geo-analytics - Digital Disruption

Report prepared for Kathleen Mitchell of TM Forum. No unauthorised sharing.
GEO
ANALYTICS
2014 | www.tmforum.org
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GEO-ANALYTICS:
ADDING VALUE TO BIG DATA
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Page 4
Executive summary
Page 5
Section 1
The origins of geo-analytics
Page 7
Section 2
Some way to go
Page 10
Section 3
Geo-analytics use cases
Page 14
Section 4
Mapping out the future
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Report prepared for Kathleen Mitchell of TM Forum. No unauthorised sharing.
GEO-ANALYTICS:
ADDING VALUE TO BIG DATA
Executive summary
Almost unbelievably large quantities of data
are being generated in the modern, networked
digital world. Much of this data has a geospatial
component – some 80 percent is a figure often
quoted in the analytics industry.
Although some question the exact
percentage, it’s undeniable that human
activities, events, transactions, business
processes and asset management all have a
location context.
Equally undeniable is the proliferation of
smartphones, wireless devices and other
communications or telematics technologies
that are being harnessed to specifically access
geospatial data.
Today the contention is that a number of
significant business benefits will result from
the ability to harvest, clean, homogenize,
authenticate and analyze this geographic
data in a cost-effective and timely manner.
These benefits include improved agility and
efficiency, the identification of new commercial
opportunities, increased competitiveness, and
reduced risk.
Section 1 of this report takes a look at what
geo-analytics are and considers what factors
are contributing to the rise of interest in the
growth of big data analytics. Among the drivers
identified are: the big data phenomenon itself;
the seemingly unstoppable growth in the
use of mobile and wireless location-enabled
devices and systems; and the widening
adoption of Geographic Information System
(GIS) technology.
Section 2 is an account of the development
of geo-analytics and an analysis of some of the
challenges attached to the greater deployment
and scaling of geo-analytics solutions. As well
as being able to handle the ‘Vs’ of big data (the
growing list includes volume, value, variety,
velocity, veracity and viability), particular
concerns are privacy, lack of standards and
location granularity.
Section 3 describes some geo-analytics
solutions and services. Three main prospective
deliverables for digital service providers are
more efficient internal operations, improved
customer experiences, and new revenue
earning services.
Section 4 examines the impediments to the
continued growth of geo-analytics, with lack of
standardization and the need to change mindsets looming large. Finally we list some possible
future digital services enabled by geo-analytics,
highlighting opportunities in the machine-tomachine, eHealth and smart grid sectors.
“Although the exact percentage is debated, it’s undeniable that
human activities, events, transactions, business processes and asset
management all have a location context .”
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Geo-analytics could become indispensable
in the big data analytics ecosystem
Section 1
The origins of geo-analytics
To some extent geo-analytics mean different
things to different people. For some geoanalytics tends to denote an emerging element
– at least in the commercial world – of big
data analytics. For others, it’s Geographic
or Geospatial Information Systems (GISs)
teamed with a range of business intelligence
(BI) and information management systems
and processes. For yet others it is the latest
iteration of GIS technologies. Meantime, some
individuals see geo-analytics as what happens
when advanced digital mapping technology
meets the ‘Internet of Things’ (which also has
a number of interpretations).
As befits an activity that lacks precise
definition, a number of observers use the
terms ‘geo-analytics’, ‘geospatial analytics’,
‘location intelligence’, ‘location analytics’, and
‘geo-enabled data’ synonymously.
This notwithstanding, it’s probably the
case that few would take strong exception
to the idea that geo-analytics is a potentially
indispensable part of the big data analytics
ecosystem. Again there’s some consensus
that the aim of geo-analytics practitioners
is to collect, examine and evaluate different
types of data in their geographic or geospatial
contexts and, in combination with a range of
other analytics and business tools, improve
the decision-making, the asset management
and exploitation capabilities, and the overall
efficiency and/or profitability of organizations
and enterprises.
Big data big time
One starting point for the geo-analytics story
is the overall big data phenomenon itself.
With the ongoing worldwide shift from offline,
unconnected to online, networked societies,
the amount of data generated by, and that
1
can be collected from, people, processes
and machines has become improbably large.
Indeed, things are now approaching the point
where even the largest of the established
units of measurement for data quantities are
becoming too small to adequately describe the
scale.
There are continuing efforts to quantify
and describe these big data volumes using
terminology that non-technical audiences could
comprehend. In November 2013 a story in
The Guardian newspaper cited a report from
investment banking firm GP Bullhound that
contained an infographic account of a minute in
the life of the Internet.
This report1 suggested that in the space
of 60 seconds, 208,000 photographs were
uploaded to Facebook, 350,00 tweets took
place on Twitter, 100 hours of video were
uploaded to YouTube, 120 new accounts
were opened on LinkedIn, 3.5 million search
queries were handled by Google, and Amazon.
com took $118,000 in revenue. It’s highly
likely, though, that most estimates of big data
volumes will be out of date by the time they
are published.
Big data is not necessarily of value in itself.
However in recent years the development of
technology to enable the economic collection,
analysis and evaluation of big data has come
to be seen as a key to unlocking any number
of business benefits. These benefits include
improving market agility and efficiency,
refining marketing campaigns, identifying
new commercial opportunities, increasing
competitiveness, lessening risk and preventing
fraud.
Estimates of the value of the big data
analytics systems and services market very
considerably. In its Worldwide Big Data
http://www.theguardian.com/news/2013/nov/22/rapid-development-in-big-data-analytics-has-led-to-increased-investment
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Report prepared for Kathleen Mitchell of TM Forum. No unauthorised sharing.
GEO-ANALYTICS:
ADDING VALUE TO BIG DATA
Technology and Services 2013-2017 Forecast
announced in December 2013, International
Data Corporation (IDC) forecasts that the big
data technology and services market would
grow at a 27 percent compound annual growth
rate (CAGR) to $32.4 billion through 2017 – or
about six times the growth rate of the overall
Information and Communication Technology
market.
