Mobile analytics: 7 best practices

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Introduction The end user’s personal requirements for mobile connectivity anywhere, anytime, have translated to the workplace. The combination of business intelligence (BI) and mobile technical maturity has created immediate opportunity, as well as the challenges of uncertainty. Concerns regarding privacy and security, device management, user requirements, and proliferation of data and performance have become paramount. These questions have given organizations reasons to pause, while end-user expectations are ever advancing. The benefits and opportunities abound with mobile analytics, including increasing business process efficiencies, resource accessibility and engagement. The mobile analytics frontier is quickly becoming the cutting edge for business transformation and innovation, empowering end users with real-time information in any location. The technical maturity of both BI and mobile applications has created the mobile analytics call to action.

Challenges and opportunities Some of the initial challenges in the mobile device and application proliferation have caused standard misperceptions in the IT realm. The initial failures in ported systems replicating point-and-click technology created a first generation of mobile Internet and application users that were quickly disenfranchised with the technology. Widespread security and privacy concerns have translated into the corporate data realm with alarming consequences. The traditional IT device management nightmare has reached new levels with the bring-your-own-device (BYOD) culture exploding. Meanwhile, mobile providers and networks were advancing capabilities in cross-platform, multienvironment suites and evolving applications to the “deploy once, deploy everywhere” model. The underlying truth is that device and application technology advancements have surpassed the quality and capability gap, making actual BI challenges equivalent to mobile BI challenges.

The 7 best practices It is possible to apply a best-practice methodology across mobile analytics implementation. These techniques could be applied to any mobile analytics deployment, regardless of the tool set; however, they are especially focused on deploying the prebuilt mobile capabilities and assume some of the inherent technical advantages.
  • Understand the role of data architecture and governance
  • SOS (start on security) now
  • Segment users and their requirements
  • Start small/start quickly
  • Target widespread user application
  • Develop purpose-built mobile applications
  • Embed mobile analytics into the BI competency center

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