Where Your Business Intelligence is Missing Information Add Location to Reveal a More Complete Picture

Transcription

1 1 Where Your Business Intelligence is Missing Information Add Location to Reveal a More Complete Picture Welcome Executive Brief How Two Businesses Use Location Analytics Location Analytics: The Next Big Step in Business Analysis Gartner Says: Location Intelligence is Expanding the Scope of BI Esri Location Analytics Solution Examples About Esri Featuring research from

2 2 Welcome Dear Friends: The demand for geographic business intelligence and analytic solutions has increased significantly. Businesses are looking for insight into the factors that contribute to their success or failure. This is driving the integration of two complementary enterprise solutions, business intelligence (BI) and geographic information system (GIS) technology. Esri Location Analytics solutions easily merge geography with existing business systems and processes to enable better understanding of your data and where things are occurring. As executives seek new ways to improve business outcomes, many are finding that location analytics results in a more complete and realistic analysis of their data than business intelligence systems alone. Location analytics provides a view of the relationship between things, like the buying behavior of consumers or the growth potential of a trade area. It lets you analyze data through smart maps, to discover patterns and trends that would have been easily overlooked with traditional business intelligence tables and charts. In this report, you ll discover real-world examples of how public and private organizations are using location analytics for better business outcomes. We look forward to helping you take the next step with location analytics. Warm regards, Jack Dangermond President and Founder

3 3 Executive Brief How Two Businesses Use Location Analytics These stories describe how two businesses benefit from using location analytics. Miele Turns to Esri to Drive Growth shows how location analytics resulted in a 70 percent sales increase for one dealer. Restaurants Use Esri Location Analytics to Optimize Site Locations shows how restaurant giants Arby s, Wendy s and Culver s use location analytics to improve market analyses and site selection. Location Analytics: The Next Big Step in Business Analysis discusses the growing use of business analytics and the value of adding geographic location to business data and mapping it. Esri Location Analytics Solution Examples discusses the market dynamics that are driving integration of two highly complementary enterprise software solutions: business intelligence (BI) and geographic information system (GIS). This paper examines how location analytics leverages corporate data and equips knowledge workers with insights that drive sound business decisions, address common integration challenges, and presents solution examples. Taking the Next Step The stories you read in this report will help you discover where location analytics can improve your business processes. We invite you to learn more from our website or by requesting a call from our location analytics experts. Visit esri.com/locationanalytics. Gartner Says Location Intelligence Is Expanding the Scope of BI, by Gartner analyst Andreas Bitterer, discusses the importance of location in a Business Intelligence environment as well as examples of significant benefits of location analytics.

