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May 19, 2014 in Big Data, Business Analytics, Business Intelligence (BI), Business Performance Management (BPM), Cloud Computing, Customer Performance Management (CPM), Information Applications (IA), Information Management (IM), Location Intelligence, Operational Performance Management (OPM), Sales Performance Management (SPM), Social Media, Supply Chain Performance Management (SCPM) | Tags: Big Data, Business Analytics, Location Intelligence, Pitney Bowes | by Mark Smith | Leave a comment
I recently attended the 2014 global analyst summit in San Francisco hosted by Pitney Bowes, an old technology company (now in business for 94 years) that has a new focus in its software along with an entirely new executive team. These leaders unveiled a business and technology strategy meant to demonstrate the company’s commitment to software. For many years it has been known mostly for mail services and postage metering, but Pitney Bowes also has made investments in software that can help companies change their business processes by optimizing their information assets. Over the past few years the company has had its ups and downs as regards its corporate mission, as I wrote in 2012. Most of the turmoil was due to conflicting agendas from past management, but other factors were the company was not as clear in communicating the value of its combined software portfolio and not capitalizing on the demand in lines of business and IT for information management and analytics software.
Pitney Bowes has several important assets. Its location intelligence software can provide consumers with accurate information about and directions to locations, enable businesses to target customers more accurately and help businesses be more responsive by adding a geographic context to customer information. Pitney Bowes also has advanced its efforts in information management to integrate and enrich data through spatial processing with a specialization in customer information. My analysis of Spectrum, its information management software suite, found innovation in its support for analytical and operational use. Organizations are changing how they make information available as lines of business and IT share responsibility for improving information availability, which they do in 42 percent of organizations participating in our information optimization research; the most common reasons for doing so are to improve operational efficiency (cited by 67%) and to gain a competitive advantage (63%).
The latest version of the Spectrum Technology Platform includes data enrichment and quality in its data integration offering. It has advanced in search, query design, in-memory caching and support for Hadoop. The platform also is the foundation for a master information hub that can build relationship-based maps that Pitney Bowes calls knowledge graphs. These maps are more powerful than data relationship-based models that can’t map complex relationships and present them visually. In IT domains this is called master data management, but it goes beyond the usual entity relationship modeling to visualize and manage customer information from a business perspective; this can help bring business users into the process. It also can discover the locations of any information, which our information optimization research finds is important to more than one-fifth (22%) of companies. Having consistent information, particularly about customers, is critical for interaction across a business in providing the best possible customer experience. The Spectrum Platform also can process data in real time, which is attractive to the company’s new customers including large retailers and social media companies like Facebook. We find that only one-fourth (26%) of organizations are happy with their current technology used to provide information, which indicates an opportunity for Pitney Bowes to take a more aggressive position in the market.
In addition Pitney Bowes has customer and marketing analytics software called Portrait Analytics, which offers an engaging way to visualize and interact with customer information. It also can predict potential results through the Portrait Miner application. Another product, Portrait Uplift, can help companies can use the analytics to apply adaptive learning from customer interactions to model how customers will interact and where changes might be needed to stimulate purchasing and reduce churn. These applications have significant potential for marketing and other customer-focused functions because they do not require a data scientist to use them. In our next-generation customer analytics research more than half (59%) of participants said it is very important to improve them while only 15 percent are satisfied with their current efforts. Predictive analytics is the type of advanced analytics most important to 69 percent of organizations, and only one-fifth (22%) are happy with their current software. Pitney Bowes is in position to look for opportunities here as long as it focuses its efforts to the top drivers that are improving the customer experience (63%) and improve the customer service strategy (57%).
The company has not lost its focus on location intelligence software. Its flagship product here remains MapInfo, but it has made investments to highlight its potential for enterprise location intelligence by supporting it in social media and Internet location-based services. A series of new releases of MapInfo after the current version 12 are coming in 2014. The company says that enhancements will include the user experience, a more contextual interface, 64-bit processing, a layout designer, contextual menus and display management. To take advantage of multiple-core processing, Pitney Bowes has segmented processes to accelerate performance. Our latest research in location analytics found that reliability, which includes performance and scalability, is the third-most important software evaluation criterion. The updates also will expand mapping from vector-based to grid-based analysis. In addition mobile technology is a priority for MapInfo, as it should be: This is the second-most important technology innovation according to our location analytics research. MapInfo Stratus is a cloud-based extension of MapInfo Pro. Some support for mobile devices is available today, and more improvements to the experience are coming. This and other advances address the innovations that are changing computing and users’ expectations and are critical to keep MapInfo relevant.
