Tuesday, May 3, 2016

From Consumer IoT To The Enterprise

Many of the most useful applications and interesting disruptions of the last several years have to do with a combination of the Internet of Things and new cloud-mobile applications.  The initial targets were primarily consumer-based and creators of these new devices and applications were building a new business to go after this space.

Consider four of best known disruptions in the last several years...

In the case of Fitbit and Nest, it's easy to see how they built a new smart device and an application that allows the consumer to control the device and analyze the data.  There is a lot more data being created by these devices than they are exposing to the end user, but a key reason these companies have been successful is that they surface all that data through a consumer-friendly cloud-mobile application that makes sense of the data and solves a customer need.

In the case of Waze and Uber, it's a little harder to see the IoT play because their smart device is not available yet - a car that drives itself or a car that senses traffic, obstacles and police cars.  So, for now, these companies have built applications on both sides.  One to create the data and the other to analyze and surface that data in a useful way.

The things that all four companies have in common is that they built the platform required to run these IoT and cloud-mobile apps, for their specific purpose.  They are building a business around these devices/apps and competing in the war for technology talent capable of building that platform.

As this IoT and cloud-mobile apps disruption is embraced by enterprises, there will need to be a core platform that supports IoT.  We need a new picture that reflects the enterprise and industrial IoT, different from the consumer IoT.

At the core of it is an IoT Data Platform.  This platform would likely cover four areas: Data Capture, Data Management, Data Security and Data Consumption.  Data Capture is a set of interfaces to pull/receive data from the things and send it to the infrastructure to be stored.  Data Consumption is a similar set of interfaces that will allow applications to get access to the data stored and managed by the platform.  Both of these functionality areas need to support broad access and the maximum possible compatibility with devices and application use cases. For Data Capture and Consumption, accessibility and compatibility trump proprietary value-add, so this is an area ripe for open source software and community-driven development.

The Data Management and Data Security layers are to, well, secure and manage this data.  Different data will have different value and different requirements for performance, retention, security, etc...  Data Management and Data Security is an area where technology vendors are likely to build "special sauce" that they want to monetize, so it will be interesting to see if these layers are as readily open-sourced.

Lastly, there needs to be a highly elastic, low cost, high performance infrastructure to power this platform and the data.  That is what people today call "cloud infrastructure", but that doesn't necessarily mean public cloud.  As the traditional infrastructure players build new technologies for this digital world, expect enterprises to choose to mix on-premise cloud infrastructure with off-premise cloud infrastructure to power their IoT deployments.

Some vendors will try to deliver this entire stack from IoT platform to infrastructure.  IBM seems to be headed this way.  Other vendors can offer a compelling solution for one part or the other.  Splunk seems to have a great opportunity in the IoT platform space and GE Predix has launched into this space.  Companies like EMC and Cisco are moving into the Cloud Infrastructure for IoT space.

As IoT grows more mainstream and digital transformation moves to the classic enterprise and industrial companies, this IoT platform space will quickly evolve.

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