How to Transform IoT Data into Real Value

Unlocking the Business Potential of Data through IoT

A recent study by GSMA Intelligence reports that by the end of 2025, worldwide IoT will have a consolidated value of about $1.1 trillion. This massive revenue estimate reflects just how much data is being produced around us — and how brands around the globe are already beginning to learn how to monetize this data.

Improving Customer Experience

The most significant business potential of data through IoT lies in how it can be used for visualizing the customer journey, enhancing the customer experience, and growing the customer base.

Many organizations are currently focusing on the customer experience and are thinking of ways to make it better. They have started tracking data from all parts of the consumer journey and are using this data to provide more relevant product offerings. Naturally, such improvements would lead to improved customer satisfaction and higher retention, referrals, and revenue.

New Products and Services

All the effort going into developing new products or services is futile if you don’t have the right data to drive your development. Data fuels the research side of research and development, making it necessary for strategizing and launching new products and services.

Launching a new product or service does not only include research about the product, but it also requires an in-depth view of customer preferences and behavior. Creating a product and then seeking customers who want it is a poor formula for business. The best innovations come when you find a need and fill it — by creating a product that solves existing problems or satisfies existing desires. Without gathering and looking at the data that reveals what truly matters to your customers, your attempts at innovation will fail. 

New Business Models

Just like launching a new product, you should also have an eye on IoT data while starting new lines of business. The data acquired through AI can help you optimize your business ventures by making sure that your models are in line with what the current marketplace needs. The advantage of AI is that it can examine vast quantities of data much faster and more efficiently than humanly possible, and thus uncover clusters and patterns that indicate previously hidden business opportunities.

Optimizing Operations

The use of data and AI in the manufacturing sector has greatly helped in optimizing operations and increasing efficiency. All the data acquired from connected devices can help limit downtime, reduce waste, and ensure business continuity. 

For example, by automatically examining historical and continuous data about equipment performance, AI can provide predictive analytics that recommends preventive maintenance, schedule optimum replacement schedules, and warn of imminent failures.

Decreasing Costs of Data Management

Data management and storage costs were at a peak during the initial parts of this decade, but these costs have gone down now and are more affordable for businesses of all sizes. The costs of managing data storage, maintaining bandwidth, and competing operations have decreased, now allowing data management to focus more on achieving outcomes than restraining budget.

How to Obtain Value

Everyone has seen success stories of organizations that have used data to optimize their processes. The business potential that can be unlocked through IoT is clear. That’s why so many organizations are now investigating how to unlock value from this vast environment of data. Here are the keys:

Have the Right Setup

To obtain value from data around you, you need to have the right setup. First, you need to have people working for you who have the right skills. Whether you hire new staff or upskill your existing team with training in data and analytics, the people handling your data should have sufficient knowledge and, ideally, experience in data management. A poor employee training or recruitment policy can hinder your progress. 

Secondly, the technology you choose is important. Keep an eye on IoT industry trends and then examine and implement the latest and emerging IoT technologies. 

One of the trends that are currently being followed by organizations is the move away from the cloud toward edge computing architecture. Edge computing not only carries all the benefits of the cloud but gives you additional feasibility in the form of real-time analysis that’s accessible from anywhere. Data governance is also easier with edge computing.

Gather Outcomes from Data

Once you have the data, what will you do with it? Gathering actionable insight from your data is what makes it valuable. This process requires fast computing power. Analytics can help you identify a use case for the organization. The use case can come in handy for identifying the possible path you should follow for gaining positive and sustainable business outcomes from the data you possess. 

Managing Hindrances on the Path to Value

There are numerous hindrances that you may encounter on the path toward finding value with your data. Here are some issues you may have to overcome: 

Data Surges

As data increases with time, you will need new technology and storage to support the needs of your growing data. While there are advanced storage technologies available in the market, they come with advanced costs, as well. 

Additionally, extracting value from data can become hindered by the conundrum surrounding data ownership. Companies that own the data they are working with are better positioned to extract value from it without contest from third parties. You must also remain compliant with all regulations, including GDPR, concerning data privacy and collection methods.

Most of the legacy systems in place within organizations are insufficient for working on the huge amounts of data made possible by IoT. While updating the skill sets of their labor, organizations will also have to update these legacy systems.

Governance and Security Risks

There are certain risks that come with IoT, which you should know. A three-stage risk mitigation goal you can follow includes: 

1. Protect device security 
2. Protect data security 
3. Protect individuals’ privacy 

These three layers were suggested in a report by NIST, which advices, “Organizations should ensure they are addressing the cybersecurity and privacy risk considerations and challenges throughout the IoT device lifecycle for the appropriate risk mitigation goals and areas.”

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Opening Up the Doors to Value

In conclusion, this recent surge in IoT has given organizations a golden opportunity to extract value from their IoT data. This opportunity demands new skill sets in data, backed by analytics and innovative thinking. While extracting this data, companies are also required to manage their IoT risks to protect their devices, their data, and their consumers. The potential for gaining value from data is exceptionally high now, with IoT still in its nascent stage. Simplilearn's Big Data Hadoop Certification course is designed to give you an in-depth knowledge of the Big Data framework using Hadoop and Spark. Learn more about gaining insights and training in data, analytics, business intelligence, and other IoT related fields by visiting Simplilearn now.