4 4 How Two Businesses Use Location Analytics Miele Turns to Esri to Drive Growth Location Analytics Propels Orange County, California, Dealer to 70 Percent Increase Miele, Inc., a premium provider of domestic appliances and commercial machines, has streamlined its distribution network in the United States using Esri Location Analytics technology. Esri s software and data are used to better understand which markets are best for the company s highquality products. By focusing on specific segments of the marketplace, Miele can pinpoint customers and help its dealers be more successful. GIS has been an important tool to help us navigate the American economy in the last few years, said Matt Kueny, senior business analyst in sales at Miele. Just because someone might have the income to spend on one of our products doesn t necessarily mean they are a realistic target for our brand based on other lifestyle variables. Using Esri technology, we have been able to better analyze patterns and share this information with our dealer network so we can get the needed item to the customer. Using location analytics from Esri, Miele was able to better gauge the health of its dealer network and ensure that products were available in the most appropriate market segments. Location analytics helps Miele communicate key marketing activities to its dealers and work in a collaborative environment. By being able to visualize and analyze sales information and business data through maps, one Orange County, California, Miele dealer achieved a 70 percent growth in sales. Miele has done an astounding job of responding to a changing and highly competitive marketplace by applying technology and expertise in an innovative manner, said Simon Thompson, director of commercial solutions at Esri. Miele really is inspirational in that it has helped its dealers grow their businesses in an environment where many businesses are failing. Miele continues to adapt to its customers evolving retail sophistication and help its dealers keep up their revenue by applying location analysis to online shopping. By tracking search engine hits in our gap markets, we are able to geotarget the nearest dealer to that Internet shopper, said Kueny. We are making the shopping experience more convenient by helping the customer find the nearest product. It s all about customer service. Restaurants Use Esri Location Analytics to Optimize Site Locations More and more restaurant and franchise owners are discovering the power of GIS to find the best sites for their restaurants. Owners of successful franchises have relied on GIS technology to discern markets for many years. The technology provides tools that help organize information by using location as the common identifier for data. By understanding where franchises, the competition, and customers are located, franchisors can make informed decisions, improve communication, and share their knowledge with others. Better Trade Area Assessment Arby s Restaurant Group, Inc., the second-largest quick-service sandwich chain in the United States, uses the Esri Location Analytics solution Business Analyst TM to guide business decisions. Arby s, based in Atlanta, Georgia, uses the solution to more accurately assess restaurants and trade areas for projects such as growing the chain and remodeling or relocating restaurants. Business Analyst, merges Esri s vast demographic and business data with detailed maps and allows organizations like Arby s to perform spatial analysis. Using the solution, Arby s can now update the locations of its restaurants and business development activity on designated market area (DMA) maps, which describe the activity taking place in individual markets. Since Business Analyst can be easily deployed across the enterprise as a web-based solution, on desktops, and even from iphones and ipads, Arby s can make these maps accessible to its staff. Development teams working in the field are able to quickly access the maps and easily discover the information they need through the Arby s intranet. This quick ability to synthesize data has made it possible for the teams to more easily and quickly monitor the business climate around each restaurant. This provides an opportunity for the organization to model different market scenarios to better serve existing customers and attract new ones.

5 5 Using one-platform instead of several different solutions, as Arby s has done in the past, helps them better manage and analyze business data. With an enterprise system, Arby s can scale to meet the changing business landscape with tools that make it competitive in the marketplace. Esri s Business Analyst has saved our GIS analyst countless hours and has had a positive impact on the Business Development department, said Dave Conklin, senior vice president, Business Development, Arby s. Site Selection and Predictive Modeling Wendy s, the world s third-largest quick-service hamburger chain, is integrating Esri Location Analytics with the restaurant s corporate IT systems. The web-based solution will be part of the company s reporting system for new locations, assisting in site selection and market analysis. Demographic data and location analytics are critical components when making investment decisions to build new restaurants, said Dennis Hill, vice president, real estate. With Business Analyst, everything we need including mapping, analytics, and modeling can be done on one platform that is scalable across our organization. The The Wendy s chain includes more than 6,500 franchise and company-operated restaurants in the United States and 27 countries and US territories worldwide. The new location analytics solution replaces a current system in use at Wendy s. Implementation was completed by Esri partner GIS, Inc., located in Birmingham, Alabama. The new solution includes server GIS applications, Esri demographics data, and customized analytics developed specifically by GIS, Inc., to streamline and enhance the Wendy s site screening and market assessment process. Staff can easily view sales records, customized demographics, and other business reports on existing restaurants through an intuitive mapping interface. The system also enables Wendy s to perform predictive modeling and assess potential restaurant cannibalization for new and existing sites by simply clicking on the map. looking at possible new sites. The first Culver s restaurant opened in Cofounders Craig Culver and his wife, Lea, oversee almost 500 restaurants in 20 states through Culver Franchising System, Inc. Although the success of Culver s stems a great deal from the delicious food it serves, the company also relies on Esri Location Analytics software and data to ensure the locations its new franchisees are selecting will be successful. Using location analytics, new sites can be easily compared and contrasted by analyzing the demographics of existing restaurants, then pinpointing new areas that are similar. We chose Esri because they have the best information available for what we need to know, says Dave O Brien, real estate manager at Culver s. Using Business Analyst, we are able to easily compare and contrast new sites by analyzing the demographics of our existing restaurants and then pinpointing new areas that are similar. O Brien uses a combination of software for an in-depth view of the market at analysts desks, providing an easy way for anyone in the company to incorporate the information they find into the tools they need to do business. Business Analyst, including the segmentation module, provides in-depth customer analytics. Business Analyst Online SM is used for creating boardroom-quality maps and easy-to-understand reports that are used by the franchise partners. We are a family company, and this is apparent in all our daily efforts, stresses O Brien. We want our franchise partners to succeed. Without them- the local owners and operators in their own communities and hometowns-we would not exist. Today, GIS is seen as a strategic business solution that helps businesses continue to grow. The company is expanding into the state of Florida, a new area for development. GIS is a tool to help us make even better decisions as we continue to expand, says O Brien. GIS doesn t replace anything we have now, including people. Instead, the software has become a necessary tool that complements our existing business process. Building a Better Franchise With almost 500 restaurants that stretch from Wisconsin s heartland east to South Carolina into Texas and west to Utah, Culver s is continually For more information, visit esri.com/locationanalytics.

