location intelligence and competitive insight

The eureka MoMenTL o c a t i o n i n t e L L i g e n c e a n d c o m p e t i t i v e i n s i g h t

in associaTion wiTh:

http://www.pitneybowes.com/us

Contents

Introduction ...............................................................................................................................2

Location Intelligence Is Business Intelligence ..............................................................3

case study: telenor Pakistan ...............................................................................................4

case study: Peugeot-citroen uK .......................................................................................5

sIdeBar: Visual Basics ............................................................................................................6

creating competitive advantage .....................................................................................7

case study: James river Insurance company ............................................................10

case study: Willis ....................................................................................................................12

sIdeBar: Why Not Google? ................................................................................................ 13

consumerization of Location Intelligence ................................................................... 14

case study: Barnsley council ............................................................................................ 16

conclusion ............................................................................................................................... 18

acknowledgments................................................................................................................ 19

2 | the eureKa MoMeNt

Visualizing data by location can be meaningful for

business in several ways. Primarily, it can help reveal

relationships between customers or operational data

and geography—this might help a telecommunica-

tions company, for example, understand where to add

new towers to its network to boost flagging signals in

an underserved or growing area. In mapping different

types of data—such as storm patterns, infrared heat

signatures or waterways—previously unseen spatial

relationships can be brought to light and, as a result,

decision making can be improved.

Location intelligence (LI) can be described as the

process of deriving meaningful insight from

geospatial data relationships to solve a particular

business problem. It involves layering multiple

data sets spatially and/or chronologically, for easy

reference on a map, and its applications span

industries, categories and organizations.

“If you’re a business that is in any way asset-centric

but has a large body of consumers that it needs to

deal with, and needs to understand how to deliver

services or communicate with them, then location

is a critical part of how you should operate your

business,” says James Buckley, Pitney Bowes’s SVP of

Location Intelligence.

Traditionally, this kind of intelligence has been the

responsibility of highly compartmentalized, highly

specialized geographic information systems (GIS)

and their users. But the evolution of these tools has

democratized both the access to and the insights

within and throughout the organizations that use

them. New insights can be gained from something

as simple as taking data off a spreadsheet and

placing it on a map, revealing previously overlooked

relationships.

As one of our interviewees, James River Insurance

Company’s Jonathan Weisenberger, puts it, “We’re

dealing with a product that exists in a physical space,

and seeing it represented in that physical space is

helpful for what you might call a eureka moment.”

In this report we look at real world location intelli-

gence use cases in the public and private sectors,

and how organizations within these sectors have used

location to reveal insights. We have interviewed senior

executives and officials from a number of industries

to understand the efficiencies and competitive

advantages location intelligence helps their organi-

zations create. During research, three key themes

emerged: location intelligence and its relation to

business intelligence; using location intelligence

to create competitive advantage; and the trend of

consumerization.

These themes are not distinct. They are interwoven

through practical usage of location intelligence tools

as they are integrated, in varying measures, through

the following case studies. Taken together as a whole,

they show how location intelligence is uncovering

real world competitive insights that drive efficien-

cies and improvements across a broad swath of

organizational types.

IntroductionIn recent years the convergence of business intelligence and big data has given rise to data-driven organizations—organizations that use data not only as a check against gut intuition, but to direct business practices, marketing, new product development and any number of other operational activities. But business intelligence platforms typically miss an important dimension of data analysis: location.

coPyrIGht © 2015 Forbes InsIghts | 3

If, as is commonly estimated, 80% of all business data contains a location component, it is critical to understand how location affects business. Properly analyzing location can provide insights that support and improve decision-making in everything from marketing to supply chain logistics and operations. Yet traditional business intelligence platforms typically lack this functionality.

“Most business intelligence systems will give you no special view of the data,” says Pitney Bowes’s Buckley. “They won’t go to that next level of analysis and answer questions about, for example, the geo-demographic characteristics of your market, or what it might say about why people are buying certain products in one area versus another. Asking and being able to answer those kinds of questions can reveal really useful insights for a business.”

