, Not Best

Guess, Drive Ad Decisions


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WHAT LEADERS CAN DOWHAT LEADERS CAN DO

y Reduced time to value: Value creation can be

achieved early in an organizations progress to

analytics sophistication.

y Increased likelihood of transformation thatsboth significant and enduring

y Greater focus on achievable steps efforts and

resources narrowly, rather than implementing

universal changes


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FocusFocus on the Biggest andon the Biggest and

Highest Value OpportunitiesHighest Value Opportunitiesy Attacking the biggest challenge carry the biggestrisk of failure? Paradoxically, no because big

problems command attention and incite action.

y Its extraordinarily hard for people to changefrom making decisions based on personal

experience to making them from data

especially when that data counters the prevailing

common wisdom


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PADIETechnique forPADIETechnique for

OperationalizingA

nalyticsOperationalizingA

nalyticsTechnique is a simple means by which acompany can operationalize insights drawn from

data. Its a three-step process.

y Step 1 Document existing processes andapplications.

y Step 2 Identify data and insights

y Step 3 Embed analytic insights


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y The single greatest opportunity and challenge - to

speed adoption of analytics is to embed them into

daily operations.

y The PADIE technique helps users across the

organization understand from the start the full

initiative as it applies to a specific business challenge.

y This technique enables business and analytic teams to

work together to create analytic models based on usecases that show analytics in action.


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Recommendation 2Recommendation 2

Within Each Opportunity, Start With

Questions, Not Data

y Organizations are tempted to start by gathering

all available data before beginning theiranalysis.

y Collecting, cleansing and converting data - that

leaves little time, energy or resources to

understand its potential uses.


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y

By defining the desired insights first, organizationscan target specific subject areas, and use readily

available data in the initial analytic models.

y Organizations that start with the data or process

change first often end up with unintendedconsequences.

y Such as data that is not extensible or processes that

are ultimately eliminated - that require rework and

additional resources to solve.


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Speeding insights into businessSpeeding insights into business

operationsoperationsy Organizations should start by pinpointing theinsights to be leveraged, then use readily

available data to test the analytic models.

y Actions based on those insights will help definethe next set of insights and data needed.

y The traditional approach of starting with a

comprehensive data program creates too much

lag time before insights can be put into action.


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y

To keep the three gears moving together data,insights and timely actions the overriding business

purpose must always be in view.

y Data and models get accepted, rejected or improved

based on business need.y New analytic insights - descriptive, predictive and

prescriptive - are embedded into increasing numbers

of applications and processes.


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Recommendation 3:Recommendation 3:

Embed Insights to DriveActions and Deliver ValueEmbed Insights to DriveActions and Deliver Valuey Use cases, analytics solutions,

optimization, work flows and simulations

y Respondents identified trend analysis,

forecasting and standardized reporting as

the most important tools they use today

y Identified tools that will have greater

value in 24 months.


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In the next 24 months Staples to be surpassedIn the next 24 months Staples to be surpassed

by;by;y Data visualization, such as dashboards and

scorecards

y Simulations and scenario development

y Analytics applied within business

processes

y Advanced statistical techniques, such as

regression analysis, discrete choicemodeling and mathematical optimization.


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ExamplesExamples

y GPS-enabled navigation devices can

superimpose real-time traffic patterns and

alerts onto navigation maps and suggest

the best routes to drivers

y Production engineers in Oil Exploration

can incorporate geological, production

and pipeline information into their drillingdecisions


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Top three Analytic TechniquesTop three Analytic Techniques

y Historic trend analysis

and forecasting

y Standardized reporting

y

Data visualization

y Analytics applied within

business processes

y Simulations and

scenario development

y Clustering and

segmentation

y Regression analysis,

discrete choice modeling and

mathematical optimization

Data visualization

Simulations and

scenario development

Analytics applied withinbusiness processes

Regression analysis,

discrete choice modeling and

mathematical optimization

Historic trend analysisand forecasting

Clustering and

segmentation

Standardized reporting

Today In 24 Months


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Recommendation 4Recommendation 4

Keep Existing CapabilitiesWhile Adding New OnesKeep Existing CapabilitiesWhile Adding New Onesy Spreadsheets and charts need not go away,

New tools should supplement earlier ones, or

continue to be used side by side, as needed

y Disciplines like Finance and Supply chain are

inherently data intensive, and are often where

analytics first take root

y 63% Transformed organizations more than

Aspirational organizations use a centralized

enterprise unit as the primary source of analytics


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Centralized Analytics UnitCentralized Analytics Unit -- AdvantageAdvantagey Advancing standard methods for identifying business

problems to be solved with analytics

y Facilitating identification of analytic business needs while

driving rigor into methods for embedding insights into end-to-end processes

y Promoting enterprise-level governance on prioritization,master data sources and reuse to capture enterpriseefficiencies

y Standardizing tools and analytic platforms to enable resourcesharing, streamline maintenance and reduce licensingexpenses


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Recommendation 5Recommendation 5Use an Information Agenda to Plan for the FutureUse an Information Agenda to Plan for the Future

y Organizations want data that is integrated,

consistent and trustworthy, which were the

leading data priorities cited by therespondents

y The information agenda is a key enabler of

analytic initiatives by providing the right

information and tools at the right times based

upon business driven priorities


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Outline for an InformationAgendaOutline for an InformationAgenda

y Information governance policies and tool kits

y Data architecture from ad hoc to optimalphysical and logical views of structured and

unstructured information and databasesy Data currency from only historical data to a

real-time view of all information

y

Data management, integration and middlewarey Analytical tool kits based upon user needs from

basic search, query and reporting to advancedanalytics and visualization


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Different CompaniesDifferent Companies differentdifferent

ApproachesApproachesy Aspirational

y Experienced

y Transformed


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Analytics Across FunctionsAnalytics Across Functions


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TechniquesTechniques

y Pick your spots

y Prove the value

y Roll it out for the long haul

y Management approaches

Reduced time to value

Increased likelihood of transformationthats both significant and enduring

Greater focus on achievable steps.

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