On the move
A second development that is sponsoring
the proliferation of geo-analytics, and one
which is closely associated with the rise of
big data is the tremendous recent growth in
the production of, and the ability to harvest,
geographic- and time-referenced data. In turn,
this is the product of the famous adoption
of mobile technologies in general, and the
rocketing popularity of smart location-enabled
devices such as smartphones, tablets and
phablets.
One estimate from the International
Telecommunication Union is that the number
of mobile phone subscriptions worldwide
will hit 7 billion this year. According to IDC,
of the 1.7 billion smart connected devices
predicted to ship in 2014, some 1.4 billion
will be smartphones and tablets. And quite
apart from smart mobile devices, the location
data generated by future machine-to-machine
(M2M) services and applications is predicted to
be enormous.
“Almost every smartphone in the world
has a navigation capability,” points out Craig
Bachmann, Director, Industry Initiatives,
TM Forum. “And then there’s the M2M
element. So you now have the ability to collect
an unprecedented amount of location data
along with transactions and events.”
2
Putting IT on the map
A third relevant consideration in the growth
of interest in geo-analytics is the increased
use of GISs in many commercial and industry
sectors to expand the scope and utility of
existing enterprise and corporate management
and business support systems. As the name
suggests, a GIS uses hardware, software and
data to acquire, manage, manipulate, assess and
display geographically referenced information.
This information can be displayed in the form
of maps, charts and reports, with multiple
different layers of information overlaid in a
single display.
It is now becoming accepted that the
addition of interactive geographic location and
mapping to the data captured and generated
by enterprises and organizations can greatly
improve understanding of that data. It
potentially reveals relationships, patterns,
trends, opportunities and risks that may not
be evident with the same data presented in a
spreadsheet and other forms.
In the context of associating GIS with geoanalytics, some interesting data were revealed
in Business Trends in Location Analytics:
Exploring the Impact of Geographic Context
On Business Processes 2 a study sponsored
by Esri and published by Ventana Research in
September 2013. It found that the tools used
for location analytics have an important impact
on how organizations view such analytics.
According to this research, heavy users of
a GIS are the most often very satisfied (49
percent), and heavy users of spreadsheets are
very satisfied least often (16 percent). Among
those saying that the use of location analytics
has improved their results, spreadsheet users
ranked last (35 percent), some way behind
users of a GIS (55 percent).
http://www.esri.com/~/media/Files/Pdfs/landing-pages/products/ventana-la-2013.pdf?WT.mc_id=EmailCampaignb16787
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Report prepared for Kathleen Mitchell of TM Forum. No unauthorised sharing.
Geo-analytics must be able to process, analyze,
interpret and evaluate huge quantities of data
Section 2
Some way to go
The preceding section of this report should
not be taken to imply that geo-analytics are in
any way already a widespread ‘done deal’. In
practice, although the use of geo-analytics by
military forces and security agencies is well
established, in many other sectors it’s at the
beginning of a rising adoption curve. In the
digital services arena, geo-analytics applications
have a higher visibility in internal operations,
mobile workforce management and customer
experience than as enablers of new, revenueearning services and applications.
To scale the implementation and operation of
geo-analytics systems, solutions to a number
of serious challenges are needed. Some
apply to big data analytics in general. Others
may be more difficult to solve due to location
components being present in the big data
mix. Yet others are specific to the geospatial
environment.
Challenges in the big data ecosystem
As with other spheres of big data analytics,
to produce the most useful outcomes geoanalytics must be able to accommodate,
process, analyze, interpret and evaluate huge
quantities of data, of many different types and
formats, and at very high speed.
The three ‘V’ model was devised by Gartner
Inc to describe these attributes of big data:
‘Volume’, ‘Variety’ and ‘Velocity’. ‘Veracity’
was a fourth ‘V’ data attribute added by IBM,
and TM Forum’s Managing Director, Insights
Research, Rob Rich added ‘Value’, and
“Viability’ is an increasingly important attribute.
Volume. As described earlier, big data
volumes are now reaching the point where
established units of measurement are
becoming inadequate to convey what amounts
of data are capable of being generated,
captured, stored and analyzed. A zettabyte,
or around a trillion gigabytes, was once
undeniably in the big data big league. But last
year the 2013 Visual Networking Index (VNI)
produced by Cisco Systems forecast that
annual global IP traffic alone would reach the
zettabyte threshold by the end of 2015, and
could reach 1.4 zettabytes per year by 2017.
Now industry experts are talking of data in
yottabyte – around one thousand zettabytes quantities.
Variety. The variety of structured and
unstructured data being produced on a daily
basis is huge. A non-exhaustive list of the
types of traceable information would include
SMS, MMS, IM, audio, cell phone calls, mobile
apps, IVR, emails, tweets, social networking
posts, GIS data, business intelligence,
transaction information, photographs, videos,
IP traffic, web searches, RFID data, M2M, data
bases and reports.
Velocity. The speed at which, to be useful,
data needs to be harvested and analyzed is
increasing, with the progression from batch,
through periodic to near real-time and real-time
processing and analysis. Examples of real-time
uses include making timely offers to customers
and charging.
“With M2M you now have the ability to collect an unprecedented amount
of location data along with transactions and events.”
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GEO-ANALYTICS:
ADDING VALUE TO BIG DATA
Veracity. This concerns being able to assess
the quality, consistency, completeness, and so
integrity, of the data being captured. Here the
emphasis is on the efficacy of data cleaning
and validation.
Viability. This describes the circumstances,
and the context in which actions prompted by
analyzing big data, are likely to positively or
negatively impact outcomes. In an extreme
example, it is probable that an SMS offer of
a discounted holiday would be wasted on
most individuals who had been tweeting, in
the vicinity of the sponsoring travel company,
about a family bereavement.
Value. In the same way that not all information
extracted from big data analysis is useful, not
all information is valuable. Here the emphasis
is on understanding what data is useful to
advance particular business cases.
Spatial is special
While privacy is an issue for big data analytics,
according to Natasha Léger, President of the
Location Forum, concerns about its loss and
violation escalate when location data is part of
the deal. “Privacy is an enormous issue relative
to location data – perhaps more so than at the
big data level,” says Léger, who is also editor
of the LBX Journal.