Location intelligence (LI) does not replace business intelligence (BI); it complements it. “Location in-telligence runs in parallel [to business intelligence] to some extent,” says Mark Smith, CEO and chief research officer at Ventana Research. “It’s trying to highlight the need for a relevance of what we call ‘where.’ It’s not the ‘who’ or ‘what,’ it’s the ‘where’ that is in the minds of most business people: Where are my most valuable customers? Where are the issues impacting my supply chain?”

There is a movement among LI vendors to offer integration into mainstream BI platforms and, with proper geocoding, such integration enables an alternative view of business data. It lets users parse the data differently, arranging by identifiers of space and time rather than disparate demographic denominators, for example.

Where BI may find one-dimensional relationships between customer demographics or store and ware-house locations, and perform rudimentary location comparisons, LI enables much deeper dives into the relationships between geography and customer data. In the combination of geographic and dynamic data, visualized on a map, location intelligence reveals characteristics that may have been otherwise obscured in a spreadsheet environment.

“If I’m a BI user, what I want to look at is business information on a map and see my data from a different angle,” says Buckley. “And then I might make a different decision than if I were looking at a box shot or histogram.”

Analyzing data by location allows businesses to ask and accurately answer questions such as “where are my customers?” or “how far are my customers from my location?” as well as “how well does my supply chain service those customers?”

41%

35%

Location Intelligence Is Business Intelligence


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T e l e n o r P a k i s T a nCase Study

With 35 million subscribers, representing about 25% of total market share, Islamabad-based Telenor Pakistan (TP) is the country’s second-largest mobile operator. But it’s an extremely competitive market, with five operators locked in a “severe price war,” according to Malik Faisal Qayyum, director customer value management and analytics. Average revenue per user is low, but customers are demanding, especially when it comes to network reliability and customer service.

In this environment, TP needs to be extremely efficient in its analysis and operations. Prior to implementing more-rigorous location and mapping tools, these issues were being approached internally in a limited way by generating reports from the data warehouse and collecting feedback individually from the field.

“The approach was time consuming, and the analysis built on raw feedback had to go into multiple iterations of review before being formed into conclusive output,” says Qayyum. “This traditional method had the advantage of on-the-ground feedback, but the time it took to formulate the analysis was the drawback. Also, the traditional approach made it difficult for non-sales staff to understand ground realities related to geographical dynamics of a situation.”

The decision to implement location intelligence tools was jointly handled by the sales and business intelligence departments, with several goals in mind, including improving workforce management and performance, converting warehoused data to more accessible, graphical and easily comprehended information, minimizing time-intensive tasks and enhancing diagnostic capabilities of the sales force.

“TP already had strong business intelligence capabilities,” says Sami Uddin Ahmad, director business intelligence and data warehouse. “To take maximum advantage of BI and to take this to the next level, the analytics were integrated with mapping services for better visualizations. Mapping geographic location in a country like Pakistan adds an important dimension to our analytics when considering market intelligence, business expansion strategies and performance reviews.”

“�To�take�maximinum�advantage�of�BI,�the�analytics�were��integrated�with�mapping�services�for�better�visualizations.”

— saMI uddIN ahMad director Business Intelligence and data Warehouse, telenor Pakistan

Ultimately, the location intelligence tools helped pave the way for a successful new operating model at Telenor Pakistan. “The scope of the location intelligence solution has now evolved to become the cornerstone of a new operating model called Cluster-Based Operating Model, aka the C-BOM,” says Qayyum.

C-BOM operates largely on feedback from and analysis of sales team performance, as well as connectivity of the network. “It was implemented successfully and continues to be useful by virtue of locations-based data, as it allows more surgical and diagnostic views and analyses of realities on the ground.” Significant growth in TP’s business performance over the last year is credited internally to the success of the C-BOM, but location intelligence, says Qayyum, “is certainly what made C-BOM possible.”


