- 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.
More than that, it should be about disseminating and collecting all at the same time, mixing the two up in an effort to build a smarter mobile app. Let me explain. Let’s say you have a mobile application built to present truck drivers with a suggested delivery route based upon which clients are the closest, where items are loaded on the truck itself, what current traffic patterns look like, etc. That kind of real-time business intelligence knowhow is quite useful, but what happens when you feed in the subsequent actions of that driver back into this same system over time?
Short answer: The system gets smarter – much smarter. Imagine if you could gather delivery data points such as delivery failures, delays and product damage reports, or truck data points such as speed, brake activity and gas mileage. Now imagine if you could feed that back into this same real-time route suggestion mobile app, combining that with historical data surrounding customers, orders, shipments and the like (everything we typically dump into our ERP applications). We would do this, however, not just to continuously optimize the current route based upon unforeseen issues, but instead to build a better, more successful suggested route for tomorrow, all based upon this past experience.
That sounds an awful lot like how we humans learn and adapt. We combine our ability to project ourselves into the future with our memories of past experiences to generate the most effective mental model possible – preferably the one that prevents us from being eaten by a bigger carnivore. Back in the world of software, that means building a mobile application that relies upon analytics, such as the delivery app mentioned above, and being sure to create a back channel (a biofeedback mechanism, if you will) capable of pulling in such information in time, context and location. After all, as the Spanish philosopher and poet George Santayana once so famously said, “Those who cannot remember the past are condemned to repeat it.”
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Reblogged this on The Redwine Model.