“The challenge here is not so much the
technology to manage and guarantee privacy
rules are observed with location data,” adds
Arthur Berrill, Chief Technology Officer of
location-based information and data quality
specialist DMTI Spatial. “It is more the
understanding of just how deeply geo-analysis is
capable of violating privacy rules even with the
permission of the user or supplier of the data.”
Léger argues that much more transparency
in how location data is collected, how it’s used
and how it’s being distributed will be required
for the use of geo-analytics to achieve its full
potential.
Above and beyond the issues facing data
analytics in general, geo-analytics brings its
own set of challenges to the table.
A major one, in the view of Léger, is the
difficulty of integrating the new capability
with other business, IT and management
systems. Moving on from that, in the case
of organizations with extended operations in
areas such business intelligence, customer
relationship management (CRM) and supply
chain management, there’s the daunting task
“While privacy is an issue for big data analytics, concerns about its
loss and violation escalate when location data is part of the deal.”
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Privacy, standards and accuracy
are challenges for geo-analytics
of getting hold of and uniting the wealth of
location data that is held on those different
systems.
“How are we going to integrate this into
workflow?” she asks. “How do you access
and correlate all of the location data within an
enterprise across the different systems on
which that data could be residing?”
Many incompatibilities
Related to this is the need for standards to
bring the data incompatibilities that exist
between the GIS and the business intelligence
worlds. “There’s a need for standards to be
able to correlate the way the data are stored
in these different systems in order to access
them effectively,” say Léger. “They don’t
speak the same language at all.”
Nor is it the case that location data itself is
lacking in diversity and incompatibility. As Mark
Reichardt, President and CEO of the Open
Geospatial Consortium (OGC) points out, even
simple GPS coordinates can be encoded in a
variety of ways, and though standards exist,
most of the major Internet platform providers
do not expose location data through published
proprietary interfaces, let alone open standard
interfaces.
Reichardt also notes that geospatial
information is variously stored as points, vectors
and polygons, point clouds, grid arrays, place
names, street addresses, civil engineering files,
sensor feeds, references to indoor coordinate
systems, and special types of encodings such
as triangulated irregular networks. “Without
open geospatial encoding standards and service
interface standards for each of these technology
types, vendors’ proprietary formats and
interfaces would make ‘big geo-analytics’ nearly
impossible,” he suggests.
A further concern specific to geo-analytics
involves the accuracy of location data. Mike
Carpenter, Vice President and Field Service
Solutions Specialist, TOA Technologies,
says that while commercial GPS accuracy is
improving and is now in the range of plus or
minus 10 meters, in some parts of the world
location system accuracy is only at the level
of 100 metres, and sometimes much greater
than that.
This is of some consequence for enterprises
and organizations operating across different
geographies. “It’s got to be accurate, or you
can’t build business processes to rely on it,”
he states.
“There’s a need for standards to be able to correlate the way the data
are stored in these different systems in order to access them effectively.
They don’t speak the same language at all.”
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Report prepared for Kathleen Mitchell of TM Forum. No unauthorised sharing.
GEO-ANALYTICS:
ADDING VALUE TO BIG DATA
Section 3
Geo-analytics use cases
Geo-analytics systems of varying degrees of
sophistication can be usefully and profitably
deployed by digital service providers to achieve
a number of business objectives. Three are:
improving and streamlining internal operations;
enhancing customers’ experiences; and
launching new applications and services.
To a degree these objectives intersect. For
example, the internal efficiencies delivered
by location-enabled mobile workforce
management (MWM) can lead to better
customer experience and a higher favorability
rating of the service provider by the customer.
In turn, this might pre-dispose the customer to
more readily sign up for new location-enabled
services offered by that service provider.
However, it’s probable that not all geoanalytics opportunities will be equally attractive
to all types of digital service providers. For
example, pure-play wireline and cable operators
may have most interest in the internal
operational logistic and efficiency benefits of
location intelligence.
Internal affairs
There is already a GIS-based geo-analytics
component in a growing number of digital
service providers own mobile workforce
management (see panel below) systems. It’s
clearly useful for service providers to have
accurate map representations of the location
and disposition of all their network elements
and customer premises. If this is married to a
spatially-oriented, automated MWM system, it
becomes possible to optimize routes for repair
and field service staff and prioritize jobs based
on factors such as customer value, service
level agreements (SLAs) and point-of-presence
(POP) density.
Geo-fencing also enables the detection of
Hitting the road
An example of a service provider commercializing mobile workforce management capabilities
is the deal struck by AT&T with the U.S.-based, business-to-business provider of roadside
assistance, Road America. Customers needing roadside assistance call Road America’s
response centers, where coordinators determine their needs and dispatch mechanics.
Rapid, accurate identification of the caller’s location is critical, yet stranded drivers don’t
always know where they are. One solution relied on maps that were updated quarterly, but
this often led to lengthy phone calls between customers and coordinators, which in turn
delayed the dispatch of mechanics, increased costs and lowered service quality and customer
satisfaction.
Working with AT&T, Road America launched its LocateMe service, utilizing AT&T Location
Information Services, as part of the incoming call process at the response centers. Once the
caller gives their permission, their location is identified through the device they’re using to
make the call, whether it is landline, cell phone or smartphone.
The LocateMe service enables Road America to access cellular and/or geo-location data
from multiple carriers’ networks. According to AT&T the solution reduces waiting times for
callers, helps mechanics get to stranded vehicles faster, increases quality of service, and
decreases average call time.
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Integration of geo-spatial data with other datasets
saves money, increases efficiency and improves records
anomalous vehicle routing and gives a service
provider the option of letting service personnel
take vehicles home at night and be alerted
to any unauthorized vehicle journeys. This
arrangement can save time, cut the number of
miles traveled, and reduce the requirement for
centralized garaging facilities.
In the context of MWM, the integration of
geo-spatial data with other datasets has many
advantages, some quantifiable, some less so.
Among these are: cost savings and increased
efficiencies; better decision making; improved
communication; better record keeping; reduced
fleet wear and tear, and maintenance; reduced
carbon footprint; and increased job satisfaction.