T e l e n o r P a k i s T a n

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P e u g e o T - C i T r o e n u kCase Study

Peugeot-Citroen (PCA) has a network of about 500 outlets—sales and/or service—throughout the United Kingdom. Reflecting the changing vehicle market and customer demands, the company needed to update its catchment area—the zone from which a business is likely to attract customers—for each outlet. Catchment areas are an integral part of the calculation for sales targets and vital to the decision making process of where to locate new dealerships without cannibalizing existing business.

In order to improve decision-making around revenue and optimal location, PCA takes into account the drive time to each dealership. “It’s important for us and for our customers to be able to get to one of our outlets in a reasonable amount of time,” says Andrew Bury, network planning manager. “From the analysis we’ve done, we see that quite a significant drop off, called a drive-time decay, occurs. The farther you get from a place, there are less and less customers that travel that far.”

In the past, PCA utilized GPS data from delivery trucks and vans to determine drive times to its dealer locations. However, as Bury points out, delivery vehicle data wasn’t representative of the behavior of retail customers— so a bespoke solution was needed. The answer, for PCA, was to combine an off-the-shelf drive-time product with customized data from navigation systems between its business hours of 7 a.m. and 7 p.m. to get a better idea of actual road conditions and drive times.

“We made the transition to these TomTom drive times, and it’s made a big difference,” says Bury. “We believe that the accuracy is as much as we can get, so we have a lot of trust in the results that we get out of it.”

“We�have�a�lot�of�trust�in�the�results�that�we�get.” — aNdreW Bury

Network Planning Manager, Peugeot-citroen uK

Although the network planning department holds the drive-time data, other departments are finding uses for the information, and in some cases it’s helping build a better case to win new business. For instance, the fleet department can now use the drive-time data to help answer questions about network coverage capabilities. “We’re able to answer that fairly accurately and quickly,” says Bury. “I believe that’s impressed a few of our customers, who then went on to sign quite significant deals with our fleet department.”

Another unplanned benefit has been in offering after-sales service outlets analysis around the drive times for service customers as well as for potential sales. Call centers can now also direct customers to the nearest dealer-ship based on drive times, whereas previously those were calculated based on a straight-line “as the crow flies” distance calculation.

“It’s had an impact on our network because we’ve recalculated the network plan based on the drive-time knowledge we have of our customers, which has been invaluable really,” says Bury. “When we’re making decisions like that, that affect people’s businesses and livelihoods, it’s very important that we have the right information and trust the data and results of the analysis that we’re using.”

“�When�we’re�making�decisions�like�that,�that�affect�peoples’�businesses�and�livelihoods,�it’s�very�important�that�we�have��the�right�information.”

— aNdreW Bury Network Planning Manager, Peugeot-citroen uK


V i s u a l B a s i c s

One of the key advantages of dedicated location intelligence tools is their capability to visually represent and manipulate data. According to Ventana Research, more than three in five organizations identified geographic representation of data, visual metrics associated with locations on a map, and selecting and analyzing locations on a map as important capabilities for effective location analytics.1

The value in this lies largely in the ability of geospatial representations to make previously unseen relationships clear. And by seeing those relationships clearly, users can make better decisions. Location intelligence tools allow users to “interpret disparate and complex data through simple, effective visualizations,” write Anesa Diaz-Uda and Joe Leinbach in “The Power of Zoom,” a De-loitte report on the transformative properties of location intelligence for government services.2

“The context of place creates an instant connection among layers of data, helping agencies zoom in on the details that matter, or zoom out to add context…and better understand the challenges unique to a specific place.”

While Diaz-Uda and Leinbach’s report specifically deals with location intelligence in relation to government and local authorities, the same benefits are available to commerce and industry. In insurance, for example, the ability to zoom into territories, counties, streets and specific properties has been extremely valuable for underwriters at James River Insurance Company.

“Being able to take, for instance, a property portfolio where you may have hundreds of thousands of little push-pin dots that represent the individual locations and policies, and being able to turn those dots into heat maps, underwriter territory maps, color-coded broker territories, or segmenting them by individual characteristics within the database,” says Jonathan Weisenberger, data and analytics manager at James River Insurance Company. “That’s all made much easier by being able to visualize it in a map, [rather] than trying to keep that in a database and summarizing it via queries and doing the visualization in Excel.”