6 6 Location Analytics: The Next Big Step in Business Analysis by Chris Ovens, Esri Director of Location Analytics Business Today it seems that no conversation about information technology (IT) is complete without a discussion about big data, the cloud, or the consumerization of IT. However, arguably, the most impactful trend to hit IT has been analytics both in media buzz and in corporate investment. Since the publication of Thomas Davenport and Jeanne Harris s book Competing on Analytics: The New Science of Winning in 2007, both private- and public-sector organizations have been sold on the notion that they need to leverage analytics on their data to gain insight and drive decision making. Business analytics has now become pervasive in most large public- and private-sector organizations. Current estimates are that 97 percent of large companies leverage analytics, with over 100 million users worldwide. Users come from across all functional areas, from executives to line operations and from managers to knowledge workers. These analytic systems basically turn an organization s data into actionable information by discovering and illustrating patterns, trends, and relationships in tabular business data. Typical output is in the form of statistical reports that summarize tabular data and sometimes display this data in graphs and charts. Analytics are often implemented as independent business intelligence (BI) systems but can also be part of larger enterprise systems, like customer relationship, enterprise asset, and resource management systems. Business Analytics and Geography There is a growing realization that by adding geographic location to business data and mapping it, organizations can dramatically enhance their insights into tabular data. Maps and spatial analytics provide a whole new context that is simply not possible with tables and charts. This context can almost immediately help users discover new understandings and more effectively communicate and collaborate using maps as a common language. While this geographic aspect has been largely absent from business analytics solutions, many organizations would like to incorporate it into their operations. FIGURE 1 Esri Maps for IBM Cognos highlights regional performance for an insurance company.

7 7 For years, a few progressive organizations have integrated maps and spatial analytics with their business data using GIS technology and netted powerful results. This approach has not become widespread because of the expense of custom integration with enterprise systems and because the capabilities of GIS are beyond the technical knowledge of the business analytics users. A second approach has been the use of consumer web mapping technologies. This has likewise been problematic because of both difficulties with enterprise integration and a fundamental lack of needed capabilities. FIGURE 2 Esri Location Analytics brings the power of the Esri platform to existing business systems. Location Analytics The Missing Perspective Industry analysts are suggesting that the demand for mapping and geographic intelligence is emerging as an important segment of the business analytics software category. This interest is reflected in the fact that spatial visualization is one of Deloitte s top 10 technology priorities of This new segment is being called location analytics and is focused on thematic mapping and spatial analysis for the world of business analytics. This solution space involves simple mapping and spatial analysis capabilities that work directly with business analytics packages and enterprise data systems with no custom integration efforts. Esri Location Analytics Esri Maps Esri has recently built a simple and powerful solution for the location analytics space known as Esri Maps. This product complements and extends the leading business analytics products, such as Cognos, MicroStrategy, SharePoint, and others. Esri Maps supports easy-to-use mapping and spatial analytics. These capabilities are complemented with a full library of geographic content for enrichment that makes Esri Maps simple to use and inexpensive, and users can immediately make maps of data contained in business analytics systems. Esri s direct integration with leading business analytics platforms means there is no cost for integration or ongoing maintenance. Also, because it is built using ArcGIS (Esri s core technology platform), it can provide powerful GIS analytic capabilities and make use of other GIS investments in an organization. Specific capabilities include the following: Mapping visualization: Point, color-coded, temporal, clustered, heat maps Spatial analytics: Bidirectional interaction, map filtering, proximity, custom area (drive time, trade area), and advanced analysis tools (geoprocessing) Geographic information enrichment: Basemaps, imagery, demographics, consumer and lifestyle data, environment and weather, social media, business, etc. Esri supports multiple business analytics platforms. For example, Esri Maps for IBM Cognos delivers maps, spatial analytics, and geographic information to the IBM Cognos BI environment. Similarly, Esri Maps for Office, a feature of ArcGIS SM Online, delivers complete location analytics capabilities to Microsoft Office users. The Esri technology augments and extends leading enterprise technology, like BI, customer relationship management, and enterprise asset management, providing mapping, spatial analytics, and geographic data enrichment in a complementary and nondisruptive manner. Users of these systems benefit

