Industrial internet big data uk market study

Eyetoeye 2015 UK Research Report.Eyetoeye 2015 UK Research Report. Industrial Internet - making the most out gathered data.

Eyetoeye 2015 UK Research Report.
Table of contents
1-3 – Introduction
4 – Notes on Methodology
10 – Big Data Overview – Market Opportunity
14 – Current Status in The UK
19 – Potential Customers Partners & Competition
21 – Smart City Participants (see Appendix)
45 – Potential Customers Partners & Competition
48 – Markets & Opportunities
72 – Potential Customers Partners & Competition – 12 Key Verticals
89 – Smart Cities
113 – Conclusion
2

The next BIG thing..
..is actually a trillion small things.
3

Notes on Methodology
Defining the market, companies & opportunities.

Methodology
.
These verticals have been further defined by researching white and blue papers
from leading investment banks and IT providers across the industry in the UK.
The introduction to this report lays out the current general UK Big Data landscape,
illustrated key insights in each of the leading twelve industry verticals.
The accompanying Appendix gives granular detail on who the key players are in
the market, the potential competitors, suppliers, partners and clients.
Where possible we have also given contact details for companies to follow up
directly with the key company executives and thought leaders.
5

Caveats
Given the nascent state of the Big Data and it’s application, opinions vary as to the
size and shape of the market in the UK.
Without knowing who the key Finnish suppliers are, we have only been able to give
a broad view across each market sector.
Once these companies have been identified we can focus on their specific
expertise and make further recommendations as part of a future, more focused
report.
We have provided a range of estimates cited from the worlds leading consulting
and research firms that detail economic effects where available.
Equally when looking at individual companies it is difficult to distinguish between
prospective clients, competition and partners. Accordingly we have broadly
identified major players in each industry that will be effected by these changes.
6

The Big Data & The Industrial Internet
Big Data is the science of analysing, interpreting and reporting on
vast sets of data from a variety of sources. The interpretation of
these data is dependent on the analysis of four core
characteristics these are velocity, volume, variety and veracity.
The Industrial internet will produce vast is typically defined as the
addition of software and sensors to formerly discreet passive
objects and connecting them to the Internet. This will generate
unprecedented quantities of data.
As a consequence the predicted explosion of the IIoT will drive
increased demand in the market for services that can deliver
visualization, analysis and application of Big Data
7

Big Data Scenario Analysis
IIoT takes several years
to take off
Some companies adopt customised
solutions and measure key variables
accurately The IoT helps them make
some key decisions ,although
implementation remains costly, with
no scale effect. Adoption in only a few
sectors.
IIoT is a success - major
impact on global GDP
High levels of standardisation helps
penetration in multiple sectors, the
increasing use of analytics leads to
significant cost saving in multiple
Industries. Cross pollination of
Algorithms across sectors is
a multiplier effect
IIoT takes a decade to
take off
Some companies adopt customised
Solutions and can more accurately
measure key variables, but without
Improvement in cost-saving decisions.
Adoption in only a few sectors because
Of high implementation costs.
IIot takes several years
to take off
Sensors are implemented in various
devices but companies fail to turn data
From sensors into useful decision-making.
Reporting is improved across several
Sectors at a relatively low cost
Low level of
standardisation
High level of
standardisation
Analytics intensive / high level of intelligence
Analytics ilimited / low level of intelligence
8Figure #1

Gartner Hype Cycle 2015
9Figure #3
:

Big Data in the UK
Big Data & Analytics in the Industrial Internet.

What is the market opportunity
for Big Data in the UK?
The Big Data in the UK is evolving rapidly:
By 2017 the uptake of big data analytics amongst UK
firms employing >100 people will reach 29%.
By 2017 132,000 new jobs will have been created in
the UK directly related to Big Data.
The sector will deliver £6.8billion in benefits to the UK
economy.
11Source:

Estimates suggest that, via efficiencies, innovation and
business creation, big data was worth £25 billion to UK
businesses in 2011, and may reach an annual value of
£41 billion by 2017.
The Government has highlighted its potential, investing
over £180 million to support big data research.
12Source:

Actual/forecast demand (vacancies per annum) for big data staff 2007–2017
13Source: e-skills UK/Experian 2012

What is the overall status of Big Data and making
the most of the data in UK?
Estimated adoption of big data analytics for larger firms, 2012–2017
14Source: e-skills UK/Experian 2012

Estimated adoption of big data analytics for larger firms, 2012–2017
However 48% of companies in France and Germany
using three or more new data types compared with
20% in the UK.*
15Source:

16Source: Teradta’s Big Data Analytics Report 2014

17Source: Teradta’s Big Data Analytics Report 2014

What is abundantly clear from the survey is that UK
companies are falling behind in the race to exploit the
new techniques of analysis that are now available.
The UK also appears to be insufficiently forward-
looking when it comes to the potential for data analysis.
Whereas most of their German and French
counterparts want to use data analytics so they can
undertake new projects, the largest proportion of UK
executives wants the new techniques to help with tasks
they are already involved in.
18Source:

