SAG_Twitter_MEME_Getting_IoT_Apr17-2.jpgThe Internet of Things (IoT) can sometimes seem like managing a playground full of unruly children.

With millions of connected devices, tons of fast-moving data, myriad integration and real-time analysis solutions, IoT has to learn how to play well with lots of participants. And just like a bunch of rowdy children can’t be controlled by one teacher, the IoT cannot be managed by just one vendor.

Because people tend to think that bigger is better, we make IoT even harder to control. The tendency is to add more device connections and thus more data in hopes that this uncovers the valuable information that can make our business better.

The challenge with controlling the IoT is that many components are needed to support a complete strategy. Most organizations already have some of the components in place that are part of an end-to-end solution, such as backend databases or enterprise integration platforms.

Choosing one solution from a single vendor can mean having to throw out valuable legacy systems, and could lock you into a situation that is difficult and expensive to unravel if things go wrong.

The right approach is to develop your own framework that addresses your unique goals. Then find partners that offer the critical modules needed to create an IoT framework, one that slots into your existing and future technology choices.

There are so many devices that can offer valuable data for your business, you need to decide what value you want to extract from them. Do you want data from manufacturing units that enable predictive maintenance? Are you looking for data that you can enhance to provide your connected customers with a personalized service? Or do you want to streamline your supply chain using IoT to provide real-time insights in the location and movement of your assets?

All of these are legitimate value-add use cases. All of these require that IoT data is:

a) Modeled: See clearly how your business processes, devices and applications all relate to each other

b) Captured: Ensure you collect all the data you need from a multitude of sources and devices

c) Analyzed: Plow through large volumes of sensor data to find patterns and trends that may not be visible to others; analyze users at a granular level

d) Integrated: Connect all of the moving parts – sensors, data, business systems, analytical tools

e) Acted upon: All of these moving parts must be coordinated to allow you to act upon events and indicators effectively and rapidly.

Making all of these technologies work together takes skill and planning. Find out more about how to make them all play nicely here.

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