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10 Mistakes to Avoid in Mobile BI Delivery

Thursday, April 4, 2013

The Mobile BI craze is going nowhere fast. Information Management has created an article on things people should avoid when implementing it. Check out some of what they have to say below

Mobile applications have gained a definitive place in enterprise adoption. The growing maturity and adoption for mobile business applications are predominantly visible with service offerings like mobile banking, mobile shopping and mobile social network connections.

The extended mobile business application for business intelligence (mobile BI) has gained momentum, with most of the BI tool vendors offering a mobile extension to the native BI suite itself. Furthermore, the variety of platform support, user-friendly devices and graphical interfaces has pushed enterprise adoption of mobile BI into the spotlight. In 2010, Gartner published a hype cycle indicating mobile BI is a climbing wave and stated that adoption will be visible in two to five years.

The important thing to remember, simply put, is that mobile BI is not just a mobile version of traditional BI; it is a mistake to overlook the unique considerations required for implementation. As a mobile BI practitioner closely following the mobile BI market dynamics, I offer 10 pointers for practitioners looking to deliver mobile BI to the enterprise.

Mistake 1: Assuming mobile BI implementation is a project, like a traditional BI implementation

The nature of a mobile BI engagement is more like a program rather than a project. It is a fact that mobile BI is an extension of enterprise BI. However, mobile BI should be focused on delivering measurable business value rather than just meeting scheduled objectives. In mobile BI engagements, it’s more important to derive effectiveness.

For a traditional BI implementation, it’s important whether the planned activities were completed within the time and budget allotted; however, for mobile BI it is more important to measure how particular information, when made available through mobile apps, can make a difference to the decision makers/users. For execution purposes, the requirements-gathering for mobile BI should be focused on identifying which reports, dashboards and alerts will be beneficial on handsets. The emphasis is on the value of the data with respect to time rather than look and feel of the reports/dashboards itself.

Mistake 2: Underestimating mobile BI security concerns

The top concern in mobile BI adoption is security, and if not designed correctly, it really can be an issue. It’s the most discussed aspect in the mobile BI world today and has a very direct impact on the rate of adoption. Security for any application beyond the enterprise firewall has always been a debate. However, the interesting fact about mobile BI security is that, when designed optimally, it can leverage more security layers and features than traditional BI apps.

  • Device level security: Utilize the handset/device security features to protect the data, including features like full-disk encryption, the ability to remotely wipe content on the device, and antivirus and firewall software.
  • Transmission level security: The security features of cryptographic shared key systems, secure socket layers and VPNs all ensure that the data can be secured at the network layer.
  • Application/network level security: The authorizations and authentications can be enforced on the applications at the infrastructure front. Most BI tools extend the same security model to mobile BI that they have designed for their native BI applications. On top of the network, policies can be enforced the same way it’s done for the enterprise.

Mistake 3: Rolling out mobile BI for all users.

Mobile BI apps should not be put in the same category as management BI reporting apps. The purpose and use of mobile BI apps are very specific and different than MIS. The most important factor is to understand who will need information at all times and what decisions will be impacted by having or not having the information always accessible.

Are these users always mobile and have only a limited amount of time to access the data, or do they have a role where they don’t need to frequently check the data? Define the user group(s) and design the mobile BI app based on these role definitions. Typical candidates for the app are users responsible for mission-critical environments, such as a data center hosting payment servers for banks, or to solve real-time problems as they arise, like power station operations. Mobile BI investment will be justified only when users and usage are understood and aligned realistically.

Mistake 4: Believing that return on mobile BI investment cannot be derived

Every investment has a justification, and a business sponsor will definitely demand one. Whenever there is cost involved, there will be a means to track it and determine the ROI. It might be challenging in mobile BI initiatives, but quantifying the business benefits can be done. Consider the following key aspects when deriving ROI:

1) Benefits associated with mobile BI. Is the initiative focused on:

  • Increasing employee productivity?
  • Closing sales in a much shorter time span?
  • Lowering business costs (like material cost, reducing administrative time, etc.)?

Once these are defined, the investment can be linked with the benefit.

2) Investment associated with mobile BI, such as buying devices (handsets, iPad, etc.) or investing in infrastructure (hardware, software, maintenance, service and training).

Now an ROI can be calculated using the defined tangible and nontangible metrics.

Mistake 5: Implementing mobile BI only for operational data

The mobile BI application can be pushed to accommodate all reports/dashboards available in a traditional BI environment, but that will defeat the purpose of having an initiative like mobile BI. A categorization of the good-fit data has to be done with each initiative. This is important because the question of “which data is good for which enterprise?” is very subjective, and only respective business users can answer this. For example, a workflow approval might be critical in one environment, whereas having current currency rates handy at all times might be critical for a different user.

To read the rest of the article click here.

Source: Information Management

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