With route optimization organizations can
get 10 percent to 20 percent savings, and if
those organizations can see their fleets on top
of their maps, it’s possible to get another 5
percent to 10 percent just based on being able
to see and better organize fleets.
Internal operations
From being a consumer of location-based
mobile workforce management solutions,
it’s a natural progression for some digital
service providers to become suppliers of these
solutions, particularly if they have built some of
the requisite competencies in-house, and have
implemented their own internal systems.
Another internal operations scenario enabled
by geo-analytics is one that applies to the cable
industry. In this instance a map of the network
enables the operator to determine where
service uptake is below average, and look at
attributes such as demography and network
performance data to see if these suggest
reasons for low uptake.
Geo-analytics also allow the service provider
to estimate the cost of building a new cablerun based on the density and type of potential
subscribers along that route. They can
combine this information with other data like
assessments of target customers’ value from
sales and marketing to estimate the potential
return on investment of the project.
Work experience
Geo-analytics can also make a major
contribution to digital service provider’s efforts
to improve customer experience. For example,
they can be used to monitor mobile network
signal quality in spatial terms. This would allow
the service provider to offer a differentiated
service quality based on location according
to the historic value of a particular customer
or whether customers were subscribing to a
premium or free service.
A milestone in the development of improved
customer experience was reached with the
release of TM Forum’s Customer Experience
Management Index (CEMI). Previously
“With route optimization organizations can get 10 percent to 20 percent savings,
and if those organizations can see their fleets on top of their maps, it’s possible
to get another 5 percent to 10 percent.”
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GEO-ANALYTICS:
ADDING VALUE TO BIG DATA
most customer experience management
measurements have been taken from actual
customer interface exchanges via the network,
call center, trouble desk and billing enquiries,
or through customer surveys. Measurements
were made of variables such as network
quality, customer service and billing accuracy.
Given that most customers today relate their
experience through other channels – including
blogs and social media posts and exchanges
– rather than directly to their service provider,
and given that the range of measurable
customer attributes is now very large,
TM Forum proposed that the CEMI would
address a much wider range of standard ‘touch
points’, both direct and indirect, across the
whole service provider organization.
Using big data analytics it would be possible
to produce a standardized global business
index that could be used to measure one digital
service provider against another in terms of
customer experience and satisfaction.
“With CEMI we said: ‘Let’s take a standard
set of touch points that we have with the
customer across the whole business – not just
in the network, not just in the billing section,
not just in the customer service activation
section’,” comments Professor Paul Morrissey,
Head of Data Analytics Group, TM Forum.
“And let’s measure these touch points against
service providers so that we can see what the
average of all these touch points is when we
aggregate them.”
Geo-analytics is part of the CEMI’s big data
analytics process. This is because many, if
not most, digital service providers’ customers
now have a mobile component in their
communications make-up, and geographic
location can be an important factor in mobile
network coverage and so mobile users’
experience.
Here Professor Morrissey, who is also Chief
Strategy and Business Development Officer,
Ventraq, instances location-sensitive attributes
such as the number of dropped calls and
signal-to-noise ratio.
Push and pull
Geo-analytics also enables digital service
providers to commercialize new services
and applications based on the discovered
and mapped proximity of mobile phones
“When marketing messages are not relevant to customers, they become
spam and customers are at risk of churning. Poorly pushed messages
can lead to customer fatigue and ignoring future messages.”
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Location-based services enable delivery
of tailored marketing to mobile devices
How the Big Data Analytics Guidebook can help you
This new guidebook, published as part of Frameworx 13.5 in October 2013, establishes a
crucial linkage between business value that big data analytics can unlock and the big data
technologies and information sources in the document’s pioneering Big Data Reference
Model. It includes more than 30 use cases for big data applications such as real-time,
personalized offers, proactive care and churn prediction.
Characteristic of the pragmatic approach throughout, the guidebook identifies and defines a
suite of building blocks that are needed to realize the use cases.
Please visit www.tmforum.org/BDA2013 to download the guidebook and access other
information and materials on big data analytics – they are free to all employees of TM Forum
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gain maximum results.
If you would like to know more and/or participate in our Big Data Analytics Community and
activities, please contact Steve Cotton, Director, Business Assurance Programs, via
[email protected]
and wireless devices to locations that are of
interest to the individuals using those devices.
As an example, one of the first generation
of these location-based services (LBSs)
could have a user requesting and receiving
information about, directions to, or a map
showing the location of the nearest coffee
shop, ATM or rail station. This is known as a
‘pull’ or ‘active’ service.
By contrast, with a ‘push’ or ‘passive’ LBS
the user does not specifically request the
service at a particular time, but is the recipient
of, say, local advertising or e-coupons based on
the user’s profile. Or the ‘recipient’ could be
the subject of a parental -monitoring service.
In the case of many retail-oriented push
LBSs, big data analytics enters the picture
because, as described in the 30 use cases
outlined in TM Forum’s Big Data Analytics
Guide Book (see panel above), when marketing
messages are not relevant to customers, they
become spam and customers are at risk of
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churning. Poorly pushed messages can lead
to customer fatigue and customers ignoring
future messages.
Big data analytics can be used in a number of
ways here, including:
n
n
n
To ensure that the mobile marketing
messages, from a catalogue of most
relevant, pre-defined campaigns, are sent
only when customer arrives or is about to
arrive at certain pre-defined geo-fenced
locations.
To identify products and services that are
relevant to a given customer behavior; these
products and services are then pushed to the
customer through the appropriate channel
and at the appropriate time.
To use customer location changes to trigger
marketing messages and thus increase the
chance of relevancy to what customers
need.
QUICK INSIGHTS
13
Report prepared for Kathleen Mitchell of TM Forum. No unauthorised sharing.
GEO-ANALYTICS:
ADDING VALUE TO BIG DATA
Section 4
Mapping out the future
To what degree there will be greater
deployment and utilization of geo-analytics
by digital service providers is dependent on a
number of factors. Some of these are related
to technology and standards, some to business
cases, and some to people, management
orthodoxies and skill sets.
In the picture
GIS technology is a cornerstone of geoanalytics. Up until recently, though, the
integration of maps and spatial analytics with
business data had not been widespread, due
to the expense of custom integration with
enterprise systems.
