10 Common Mobile BI Assumptions You Should Avoid

If organizations are going to utilize mobile business intelligence (BI) to drive growth and profitability, they must take a holistic approach that leverages technology’s strengths and minimize its weaknesses within a supported infrastructure. Moreover, organizations must deliver the power of mobile BI through innovation and without disruption. Just as we know that mobile isn’t just about one or two sexy apps, the step to gain the ability to deliver reports on a mobile device alone doesn’t guarantee success with mobile BI.

Here are the ten most common mistaken assumptions people make with mobile BI projects.

BI Does Not Guarantee Better Decisions, Only Better-Informed Decisions

What does it mean when we say “faster” decision making? And why do we say “better-informed” decisions instead of “better decisions?”

Putting aside the semantic differences and nuances of meaning, these two concepts play a significant role in delivering BI solutions that can address both the urgency needed by business and the agility required by IT. Moreover, exploring these concepts–regardless of your interpretation—will further facilitate better engagements and result in tangible outcomes that can benefit the entire organization, both in the short term and in the long run.

Ten Mobile BI Strategy Questions: System Integration

More and more mobile devices are becoming connected with the software that runs on them. But the true value of mobility can’t be realized until these devices take advantage of the necessary integration among the underlying systems. The same principles hold true for mobile business intelligence (BI). Therefore, when you’re developing a mobile BI strategy, you need to capitalize on opportunities for system integration that can enhance your end product. Typically, system integration in mobile BI can be categorized into three options.

We Were Once That Kid: Curious and Analytical

Although you’re now a grown up adult, you probably remember what your life was like when you were a child. I am referring to elementary school ages. We all can look back on what we were like then –somewhat naïve children. Imagine if you could go back in time and speak to yourself when you were that kid. What would you say to yourself? What advice would you give yourself knowing what you know now?

More specifically, what counsel or warnings would offer that would better prepare yourself to leverage analytics, big data and quantitative methods to help organizations improve their performance? More importantly, what would you say to yourself that would lead to a more fulfilling career and job prospects than you have now?