Reinventing Email Through Analytics, One Inbox at a Time

Brad Shimmin

Summary Bullets:

• Building on big data ideas such as machine learning and predictive analytics, vendors are busy building the inbox of tomorrow
• But don’t expect a radically different user experience. It will look a lot like the inbox of today — only minus the usual hateful elements and much, much smarter

The last time I checked, which was about ten seconds ago, which was itself about 60 seconds before the previous time I checked, email still sucks. And I’m sure it will continue in that vein another 50 seconds from now, when I again feel habitually compelled (or when a mobile alert instructs me) to inquire as to the current state of my world, which is wrapped up neatly within the messy confines of my inbox.

Mobile Analytics Form a Two-Way Street Between the Past and the Future

Brad Shimmin

Summary Bullets:

• There are great advantages to disseminating analytics smarts to mobile users such as sales persons.
• Real innovation, however, comes when you combine that dissemination with the collection of data points.

I spent a few hours yesterday listening to a number of SAP ISV partners including ExpertIG, Rapid Consulting and Liquid Analytics demonstrate mobile software built to support the wholesale market.  I know, that doesn’t sound incredibly exciting.  Yet, long before the expiration of my admittedly short attention span, I was struck squarely by what was for me a stunning realization.  Big data should be as much about collecting data as it is about gleaning knowledge from that data.

Big Data and Predictive Analytics Need More People, Not More Data

Brad Shimmin

Summary Bullets:

• Machine learning, data mining, and advanced analytics coupled with big data seems poised to reshape the way we make business decisions, automating them and making them more effective.
• However, if our early work with stocks, recruitment and credit scoring are any indications, our algorithmic innovations need human oversight now more than ever.

My Google Nexus tablet knows when I should leave the house in order to keep my daily routine humming along smoothly. Using historical geolocation data, search results and email trafficit knows, for instance, where I like to dine and how long it will take me to get there at the prescribed hour on the customary day of the week.