There’s another benefit to consider: when data is represented visually, especially in a format as commonly understood as maps, it is more widely accessible. Visualizing data geospatially helps create understanding of the factors affecting an organization in a more relatable way than spreadsheets or specialist GIS tools. As Pitney Bowes’s Buckley points out, you may never get people from non-technical departments to use highly specialized tools, so information needs to be provided through a familiar user interface. “If I’m looking at a simple grid of data and then I can put that data onto a map—that gives an alternate view of what might be happening in your business and among your customer base.”

1 (2013). Business Trends in Location Analytics: Exploring the Impact of Geographic Context on Business Processes (Benchmark research). Ventana Research, San Ramon, CA.

2 Diaz-Uda, A., & Leinbach, J. (2013). The Power of Zoom: Transforming government through location intelligence. Retrieved October 14, 2014, from http://j.mp/1GnFYne


Creating Competitive AdvantageIt perhaps is not surprising that the desire to realize competitive advantage is high on the list of hoped-for outcomes by businesses investing in location intelligence, according to Ventana Research.3 In a commercial environment where price is less and less relevant as a differentiator, businesses do need to find ways to improve their responses to market conditions and their customers’ experiences in order to earn competitive advantage. And location intelligence is increasingly recognized as a tool to reveal and create those opportunities to innovate.

“There are just so many examples where you can see reference to location that gives you the ability to compete more effectively in the marketplace or go after market areas not addressed,” says Ventana Research’s Mark Smith. “You’re able to actually see there is market opportunity in certain geographic areas where you can place new stores or service people, respond to customers in the field. All those are really only possible with reference to location intelligence.”

While location intelligence tools are often designed to help solve a particular problem or issue, businesses

are innovating new ways to apply the intelligence to secondary issues, and in doing so, often open up new efficiencies or ways to compete.

In the Peugeot-Citroen case study (see page 5), the automaker not only solved its immediate problem around decision making for outlet site location, but it has also used the same drive-time data to strengthen its fleet management bids. As Peugeot-Citroen’s Andrew Bury says, “When people have come to us asking for help, we’ve found another use for [the intelligence].”

And at Barnsley Council (see page 16), Riley Marsden, systems manager, says opening access to internal location intelligence systems to all staff has revealed a number of originally unforeseen uses for the data. “You’re increasing the number of people who can access data and who are aware of location-based data,” he says. “The more people know about it, the more they’ll come to you with ideas and projects of how they can improve their ways of working by using it.”

3 (2013). Business Trends in Location Analytics: Exploring the Impact of Geographic Context on Business Processes (Benchmark research). Ventana Research, San Ramon, CA.


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James river insuranCe ComPanyCase Study

There are few industries where location is as important a component to understand as in the insurance industry. Typical geopolitical boundaries, such as zip codes or county lines, mean little in the face of disasters, but even without the upheaval of a catastrophic event, geophysical attributes are critical to the decision of whether or not to offer a particular policy in a particular location.

Jonathan Weisenberger, data and analytics manager at James River Insurance Company (JRIC), a Richmond, Virginia-based property and casualty insurance company, says location is hugely important for the insurance industry to manage risk exposure. Exposure can be defined a number of ways, he says, from the property or individual being insured, to the marketplace and pricing competition, or a concentration of risk.

“It’s the idea that it’s not just the ‘where’—meaning the physical premises—but it could be the ‘where’ meaning the marketplace and how pricing affects you in that area,” he says.

“Even though you may not think there’s a location component to your risk, there actually is. And it’s understanding how your risk exists within a market. Understanding how that risk localizes can be beneficial, both from pricing the risk to get the business, to servicing the risk while you have it, to being responsive while managing claims and understanding how losses may be correlated.”

“�Even�though�you�may�not�think�there’s�a�location��component�to�your�risk,�there�actually�is.”