What kind of companies are using their ‘big data’
and how far along are they in the UK?
19Source: IDC on IDC European Vertical Markets Survey 2012)
European Companies' Current and Planned Adoption of Big Data by Vertical, 2012

Current customer requirements UK Firms
Data IQ identify five investment drivers:
Gaining better customer insight 57.7%
Improving productivity through less wastage 37%
Make more evidence-based decisions 51.9%
Become customer-centric 46.2%
Improving marketing performance 51.9%
20Source:

Current customer requirements UK Firms
The opportunity is understood, however there are major
challenges to overcome EY & Numbus Nimby found that:
32% of respondents admitted to being overwhelmed by
data.
81% agree that data should be at the heart of decision
making
31% have restructured their operations to do this.
21Source: EY Digital report 2015

It is possible to categorize opportunities in different areas,
both supply and demand side:
► On the supply side, companies that generate big
data
► On the demand side, companies that use that data
to develop products and services
Both sides of this market will require the same products
and services from Finnish companies.
22

Opportunities for Finnish companies:
Big Data Consulting
Big Data outsourcing, hosting, and as-a-service
providers
Enhanced eCommerce and Web Marketplaces
Analytics Software (beyond customer analytics)
These industries are listed in the 12x Vertical Market
Opportunities section later in this deck.
23

Big Data application for UK Companies will include
Supply chain
Operations
Administration (focused on finance and accounting,
human resources, legal, etc.)
Research and development
Information technology management
Risk management
24

Financial services:
Algorithmic trading
Fraud prevention and detection in both banking and
insurance
Predictive damage assessments in the insurance industry
Claims analytics in insurance
Customer insights from the integration of transactional data
(from CRM, credit card payments, account transactions) and
unstructured social media feeds
25

Financial services continued:
Portfolio and Risk exposure assessment
Customer profiling, targeting, and optimization of offers
for cross-selling
Influencer analysis
Customer center and call center efficiency
Sentiment analysis and brand reputation
26

Financial services continued:
Correlation of social media sentiment with stock returns
to support investment decisions
Catastrophe modeling in insurance
Customer value management
Underwriting and loss modeling
27

Telecoms:
Network optimization
Customer retention based on call data records and
activity in subscribers' networks
Customer scoring and churn mitigation
Optimization of offers to clients for cross-sell
28

Telecoms continued:
Fraud prevention
Location based services using GPS data and
geospatial analytics
Bandwidth allocation based on use patterns
29

Media:
Customer scoring
Fraud prevention
Churn prevention and customer retention
Intellectual property management
30

Media continued:
Digital asset management
Digital content management
Audience and marketing optimization
Bandwidth allocation based on access patterns for
video, music, and game software streams
31

Utilities/ Oil & Gas:
Smart meters monitoring, real-time usage patterns analysis to
optimize energy consumption and pricing
Predictive analytics, distribution load forecasting and scheduling
Sensor monitoring for condition-based and predictive maintenance
Smart grid optimization, weather pattern and real time usage and
distribution
Operational modeling
Distribution load forecasting and scheduling
32

Utilities/ Oil & Gas continued:
Targeted customer offerings
Disasters and outages management
Compliance checks and audits
Customer feedback and call detail record analysis
Natural resource exploration in the oil and gas industry
Seismic data processing
Drilling surveillance & optimization
33

Professional services:
Demand signaling
Social media presence to assess competitive
positioning in advertising
Ad targeting, analysis, forecasting and optimization
Social media listening and sentiment analysis for
marketing service providers
Campaign management and loyalty programs
34

Professional services continued:
Crime prevention and detection for providers of security
services
Personalized pricing for travel
IT infrastructure monitoring, predictive maintenance,
and management in IT
Security breach pattern detection and machine learning
to create rules engine in IT
35

Transport:
Logistics optimization
Location based analytics using GPS data
Customer analytics and loyalty marketing
Predictive maintenance
Capacity and pricing optimization
36

Retail/wholesale
Customer behavior analysis from omnichannel retailing
and social media feeds
Actionable customer insight, micro-segmentation
Loyalty and promotions analysis
Store location and layout
Supply chain optimization
RFID tracking
37

Retail/wholesale continued:
Cross-sell and up-sell at point of sale
Markdown optimization based on actual customer
buying patterns
Market basket analysis based on demographics
Merchandise optimization
Fraud detection and prevention
eCommerce fraud detection
38

Manufacturing:
Predictive maintenance
Process and quality analysis
Warranty management
Factory automation
Automatic detection of adverse drug effects in Pharma
39

Manufacturing continued
Sensor monitoring for the maintenance of automobile,
buildings, and machinery
Smart meters monitoring to optimize energy
consumption
Location based analytics using GPS data
Analysis of social media comments for vehicle quality
management in automotive
40

Manufacturing continued:
Social media listening for marketing in consumer
industries
Concurrent engineering and product lifecycle
management
Design-to-value
Crowdsourcing
41

Manufacturing continued:
Demand forecasting and supply planning
Sensor-data-driven operation analytics
Digital factory for lean manufacturing
Distribution optimization
Quality management based on social media feeds
42

Public sector:
Enhanced citizen/patient services
Weapon systems and counterterrorism
Tax analytics
Fraud detection
43

Public sector continued:
Cybersecurity
Surveillance and response programs
Health informatics, bioinformatics and
pharmacogenomics
Optical treatment assessment
Clinical decision support systems
44

Big Data in the UK
What kind of companies are using Big Data?