8 8 from enhanced insight into their business data without leaving the business system or changing their information workflow making these systems more impactful and effective for the users, as well as the business at large. FIGURE 3 Creating interactive maps inside existing business systems can help users see patterns that graphs and charts cannot reveal. Enterprise Implications of Location Analytics While Esri Maps provides a location analytics solution for business analysts, this capability is also part of a larger web mapping platform (ArcGIS Online arcgis. com) that provides enterprise mapping and geographic analysis services for an entire organization. ArcGIS is used to share, visualize, and analyze all sorts of organization data using geography as a common framework. This system can also dynamically integrate (mash up) all sorts of data, including data that has been mapped using location analytics. When integrated with the growing volume of geospatially referenced data available on the web, whole new insights begin to emerge. ArcGIS Online is helping enterprises extend the concepts of simple location analytics into whole new areas of information sharing; communication; collaboration; and, ultimately, better decisions. In the private sector, this capability is helping companies be FIGURE 4 Business intelligence dashboards are enhanced with interactive maps. more efficient and create a competitive advantage. In the public sector, it means more effective, transparent, and efficient services. Location Analytics and Enterprise GIS The Esri Location Analytics platform is designed for business analysts who spend much of their day using tools such as BI and Excel to see patterns and relationships in transaction data. They want selfservice mapping and simple spatial analytics that are delivered within the analytic systems they use every day. These users will drive the proliferation of location analytics across the organization. GIS professionals are in a unique position to help these analysts. They are already creating useful frameworks, data, and map layers that let non-gis professionals, knowledge workers, and anyone in the organization start to use location and geography to make better business decisions. They can also support this new community and help integrate and leverage their capabilities with other enterprise data to maximize the positive impact. The integration of mapping and geographic intelligence across the entire enterprise will reinforce and leverage the mission of GIS professionals, particularly in transforming the way organizations leverage geographic knowledge. For more information, visit esri.com/locationanalytics.

9 9 Gartner Says: Location Intelligence Is Expanding the Scope of BI Most business intelligence initiatives lack a location data component, despite most managed entities in a BI environment possessing a location (customer, supplier, vehicle, device). BI managers need to grasp the importance of location and leverage the location context awareness of mobile devices. Key Challenges Virtually all business intelligence (BI) initiatives all but ignore location information. Geocoding of physical elements is rarely within the scope of BI deployments. Many organizations lack the appropriate skills to leverage spatial data. The location awareness of modern mobile devices is not pervasively used as additional information in a decision-making context. Recommendations Learn about spatial data. Identify three moving entities that have a high impact on the organization because of their location. Investigate three business processes that could be improved if location information was available. Conduct three brainstorming sessions with mobile users to discover location-aware scenarios. Strategic Planning Assumption(s) By 2013, 33% of BI functionality will be consumed via handheld devices. Introduction Three important things are missing from virtually every BI implementation; care to take a guess? The answer is borrowed from real estate agents when they pinpoint the three most important aspects of real estate, Location, location, location. In the greater scheme of things, there is hardly any BI environment that has a comprehensive coverage of location data. At best, postal addresses of customers, suppliers or facilities are stored, but proper geocoding, analysis of location information, or inclusion of geographical information in the decision process are really the exception. This fact is rather surprising, because pretty much everything an organization does whether it s buying, selling, manufacturing, assembling, building, shipping, servicing or contracting is in one way or another associated with a location. Even an e-commerce purchase transaction from an online retailer, with nothing moving anywhere, has (potentially) half a dozen location elements that may be worthwhile storing and analyzing: the physical location of the customer s home address, the location of the requested shipping address, the location of the server from which the transaction was executed, the location of the nearest warehouse, the distance to the nearest retail store, the location of a delivery truck carrying the ordered items, the location of the container with the backordered items, to name a few. Analysis In virtually all BI implementations today, location information isn t ignored, but it is pretty much used exclusively as a descriptive attribute or very coarse-grained and often static dimension. Even though we ve been storing a customer s street address, city or state all of which represent a certain location this information alone isn t really enabling organizations to derive a lot of insight. We have always been able to cut data by location (for example, show the sales for this store or this state), and we can categorize the location of objects (aisle or window, end cap or shelf), but this wouldn t qualify as location intelligence. Very little intelligence is derived from database queries that are simply adding up sales figures with conditions such as WHERE STATE= GA or WHERE SHELF= 12 although both state and shelf represent a certain area (or rather a coarse-grained location). More sophisticated use of location information is seen in deployments when the categorical variable of location is turning into a continuous variable, enabling users to track items across locations and over time. This is an important aspect, but the holy grail of location intelligence is really in the analytical capabilities that come with correlation of locations with other things. Location intelligence must be understood as much more than the reporting of location dimensions or tracking of items across locations. The