— JoNathaN WeIseNBerGer data and analytics Manager, James river Insurance company

With 12 underwriting divisions issuing policies across all 50 U.S. states, JRIC well understood the need to factor location into its underwriting. Several years ago it implemented location intelligence software to improve these decisions both in the understanding of location-related risk factors attached to a particular policy, and of how the concentration of risk in a specific area would affect its overall portfolio and exposure burden. And by layering in National Oceanic and Atmospheric Administration weather data, for example, location intelligence can also help JRIC predict how actual events are likely to affect policyholders, in real time, and mobilize claims personnel accordingly.

Weisenberger identifies three main benefits of upgrading the location capabilities of the organization. First, all data has been geocoded with information on the location characteristics of a particular property—occupancy, construction, age, height, etc.—allowing better underwriting decisions to be made.

Having this information stored in a geocoded database allows the flow of information to go easily both ways between broker and insurance company, and between insurance company and adjuster, for use in the field.

Another important factor is in assessing where there are high concentrations of risk. In the past, that was deter-mined by zip code and county boundaries, but Weisenberger points out that hurricanes don’t stop at the county line, and neither should risk exposure analysis.

“If you have a lot of risks on one side of the county line and a lot of risks on the other side of the county line, you have a lot of risk in a very small area,” he says.


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James river insuranCe ComPany c o n t .Case Study

“Being able to pull loss information out of the catastrophe model vendor and put it into a more dynamic GIS solution, like MapInfo, allows us to get a better feel for where our concentration of theoretical losses are relative to our portfolio, and then also get a better understanding of incremental addition to that portfolio.”

The third major way location intelligence has improved processes at JRIC has been in its ability to predict and respond to disasters, in real time. By analyzing the areas potentially affected by a specific event, JRIC is able to deploy claims adjusters faster and know when to hire local adjusters to supplement the force. And by doing so, it is able to differentiate itself in the marketplace.

“If you know where things are going to happen relative to your own portfolio, that really helps you be of service to your customers,” says Weisenberger. “Being responsive in the face of a claim is where you really get your reputation. Otherwise, you’re selling a commodity. It’s just price, and then coverage differences are unknown until they’re called into question. Being out there helps us.”

“�Being�responsive�in�the�face�of�a�claim�is�where��you�really�get�your�reputation.�Otherwise,�you’re�selling��a�commodity.�It’s�just�price,�and�then�coverage�differences��are�unknown�until�they’re�called�into�question.��Being�out�there�helps�us.”

— JoNathaN WeIseNBerGer data and analytics Manager, James river Insurance company

Reinsurance provides coverage should an insurance company be faced with mass payouts at one time, as would happen in the case of a major disaster or terrorism. To manage the costs of reinsurance treaties, companies like JRIC need to pay close attention to how geographically concentrated their policy portfolio is.

Weisenberger says managing the aggregation of risk is as important as managing theoretical loss potential. But that’s been another area where location intelligence has been able to prove its value for JRIC, because the mapping tools track its concentration of risk historically as well as spatially.

“At any point in time, if one of our reinsurance partners wants to call up and say, ‘Hey, you gave me this report back in July and it’s now September, I want to see what it looks like now,’ we can provide that information in a matter of days,” Weisenberger says.

“And that’s helpful to us because it can lead to a better cost for reinsurance, which can be a pretty significant expense when it comes to managing property insurance.”


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W i l l i sCase Study

With its origins dating back to 1828, global risk adviser and re/insurance broker Willis knows a thing or two about catastrophe: it was the insurance broker for the Titanic and the reinsurance broker for the Hindenberg. It has also brokered insurance for such notable vehicles as the Lunar Rover and the first commercial service of the Airbus A380. As a global company led by offices in New York and London, with satellites from Mumbai to Nashville, and covering risks in more than 150 countries, Willis needs to have trust and control of its catastrophe modeling.

Willis’s reinsurance branch, Willis Re, was the first part of the company to use location intelligence in catastrophe modeling. At that time, it wanted a tool to provide faster and more precise assessments of potential client losses based on their geographic exposure. Part of that required greater control over the geocoding capabilities of the software used, so it moved from a vendor model to an internal, neutral geocoding model. “Because we develop our own [catastrophe] models and our own analytics, we need to go beyond the constraints of a vendor platform to develop our own view,” says Sharon Palmer, head of spatial analytics at Willis.