Current adoption of Big Data technologies in telecom
neared 40% in October 2012, with close to 40% of
respondents planning to adopt them by 2015. So by
2016 adoption will be running at 80%.
A similar percentage of European media companies
are expected to invest in big data technologies over the
next three years, with adoption rising from 8% to close
to 46%.
46Source: IDC European Enterprise Software Survey.

Overview:
Morgan Stanley have identified twelve sectors that are
likely to be the first to invest in leveraging the
opportunities presented by big data.
The following slides provide an overview of each of
these sectors, details of contacts in each are given the
attached appendix.
47

Utilities
Gas & Electricity Consumption.
This sector is among the forerunners in Big Data adoption and is
widespread in the oil and gas processing sector, reaching 46%,
but is also significantly above average among utilities.
The €14.8bn (£10.9bn) investment by the UK government in smart
metering of gas and electricity is the biggest government
investment in IoT to date.
In addition the UK is part of the European consortium developing a
smart distribution grid.
48Source:

Utilities
Water Distribution.
Smart water grids, like Smart Electricity grids are primarily
concerned with flow management and usage metering.
Specialist Big Data skills combined with Spatial Analytics will be
required to develop this infrastructure.
49

Insurance
Overview.
This is a highly competitive global market which is centered in
London.
There is substantial demand for Big Data and Actuarial skills to
assist in the assessment and modeling of risk scenarios.
plans for adoption are strong particularly among banks and in the
midsize segment.
50

Insurance
Automotive.
Insurance companies in the UK offer reduced premiums to
consumers prepared to have a small device attached to a vehicle
that tracks time of trip, speed, driving style etc.
In the UK Aviva http://www.aviva.co.uk have used smartphones
to asses driving styles (this reduces the cost to the insurer and
mitigates the risk of damaging additional expensive electronics in
the event of an accident.)
In the longer term autonomous vehicles promise to reduce
accident rates and provide higher resolution data that will further
assist in the calculation of risk.
51

Insurance
Life.
As mentioned previously privacy may be a barrier to entry for
Finnish companies here.
Morgan Stanley suggest that customers may be more willing to
give data from health monitoring devices following a major health
scare such as a heart attack.
52

Capital Goods
Overview.
Big Data has massive implications for industry. The ability to a to
optimise performance and, reduce maintenance and extend the
lifecycle of plant will deliver significant efficiencies.
Combining these efficiencies may result in productivity
improvements of 1-1.5% adding €8.9-€17.8trillion ($10-$15) trillion
to global GDP over a twenty year period.
GE estimate that Big Data could rapidly deliver a 1% reduction in
fuel consumption for commercial jetliners saving the industry
€1.7bn a year
The UK has world beating aerospace business that included air
craft manufacturing Airbus & Rolls Royce and satellite production
and management Immarsat.
53

Capital Goods
Opportunities.
Opportunities in this vertical for Big Data analytics and
visualisation abound throughout the technology stack.
Smart machines, new plan designed with sensors embedded or
augmenting existing plant with sensors and devices.
Communications, wireless technologies to transmit data over
both short and long distance at a variety of volumes and
velocities.
Analytics and applications as discussed previously predictive
analytics and programmatic responses will have a major part to
play.
54

The continued ageing of the UK population will put increasing
strain on the National Health Service.
The average value of NHS services for a retired household in the
UK is £5,200 p/a.
The potential Big Data to deliver improved efficiencies in the NHS
is enormous. The Service is currently focusing on three areas of
opportunity.
Early identification
Research
Tailored healthcare
Healthcare
Overview.
55

Healthcare
Prevention & Early Identification.
Private health providers, insurance companies, pharmacticals
companies and the NHS will be keen to develop applcations and
servies that leverage the following
The explosion of wearable's and other health monitoring devices
coupled with smart phone applications can provide clinicians with
essential diagnosis tools.
Such devices may also provide helpful ‘nudges’ such as
suggesting an individual take some exercise. Or alert them to
environmental factor such as air pollution that may trigger an
asthma attack.
Dedicated devices in the home may also assist the elderly and
mentally ill to live more independently.
56

Healthcare
Research.
The ability to gather more data can only accelerate and improve
studies into the overall health of a population.
Specific devices and programmes may be used to analyse
whether particulate combinations of genetics, lifestyle, and
environment result in predispositions or resistance to specific
conditions.
Including data from wider networks (meteorological, social, and
search) will also assist in research into the prediction of epidemic
and pandemic.
57