10 10 additional value comes more from a geographical angle: considering calculated distances between locations, median drive times, market potential polygons considering physical terrain constraints and navigation, optimal locations based on demographics or traffic patterns from GPS data, and other things of that nature. None of those values could be stored in a database s table cell, because they can t be described in a single variable, and that s exactly where location intelligence adds new value to existing BI implementations. Everything Needs to Be Somewhere Obviously, physical items always have a specific location, whether it s known, important or interesting, or not. The exact position of an item, however, can be stored in a variety of ways depending on a so-called reference system. A location can be defined by longitude and latitude, a shelf in an aisle, a postal address, a seat in a row, and many more. Also, a location is not only an attribute in the physical world, but can also be applied to artificial constructs such as contracts or a phone conversation, where the actual location of the contract or phone is not relevant, but is a reference to a certain location. In fact, there may not even be a physical contract on paper, just a record in a database. With the increasing pervasiveness of smartphones and tablets both of which are able to pinpoint the owner s exact location (for example, through cell tower triangulation or GPS) the user of such devices can use location as an additional context. There are many consumer applications, such as Foursquare, AroundMe, or mytaxi, that use the context awareness of the device to provide location-relevant data to the user such as the nearest gas station, hospital, or coffee shop and even show the shortest or fastest route to the selected destination. In a business environment, organizations may want to use location information about certain vehicles, devices, packages or other moving objects, for better tracking and location-dependent decision making. Adding a New Dimension to BI Any BI initiative s initial value proposition is to provide answers through reports, dashboards or scorecards. The more sophisticated BI programs take it a step further by including interactive visualization techniques in the mix. While those tools can also provide answers, more often than not an active user of an interactive visualization tool raises more questions. This is useful as it highlights anomalies, trends or outliers that are worth investigating. At any rate, all of those BI tools are set to answer questions such as: Who? Customer, supplier, agent, driver, clerk What? Product, order, contract, account, item When? Date, time, day, quarter, year, second Why? Out-of-stock, cancellation, overdraft, fraud How? Channel, online, recommendation, behavior Only a very few BI implementations can answer: Where? Person, store, accident, building, vehicle This is where location intelligence comes in, because it adds a new dimension to the traditional lines of questioning of BI. With location intelligence, questions like the following can be asked which are virtually impossible to answer with a basic BI platform: What is the average income of our target group in a 10-mile radius around our planned new store location? How much will the daily commute increase for our employees after our office has moved? How long will it take our service technician to travel from the current location to the next repair job, and are all necessary parts on the vehicle? Where do the top 10% of our customers come from, what are their purchases and what is their distance to the nearest store? What is the median distance of our facilities to the closest water hydrant? Bridging the Different Worlds of BI and Location Intelligence Developers and users of BI solutions have long been familiar with the typical language. When asked about the business case for their BI investments, customers often quote the rather unspecific claim of making better decisions. While the reasoning of better decision making can equally be applied to the geospatial world of