Palmer says having an internal geocoding functionality not only dramatically increased the capability of Willis’s models to handle location coding—from somewhere around 50 to half a million locations—but it increased the transparency of the modeling, too.

“If you rely on geocoding functionality within a vendor model, it’s a black box. You’re less aware of what they’re bringing back to you,” she says.

Having an internal platform has seen benefits in the time it takes to geocode data, too. Workflows that used to take eight hours to geocode can now be completed in an hour.

The success of location intelligence at Willis Re has seen the function broaden to be used group-wide, and Palmer says her team now supports the wider organization as a whole. “Since we’ve centralized and created our platform and our own products for the group, it’s been easier then to put it into other applications that we find useful throughout the business.”

With respect to Willis’s commercial clients, Palmer says, while the size of those clients’ risk isn’t the same, they still have the same need to understand it. “They need to get down to that rooftop level and understand that location. They have a different appetite for location intelligence [from reinsurance clients], but they also have similar needs.”

Although the reinsurance side of the business is fairly familiar and established with location intelligence usage, Palmer says its introduction to the wider business may yield new uses in other areas. “There is a great trend for merging socio-economics and population demographics with location. It’s slightly outside of the natural catastrophe sphere, but all those types of things are emerging areas that I think we will be exploring in the future.”


W h y N o t G o o g l e ?

Consumer-level mapping applications, such as Google and Bing, may be in part responsible for driving the uptake of location intelligence in business, but on the whole these services do not offer the level of precision and accuracy typically required by enterprises.

Location intelligence software vendors offer businesses several advantages over the piece- meal DIY-approach. One is the ability to integrate technology with existing systems, especially business intelligence software. Professional vendors offer flexibility in how to deploy technology, whether as standalone platforms or integrated into their clients’ own technology.

Often free or low-cost consumer applications simply do not meet the needs of businesses nor provide the type of precision in functionality or accuracy in results needed by professional organizations. “We’re dealing with an entirely different level of accuracy here,” says Riley Marsden, systems manager at Barnsley Council, where location intelligence tools have been implemented to public-facing communications as well as internal operational and policy decision making efforts. “When internal staff are dealing with mapping, they need to do it on a far more granular level than something like Google is ever going to provide. It’s a whole new ball game of accuracy.”


Consumerization of Location IntelligenceMaps have been used to represent information throughout the ages, but the roots of location intelligence are most often traced back to London in 1854. During the cholera epidemic in the city that year, John Snow was able to trace the source of infection to a single contaminated city water pump. In so doing, he upended the conventional wisdom of the time about how cholera was spread. His master-stroke? Overlaying a map of the area with water pump locations and sites of reported cases to reveal the underlying relationships. The same principle— the layering of information on a map to derive information from geospatial relationships—continues to act as the core of location intelligence today.

As technology has progressed, so have the tools. But until recently those tools had remained reserved for use by geographers, government and military specialists. Even so, the capability to derive insight, especially business insight, from geographic data representations was limited.

What’s changed in recent years, particularly since the latter half of the 2000s, is that consumer mapping applications, cloud technologies and Software-as-a-Service delivery methods have not only brought enterprise-level location technology within the realms of affordability for a wide range of businesses, but they have also increased familiarity with the principles of GIS for non-specialist users. In parallel, usability has increased with the development of com-prehensive user interfacing. With the rise of Google Earth and mobile mapping applications, consumers

are increasingly skilled in using maps and layering information to make decisions in their own every-day lives.

“The consumer marketplace has driven more of the business demand for this segment than anything else,” says Ventana Research’s Smith.

“The demand from the business side has increased as people are able to talk to their smartphones or find out, in two clicks, where they are and what stores are around them,” he says. “They are able to do things that they have high expectations they can do in the business workplace.”