Healthcare
Tailored Healthcare.
Tailored healthcare, the aggregation of real time health monitoring
and the identification of trends has potential for the NHS.
There is already steady growth in demand hardware and software
that facilitate the notion of “the quantified self” and “body hacking”.
Platforms such as Apple’s Health Kit will result in growth in these
types of applications.
A peculiarity of the NHS is the ability for individual NHS Trusts to
commission software over the past 5 years has seen individual NHS
Trusts develop apps to overcome management and healthcare
issues. There is a market opportunity here.
58

Healthcare
Challenges & Risks.
Data Security: Minimum standards must be agreed so that an
individual knows who is using their personal data, why it is being
used and for whom it is being used (see insurance).
Interoperability and standards. The NHS has a poor track record in
automation and digitisation of records. Introducing additional
inputs from Big Data will only make this environment more
complex and challenging.
Education and change management: Healthcare professional must
work with patients to ensure they understand the benefits of these
new technologies and have sufficient knowledge to respond to the
data available to them.
59

Retail
Overview.
Smart phone technologies are already revolutionizing shopper
behavior and major retailers are adapting Omni-Channel strategies
to meet these needs.
However it is the smart phone and not Big Data as such that is
revolutionising the way retailers interact with their customers.
The dramatic impacts will be in the automation of warehousing,
stock tracking and supply chain management.
60

Retail
The automation of warehouses in which orders are picked and
packed by robots to supply individual customer orders is yet to
become ubiquitous.
This will change as the cost of RFID and other tagging
technologies continue to fall.
Tagging of individual items delivering further operational
efficiencies as automated check out in supermarkets become
reality such as iBeacons.
61

Retail
Big Data Opportunities.
Opportunities exist for the tracking and management of
many thousands of product variant SKU’s (Stock
Keeping Units) from factory to retail environment to
consumer.
Inventory management and inter-operability with supply
chain will also provide opportunities for innovation.
62

Logistics
Overview.
This sector is set for a strong jump within the next two years, with
nearly 35% of UK firms planning to invest in Big Data Programs.
The impact on the global logistics industry will be profound
impacting almost every process and operation involved in moving
goods, raw materials and people from A to B.
GPS and the internet have allowed for the tracking of assets and
individual items as the pass through a delivery chain.
Big Data will allow for the the better utilisation of these assets
monitoring operational procedures, operator behaviors and
maintenance requirements.
63Source:

Transport & Logistics
64Source: DHL

Logistics
Overview.
GPS and the internet have allowed for the tracking of assets and
individual items as the pass through a delivery chain for many
years.
This GPS data will become more dense as, individual containers
and the items within them are able to transmit there whereabouts.
Containers will become more secure as sensors are used to detect
whether container has been opened.
65

Logistics
Overview.
In 2013 DHL surveyed customers across Europe and asked whether
they had considered how data tracking might be exploited in terms of
customer innovation and increased efficiencies:
64% No
23% Planned
14% Yes
66Source:

Factory Automation
Overview.
In terms of adoption of Big Data the sector appears as a laggard,
with some 6.2% of current adopters, However further 26.4%
planning to invest in Big Data. This low figure is due to legacy
infrastructure “M2M Islands” not yet interfacing with Big Data.
Factories currently produce “islands” of M2M intelligence. Big Data
will see these islands integrated facilitating greater automation.
Enabling individual components in the manufacturing process
become more responsive and flexible.
Efficiencies in energy use, reduced manpower and improved
safety will result in cost saving and efficiencies.
67Source:

Mining
Overview.
Better utilisation of infrastructure will result in higher production at
lower operating costs. Monitoring of plant will facilitate better
maintenance and energy efficiencies.
Autonomous plant will result in lower costs of extraction. Rio Tinto
in Australia already operate autonomous extractors that deliver
waste rock and ore to automated trucks. Plans are afoot for these
trucks to deliver ore to an automated rail link.
As there is a limited mining industry left in the UK this is not an
area we have focused further on. Europe may be a better
opportunity to research. This may change with the investment in
Fracking depending on future legislation.
68

Big Data in the UK
What is the potential market accessibility for Finnish
companies in the UK?

What is the potential market accessibility for
Finnish companies in the UK?
As a European partner Finnish companies face no
barriers in the UK other than potential business
competitors operating in their area of specialisation.
The UK has a skills shortage with regard to Statistics,
and Big Data analysts. Accordingly many UK
companies will be seeking advice and services from
third parties
70

What is the potential market accessibility for
Finnish companies in the UK?
Lists of potential competitors (and suppliers and
partners) are supplied in the PDFs attached to this
deck.
We have listed them by geographical region – in UK
“Smart Cities” and by largest industry vertical*.
Please note some of the potential competitors identified
could also be potential partners.
71Source: *As defined by Morgan Stanley.

Potential Customers
Partners & Competition
Who are the potential competitors, partners & suppliers in the
UK market and what is their offering?