Pitney Bowes built its position in location intelligence on geocoding, integrating data sets across on-premises and cloud systems for access from a range of applications. Pitney Bowes includes 122 countries in its geocoding, and its software can provide multiple levels of accuracy based on what is available in a cascading approach. It also provides reverse geocoding, which helps identify locations through longitude and latitude; this is used by major social media. Pitney Bowes has advanced the capabilities so users can type ahead to find locations in proximity; this is especially critical for mobile application support. The ubiquity of mobile devices and Internet use and the growth of complex event processing and visualization are bringing new opportunities for Pitney Bowes’ geocoding and location processing. Our location analytics research finds that many organizations view current methods as not reliable, taking too many resources and too slow. Using a dedicated approach can deliver business value like improve customer experience (20%) and gain competitive advantage (17%).
Pitney Bowes has announced the release of Spectrum Spatial, a location intelligence platform built on MapInfo. Additionally Spectrum Spatial Analyst is an interactive tool to examine spatial and location attributes of data. The Spectrum Spatial technology and Spectrum Spatial for BI are the basis for Pitney Bowes establishing new partnerships with IBM and SAP. Having location analytics with business intelligence is still rare and has potential to enhance business analysis as found in almost a third (30%) of organizations while using a dedicated approach with GIS and location analytics provides satisfaction in almost half (49%) of organizations.
Our big data research finds that only 16 percent of organizations are using geospatial analysis in big data analytics; we think this is an overlooked opportunity given the value of location in enhancing information assets. Pitney Bowes has focused on providing location intelligence to suppliers of standard RDBMSs and data warehousing, which are only a subset of the big data environment. But the company realizes the importance of big data and has announced expanded support for it in Spectrum to ensure it can rapidly access these new sources. It includes new in-memory support (50%) for SAP HANA and Hadoop (42%), which are the two types of big data support revealed as most important in our research.
Overall Pitney Bowes software combines data management and analytics with its specialization in location to meet today’s need to optimize information in real time to support both consumers and business decision-makers. In the past year it has gained traction with social media companies and other types of businesses through direct approaches. Its main challenges are that its brand is not known for solving these types of problems and that it has not been able to assert its presence through marketing. Our research on buyers and users of software for information management and big data analytics has identified demand for these capabilities; Pitney Bowes should use its own software to better market and sell its products as well as the technology deserves. Its new executives have made the strategy more clear; now it is time for the organization to execute it through more and better marketing to ensure that potential customers consider its products that deliver business insights.
CEO & Chief Research Officer
April 1, 2014 in Big Data, Business Analytics, Business Collaboration, Business Intelligence (BI), Business Performance Management (BPM), Cloud Computing, Customer Performance Management (CPM), Financial Performance Management (FPM), Information Applications (IA), Information Management (IM), IT Performance Management (ITPM), Location Intelligence, Operational Intelligence, Operational Performance Management (OPM), Sales Performance Management (SPM), Social Media, Supply Chain Performance Management (SCPM) | Tags: Business Analytics, Business Intelligence, Data, geographic information systems (GIS), GIS, Location Analytics | by Mark Smith | Leave a comment
Our latest benchmark research into the market for location analytics software finds significant demand for location-related technology that can improve business outcomes and generate relevant information for various types of users. (Location analytics is an extension of business analytics that can enhance the sophistication of data and processes by adding a geographic context.) My last analyst perspective on this topic discussed the business value of insights based on geography and what organizations are doing to advance their efforts here. Our research also shows, however, that most still lack satisfaction and confidence in using the technology. Just 12 percent of all participants said they are very satisfied with the location information and analytics available in their organization. Further analysis shows that satisfaction increases with use of a dedicated application for location analytics: 71 percent of those are satisfied or very satisfied, substantially more than those using location analytics within a BI tool (22%); findings are similar for both B2B and B2C use. We find similar levels of confidence in the quality of location information: 15 percent of those using a dedicated application are very confident in their location analytics. Confidence in the reliability of such information is essential to more organizations adopting location analytics.
One cause of limited satisfaction and confidence appears to be the difficulty of analyzing information that has a location context. Two-thirds of organizations said doing so requires significant effort or some effort, and 17 percent said that is very difficult or they cannot do it. Thus it is not surprising that about three in fiveorganizations plan to change the way they use location information in the next 12 to 18 months. For more than 40 percent each, that change is driven by efforts to improve processes: a new initiative to improve information and decision-making (51%), a need to improve business-to-business planning and collaboration (50%), the desire to promote operational efficiency (49%) and as part of a wider analytics and business intelligence initiative (44%). Participants with IT titles most often identified as the driver a new initiative improving information and decision-making (61%), as did those from the services (69%) and government (63%) industry sectors; those working in lines of business insisted more on seeking change to improve B2B planning and collaboration (54%). The need for improvement shows that organizations recognize a potentially important role for location analytics in various business processes, from information use to decision-making.