11 11 location intelligence, there is a rather different set of words used to describe the common entities as shown in the examples in Table 1. The artifacts used in the respective technologies, although semantically easy to understand, are typically more difficult to deploy for the untrained user. For example, every BI user knows what a polygon is from high school math, but defining one in proper coordinates, storing it in spatial formats and even leveraging it in a BI application context is not a widespread skill found anywhere in the BI community. Table 1. Language Difference Between BI and Location Intelligence Business Intelligence Reports Cubes Metrics Models Sums, Averages Rows, Columns Location Intelligence Points Curves Polygons Maps BI = business intelligence Source: Gartner (November 2012) Routes, Distances Longitude, Latitude Although most of the terms in the location intelligence world are well understood by everyone (with the possible exception of special artifacts such as TIN, which is short for triangulated irregular networks ), the use of these terms in a decision making context requires deeper understanding of geospatial data, how it is stored, queried, calculated, and so on. Organizations must build up skills in the geospatial domain to even begin to be in a position to leverage the available location information. A good place to start is learning about the various geographic information system vendors in the market, such as Esri or MapInfo. Understanding Reference Systems In order to leverage the geospatial world, users must understand reference systems. There are countless reference systems that we all use on a daily basis, such as seating charts in a theater, floor plans in office buildings, or the gate layout at an airport. However, reference systems can have many other formats, which are neither understood by nor meant for the general user. For example, a company in the oil and gas business may use highly detailed coordinates, such as latitude, longitude, altitude or depth, to define the exact location of a drilling site or an expected oil reservoir. That information is often stored in an XML derivative named Geography Markup Language (GML) and may look like this example: <gml:point gml:id= p21 srsname= urn:ogc:de f:crs:epsg:6:4326 > <gml:coordinates>45.67, </gml:coordinates> </gml:point> where: URN = Uniform Resource Name OGC = Open Geospatial Consortium SRS = Spatial Reference System CRS = Coordinate Reference System EPSG = European Petroleum Survey Group What Is a Map? You know what a map is, of course. In the location intelligence world, users distinguish between many types of maps, from topographical or political maps to geological or many industry-specific maps. Some of those maps are commonly referred to as base maps and work as the backdrop to the actual mapping of certain elements such as buildings, vehicles, seats, wells, sensors, fire hydrants, cell towers, accidents, crime scenes, animal sightings, or any other item or event whose location may be of interest. Although they can often be considered pieces of art, base maps themselves aren t typically all that interesting. The map only comes to life once the location-relevant information is overlaid to give the base map the required context. For example, the well understood seat map of an aircraft in Figure 1, without the color coding, layout indicators and occupancy information, would be of very limited use. Similarly, having only a passenger list with the corresponding seat assignments does not provide the necessary insight for the airline s reservation agent or booked passenger. Only the combination of both the seating chart base map and the overlay from the transactional booking system turns it into a useful map.

12 12 FIGURE 1 Sample Map Seating Chart In another example, a retailer may be interested in the behavior of customers visiting a store: where they go, how long they remain in a certain section or aisle, which store areas are rarely visited, and so on. By continuously scanning the location of individual shopping carts, a sensor network could generate a profile of a store s hotspots by color coding total time spent at a certain location in the store s layout (see Figure 2). Source: Lufthansa FIGURE 2 Sample Map Store Frequentation Figure 1. Sample Map Seating Chart Source: Geobusiness Group The visual frequentation map alone may be quite interesting, but by correlating the spatial information with details about sales figures, revenue, profitability, perishable goods, promotions, or other transactional types of data, the potential insight becomes a real kicker. For example, store managers can analyze why certain products are not selling as expected, because this may have very little to do with price and more to do with the fact that shoppers aren t frequenting the relevant store section. The combination of spatial and transactional insight also enables retailers to optimize a store s layout, placement of products, stock levels, advertising, and more. Bringing Location Use Cases to BI In order to leverage the location information of an organization s data elements, an obvious starting point is the geocoding of customers, suppliers, stores, warehouses and anything with a postal address or other geographical location. Once those locations are known ideally as longitude and latitude pairs organizations can start visualizing those elements, typically by placing pins or other icons on maps. Many BI platforms are able to do this already today, often demonstrated via interactive dashboards on tablet devices where the user can swipe across the map, zoom into a certain region on the map, tap on an icon to see relevant detail information, and similar gesturedriven user interactions. The mapping providers that are typically used by BI platforms are Google Maps and Bing Maps. Through a set of available APIs the BI platforms exchange information with the mapping service, identify the proper location of indicators, generate an interactive widget on the fly and show it on the BI portal. This is relatively trivial, does not require deep technical expertise and, while it may be more visually appealing than a bland data grid or piechart, the extracted insight can be equally limited.