It’s also been the case that heavy duty GIS
requires special skill sets; there is even the
suggestion that you needed a Chief Geospatial
Officer and dedicated staff and equipment.
“Until we break that down and make spatial
commonplace, there is a huge barrier to
success,” reasons Arthur Berrill, Chief
Technology Officer, DMTI Spatial.
Allied to this, it may be that the geo-analytics
community is guilty of looking inward, rather
than outward. Berrill has characterized the
geo-analytics industry as spatial people doing
spatial things with spatial data and spatial tools
for spatial people. He contends, “We as an
industry need to work out how we help the
other industries – not how we help ourselves.”
There is some progress on this front, with
the price of the underlying GIS technologies
falling and the availability of GIS services using
the cloud model on the rise. As has been well
remarked, the cloud-computing model can
reduce the requirement for specialist in-house
skill sets, and can farm out responsibility for
technology refresh.
Keeping up standards
There remains a pressing need for sets
14
QUICK INSIGHTS
of standards to advance interoperability
between the different types of location data
and between geo-analytics and business
intelligence and enterprise systems.
Again some advances are evident, with a key
development being the October 2013 liaison
agreement to connect the OGC’s location
standards framework and industry consensus
process to TM Forum’s core competency
programs, vertical industry initiatives, and
Frameworx standards and best practices.
Through partnership, the TM Forum and the
Open Geospatial Consortium (OGC) seek to
collaboratively advance standards-based best
practices to further the location enablement
of digital services to serve a wide range of
stakeholders. Both organizations have an
obvious interest in domains such as smart grid
and smart cities, but they also share interests
in eHealth, sensors, machine-to-machine
(M2M) communication, and business process.
OGC can help TM Forum develop best
practices for the use of standards. In addition
to promoting OGC standards through
promoting these best practices, the TM Forum
can help the OGC by providing requirements to
guide development of standards.
Down to business
According industry experts, in the enterprise
space it’s imperative that the introduction of
geo-analytics be informed by the recognition
that the process is aimed at yielding actions
rather than just knowledge, and that the
intention is to achieve a business benefit.
This benefit could be more efficient business
practices, cost savings or additional revenues,
or a combination of these. Without the aiming
for tangible ROI, though, the net result of geoanalytics for enterprises can be little more than
colorful maps and charts on screens.
Something of a change in end-users’
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Report prepared for Kathleen Mitchell of TM Forum. No unauthorised sharing.
M2M, smart grid and eHealth are leading
candidates for geo-analytics applications
approaches is likely needed as well for
the more widespread implementation and
exploitation of geo-analytics solutions. In the
case of mobile workforce management (MWM)
and geo-fencing, for example, the technology
exists to allow digital service providers to see
where their vehicles are parked overnight.
Yet management needs to tread carefully:
Where those vehicles are parked at or close to
employees’ homes, this surveillance this might
be viewed as an unacceptable level of intrusion
into employees’ privacy or even illegal.
What next for geo-analytics?
If the issues outlined above can be resolved
satisfactorily, the geo-analytics future in the
provision of digital services looks promising,
particularly in the case of providing new
services with partners from different industry
sectors. After all, mobile operators have
unrivaled access to a wealth of background
customer information in general, and to
location data in particular.
In the opinion of TOA Technologies’ Mike
Carpenter, this is a compelling reason for them
to get involved in geo-analytics. He believes
mobile operators have the opportunity to
control the high ground in terms of marketing
geo-analytics services – but mobile networks
are far from being the only game in town (see
panel below).
Natasha Léger, President of the Location
Forum, even suggests that mobile operators
could turn concerns about geo-analytics and
privacy to their advantage: They could create
privacy-aware services and products based on
individuals having control over how their data
is used in the consumer and in the enterprise
sectors. As an illustration, users could specify
that their data could be used for operational
and customer experience purposes but could
veto data sharing, selling or integration with
other data.
Outside of that generalized potential
opportunity, industry sectors such as M2M,
smart grid and eHealth, in which many service
providers already have varying levels of
involvement, are among the leading candidates
for the geo-analytics treatment.
M2M
Among the observations contained in Software
strategies for operator profitability 3, a study
produced by Analysys Mason for TM Forum’s
Management World 2013 event, Senior Analyst
Justin van der Lande argues that the M2M
Sources of location-based information
A 2013 study by Allied Market Research estimates that global real-time location-based
services (RTLS) market was worth $11.7 billion in 2013 and could grow to $43.7 billion
by 2020*. Allied Market Research says that due to its enhanced accuracy levels, Global
Positioning System (GPS) has emerged as a market leader among all RTLS technologies and
could reach market revenue of $15 billion in 2020.
Other options, which may be used in various combinations, include cell tower localization,
Wi-Fi connections, IP addresses and self-reported or check-in positioning.
*www.alliedmarketresearch.com/global-real-time-locating-systems-rtls-market-expected-to-reach-437-billion-by-2020.html
3
http://www.analysysmason.com/Research/Content/Reports/Software-strategies-May2013/
www.tmforum.org
QUICK INSIGHTS
15
Report prepared for Kathleen Mitchell of TM Forum. No unauthorised sharing.
GEO-ANALYTICS:
ADDING VALUE TO BIG DATA
sector could generate significant revenue
streams from data analytics, with service
providers monitoring or analyzing the data
content that is used within M2M.
Among others, these services include
emergency location services, car alarm or
security services and logistics tracking, which
network operators are well equipped to provide.
Van der Lande instances the analysis of road
traffic fed back from Vodafone to navigation
solutions and digital maps company TomTom.
In this case TomTom’s technology uses
traffic data generated by the movement
patterns of mobile phones inside vehicles
collected anonymously from Vodafone’s
network. This is combined with anonymized
data from TomTom devices, as well as other
traditional sources of traffic information, to
provide advanced traffic information services.
Smart grids
Being able to capture, process, manipulate
and display spatial data provides a lot more
tools for the operation of modern utility power
distribution networks.