Who are the potential competitors, partners &
suppliers in the UK market?
Caveat: Without knowing exactly who the Finnish
Companies are we are unable to differentiate between
who is a potential supplier, competitor or partner.
The following list of companies reflects the leading
businesses working in Big Data Analytics and
Visualisation in the UK across those three areas.
It includes both major global companies with UK offices
and SMEs with contact details where found.
73

SIX DEGREES – Six Degrees Group provides integrated
managed data services linking people, places and clouds.
http://www.6dg.co.uk
BLUEFIN SOLUTIONS – Business consulting. Technology
strategy. Implementation & Change.
http://www.bluefinsolutions.com
OGILVY ONE – Communications Agency. Matthew Bayfield, Head
of Data Practice UK & EMEA, OgilvyOne.
https://www.linkedin.com/in/matthewbayfield
ENGINE GROUP – Communications Agency. Contact: Charles
Ping, CEO, Fuel Data - Engine
Group.https://www.linkedin.com/pub/charles-ping/0/4a6/a32
74

IBM –
WATSONhttp://www.ibm.com/smarterplanet/us/en/ibmwatson/
SIGFOX – Contact: LUDOVIC LE
MOAN, CEO, Sigfox.https://www.linkedin.com/in/lemoan
TELEFONICA – Telecommunications company. Contact: Simon
Boyd, M2M Global Partner
Manager, Telefonica.https://www.linkedin.com/profile/view?id=246
90474
VODAFONE – Telecommunications company. Contact: Cyril
Deschanel, Head of M2M Sales Northern
Europe, VODAFONE M2M.https://www.linkedin.com/profile/view?i
d=4896880
75

CISCO – IT Solutions Company. Bernd Heinrichs, Managing
Director IOT
(EMEAR) CISCO.https://www.linkedin.com/profile/view?id=126568
5
ORANGE – Telecommunications company. Contact: Emmanuel
Routier, Vice-President M2M
Center, ORANGE.https://www.linkedin.com/profile/view?id=113452
8
O2 – Telecommunications company. Contact: Simon Kaffel, Head
of Information Management -
O2.https://www.linkedin.com/in/simonkaffel
76

CAP GEMINI – Consulting company. Contact: Paul Gittins, Pivotal
Partner Executive at
Capgemini.https://www.linkedin.com/in/paulgittins
CAPGEMINI – Consulting company. Contact:Steve Jones, Global
Vice President - Big
Data, CapGemini.http://www.linkedin.com/in/stevegjones
FJORD – Digital Agency Contact: Claire Rowland, Head of
Research, Fjord, is the lead author of ‘Designing Connected
Products’. https://www.linkedin.com/profile/view?id=1943187
77

DEUTCHE BANK – Investment Bank. Contact: JP
Rangaswami, Chief Data Officer at Deutsche
Bank.https://www.linkedin.com/in/jprangaswami
IBM – http://www-935.ibm.com/services/us/gbs/business-
analytics/?lnk=mseBS-bana-usen Contact: Lauren Walker, UK Big
Data & Analytics Leader, IBM UK &
Ireland.https://www.linkedin.com/pub/lauren-walker/0/b21/6b6
IBM – WATSON
http://www.ibm.com/smarterplanet/us/en/ibmwatson/
78

EVRYTHNG - Lean & agile development, commercial strategy,
executive leadership, marketing, end-to-end product management,
cross-platform service design, UX design, systems thinking,
design thinking. Contact: Anna Kuriakose, Chief Product Officer at
EVRYTHNG.https://www.linkedin.com/in/annakuriakose
APT – APT provides native, cloud-based software tools that
enable large, consumer-focused businesses to seize the Big Data
analytics opportunity by triangulating between business strategy,
algorithmic math, and large databases to improve decisions.
http://www.predictivetechnologies.com/about.aspx
79

EDITD – EDITD is the market leader in real-time analytics of
pricing, assortment and deep product metrics for apparel
professionals. https://editd.com
PUSH TECHNOLOGY – Push Technology’s Diffusion software is a
development software platform to remove the complexity and
associated challenges of developing for scale, coping with the
explosion of data across networks, delivering a rich application
experience and real-time conversational interactions.
http://www.pushtechnology.com/diffusion/#sthash.H2UYxFTn.dpuf
80

DATA SIFT – DataSift delivers Human Data into business intelligence
tools and business processes in real-time. You can also innovate with
their API to build your own apps.http://www.datasift.com
QUBIT – Web personalization, A/B testing, audience segmentation,
and digital analytics, built for the cloud. http://www.qubitproducts.com
AMOBEE – Provide marketing intelligence and cross channel, cross
device advertiser and publisher solutions. This unified data and
technology platform deconstructs big data, dissects channels,
discovers trends and distributes advertising. With a dedicated data
team alongside cutting edge technology Amobee provides the
insights, optimisation, data and targeting required to successfully
execute and scale performance campaigns. http://www.amobee.com
81

TUMRA LABS – Their API allows you to make predictions about a
person based on a small amount of metadata such as their name.
The resulting prediction could be used to personalise the user-
experience of a website, or extend the metadata available in your
customer/subscriber databases.
http://labs.tumra.com/doc/demographics
MANGO SOLUTIONS – A team of statisticians, mathematicians and
data scientists with cross-industry expertise. Mango provides a range
of consulting options from ongoing consultative engagements to
smaller one-off projects or tasks. Mango offers tailored big data .
http://www.mango-solutions.com/wp/
WE PREDICT – Global leaders in predictive
analytics.http://www.wepredict.co.uk/en/
82