13 13 Far more interesting use cases in location intelligence go beyond the mere positioning of elements on maps to, for example, calculate distances between two points on a map. Of course, the simple option would be to draw a straight line between the two locations (that is, as the crow flies ) so that distance would only be relevant if someone was traveling in a helicopter. In the real world, where most people and goods travel on the ground, there are many more constraints, such as roads, bridges, mountains, or rivers. Highly analytical algorithms are needed to calculate the actual distance, using available travel routes and even considering road types, to calculate the fastest route or shortest route as regularly used by everyone s car navigation system (see Figure 3). An organization trying to identify the market potential of a proposed new store location may want to know which neighborhoods to target and the individual households average driving time to the new store. Assuming the new store s location was at the center of Figure 3, the colored areas from orange to yellow may show the different drive time brackets, for example, up to 10 minutes, up to 20 minutes, and up to 30 minutes. Complemented with information from a company s own customer database, thirdparty direct marketing firms or demographics from the government s census bureau, the analytical capabilities of location intelligence allow for new insights that were generally not thought possible in common BI environments. Source: Gartner Research, G , Andreas Bitterer, 23 November 2012 FIGURE 3 Sample Map Driving Distances Note: Assuming the new store s location was at the center of this figure, the colored areas from orange to yellow may show the different drive time brackets, for example, up to 10 minutes, up to 20 minutes, and up to 30 minutes.

14 14 Esri Location Analytics Solution Examples Here are a couple of examples of how an Esri Location Analytics solutions can add value to an in-place BI solution. Below, a typical BI dashboard shows sales by channel for a wholesaler of camping and outfitting products: FIGURE 1 Here is that dashboard enhanced with a map that provides a very clear and easily interpreted visualization of the organization s sales and revenue performance at the state and national levels, as well as for specific sales outlets: FIGURE 2

15 15 The map s impact is instant and obvious. With a glance, knowledge workers and analysts can see which regions and locations are performing well and which are not. In another case, a dashboard shows lease and well performance for an oil company. The dashboard displays historical trends for lease revenue together with key metrics for revenue, royalties paid, and operational costs: FIGURE 3 Here is that same dashboard enhanced with a map showing actual lease performance, symbolized for all the key measures of concern. Analysts can use the map to drive the analysis based on the patterns they see: FIGURE 4

16 16 Industries that use location analytics include the following: Insurance Analyze total insured value (TIV) by region and policyholder; revenue; gross and net losses; claims; fraud detection; or risk based on weather, potential terrorism, or other extreme events. Financial Analyze key financial measures such as total deposits, household savings, household automotive loans, and liquidity, as well as period-over-period changes in these key measures by region and branch. Utilities View and analyze key measures such as outages and associated costs and anomalies in delivery and employ customer location-based analysis on products and services to optimize revenues and costs. Transportation View and analyze route performance based on scheduled versus actual times, average revenue per seat, percentage of late deliveries or flights, and proximity to enroute service depots. Retail Analyze sales territory revenue and profitability by region and location, as well as key physical contextual influencers such as competitor location and demographics. Analyze marketing campaign effectiveness. Public sector View and analyze delivery and costs of services by service area, as well as public-sector projects and fund allocation by region and project location. Education Analyze alumni fund-raising and management and recruiting based on demographics. Location Analytics Benefits The benefits a BI group will achieve from location analytics depend largely on a person s role within the organization. However, from a business perspective, some primary advantages that location analytics offers to the BI group are listed here: Complementary technology Because the location analytics solution extends in-place assets and solutions in ways designed to fit those systems, there is a short learning curve and quick results. Nondisruptive workflows The familiar workflows of the target BI system remain completely intact for both the design personnel authoring BI content and the business personnel consuming the information in published reports and dashboards. High-value analytics With the ability to visualize and interact with data in new ways, users can recognize patterns and connections that may not be revealed with only charts and graphs. For example, two locations may be operating at less than 50 percent capacity. If these locations were exposed only through a list, it may not be apparent that they are in close geographic proximity and potentially cannibalizing each other. People Using Location Analytics Users, developers, and stakeholders in a BI solution span a wide spectrum. The actual benefits derived from a location analytics solution according to the role of the user are included below: CIO Quick-win delivery of business advantage, with a low-cost, low-risk combination of two highly complementary technologies

