How IoT Aids in Monetizing Your Data through Predictive Analytics

How IoT Aids in Monetizing Your Data through Predictive Analytics

March 30, 2021

Tanya Surfian, Sr. Manager of Marketing & Business Development, JIG-SAW US

Business Advantage

One of the remarkable parts of our emerging world is we are finding more creative and innovative ways to be efficient. From electric cars and automation to things like VR and space travel, we have been able to transform the way that we live and interact. This type of forward-thinking has enabled us to focus on operational efficiency to optimize our profits and meet our strategic objectives with advanced technology.

When a product makes its way from the maker all the way to the hands of the end-user, there is almost always a long and very specific process involved. Whether it’s advertisement and strategy, machinery or skilled workforce, enterprises specifically invest a lot of time and money into getting this process right.

To be as efficient as possible, a huge factor to consider is the Internet of Things.  IoT is an exponentially growing industry that will continue to breakthrough in every sector of life. However, I am going to go into a specific area where IoT is growing extensively right now; predictive analytics.

Predictive Analytics Use Cases

When we extract information from things, this data usually sits in a database that oftentimes goes to no use. However, with the power of IoT and predictive analytics, we are able to put that data to use and make real-time business decisions that optimize profits.  Let’s go through some examples of how we can use predictive analytics to monetize data.

Predictive Maintenance
When you work in a manufacturing facility, as mentioned earlier, there is a very organized process to complete daily operations. This includes heavy and expensive machinery that is a key part to the entire process.

If a machine unexpectedly breaks down, business is disrupted, resulting in a hit to revenue and increase in costs. IoT can integrate into these machines and send critical data and information back to a cloud of the manufacturer’s choice.

For example, when there is pipeline damage, IoT technology can detect this and send an alert, triggering maintenance that there may be a potential failure. This can be looked into at the end of the day verses in the middle of operations where productivity halts and costs start to tally up.

Risk Management
Another major key to utilizing data and analytics is risk management. IoT allows enterprises to manage risk and analyze whether or not we move forward with things like a loan application, insurance or even stock bets. We are able to connect sensors and networks to be able to gain insightful data that can be grouped, categorized and analyzed for the strategic advantages of the business.

Key indicators that are either from historical data or current conditions are used to measure and calculate how an enterprise would like to strategically move forward. 

If we are able to manage our data to mitigate the risk involved in our operations, then IoT and predictive analytics become a powerful and valuable tool to an enterprise’s complex processes.

Demand Sensing
Businesses are implementing demand-sensing solutions to be able to understand and plan for changes in the market. There are many different reasons you would want to perfect your demand sensing. If the data is used properly, enterprises can minimize the number of inventory shortages or surplus of any kind.

Additionally, we can understand what promotions to use along with what areas will have a positive or negative demand reaction to key indicators. Naturally, this type of information will unlock the opportunity to make decisions that increase efficiency and thus maximize profits for the company.

There are two separate factors to understanding how we accurately estimate the demand for a given period or place. There are internal and external data factors to consider. Some internal data examples include, but are not limited to, current orders, promotions and customer service. We can also leverage external factors such as weather, competitors, and current events. With these elements we use machine learning and IoT to send data to a cloud, analyze it and come out with the best forecast of demand to use for real-time business decisions.

With everything considered, all the benefits of investing in IoT and predictive analytics are obvious. Ultimately, I think we can safely say that relevant and insightful data will always be the single most important factor to deeply understand how to improve daily operations and increase revenue.

Tanya Surfian leads marketing initiatives at JIG-SAW US – an IoT solutions company that helps enterprise businesses enable rapid development of IoT products. Our solution NEQTO, provides our partners and customers the world’s most versatile JavaScript-based edge processing & IoT device management platform.