Geo-analytics’ support for smart grids could
include:
enabling ‘demand response’ programs
whereby consumption of power varies
depending on time-based price incentives
or targeted tariffing to lower energy
consumption at peak times and balance
supply and demand;
n a geographic view of consumption by
domestic and industrial users;
n the provision of oversight of where power
is being generated, which is an increasingly
complex management task due to the
variability of renewable energy generation
and the contribution of micro-generation
feed-in power from consumers;
n
16
QUICK INSIGHTS
optimized siting of smart grid components;
enriched insight into smart meters’
performance;
n improved data management and billing; and
n workforce automation.
n
n
eHealth
Geo-analytics has many potential applications
in the eHealth sector including:
predicting epidemics;
early warning and control of outbreaks of
disease;
n identification of areas where the environment
and/or demographics and lifestyle can have
an adverse impact on health;
n highlighting areas to be targeted with the
preventative information;
n improving the efficiency of emergency and
rescue services;
n tracking at-risk individuals and patient
monitoring;
n better management of assets and healthcare
workers; and
n optimizing the location of new facilities based
on projected need and demand.
n
n
For the future, TOA Technologies’
Carpenter sees continuing improvements in
position accuracy and, using combinations
of technologies, considerable growth of
in-building location capabilities. These last
will enable new digital services such as: the
pinpointing of patient and asset tracking in
eHealth; real-time, granular retail marketing;
and premium private security services.
There is little doubt that geo-analytics have
a huge role to play in the provision of many
digital services; the big question is how fast
will it happen – put another way, how quickly
can we find more standardized, economic ways
of deploying and scaling them?
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Report prepared for Kathleen Mitchell of TM Forum. No unauthorised sharing.
Partnerships are necessary to deliver
all types of digital services quickly
The essential ingredient
Partnerships are an essential ingredient in the
delivery of all types of digital services, quickly
and at scale. First because the last few years
have seen the demise of communications
service providers that: own, operate and
maintain all their own network elements;
develop and deliver discrete services over
those elements; and exclusively manage
relationships with customers.
They have been replaced by horizontallyintegrated enterprises obligated to work
collaboratively with suppliers and partners to
offer new services via multi-tenanted value and
service delivery chains.
Second, to fully exploit the opportunities
presented by big data- and geo-analytics, all
types of digital service providers will need to
collaborate with one or more partners (see
AT&T case study on page 10), whether they
are retailers looking to boost customers’
footfall or utilities aiming to streamline smartgrid operations.
While it is relatively straightforward to
implement partnering in a one-off manner, to
make partnering a repeatable, scalable and
industrialized process, a number of additional
concepts have to be adopted to handle
business and technical changes throughout
the life of the partnership, and for the services,
from end-to-end.
TM Forum’s Collaboration Community has
Figure 4-1: Overview B2B2X Accelerator Document Pack
B2B2X Accelerator Schematic
Business Pack
B2B2X Partnering Guidebook:
Concepts and examples
(TR211)
B2B2X Partnering Guidebook:
Step by step guide
White paper:
Implementing Wholesale
B2B for a Network Operator
DBP2
www.tmforum.org
B2B2X
Accelerator
Introduction
Developer Pack
B2B2X Developer Pack
Pt1: Concepts
Pt2: Step by step guide
Pt3: Where to find what
NBN Co
Contributions
BT/NICC
Contributions
NTT
Contributions
Digital Services
API Specification
SM-API
SM API materials
QUICK INSIGHTS
17
Report prepared for Kathleen Mitchell of TM Forum. No unauthorised sharing.
GEO-ANALYTICS:
ADDING VALUE TO BIG DATA
addressed these additional issues with a
comprehensive set of tools and best practices
to enable the business goals of enabling:
the quick set-up of partnering arrangements,
efficient on-boarding of new partners through
a consistent, repeatable process,
n partners to swap out the products; and
n evolving partnerships.
n
n
TM Forum’s B2B2X Partner Accelerator
document pack – see Figure 4-1 – is freely
available to all the Forum’s members. It sets
out an approach for business and technical
people to deliver robust partnering agreements
and solutions for B2B, B2B2C and B2B2X
business models, based on reusable service
components, processes, functions and
application program interfaces.
Partnership Service Lifecycle Model
The Accelerator includes a Partnership
Service Lifecycle Model – Partnering, Design,
Implementation, Operations and Monetization
– tailored to the needs of partners working
together to co-provide end-user services. This
lifecycle model recognizes and supports the
different lifecycles for process, information,
products and partners within the partnership.
The Model has a step-by-step set of
checklists for executing each stages of the
Service Lifecycle and provides an overview
and detailed treatment of the key concepts
and patterns needed to define business and
technical collaboration in a systematic, agile
repeatable manner at industrial scale.
The Model also offers a set of technical
assets for creating practical technical
integrations covering the wide range of nonfunctional requirement encountered in these
types of B2B and B2B2X deployments.
Please go to www.tmforum.org/
B2B2XPartneringAccelerator to find out more
and to download any of the documents. You
can also contact Dave Milham, Chief Architect
Service Provider Engagement, TM Forum,
for more information, including how to get
involved, via [email protected].
“The Model has a step-by-step set of checklists for executing each stage of the
Service Lifecycle and provides an overview and detailed treatment of the key
concepts and patterns needed to define business and technical collaboration....”
18
QUICK INSIGHTS
www.tmforum.org
Report prepared for Kathleen Mitchell of TM Forum. No unauthorised sharing.
What’s new in Frameworx 13.5 and how can it help you?
Frameworx 13.5 centers around the crucial issues facing
service providers of all kinds in an open digital economy
which are reflected in TM Forum’s three Strategic Programs:
n
n
n
Agile Business and IT Program focuses on improving
operational agility while reducing cost and risk;
Open Digital Program is designed to drive new digital
services’ revenue growth; and
Customer Engagement Program targets better market
share retention and greater growth.
Frameworx was created by and is constantly evolved to meet
changing needs of TM Forum’s members. They include all
sorts of service providers, software suppliers, integrators,
universities, and enterprises. Members set priorities and
lead collaborative project groups to implement the work and
create updates to the standards and best practices.
While Frameworx major releases are published every six
months, some features in Frameworx 13.5 were developed
in short-term agile-style development projects and have
been made available to the broader membership several
months in advance.
