the power of insights - using analytics to create business value

0 Copyright 2016 FUJITSU

Fujitsu Forum 2016

#FujitsuForum


The Power of Insights - Using Analytics to Create Business Value

Naeem Sarwar

Head of Analytics, Fujitsu Digital

BAS, EMEIA


Digital is different things to different people

Transforming customer & user experience

Digitalizing business operations

Product leadership & innovation

Business-model transformation


Fujitsu Digital – our capability

Engagement & Incubation

Strategic Consulting Digital Applied Technologies

Digital Business Solutions

Internet of Things Analytics Software as a Service

Digital Industry Solutions

Retail

Financial Services

Transport


Customers of yester year


Customers of today


The era of BIG DATA


Customers Sharing Data

82

You have checked in at Train Station

189

161


The New Consumer

EMPOWERED

HYPERCONNECTED

OPINIONATED

HIGHLY VOCAL


New Breed Of Data – IoT


Shifts in the ecosystem are driving advanced analytics…

Big Data: real-time analytics of in-flight transitory data

Human Centricity 1. Consumers now demand to be placed at the centre of the organisation. Organisations are looking to improve productivity and staff morale. Workforce are demanding agility in their own working life and the use of technology to make their jobs easier.

New Channels & Data 2.

Emergence of new channels is creating significant data deluge. A wider range of connected devices – the ‘internet of things’ -will contribute to ever growing quantities

of data.

Operational & Asset Management 3.

Organisations are now looking to use Big Data to extract value from IoT and move towards a more proactive maintenance model and prevent instead of detect.

Through cutting edge analytics and platforms, organisations now have the ability to deploy strategies in real time.

Complexity of Interactions 4.

The growing complexity of interactions between marketing channels is proving difficult to navigate.

A convergence of marketing, analytics and technology will help drive effectiveness across every channel.


Descriptive Analytics

Diagnostic Analytics

Predictive Analytics

PrescriptiveAnalytics

Deployed across multiple markets

Financial Services and banks

Retail

Telecommunications and utilities

Insurance

Healthcare

Travel

Leisure and media

Automotive

Public sector

How can we make it happen?

What will happen?

Why did it happen?

What happened?

Difficulty

Valu

e

Advancement in analytics Data leads to decisions, actions & enablement…

Business Value

Com

plex

ity

of D

ata

Next generation analytical techniques that enable you to move from descriptive to prescriptive analytics


The Big Data Landscape


Data Strategy/Scoping Platform/ Architecture Advanced Analytics Visualisation

Wh

at

Is I

t / H

ow

do

we

do

it? Business Problem analysis Enterprise Architecture Descriptive and Predictive Real-time

Requirement Engineering Solution Architecture Clustering Dashboards

Workshops Platform Transformation Time Series Automated reports

Interviews Data Integration Network Analytics Business User Access

Data profiling Data Enrichment Recommendation Engine Querying

Initiation & Scoping Linkage and Matching Classification Location & Geo Spatial

Deep Learning

Machine Learning

Big Data – Fujitsu’s Expertise and Alliances


Big Data Value Chain – Execution & Deployment

Input can be structured data (from traditional database systems), unstructured data (such as image data, Twitter updates, online reviews, location data) or data from web- or network-connected devices such as weather sensors.

Data is analyzed and filtered – “crunched” – to turn it into meaningful intelligence.

These insights can be deployed in various ways – e.g. be mined by business users via visualization tools or reports, or serve to trigger automated actions in production.

1 2 3


Fujitsu Proposition and Capabilities

Strategy & Approach

SMART Technology

SMART People

SMART Data

SMART Themes

Detailed strategy of what we need to have and what we need to do with a tried and tested approach to deliver

Comprehensive themes that tackle customer lifecycle and IoT analytics. Built around solving business problems NOT IT

Extensive toolkit of for technology enablement and platforms where we will work with you to deploy the most effective solution into your business

Without people we can not deliver. The practice is staffed by MSc / PhD data scientists and architects as well as consultants that understand your business issues with over 50 years experience

Data is fundamental and acts as a USP with the ability to provide that 360 view – Access to the most comprehensive datasets. Consisting of 857 M individuals and 500+ attributes

Analytics Centre of Excellence that drives cutting edge innovative analytical solutions to solve business problems by leveraging Fujitsu and its partners’ technologies (via a consultative, collaborative Think big, start small approach).


