Jan 082013

Last year, organizations across almost every industry became really serious about using mobile technology. The majority of these initiatives involved companies enabling existing applications and business processes with mobile capabilities to extend their usefulness to workers in the field or those on the go, as well as to customers and partners beyond the firewall. This trend will accelerate in 2013, with organizations continuing to deploy mobile apps in the form of management dashboards and tools for supporting the three main domains of CRM (i.e., sales, marketing, and service).

That said, however, I believe that in 2013 we are also going to see end-user organizations and vendors develop applications that apply mobile technology in conjunction with other so-called disruptive technologies such as social networks, the cloud, analytics, and location-based services to create new game-changing or “killer” applications and services. In fact, some forward-looking organizations are already doing this now.

Mobile + Analytics + Social = Improved Collaboration and Decision Making

The number-one goal organizations seek by adopting mobile technology is increased productivity. The goals of improved response to customers and better knowledge sharing and collaboration among employees rank second and third in importance. In reality, however, these activities are actually quite dependent on the efficiency of one another. For this reason, I believe that organizations stand to reap the greatest benefits from mobile technology by combining its use with analytics and enterprise social networking to facilitate better collaboration, knowledge sharing, and informed decision making. It is this combination that will lead to optimum productivity. For an example of the advantages afforded by combining such technologies, we need only consider the recent US presidential election.

The Obama election campaign was powered by workers in the field and those in offices constantly being fed information that had been collected via email (from the Obama campaign website, etc.), phone calls, marketing lists, on-location volunteers, and so on. This info was not just stored in a database; it was analyzed and crunched by an elaborate system (VoteBuilder), which then churned out detailed lists of potential voters to target, along with their likes and dislikes.

Campaign workers also collected information while canvassing voters, entering the information into the system via smartphones, tablets, or laptops. (The campaign also had many volunteers dedicated solely to inputting information collected from surveys, phone calls, and other voter interactions.) Thus, as more information came in, it was added to the existing data — in effect allowing the generation of ever-more-detailed information about possible Obama-leaning voters. There was a social component, too. For example, users working on the same campaign committee could easily share information with each other, yet were able to shield it from workers on other committees.

The result was that Obama campaign workers in the field were not going neighborhood-by-neighborhood, street-by-street, and house-by-house knocking blindly on doors. Nor were those in the campaign offices having to resort to cold-calling potential voters. Rather, they were able to target specific prospects at specific residences in certain neighborhoods. Moreover, Obama workers were informed about what the person they were talking to was likely to be interested in hearing about. Consequently, workers didn’t have to waste their time trying to deduce what they might possibly say to the prospective voter in order to engage them. Instead, they could just start discussing Obama’s views on the environment, banking regulations, healthcare reform, alternative energy, or whatever — in other words, subjects that were likely to catch the voters’ interests.

While you might consider this a fairly unique application, it does offer valuable insight. Trying to market a presidential candidate does not differ terribly from trying to market cars or shampoo or some other consumer product. At some level, they are all just brands. Thus, Obama campaign workers told prospective “buyers” what they wanted to hear in a manner that was interesting and engaging for them.

Combined Technologies Leading to New Applications and Streamlined Services

The combination of mobile with the cloud, analytics, location-based systems, and other technologies is also making it possible for companies to practically implement new applications that automate formerly labor-intensive or difficult-to-perform tasks. Some good examples include using mobile technology to remotely monitor patients outside of healthcare facilities and for audience tracking and participation-enhancement for live performances and events.

Remote Patient Monitoring

One interesting example is The BodyGuardian System, developed by mobile health solutions provider Preventice in conjunction with Samsung. This application allows physicians to monitor key biometrics in patients with cardiac arrhythmias outside of a clinical setting, allowing patients to go about their daily lives while remaining connected to their physicians.

It uses smartphone technology to create a dedicated mobile environment to provide a secure, reliable wireless connection for transmitting biometric data. Patient data is captured with a small, wearable sensor and delivered via Bluetooth to a dedicated (Samsung Galaxy S II) smartphone. Physiological data is then transmitted via cellular network to the BodyGuardian system deployed in the cloud. Physicians and other personnel in monitoring centers can access the data using tablets and other devices.