COGENT ANALYTICS – Cogent Analytics is part of The Collinson
Group, a privately owned global organisation that uses data, customer
insight and marketing expertise to the benefit of its companies, clients
and their customers. http://www.cogentdataanalytics.com
ROSSLYN ANALYTICS – Rosslyn Analytics is a leading global “data
tech” company that is recognized for its new approach to helping
organizations create business value from previously inaccessible
data. http://www.rosslynanalytics.com/our-story/overview/
TESSELLA – Tessella is an international analytics, software services
and consulting company known for finding and delivering innovative
answers to the complex business and technical challenges of some of
the world’s most forward-thinking organizations. http://tessella.com
83

KANTAR – Kantar is home to some of the worlds leading
research, data, and insight companies .Individually, companies
such as Millward Brown, TNS, Kantar Media, Kantar Worldpanel,
Added Value and The Futures Company are famous and highly
respected experts in their fields. Collectively, they offer the most
complete view of consumers – the way they live, shop, vote, watch
and tweet – in over a hundred countries worldwide.
http://www.kantar.com
BRANDWATCH – Brandwatch is a social technology company.
http://www.brandwatch.com
84

WALKBASE – Walkbase Analytics empowers retailers to make
data-driven decisions, and adapt for best in-store sales
performance and loyalty. http://www.walkbase.com
KPMG / IMPERIAL COLLEGE – KPMG Centre for Advanced
Business Analytics.http://www.imperial.ac.uk/business-
school/research/kpmg-centre-for-advanced-business-analytics/
METHODS – Methods Group comprises a group of companies
with clear specialist offerings, their own dedicated management
teams, and specialist staff. Our companies specialise in the
provision of Advisory, Analytics, Digital, ERP and Professional
Services. http://www.methods.co.uk
85

INFORMATICA – Have a number of Big Data solutions: Big Data
Edition Provides a safe, efficient way to integrate all types of data
on Hadoop without ever having to learn Hadoop. Big Data Parser
Provides pre-built parsers on Hadoop for a variety of industry
standards, documents, log files, and complex file formats. Big Data
Relationship Management Discovers relationships among parties
and groups them to create a 360-degree view. Connectors
(PowerExchange) Provides out-of-the-box, high-performance
connectivity to all enterprise data, eliminating the risk and cost of
hand coding. Vibe Data Stream Built on fast brokerless messaging
technology that helps you manage many small pieces of incoming
streaming data. https://www.informatica.com/products/big-
data.html#fbid=eZeGtwIabvZ
86

MOBIUS – Mobius are an independent supply chain management
consultancy. http://www.mobiusuk.co.uk
EXPERIAN – Decision Analytics - Credit Risk and Fraud
management Consulting Services and Products.
http://www.experian.co.uk/decision-analytics/
ROELTO – Cutting edge tools to help you collaborate more
effectively, boost your efficiency and grow a better business.
http://roelto.com
87

VIZZUALITY – From data visualization to citizen science.
http://www.vizzuality.com
APPLIED WORKS – A design and technology studio.
http://appliedworks.co.uk
DATA SCIENCE CENTRAL – Data Science Central is the
industry's online resource for big data practitioners.
From Analytics to Data Integration to Visualization, Data Science
Central provides a community experience that includes a robust
editorial platform, social interaction, forum-based technical
support.http://www.datasciencecentral.com
88

Smart Cities.
Who are the potential competitors, partners & suppliers in the
UK market by geography?

Building the Industrial IoT & Big Data
The development of the infrastructure that will power the Industrial
Internet will provide a rich environment for inward investment.
To support this growth the British Government has initiated the Smart
Cities Program. Working with local authorities, academia, and local
business the Smart Cities Program will develop network infrastructure
that will deliver better services for citizens such as traffic management
and recycling.
It is anticipated that the development of this infrastructure will foster
innovation and growth in this field. Contracts for the development of Ultra
Narrowband low powered networks have been granted to Arqiva, and their
partner Sigfox. Nuel are also deploying their weightless networks
providing wide area connectivity in these cities. The network in set to go
live in April 2015.
90

The UK Smart Cities Program.
Infrastructure: Why Smart Cities are the Key to Growth.
The biggest inhibitor to change is the lack of connectivity. So in
areas where councils are installing Sigfox ULB networks and
Weightless (transmitted through the UHF end of the Spectrum)
protocols, almost any object can have “always on” two-way
connectivity to the internet – a bin in the middle of a park for
example.
It is the introduction of theses networks that will drive innovation
and change. Therefore in terms of investment the money is likely
to flow to these hubs. Accordingly it’s in these cities that clusters of
innovation are most likely to emerge.
91