Frameworx releases cover the full suite of TM Forum’s best
practices and standards including our core Frameworks –
Business Process, Information, Application, and Integration
– as well as our Business Metrics and our broad range of
best practices. Frameworx 13.5 is no exception with 47 new
items introduced across the full range.
Facts about Frameworx 13.5:
n 27 projects were chartered to create this release;
n 141 companies participated in creating the deliverables;
n About 380 individuals joined projects in the community –
approximately 40 percent of them were active contributors,
while the rest had the opportunity to observe and review,
comment or ask questions.
New B2B best practices and APIs
TM Forum has defined a comprehensive set of Accelerators
– tools, methodologies and standardized interfaces for
creating and managing partnerships in a B2B2X environment
with multiple partners, in a repeatable manner, and at
industrial scale. They include new REST 2 application
program interfaces (APIs) for catalog management, trouble
ticketing and partner ordering.
www.tmforum.org
Big Data Analytics Guidebook
Unleash the power of big data held by service providers
using the new reference model, methodology and more
than 30 use cases. This document defines a crucial linkage
between business value that analytics can unlock and the
big data technologies and information sources represented
in the document’s Big Data Reference Model.
Threat Intelligence Dashboard and ROI Calculator
The Cyber Security Readiness Dashboard uses newly
defined metrics to communicate Cyber Security readiness
for C-Level management. The dashboard reduces risk by
providing insight into issues that could have financial, legal/
compliance and human safety impacts.
Customer Experience Management
Take a new approach to managing customer engagement
with integrated Maturity Model, Lifecycle Model and
Metrics. This new version of the Guidebook (incorporating
250 new metrics) marks the first step in the transition from
managing customers' experiences in a snapshot piecemeal
way toward managing engagement with the customer
across their entire lifecycle.
Core Frameworks Enhancements
There have been key new additions to all four Frameworks
to extend their application and make them more immediately
useful. For more information about how they apply to you and
your business, please see www.tmforum.org/Frameworx13.5
QUICK INSIGHTS
19
Report prepared for Kathleen Mitchell of TM Forum. No unauthorised sharing.
Sponsored feature
Enhanced Business Intelligence
with Location Analytics
By Randall Frantz, Director, Telecommunications Solutions, Esri
The integration of two highly
complementary enterprise software
solutions, business intelligence (BI) and
geographic information system (GIS)
technology, delivers new, powerful
tools to telecommunication companies
interested in gaining a competitive
advantage. BI leverages corporate data
to provide insight into how businesses
are performing. GIS allows users to
visualize and intelligently analyze data
while discovering new patterns and
trends not typically seen in traditional BI
implementations. The fusion of GIS and
BI, known as location analytics, gives
decision makers powerful tools to gain
insight from historically underutilized data
and frees them from the constraints of
conventional analysis and geographic
boundaries. It is now possible to analyze
external and internal factors that influence
business performance while addressing
issues on a local level.
There is no limit to the types of
data or the source from which it can
be collected, visualized, and analyzed
using an integrated BI and GIS platform.
Development of BI software now
provides more advanced analytical tools
migrating from descriptive to predictive
and even prescriptive analytics, which
use the output of predictive algorithms to
recommend business decision options.
Despite these advances, BI tools still lack
the important component of location.
Even with simple events such as network
or organizational performance, the lack
of location awareness limits the ability of
BI solutions to present a complete and
accurate picture of events.
The ability to filter and isolate results
is also an advantage when it is time to
identify smaller, less dramatic service
interruptions or anomalies. Companies
collect vast amounts of data with
the expectation that managers who
understand organizational performance
will ultimately make good business
decisions. Dynamic businesses, such as
telecommunications, require accurate
and timely data to respond quickly in
highly competitive markets. In the past,
managers often received incomplete
and outdated data. The thinking has
been that if a little data improves the
decision-making process, then more
data must lead to even better decisions.
Unfortunately, when data is collected and
analyzed on a regional or national scale, it
is possible to miss small local anomalies.
Figure 1 – Integrated BI and Heat Map
20
QUICK INSIGHTS
www.tmforum.org
Report prepared for Kathleen Mitchell of TM Forum. No unauthorised sharing.
To take corrective action, the problem
areas must be identified. This is where
location becomes important.
When a marketing campaign or
network performance is measured across
a region or the entire company, the
results are summarized as an average.
The granularity of the data is often lost.
Some areas might be delivering superior
results while others are subpar. In order
to improve results, these subperforming
areas must be identified and corrective
action taken at the local level. GIS
provides powerful tools, such as heat
maps, and the ability to drill deeper
into the data without additional coding.
The heat map provides a color gradient
to help quickly locate where there
are deviations from the average, both
positive and negative (see figure 1). The
heat map can be integrated with BI to
provide supporting graphs and charts.
The map can then be used to drill deeper
and analyze the data at the designated
location so corrective action can be
taken. The heat map and local analytics
provide the actionable intelligence at an
appropriate level to address the issue.
Location analytics can also predict the
impact of external events on network
performance before they affect service.
Alarm and monitoring systems fed into
a traditional BI system are reactive. The
introduction of location provides the
ability to evaluate environmental factors
and transform a reactive system into a
predictive one.
External events often affect network
performance and impact customer
experience. Some of these events are
obvious, such as major fiber optics cuts
or natural disasters including storms and
floods. The major storm shown in figure
2 will impact a large portion of Florida and
www.tmforum.org
Figure 2 – External Events Impact Network Performance
“The fusion of GIS and BI, known as Location Analytics, gives decision
makers powerful tools to gain insight from historically underutilized
data and frees them from the constraints of conventional analysis and
geographic boundaries.”
QUICK INSIGHTS
21
Report prepared for Kathleen Mitchell of TM Forum. No unauthorised sharing.
Sponsored feature
Enhanced Business Intelligence
with Location Analytics
could affect telecommunications service
throughout the state.