17 17 Director of BI A richly enhanced location analytics solution in a fraction of the time required to custom develop, with minimal disruption of existing BI assets and resources BI report developer Seamless access to enterprise GIS capabilities directly within BI authoring environments for immediate productivity without custom development Line-of-business manager (sales, marketing, operations, procurement) Enhancement of the ability to analyze and understand performance using the intuitive and familiar visual context of maps; instant availability of performance and maps to drive BI analysis Report consumer A seamless map experience in BI, with instant-impact visuals, to show exactly where performance is meeting expectations and provide the ability to perform complex spatial queries visually in conjunction with key business intelligence data Summary The maturing business intelligence market is ready for value-added extensions and enhancements. Many organizations are beginning to use location analytics to enable spatial analysis of data and drive business performance. These organizations typically have very large investments in business intelligence. Esri Location Analytics offers a low-cost, low-risk opportunity for organizations looking to realize increased business value and agility. For more information, visit esri.com/locationanalytics.

18 18 About Esri Esri s geographic information system (GIS) technology gives you the power to think and plan geographically. Used today in more than 350,000 organizations worldwide, Esri s GIS helps governments, universities, and businesses save money, lives, and our environment. GIS helps you understand and question data in ways that reveal relationships, patterns, and trends. So whether you are transporting ethanol or studying landslides, you can use GIS to solve problems and make better decisions, because a GIS enables you to look at your valuable data in a way that is quickly understood and easily shared. Esri supports the implementation of GIS technology on the desktop, servers, online services, and mobile devices. For more information about Esri Location Analytics technology, please contact us directly: 380 New York Street Redlands, California GIS-XPRT ( ) T: F: info@esri.com esri.com Offices worldwide: esri.com/locations Where Your Business Intelligence is Missing Information is published by Esri. Editorial content supplied by Esri is independent of Gartner analysis. All Gartner research is used with Gartner s permission, and was originally published as part of Gartner s syndicated research service available to all entitled Gartner clients Gartner, Inc. and/ or its affiliates. All rights reserved. The use of Gartner research in this publication does not indicate Gartner s endorsement of Esri s products and/or strategies. Reproduction or distribution of this publication in any form without Gartner s prior written permission is forbidden. The information contained herein has been obtained from sources believed to be reliable. Gartner disclaims all warranties as to the accuracy, completeness or adequacy of such information. The opinions expressed herein are subject to change without notice. Although Gartner research may include a discussion of related legal issues, Gartner does not provide legal advice or services and its research should not be construed or used as such. Gartner is a public company, and its shareholders may include firms and funds that have financial interests in entities covered in Gartner research. Gartner s Board of Directors may include senior managers of these firms or funds. Gartner research is produced independently by its research organization without input or influence from these firms, funds or their managers. For further information on the independence and integrity of Gartner research, see Guiding Principles on Independence and Objectivity on its website, Copyright 2013 Esri. All rights reserved. Esri, the Esri globe logo, ArcGIS, Business Analyst, esri.com, are trademarks, service marks, or registered marks of Esri in the United States, the European Community, or certain other jurisdictions. Other companies and products or services mentioned herein may be trademarks, service marks, or registered marks of their respective mark owners.