In turn, software vendors are increasingly gearing spatial analytics products toward everyday business professionals. The resulting offerings feature intuitive interfaces, live editing capabilities and significantly reduced training timeframes for new users.

At telecommunications provider Telenor Pakistan (see page 4), the ease-of-use of the tools has opened up their deployment in a wide number of situ-ations. “There are numerous ways to use the tool,” explains Telenor Pakistan’s Sami Uddin Ahmad, director business intelligence and data warehouse. “A sales team executive can retrieve location-specific data by simply drawing a circle on the map. Another common practice is to click on a franchise shown on the map, and the tool retrieves its specific targets, progress and sales trends.”


4 (2013). Business Trends in Location Analytics: Exploring the Impact of Geographic Context on Business Processes (Benchmark Research). Ventana Research, San Ramon, CA.

This same mechanism can be used for cell sites, regional outlines and surrounding areas—and allows comparisons to be drawn among them. Another feature is route planning, which Ahmad says maps the optimum route for teams in the field to plan visits to a number of franchises. “It works similarly to Google maps on a smartphone, but having TP-specific land-marks like franchises and cell sites adds more value to the function.”

Ventana Research’s work shows that the tools used for location analytics heavily influence how well organizations view the practice. For example, those

that rely predominantly on spreadsheets, instead of dedicated location or business analytics tools, are least often satisfied with outcomes. Conversely, users of dedicated location analytics tools report significant improvement in the results of their activities and processes more than twice as often as those that use only business intelligence.4

Research like this underscores the need not only for location analysis in business, but also for tools that make the intelligence accessible and usable through-out an organization.


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B a r n s l e y C o u n C i lCase Study

Local government operations and location are intrinsically linked. Infrastructure, zoning, waste collection routes, bus routes, street lighting, public health and service delivery—nearly every function of government has a location component to it. On top of that, most authorities also have obligations for transparency and accountability to residents for the works they undertake. It is perhaps no surprise then that local and regional authorities have been quick to add location intelligence to their operations.

Barnsley Council in the U.K. is a metropolitan borough council in South Yorkshire, with around 225,000 residents and more than 3,500 staff. As a local planning authority, it’s responsible for a full range of functions, such as building controls, infrastructure, planning consent, children’s and adult services, etc. Like most local body authorities in the U.K. over the last few years, it’s facing significant budgetary pressure to cut costs and enable the public to self-serve more of their needs.

The council built on to its existing location intelligence platform around 2010 by developing Barnsley Interactive Maps and MyProperty. These are public-facing mapping functions that provide detail on information both with borough-wide relevancy—planning consents, road works, public health providers and the like—as well as specific to a particular property, such as the nearest schools, or bus stops and timetables. Among the outcomes of these platforms have been cost efficiencies, but Systems Manager Riley Marsden says it was the self-service aspect, not cost, that was the initial driver for these initiatives.

While residents may have access to around 50 layers of data on the interactive maps, the staff has access to as much as 10 times that amount internally. And the uses of that data filters throughout the organization to sup-port both operational and policy decision making. As Marsden says, “Operationally, we would be using location data in pretty much every department throughout the organization.” There are some key ways location data is used internally, and those mainly revolve around decision making. Typically, that involves things such as route optimization to minimize the numbers of vehicles and amount of fuel used, or to support the planning consent-granting process. Through the interactive maps portal, residents are also able to view proposed changes to the local plan and offer input on the process.

“�Operationally,�we�would�be�using�location�data�in��pretty�much�every�department�throughout�the�organization.”

— rILey MarsdeN systems Manager, Bardsley council


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B a r n s l e y C o u n C i l c o n t .Case Study

But in a climate where budget pressure is high, a major recent project has involved determining where services can be cut or buildings closed with the least impact on the affected population. That process takes into account not only the location of assets, but also the demographics around them, bus routes and travel times, for example.

In the past, Barnsley Council endeavored to provide much of the same information to residents as it does now through the interactive maps portal, but due to technological restrictions it was limited to publishing static maps online or providing PDFs on request. Apart from being labor intensive, providing information to the public in this way suffered from being out of date soon after publishing. This was especially the case with constantly changing data like planning applications. Establishing the interactive maps has eliminated these issues, as maps are available on demand and regularly updated from the relevant databases.