Traditional BI solutions can only
account for events after the fact, and
the data collected from an impacted
area often overshadows the results
from other, unaffected areas. BI tools
using network monitoring systems by
themselves are unable to predict the
impact of external factors on network
performance. Location analytics provides
this additional capability. In addition,
location analytics provides post event
ability to segment data from affected
and unaffected areas. Without this
segmentation, an organization might
disregard all the data collected during
major events, lest they skew the overall
results.
Eliminating event data from an analysis
creates some obvious problems. First,
customers are still affected by these
types of events. Understanding the
impact on service levels will help evaluate
the effectiveness of the response and
lay the foundation for preparing for future
events (figure 3). Second, it will be
important to keep in mind that customers
directly affected by such events might
be more tolerant of service interruption.
However, customers in nearby unaffected
areas could experience longer installation
times and repair intervals due to critical
resources being diverted to the impacted
areas. Customers in unaffected areas will
likely be less tolerant of service issues.
Integrating GIS into BI solutions
provides the ability to isolate affected
areas from regions with normal
operations and evaluate service
performance for both. Unaffected areas
can still be evaluated using standard
service-level benchmarks, while stormimpacted areas can use a modified
measurement standard. This provides
a true picture of the actual customer
experience in both areas, taking into
consideration each situation.
With greater understanding afforded
by location-aware business intelligence,
decision makers have powerful
visualization and analytics tools. This
capability is backed by systems that can
make recommendations on allocation of
resources to improve performance and
customer experience. In other words, GIS
plus BI is the foundation for prescriptive
analytics.
Find out more at esri.com/telecom.
Figure 3 – Segmented Performance Information
“With greater understanding
afforded by location-aware business
intelligence, decision makers have
powerful visualization and analytics
tools.”
22
QUICK INSIGHTS
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Report prepared for Kathleen Mitchell of TM Forum. No unauthorised sharing.
Have you seen our other recent TM Forum publications?
TM Forum's research reports are free for all employees of our member companies to download by
registering on our website. The reports are also available for non-members to purchase online.
Customer experience: Hitting a moving target
This latest, in-depth Insights Research report looks at how service providers are working to
improve customer experience to differentiate themselves, increase profitability and expand their
businesses. The heart of this report is unique insights from in-depth interviews with service
providers, and survey results, from around the world. The author, Rob Rich, focuses on mobile
users, discussing mobile and digital services trends as drivers.
INSIGHTS
RESEARCH
September 2013 | www.tmforum.org
Free to tmforum members $495 where sold
In previous annual Insights Research reports on customer experience, operators’ top priority has
been cost cutting. Now they are the differentiating strategies in terms of outcomes, and longer
term profitability and impact on brand.
The report offers pragmatic recommendations about how to get the biggest benefits from
investment in customer experience across the organization. It also explains TM Forum’s ongoing
work on customer experience, including the Maturity Model, to help service providers move
from piecemeal customer experience to engagement throughout the customer’s lifecycle.
Customer experience:
Hitting a moving target
All employees of TM Forum’s member companies can download it free by registering on our
website from www.tmforum.org/CEtarget
Sponsored by:
Digital Life – After the hype, where’s the money?
This is a clear-eyed analysis of how the digital services market is shaping up after the initial hype
and identifies some great opportunities for service providers to develop new, sustainable lines
of business. Expectations around the profitability of machine-to-machine (M2M) communications
are shifting, but network operators can compete by adding value, and we look at some
examples.
October 2013 | www.tmforum.org
Analysis:
What we’ve
learned from
real-life lessons
The regulatory and legal framework will also have a big bearing on the profitability and viability of
M2M services of all kinds – as detailed in the second section.
Insights:
Digital disrupters
from diverse
industries
Viewpoint:
KPN Group’s
Erik Hoving on
living in a world
of screens
Sponsored by:
AFTER THE
HYPE, WHERE’S
THE MONEY?
Exploring the evolution of digital services
www.tmforum.org
HANDBOOK 2014
Agile IT
Less risk, less
cost and less
time-to-market
Customer
Engagement
Greater growth
and loyalty
Digital Services
Partnerships
secure fast
new services
SHOWCASING
INNOVATION
AND SUCCESS
Everyone can download this new edition of Digital Life free from www.tmforum.org/DL2013
TM Forum Case Study Handbook 2014
This brand new edition is packed with innovative and inspirational success stories from different
kinds of service providers around the world. All have used TM Forum’s assets and activities in
many different ways to achieve a variety of different business goals.
CASE STUDY
Everything that can be digital will be.
We’ve seen the future. And it’s digital. In just
ten years, the way we communicate,
consume information and entertainment has
been changed forever. And that’s just the start.
The third element looks at how a number of digital disruptors are changing lives and business
models. Coursera’s mission is to offer a free college education to everybody and make money.
It signed up its first million ‘customers’ faster than Facebook. We explore a model to enable
mobile universal payments without merchants even having to belong to any mobile money
schemes, and how big brands – digital and physical – can bring more imagination to emerging
markets to reap huge rewards.
There are five core principles of the Initiative:
From Argentina to New Zealand
The Digital Revolution is transforming our
personal and professional lives. We demand
simplicity, but the complexity behind our
interconnected digital lives is only growing.
Read how Telekom Malaysia used Frameworx to help it launch Metro Ethernet services within
10 months and how GuangDong Mobile is saving $3.3 million a year in operational costs while
improving customer experience. Commonwealth Bank of Australia leveraged cloud technology to
excel at customer service while slashing costs. BT for Life Sciences’ cloud-based model speeds
research in pharmaceuticals and the platform is sufficiently flexible for use by other verticals.
Wellink helped Russia’s biggest communications operator, Rostelecom, automate and resolve
service level agreements to improve service to enterprise customers and strengthen its position
in that sector. India’s Reliance Communications worked to identify and fix the causes of service
violations to ensure, for example, service closure was improved to handle 95 percent of instances
within 30 minutes.
Sponsored by:
These and many more success stories are available free to everyone to download from
www.tmforum.org/CSH2014
TM Forum’s Digital Services Initiative focuses
on overcoming the end-end management
challenges of complex digital services,
enabling an open, vibrant digital economy.
For more information on the TM Forum Digital Initiative visit www.tmforum.org/digital
DigitalServicesAD2012.indd 1
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