Mobile technology (and the cloud) makes remote patient monitoring practical; moreover, it is expected to significantly change the way patients with heart disease and other chronic conditions are treated, helping to reduce expenses for care providers, while freeing patients from time-consuming office visits.

Real-Time Monitoring and Influencing of Live Crowds

We are also seeing the application of real-time analytics in conjunction with location-based services and mobile devices to assist organizations with monitoring and influencing the electronic behavior of live crowds.

A particularly interesting application is CrowdOptic, which lets producers of live events — such as sports matches, concerts, and other performances — monitor and track what crowds are looking at and what they’re photographing and sharing (via Facebook, etc.) during a live event, in near real time. It also allows event organizers to display information on the audience’s mobile phones, depending on what they are looking at, and can alert event organizers to shifts in crowd focus and momentum. The purpose is to optimize and enhance the in-venue experience for fans and to give sponsors and event organizers live feedback they can apply immediately or utilize for future performances.

CrowdOptic uses triangulation and real-time streaming analytics to sense where crowds are focusing from moment to moment, thus tracking the precise paths of spectators’ phones as they view and take photos and video of live action. It monitors the GPS location and compass headings on each of the hundreds or thousands of mobile phones in a crowd (using GPS to locate the phones and compass headings to determine the direction the phones are pointing) and finds the point where two bearings, taken from two different locations, intersect. This triangulation provides the exact location where phones are pointing and pinpoints where the action is. CrowdOptic can identify clusters of fans in the crowd looking at the same spot at any given moment, even when the action is constantly moving, such as during a sporting event when fans are taking photos of the athletes.

When I first discussed CrowdOptic about a year ago, the technology was undergoing testing with several companies. Today, the technology is utilized in a number of applications.

Ticketek, a ticketing partner to sports and live entertainment businesses inAustraliaandNew Zealand, offers Friend Spotter, an iPhone app that lets friends locate each other instantly in a crowd using their smartphones.

Friend Spotter combines Facebook data and CrowdOptic technology to enable friends to spot each other in the stands at Ticketek events, simply by scanning the crowd through their camera viewer. In this manner, fans can share the live event experience with friends during the event itself.

CrowdOptic has also applied its focal clustering technology for smartphones to analyze photos posted on social media sites in order to reveal the top locations photographed when Hurricane Sandy recently devastated the east cost of theUS.

This application analyzed a set of thousands of publicly shared, crowd-sourced photos from social media sites containing Sandy-related hashtags. The analysis revealed instances in which multiple lines of sight by amateur photographers converged around specific locations, pinpointing these locations as the most frequently documented by witnesses of the storm.

To identify the photos of greatest significance, CrowdOptic used the existing photo meta data, as embedded in image EXIF format — including GPS position, compass heading, and time stamp — and applied statistical and analytic algorithms and triangulation techniques to arrive at a relative significance value for each photo object. (The company claims that analysis using such algorithms took a total of 1.216 seconds to complete.)

Some of the most significant focal clusters that were revealed include a downed tree caused by the hurricane and a devastated home documented by onlookers, owners, and insurance appraisers. In short, CrowdOptic technology was able to create a cohesive chronology of an event location over time by annotating and authenticating all photos taken of the site by various onlookers. Such an application has potential uses for broadcasting, publishing, marketing, and, potentially, disaster aid.

CrowdOptic is mainly positioning its technology for use at live performances like concerts, sporting events, and debates and for after-the-fact analysis (i.e., analyzing large image repositories). However, I can also see it used for other events as well, such as big store promotions, parades, and political rallies. For that matter, it also probably has applications for monitoring crowds at protests, demonstrations, and other civil disturbances. (For more on CrowdOptic see ” Innovative Applications of BI.”)


These are just a few examples of how mobile technology — in conjunction with other disruptive technologies — is leading to new applications that were either impossible or impractical to implement just a few years ago.

In particular, I think that the use of mobile technology — in conjunction with analytics and enterprise social nets — is going to lead to an increased focus on knowledge management over the next few years. Organizations should consider and investigate further how they can take advantage of the unique capabilities offered by combining these technologies.

[Editor’s Note: This post is part of the annual “Cutter Predicts …” series.]


  2 Responses to “Mobile + Disruptive Technologies = Killer Apps”

  1. Nice, found some new things to read today 🙂

  2. Thanks, glad you found it interesting.

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