Barnsley Council has also been able to realize additional cost savings by reducing the number of desktop software licenses and replacing them with Software-as-a-Service access. This browser-based access works on a permission basis, easily controlling which staff members have access to deeper functionality, while still allowing the tools to be used widely. Marsden says this has reduced licensing costs by around a third.

“Any staff member within the organization can use the system now—it’s available on any desktop,” he says. “Essentially, you’re widening the base and widening the reach of who we can pass this data on to, but the license cost for the system is one-off.”

“�Any�staff�member�within�the�organization�can�use��the�system�now—it’s�available�on�any�desktop.”

— rILey MarsdeN systems Manager, Bardsley council

Another benefit the council has realized is the staff-wide interaction with location intelligence. Marsden says that previously GIS were considered a niche responsibility housed within the IT department. That has since changed.

“As people became aware of the system, people who would never have used mapping systems within the organization before were starting to use it,” says Marsden. “They will very often come to us and say ‘We’d like to see this data set, and this data set, and we’d like to use it for X, Y and Z business process.’” A recent library strategy review, for example, used location intelligence data that Marsden says was a direct result of senior managers recognizing the new capabilities that the location intelligence tools brought to the organization.


By supplementing traditional business intelligence capabilities with location intelligence, new ways of looking at existing data are revealed. These lenses empower decision makers with precise information, able to be parsed quickly and accurately, that can be trusted by all stakeholders. Location intelligence also reveals competitive insights, ways to improve customer experience or speed to market, for example, helping organizations compete on points other than price. And democratized access to the data offers opportunities for other benefits to be realized, whether strengthening bids, improving strategy or finding opportunities to reduce costs.

It is through the geographic visual representation of business data that previously unseen relationships are revealed. The implications for the ways in which these relationships can be used to gain competitive insight are only just beginning to be realized.

ConclusionHistorically reserved for highly specialized uses, location intelligence is coming into its own, thanks in part to the driver of consumer location applications that familiarize users with its basic principles. Organizations in both the public and private sectors are using location to identify relationships between customer and operational data and the geography of their interests.

L o c a t i o n I n t e l l i g e n c e f r o m P i t n e y B o w e s

Pitney Bowes has developed the most intuitive Location Intelligence

GIS suite and comprehensive global data catalogue. These easy-to-use

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For more information go to pitneybowes.com.


AcknowledgmentsPitney Bowes and Forbes Insights would like to thank the following individuals for their time and expertise:

Sami Uddin Ahmad, Director Business Intelligence and Data Warehouse, Telenor Pakistan

Andrew Bury, Network Planning Manager, Peugeot-Citroen UK

Riley Marsden, Systems Manager, Barnsley Council, UK

Sharon Palmer, Head of Spatial Analytics, Willis

Malik Faisal Qayyum, Director Customer Value Management and Analytics, Telenor Pakistan

Mark Smith, CEO and Chief Research Officer, Ventana Research

Jonathan Weisenberger, Data and Analytics Manager, James River Insurance Company

P I T N E Y B O W E S

James Buckley, SVP of Location Intelligence

Richard Rollins, Director, Global Product Marketing – Location Intelligence



NOTES

aBouT ForBes insiGhTsForbes Insights is the strategic research and thought leadership practice of Forbes Media, publisher of Forbes magazine and Forbes.com, whose combined media properties reach nearly 75 million business decision makers worldwide on a monthly basis. taking advantage of a proprietary database of senior-level executives in the Forbes community, Forbes Insights conducts research on a host of topics of interest to c-level executives, senior marketing professionals, small business owners and those who aspire to positions of leadership, as well as providing deep insights into issues and trends surrounding wealth creation and wealth management.

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Brenna SnidermanseNIor dIrector

Kasia MorenoedItorIaL dIrector

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Lawrence BowdenMaNaGer, eMea

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