Ovum - data is changing the game - Tim Jennings

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Industry Transformation: How

Data is Changing the Game

Tim Jennings, Chief Analyst & Research Fellow, Ovum IT

[email protected]

@tjennings

Nov 25, 2013

mailto:[email protected]

© Copyright Ovum. All rights reserved. Ovum is an Informa business. 2


Agenda

Changing the game

Optimizing business processes

Transforming business functions

Disrupting industries



Heerenveen performance – Season 2013/14

Source: www.squawka.com


Data-driven digital transformation

Businesses and industries are becoming digital

What does this mean?


Tim’s digital journey


Data-driven digital transformation

Businesses and industries are becoming digital

What does this mean?

Data is at the heart of industry change

Data has become a fundamental asset to exploit

On a par with capital and human resources

Applies to all strategic models

Customer-centric

Operations-centric

Product-centric


Banking example – Commonwealth Bank of Australia

Integrated transactional data with social

interactions and on-site behaviours to provide

personalized web experience and online tools

Data from these tools creates deeper insight

into customer needs and behaviour

Adopting analytics for fraud detection has

reduced cheque fraud by 50% and internet

fraud by 80%

Monitor social media to find disaffected

customers from other banks

Creating relationships with other data sources

such as consumer property portals

“Information gleaned from customer

transactions … is now more important than the

transaction itself” – Michael Harte, CBA CIO


Telecoms example – Telecoms Italia

Monitoring of network and service provisioning.

Real-time performance and capacity planning for

network traffic

Competitor network analysis to inform strategic

decisions and investments

Optimizing quality of service to increase customer

lifetime value

Creating campaigns to target customer micro-

segments. Increased campaigns from 20 to 350

per month

Analysis of social media activity to monitor and

influence brand reputation and measure digital

communication strategy


Are things really changing?

Haven’t we always exploited (or tried to exploit) data?

What about social, mobile and cloud?

These are channels

Technology + business innovation

Data is the driver for change


Data storage has moved from analogue to digital

Source: Hilbert and López, “The world’s technological capacity to

store, communicate, and compute information”, Science, 2011



A blast from the tennis past


Source: Hawk-Eye /tennistv.com


Source: BioSport Technologies

• Power generation

process

• Trunk stability

• Lower body mechanics

• Muscular loading

• Arm speed

• Racquet speed


Retail example – Tesco

Well-established utilization of customer data,

based on loyalty card – now exploiting adjacent

channels – financial services, video on-demand

Using weather forecasts, updates store forecast

for 18 million items, three times a day

More intelligent discounting as fresh food

approaches sell-by dates

Demand forecasts using big data analytics saving

£30 million in food wastage, £50 million less

stock in warehouses

Analyzed 70 million data points to cut

refrigeration costs by 20% and save €2 million

Paving the way for further engagement with own-

brand tablets and in-store wifi


Emerging patterns

360o customer insight and personalized marketing

Aggregating transactional data, social media, customer interactions

Acting in real time

Tailoring campaigns, customer offer or customer experience ‘on the fly’

Asset and service management

Analyzing streaming data to identify disruption and maintenance needs

Process optimization

Predictive analytics and process simulation to reduce waste and cost

Risk management and fraud

Identifying patterns across all available data to improve risk-based decisions

Performance management

Optimize financial and operational decisions based on deep data insights


Healthcare and Life Sciences examples

Toronto Hospital and University of Ontario

Institute of Technology integrating 1256 readings

per second in neonatal ICU to predict adverse

changes in a baby’s condition

UNC Health Care analyzing registrations, clinical

notes, phone calls, to reduce patient readmission

rates

Clinicians analysing large data banks to establish

“virtual cohorts” of patients with similar medical

histories in order to work out the most successful

treatment regimes for an individual patient.

Governments seeking to compare data on key

metrics, both nationally and internationally

Challenge is how to integrate the data across the

healthcare and life sciences ecosystem


What capabilities must organizations develop?

Data: transaction + interaction + acquisition

Data-driven culture

Information governance

Data processing and analytics platform

Intelligent BI tools

Superior user experience


Education examples

Predictive analytics being incorporated into virtual

learning environments to drive improvement

University of Huddersfield analyzing resource

usage to identify under-performing students

Georgia State using predictive analytics to

prioritize student grants

Purdue University monitoring student

demographics, academic history, engagement

with online resources, and current performance to

improve student retention

Big Data techniques being used to personalize

alumni marketing and increase donation rates


What barriers must be overcome?

Understand that this is strategic

Data privacy, data security and data ownership

Internal data silos

Skills shortages

Funding and business case

Data governance, data quality and integration

Technology is the least of our concerns


Agriculture example – grain yield monitoring


Case study example – Climate Corporation

US crop insurance provider, founded by two

ex-Google employees

Utilize publically available data sources on

crop yields and soil types, for every two

square miles of the US

Crop data linked to one million data weather

points used for storm warnings, to create

crop impact predictions

Use Hadoop and Map Reduce, running on

Amazon Web Services to process the large

volumes of data


Call to action

Review key adoption patterns in the context of your

business – consider processes, functions, business model

Align specific data-driven opportunities with strategies

objectives, and develop a business case

Assign responsibility for developing a

data strategy and capabilities

1

2

3 Explore new data opportunities – think about

transaction + interaction + acquisition 4

© Copyright Ovum. All rights reserved. Ovum is a subsidiary of Informa plc. 26

Thank you

Tim Jennings, Chief Analyst & Research Fellow, Ovum IT

[email protected]

@tjennings

Nov 25, 2013

mailto:[email protected]