How To Launch an IoT Pilot & Deploy Across The Enterprise
“More than 40% of organizations expect the IoT to have a significant impact in the short term, and this number rises to more than 60% in the long term.”
Gartner, Survey Analysis: The Internet of Things is a Revolution Waiting to Happen by Nick Jones, Stephen Kleynhans and Leif-Olof Wallin, 19 January 2015
In this video we’re going to show you how to successfully pilot IoT and scale it across the enterprise.
The value of having access to real-time IoT data is determined largely by your ability to act and respond to events as they happen. Having dynamic event-based hybrid processes will give your team the flexibility they need to act in a way that suits the situation best.
As you roll out your Internet of Things projects across the enterprise you can start to provide process options to optimize for specific goals.
Keep in mind that you’ll be working with simple, clean data from a small number of data sources when starting an IoT pilot program. But it is of critical importance that you think more strategically and plan for the big, imperfect data you’re going to have to deal with in enterprise deployment.
Your IoT pilot will allow you to incorporate predictive analytics and create real-time dashboards for supervisors. Examples of use cases are optimized route planning to minimize fuel costs or installing sensors on equipment to do predictive maintenance. One mistake we often see companies making is that they don’t embed their analytics inside their business processes. Data-driven decisions will only happen if you make it easy and intuitive for people to access the data.
To move to the IoT enterprise stage on the maturity curve you must be able to scale your IoT analytics across multiple asset classes and use cases, without needing to write custom code for every application.
By analysing process data and creating new predictive models, your predictive analytics can then progress to prescriptive analytics. In the case of industrial waste removal, you can proactively provide workers with safety instructions based on sensor data about hazardous materials in the waste bin.
With a solid foundation in place you can now connect to external data sources like sensors, API’s and web services. This can also include open public data like traffic and weather reports.
An important consideration when implementing an IoT Pilot program is to invest in a platform that will support future device models and brands. You won’t be operating in a homogenous environment. You’ll be using different vendors and models, which need to be integrated and managed.
Many smart device vendors have created their own platforms, but building your IoT Pilot on one of these platforms will lock you in to using one specific vendor. We recommend building your IoT programs on the right platform from the start. One that can handle the growing number of data sources and allow you to integrate easily using a no-code framework.
In the IoT Pilot stage you are likely to move from Google Maps to more robust GIS mapping solutions like Esri or QGIS, which provide additional metadata. This allows your maps to show information like the asset’s number or live data from its feed.
When moving to enterprise IoT deployment your maps can include relevant operational data as well. The metadata on the map can indicate where your other live and operating assets are.
You can set up geofences around assets that create dynamic no-go zones that move as the asset moves. An example of this is oil well drilling rigs which have a geofence with a 100ft radius around them when they are live and operating. This data allows maintenance crews to check which areas and roads are restricted before going out to the field.
More advanced GIS mapping tools can add overlays with business data onto maps. This is particularly useful for construction and digging crews. It enables them to see where electric cables and water pipes are beneath the ground before they break the surface.