Long before the Internet of Things (IoT) was a conceptual buzzword being tossed around, the idea of remotely tracking the performance of a machine has been well established in both the industrial equipment and healthcare technology industries. The idea of tracking the data captured by this equipment, and even having a localized network of these machines being connected to one another is not new.

What is new is the advances in computing power at a smaller scale, the sophistication of networks, and the volume of data that is able to be transferred over the internet. This is now unlocking people’s minds to imagine new possibilities and contribute to the Internet of Things. In this blog, I’m going to talk about how you can begin creating your IoT strategy.

What is the Internet of Things (IoT)?

The Internet of Things (IoT) is when everyday mechanical objects, such as cars, appliances, and other machinery, can send and receive data via the internet. The data, which is collected via sensors embedded within the device, captures a digital representation of physical properties, such as the machine’s real-time performance and functionality. This data is either stored in a cloud repository, or can be sent between different machines within an ecosystem of connected devices that then “talk” with one another. This data is sent and received independent of human interaction.

The Internet of Things (IoT) is a concept; it’s a platform of possibilities. It’s not something tangible you can pick up or point at and say, “There, that’s our IoT”. The Internet of Things isn’t about technical capabilities, it isn’t about new product features, it’s not even about designing and packaging value-added services. IoT is about expanding your imagination into the world of possibilities that emerges when you comprehensively integrate all aspects of your products through the collection data.

How to Create a Data Strategy for IoT

Getting started with implementing IoT into your current operation can be frustrating, because you don’t know what you don’t know. If you are in this stuck or frustrated point, start by identifying what you want to know. This means starting by creating a data strategy for IoT.

1. Think of What Data You Want to Collect

When first conceptualizing what an IoT strategy will be for your business, allow yourself some free thinking imaginative brainstorming space to generate a wish list of possibilities.

This sort of brainstorming session should be collaborative and inclusive across all areas of your business that can be integrated through IoT. I know it’s hard to get these bodies into the same room at once, but it is an upfront effort that will ensure the success of any IoT initiatives.

When conducting this imaginative exercise, keep in mind the following category groupings for an IoT strategy:

  • Data Acquisition
    • Sensors embedded in the device
    • Remote connectivity: identify which devices in your product line to be remotely connected
    • Edge computing to distill down the data collection to usable bits of information
  • Data Transmission‚Äč
    • Centrally collecting the results of interconnected devices
  • Data Management
    • Implement a management strategy to handle incoming flow of data
  • Data Analytics

2. Identify How You Will Use That Data

Once you have your data inventory and wishlist assembled, look for novel ways that the data being collected can be used. Over time, the data you collect through your network of interconnected devices will become more valuable than your products themselves.

When you are first designing an IoT strategy, keep an eye out for these pockets of data resources that may not be essential to your business, but will be extremely valuable to someone else. For example, the weather and temperature sensors on cars that predictively turn on windshield wipers is extremely useful to weather companies who are seeking insight into localized weather.

3. Keep Asking Questions and Refining Your Strategy As You Go

When first getting started with IoT ask yourself the following questions:

What do I want to know from my products?

How can I collect it?

Where else could the data collected from my devices be used?

Start small with one product or business, and build out from there by continuously asking the above questions again and again. As you learn more and answer your first question, new questions are going to emerge and more capabilities and interconnectivity can be developed.

If you want more details on the capability requirements for a successful IoT strategy, refer to TSIA’s ebook, “Why Services is the Key to Digitally Transforming Equipment Manufacturers”

Keep in mind that there is never going to be a point at which a company arrives at “doing the Internet of Things”. It is not a destination, it is a concept and inherently abstract. It is a collection of technological advancements begging to be integrated and we are only limited by our psychological barriers when imagining the possibilities of IoT.

Need More Help With Your IoT Strategy?

TSIA is helping hundreds of companies in the industrial equipment, healthcare technology, enterprise IT industries develop and implement their IoT strategies, paving the way for future success in a rapidly changing world. Members of our Field Services research and advisory program have access to an unparalleled vault of proven business frameworks, data-backed insights, and strategic plans of action to prepare their organizations for the future of IoT and services-led business models that OEMs and hardware suppliers can implement.

Contact us today to learn how membership in any of our research and advisory programs can help your organization achieve the results you’re looking for.

In the meantime, please be sure to read other posts in my “IoT Strategy for Industrial Equipment and Healthcare Technology” blog series:

 
 
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About Sarah Swanson

About Author About Sarah Swanson

Sarah Swanson is a research analyst for TSIA and is part of the company's "A-Team", which works to collect and analyzes technology and services industry data for the benefit of TSIA members. She holds a Masters in Social Science Research from University of Chicago and has worked in the analytics field for 5 years applying research methodologies and quantitative analysis to various data sources. She has a passion for using data-driven processes to improve efficiencies and optimize performance.