The Financial Commitment to Big Data by the UK
Government.
As part of an EU wide initiative the every household in the UK will
use smart energy metering.
In January 2015 trials of self driving cars began in Bristol,
Greenwich, Coventry and Milton Keynes.
In December 2013 Tech City awarded £1m in funding to 7 UK IoT
start ups.
Favorable tax regime that incentives R&D and patent applications
(Europe’s only IoT incubator, Breed Reply headquartered London
– it’s parent, Frankfurt).
92Source: Department for Business, Innovation & Skills

Smart Cities Gov. Funding
£95m (€128m) Smart Cities funded by The Research
Council.
£50m (€67m) over 5 years to fund the Future Cities
Catapult Center established by the Technology
Strategy Board, London.
£33m (€44m) Future Cities Demonstrator
93Source: Department for Business, Innovation & Skills

Smart City Participants
Birmingham
Bristol
Edinburgh
Glasgow
Liverpool
London (Greenwich)
Manchester
Milton Keynes
Sheffield
94

Birmingham
Birmingham has an aspiration of becoming a smart, connected city
and has ambitions to deliver a 60% reduction in carbon emission by
2026.
Digital Birmingham, the City’s strategic digital lead is developing a
roadmap and action a plan, working in partnership and collaboration
with leading community experts, universities, SMES, and several
major businesses including, CISCO, ATOS, Carillion, TATA, AMEY
and IBM, developing the key strands of a smart city.
95

Birmingham
Strengths: High-performance automotive, software,
enterprise.
Key players: Oxygen Accelerator, Entrepreneurs for the
Future.
Tech firms: Redbull Racing, McLaren F1, Shell Global
Solutions UK.
96

Bristol
Bristol is fast becoming the UK’s most creative, smart, green and
connected city. Being the only city in the UK to win funding from
government to be both a Super Connected City and a Future City
Demonstrator is testament to this.
Furthermore in 2015 Bristol will be European Green Capital, staging
an inspiring programme of events centered around the idea of Bristol
as a ‘Laboratory for Change’.
Smart technologies can help deliver a cleaner environment, a higher
quality of life and a vibrant economy. Bristol aims to be in the top 20
European cities by 2020 and has made a commitment to create a
world-class and inclusive green-digital economy.
97

Bristol
Strengths: Semiconductors, Robotics, Web.
Key players: SetSquared Business Accelerator, Silicon
Southwest, XMOS.
Tech firms: XMOS, MDb, Future Publishing, IPL, HP
Labs.
98

Edinburgh
The City of Edinburgh has a customer service strategy that aims to
design and deliver user centric services. In accordance with this
strategy the municipality is committed to the co-creation of a series of
Industrial IoT services in conjunction with it’s citizens
“The Business Process Change pilot will incorporate both lean
thinking and customer journey mapping approaches into a strategy to
improve our internal business processes. The approach is being
trialed in the Council’s Revenues and Benefits Division.”
The procurement and development of a new Internet presence for the
City of Edinburgh Council provides the capability to deliver a more
useful, accessible web services with up to date, reliable and accurate
information.
99

Edinburgh
Strengths: High-technology manufacturing, ICT, AI.
Key players: Technopole, Launch.ed, Startup Café.
Tech firms: Amazon, Cisco, Oracle, Skyscanner,
Freescale.
100

Glasgow
Glasgow has secured £24 million funding through the Technology
Strategy Board to develop a future cities demonstrator.
The city will demonstrate how providing new integrated services
across health, transport, energy and public safety can improve the
local economy and increase the quality of life of Glasgow’s citizens.
The city OpenData project recently launched the city dashboard
which can be seen at: http://dashboard.glasgow.gov.uk
101

Glasgow
Strengths: Academic, Innovative local authority,
Proximity to Silicon Glen
Key players: Glasgow University, University of
Strathclyde, Open Glasgow, Digital Enterprise Glasgow
Tech firms: Kiltr, Dizeo,
102

Liverpool
Liverpool aims to become the first Smart City in the UK creating
ongoing monitoring of resource deployment, insightful visualizations
and constant feedback loops to develop a highly efficient, interactive
and engaging city stimulating behavioral change.
The city will focus on six main areas for improvement identify smart
cities, that of: economy; mobility; environment; people; living and
governance.
Each of these areas include a wide range of needs that must be met
in order to help communities grow and reduce strain on resources.
103

Liverpool
Strengths: BioHealth, Gaming, Advertising.
Key players: Liverpool Vision, ACME.
Tech firms: Reputation 24/7, Hammerkit/CloudStore.
104

London (Greenwich)
The ‘smart city’ agenda for London is gathering momentum. The
drivers are clear, fuelled by increasing constraints on urban
resources, such as transport, energy and healthcare and London's
desire to provide attractive and enjoyable places to live and work.
London also has to plan for population growth and avoid peak-load
and congestion on its infrastructure.
The Mayor’s view is clear. To support London’s future growth, we
must look to what new approaches innovation in digital technology
can bring. The Smart London Plan is for Londoners, businesses,
researchers, investors and everyone who has an interest in the
capital’s future.
105