A range of technologies can be used for location analytics, but not all options work equally well. Today nearly half (49%) of organizations use spreadsheets heavily for analyzing information that includes location data; significantly fewer use other tools heavily – custom applications (36%), analytic or BI tools (34%) and a geographic information system (GIS, 23%). Many organizations use business applications heavily for analyzing this type of information, most often customer relationship management (CRM, 28%), supply chain management (16%) and enterprise asset management (14%) systems. Yet heavy users of a GIS or a dedicated application are the ones most often very satisfied (49%), and heavy users of spreadsheets are very satisfied least often (16%). Among those saying that the use of location analytics has improved their results, spreadsheet users ranked last (35%), far behind users of a GIS (55%) and analytic or BI tools (49%). Organizations that use a dedicated tool for location analytics (49%) are the most satisfied significantly more than those that use only spreadsheets (16%).
A look at the capabilities necessary for effective location analytics indicates why tools designed for the purpose get better results. More than three in five organizations said three basic capabilities are important: geographic representation of data, visual metrics associated with locations on a map, and selecting and analyzing locations on a map. One-half to one-third said interacting with maps and locations for further analysis, determining distance and drive time, and adding layers to maps are important. All of these basic capabilities are the building blocks for conducting specific analytics that can identify or recommend actions from the mashup of data about a location or to provide insights to guide decisions based on location-specific indicators.
Another technology approach used most frequently is business intelligence (BI). These tools are designed for reporting, creating dashboards and general access to analytic information such as metrics. BI tools and processes are established in both IT departments and lines of business, and location information can further enhance BI efforts. Nearly half (48%) of participants in this research ranked business intelligence interfaces as the most important to integrate with other enterprise software; custom interfaces was a distant second at only 13 percent. IT participants (55%) put BI first more often than did those in business (44%), and manufacturing (55%) ranked it higher than other industries. BI also is the application most often integrated with location analytics (45%), even more so in the largest companies by number of employees (56%) and by annual revenue (65%). In terms of planning and developing a strategy to use location analytics with other systems, most intend to integrate it with marketing automation (33%), sales force automation (30%) and enterprise content management (also 30%).
However, the research also finds impediments in using BI and location analytics together. Almost half (46%) of participating organizations said that integrating the two requires significant effort; another 16 percent said doing that is very difficult and requires substantial time or that they have no practical way to do it. On a positive note, integration of these two technologies has advanced significantly in the last several years, and it is easier to exchange data and add it to presentations. In addition, organizations that use business intelligence to conduct location analytics reported benefits, particularly improving the customer experience (21%) and gaining competitive advantage (20%). More than three in five companies that use BI with location analytics are very satisfied (17%) or satisfied (44%) with theinformation and analytics they have available. Thus the research clearly shows that integrating location information into business intelligence can deliver value.
Looking at location information in a broader sense we find many organizations using consumer mapping to plot data quickly, predominantly free software such as from Google (which 45% use) and Microsoft (31%). The research also reveals that while almost one-third (31%) have used these for enterprise needs, only 8 percent are very satisfied with them. Like personal productivity tools, these tools can help in individual tasks like driving instructions and plotting locations for quick geographic placement, but they lack task support and operational or specific analytical context that requires secure, integrated access to enterprise systems. Free and easy access makes them attractive, but they do not provide enough capabilities for skilled workers to use in complex business tasks.
As deployments grow, so does the need to integrate and adapt location analytics to other technologies. For example, one in five research participants said mobile technology is critical for improving location analytics, as did smaller numbers for cloud computing (15%), big data (15%) and collaboration (8%). Ways of deploying location analytics also are changing, as more organizations realize that buying and installing the software on-premises (which 35% prefer) is not the only approach; nearly as many (33%) want to access it on demand through software as a service (SaaS). Very large companies by number of employees (44%) and annual revenue (39%) have the strongest bias for on-demand deployment, as does manufacturing (43%) among industry sectors. Exploiting the full potential of big data investments, whether representing machine data or customer locations, is a prime example of where location analytics can help use data effectively. The research strongly suggests that location analytics will have a place in evolving business technology environments and that broader use of innovative technology will extend the value of this investment also.
However an organization deploys location analytics, the research shows that experience in using it is critical to success. Half of participating organizations have deployed location-focused technology, and the percentage is highest among very large companies by number of employees (56%) and annual revenue (67%). Almost two-thirds (62%) of all companies that have the most experience said location analytics has helped improve results significantly; among those who are somewhat experienced just 23 percent said this.
Organizations of course expect to realize important benefits from software investments. The top five benefits being sought from location analytics are to improve the customer experience and customer satisfaction; gain competitive advantage; improve access to and value of existing information; improve organizational alignment and coordination; and deliver products and services faster. Organizations that use a dedicated technology focus most on gaining competitive advantage (21%) and delivering products and services faster (16%). Investment in a dedicated tool for location analytics can increase the value of an organization’s information and analytics, which improves with experience in using the technology. We recommend that organizations develop a location-specific component in their agenda for analytics. If you want to learn more on the value and potential of technology in location analytics our community is available to help with more depth in best practices and insights on this topic.
CEO & Chief Research Officer