Business Objectives & Strategy Understanding the business problem to assess what data will be required as a starting point – Consultative Approach

Assess Current Capability Detail the current picture in terms of data, sources, process

Design Future Capability Create both a vision, architecture and roadmap of future capability, ordered by anticipated return on investment

Valuing and Building the Data Asset What data do you need and what is going to deliver the solution

The Business Case Produce a high-level business case and implementation plan to unlock the benefit streams identified

Build Strong Partnerships

Fujitsu’s Approach and Methodology


Comprehensive partner agreements allowing access to data across 26 countries consumer classification that connects to over 2 billion consumers and approximately 857 million households

Global Data Reach


Analytics and Propositions

Make your data and infrastructure fully optimised and fit for analytics and marketing purposes to drive your strategy

Add forensic insight to your business by understanding and targeting customers and prospects for maximum return

Identify the best locations for your stores and what to stock in them.

Comprehensively understand footfall patterns throughout your store

Have the ability to serve tailored communications to your consumers digitally in real time whilst they are browsing on line or in store

Is your business geared up to be best in class to identify fraudulent clams utilising a 360 view of your applicants across big data sources

Improve operating cost efficiencies by utilising big data and IoT across your infrastructure and predictively identify problems before they start.


• Consultancy and analytics engagement • Tailored prioritised data driven strategy to

optimise collections strategy and enable individuals to enrol in a payment plan, placing the customer at the heart of the business

• Management and development of customer behavioural, value segmentation models, propensity to pay models and key performance indicators

Outcomes

• Client can make knowledge based decisions • Identification of customer ability to pay, payment

plans and contact strategy across best channels • Ability to launch new tailored products • Increase in productivity and efficiencies across

customer contact • Collections rose £12.7m in 9 months

Response

• Leading debt collection agency was not aware of customers not on a payment plan due to a lack of data driven strategy

• Business diagnostic we helped identify that 1.5m individuals were not in any payment plan which equated to £2bn of uncollected debt

Situation

Financial Services Optimising Collections Strategy


• Working in partnership with the agency Fujitsu developed a PoC predictive model geared to predicting fraudulent claims at point of application to prove the robustness of the model

• The predictive model utilised a vast array of data attributes using agency data as well as third party data

Outcomes

• The initial PoC model identified an uplift on fraudulent/erroneous claims of 25%

• Now in full BAU and runs in a dynamic automated real time environment, preventing fraud from entering into the system

• Identification of more than £85m per annum of fraud and error activity via the solution

• On average 13% of new applications were subject to fraud and error

Response

• Agency needed to reduce and understand level of fraud. Move towards a prevention and detect strategy at the point of application

• Improve monitoring and evaluation to ensure resources focused on areas of greatest financial loss and risk

• Need to quickly identify incorrect cases and deploy the appropriate follow up actions

Situation

Government Reducing fraud and error


• Roadmap identifying current capabilities and how to deliver best in class analytics identified

• Developed a data strategy for hygiene, enhancement and a single version of the truth

• Utilisation of data for predictive maintenance • Streaming of data in a near real time • PoC predictive models across a number of assets • Real time social media listening linked to call

centre management

Outcomes

• Improved Customer Experience Scores • Increased knowledge share across internal team

through utilisation of self serve analytics, single version of truth for data, analytics in a real time environment, effective dash-boarding and reporting on KPI’s

• Reduction in operating costs • Enablement of cross channel communications to

customers

Response

• Needed to improve Customer Experience Scores and customer centricity

• Increase engineer productivity • Move from scheduled maintenance programmes

to conditional based programmes via advanced analytics

• To enable the internal data and analytics teams to be best in class

Situation

Utilities company


A few Quotes…

In 2016, more businesses will see that customer success is a data job.

Companies that are not capitalizing on data

analytics will start to go out of business

The true value of analytics will be realized when ROI is maximized by analytics that

tell you what to do.

Today, most analytics projects start from the wrong place, end too soon, take too long – and still fall short. The reason: they

start with available data sources as the primary constraint. The solution: start with the business questions you want to answer

Companies will continue to seek

competitive advantage by adopting new big data

technologies

Technologists will shift their attention from Big Data to machine learning and providing proactive insights.

Active intelligence will become the new focus

Automated personalization will be a critical business benefit that big data analytics will

begin to deliver

Companies … will take a more thoughtful approach to

analyzing “useful” data to

reach fast, meaningful, holistic insights. Rather

than investing time and money in IT infrastructure to manage high

volumes of data Data itself is no longer the number one

problem; connected data is the problem. It is becoming increasingly difficult to reach that data, secure that data, much less draw insight and enable a person

or process to take action on the data