London
We have a dedicated Appendix to this document
detailing potential competitors, partners and suppliers
as they are too numerous to list here.
A list of identified companies and contacts for potential
partnerships, suppliers and competitors in Big Data are
listed here.
106

Manchester
Greater Manchester is working to take advantage in development on
the use of data, such as mobile phone data, vehicle systems, satellite
data and camera data.
They are developing an approach to bring all of this data together to
create an oversight of the city.
This will then used for things such as seeing where people flows
might have an impact on the transport system; resulting in the
creation of more efficient and reliable routes. Enabling selective
priority to buses on certain routes for example.
107

Manchester
Strengths: Media, life sciences, software.
Key players: Media City, Sharp Project, MIDAS inward
investment agency, TechHub.
Tech firms: Satellite Information Services, Deltra/Tre
Media, Laterooms.
108

Milton Keynes
Milton Keynes MK:Smart is funded with an £8 million grant from the
Higher Education Funding Council for England’s Catalyst Fund,
match-funded by partners in a consortium led by The Open
University. The investment aims to demonstrate how universities can
apply their expertise to support cities’ economic growth.
The MK:Smart consortium brings together The Open University, the
University of Bedfordshire, Cambridge University, British Telecom,
Dell, E.ON, Anglian Water, HR Wallingford, the Technology Strategy
Board’s Satellite Applications Catapult Centre, Milton Keynes Council,
Community Action MK, Graymatter, Fronesys and Playground Energy.
109

Milton Keynes
Strengths: Highly educated population, Location,
advanced infrastructure.
Key Players The Open University, Network Rail.
Tech Firms: AirWatch, Tech Mahindra, T-Systems,
Siemens, Dimension Data.
110

Sheffield
Sheffield City Council has committed to contribute all data that can
be made available in relation to the City and its circa 600,000 citizens.
The consortium consists of the University of Sheffield’s Sheffield
Urban Institute (SUI) and Sheffield City Council, and is supported by a
broad range of industrial partners including Siemens, Arup and Amey.
This group together with the Open Data Community in Sheffield are
developing a Smart City Plan for the city which responds to the
broader definitions as set out in the Strategic Implementation Plan
rather than the typically narrow Smart City definition. Through this
partnership we are exploring how technology can be leveraged to
integrated ICT, energy and mobility within the city.
111

Sheffield
Strengths: Media/creative tech, advanced
manufacturing.
Key players: Sheffield Digital Campus, Made in
Sheffield.
Tech firms: WAN Disco, Learndirect.
112

Eyetoeye 2015 UK Research Report. 113Source: IBM Data November 2014
Big Data Value Chain
The Big Data Eco System and Value Chain.

114Source: IBM Data November 2014
The key to understanding the key steps in the value chain is
to take a focused look at each stage of the data lifecycle.
Discover: In today’s digitized world, there are many sources
of data that help solve business problems that are both
internal and external to organizations. Data sources need to
be located and evaluated for cost, coverage, and quality.
Ingest: The ingest pipeline is fundamental to enabling the
reliable operation of entire data platforms. There are diverse
file formats and network connections to consider, as well as
considerations around frequency and volume.

Process: Many applications are well served by processing
data immediately following the ingest stage, to transform the
data into a format that facilitates its reuse or to take
immediate action based on incoming events.
Persist: Cost-effective distributed storage offers many
options for persisting data. The choice of format or database
technology is often influenced by the nature of other stages
in the value chain, especially analysis.
Integrate: Much of the value in big data can be found from
combining a variety of data sources to find new insights.
Integration is a nontrivial but valuable step in which this
combination process occurs.

Analyze: The star of the big data show—analysis—
depends critically on every other step in the value
chain—the so-called data janitorial work that makes up
80 percent of data science. New insights and actions
are derived from data, enabled by an ever-growing and
nuanced choice of tools and platforms.
Expose: The results of analytics and data that are
exposed to the organization in a way that makes them
useful for value creation represents the final step in
deriving value from data.

117Source: E&Y Insights on risk and compliance April 2014

118Source: E&Y Insights on risk and compliance April 2014

The Big Data Eco System
119Source: Data Economy Understanding Big Data 2014

Conclusion
32% of respondents admitted to being overwhelmed by
data. This would indicate there is an opportunity for Finnish
companies to collaborate and win contracts in many UK
cities, particularly “Smart Cities” and in particular London.
There are a wide range of UK companies competing in Big
Data Analytics and Visualisation but many are open to
collaboration and new insights from 3rd parties.
Big Data Analytics and Visualisation is a growing market well
supported by the UK Government which will stimulate more
growth and opportunity in 2015 and beyond.
120

Conclusion
51.9% of current customer requirements demand they need
to make make more evidence-based decisions.
Big Data technology adoption will be running at 80% by
2016.
The current UK rate of adoption is running at 38% opposed
to Germany & France at 58% indicating key growth
potential.
The Smart Cities indicated here are well funded by the UK
government so budget is available.
There are no commercial restrictions on Finnish companies
working in the UK.
121

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