Over the past few years, there has been much hype surrounding the internet of things—both consumers and businesses strive to follow technological developments in the area of connected devices. But does IoT really merit attention, or is it just overhyped?
The IoT market is expected to reach a value of $6.1 billion by 2024 at a CAGR of 31.8% according to the Mordor Intelligence 2019 estimates. The global market is clearly in favor of IoT development and its potential to bring considerable benefits to the economy. One component of growth in the IoT market is the combination of IoT and big data—IoT data analytics.
Simply put, IoT data analytics is the analysis of huge data volumes generated by connected devices. Organizations can derive a number of benefits from it: optimize operations, control processes automatically, engage more customers, and empower employees. The combination of IoT and data analytics has already proven to be beneficial in retail, healthcare, telematics, manufacturing, and smart cities. However, its true value for organizations has yet to be fully realized.
At least a decade ago, it was exceedingly difficult and expensive to analyze massive volumes of information provided by a variety of connected devices. As time goes on, the cost to store data is going down, and analytics capabilities are making huge leaps forward. This creates favorable conditions for organizations to start investing in and implementing IoT data analytics.
As the accessibility of IoT data analytics grows, more and more organizations are seeing the benefits of having it. Widely-known companies such as Microsoft, GE, Amazon, SAP, and Salesforce have already started implementing IoT data analytics into their day-to-day processes.
A huge variety of devices connect to the internet and share data through sensors every day. This data is worthless without analysis. However, with an IoT analytics solution put in place, the data that organizations produce is effectively collected, analyzed, and stored. As a result, it allows organizations to optimize their operations at all levels, improve decision making, and achieve a number of benefits.
Some organizations install smart sensors throughout their facilities to collect data on employee engagement, performance ratings, and other work-related activities. This data is later used to improve day-to-day business operations and help utilize employee time and energy more efficiently.
As an example, Humanyze has developed a system that uses smart employee badges with sensors that capture more than 100 data points to measure the productivity of workers. It analyzes how people interact, how much they gesture or listen, and what their tone of voice is. At one point, this data helped discover that bringing call-center workers together for lunch at the same time instead of staggering them so that somebody is always available to answer the phone, significantly improved productivity due to:
If IoT data analytics is evaluated and implemented properly, it can have a positive impact on employees’ productivity and overall business success. However, there is a privacy concern: Accenture reports that only 32% of employees consent to their company using their workplace data, and 55% of businesses don’t ask for consent.
The combination of IoT sensors and data analytics may help companies, especially in the manufacturing industry, to determine when equipment requires maintenance by measuring vibration, heat, and other important figures. Smart equipment can also send messages to operators about potential breakdowns, wear, and delivery schedules. This not only facilitates regular equipment maintenance but also contributes to predictive maintenance.
Sensor data is used to predict when assets need to be serviced, which allows maintenance to be scheduled at the optimal time, thus reducing breakdowns and saving maintenance costs.
IoT allows workers to see exactly how their machines are performing in real-time, and alerts them to any issues that might be arising. Being able to prevent unscheduled downtime by using predictive maintenance can provide significant benefits. According to PwC’s Predictive Maintenance 4.0 study, utilizing predictive maintenance can reduce costs by 12%, improve uptime by 9%, and reduce safety, health, environment, and quality risks by 14% on average. Additionally, it can extend the lifetime of an aging asset by 20%.
With IoT and analytics working in tandem, organizations can automatically control processes that previously could only be tracked manually. For example, it gives manufacturers a comprehensive view of what’s going on at every point in production. This allows them to maintain a continuous flow of final products, identify bottlenecks in real-time, and avoid defects. It also reduces the risk of human error.
General Motors, for instance, monitors humidity with IoT sensors to optimize painting. When conditions for painting are unfavorable, they send the detail to another place with more appropriate humidity levels, thereby reducing downtime and the need for repainting.
When another major manufacturing company, Bosch Rexroth, started utilizing IoT, they saw a significant increase in productivity of both workers and equipment.
Be it a retail shop or a healthcare center, each organization strives to create a better and more personalized customer experience. The implementation of IoT data analytics can help with this onerous task. IoT data reveals a wealth of customer behaviors and preferences that can be analyzed and used to predict customer needs.
For example, when a customer enters a store, the IoT data analytics system can guide the shopper to the jeans they have been looking at online. It can also send them a personalized coupon to make the purchase in-store that day. In addition, retailers, restaurant chains, and makers of consumer goods can use IoT data to do targeted marketing and promotions.
In healthcare, hospitals can use real-time IoT data analytics to manage increased patient traffic and improve general operational efficiency.
This is beneficial to both parties; consumers gain more value through convenience and time saving, while organizations increase their revenue and stay more attractive to customers.
IoT data analytics can certainly provide benefits in many business areas, like reducing maintenance costs, avoiding equipment failures, and improving customer experiences and human productivity. But despite the proven benefits of applying IoT data, many organizations don’t derive value from their data assets simply because they don’t know what to do with the technology.
Also, sometimes employees get overwhelmed with the amount of data coming in, preventing them from sifting through it all and finding efficient ways of utilizing it. With multiple sensors providing information as frequently as every 30 seconds, it could result in data overload for the workers or the computers, if the right ones aren’t being used.
Other possible barriers to IoT data analytics adoption include security issues and high costs. Since it requires multiple machines and devices working together and exchanging information, if one system is subjected to a security breach, it could spread throughout all systems.
Additionally, because IoT data analytics is still fairly new, the implementation costs can be high. This can deter business owners from adopting it, especially if it is difficult to see the long-term benefits of making that investment.
At a time when organizations are looking to gain a competitive edge, many are starting to look toward the internet of things. It offers an opportunity to gather even more information than before, which can improve processes, drive innovation, and enhance customer experience. While it hasn’t reached every corner of business and operations yet, it is already being used to make workplaces safer and more efficient.
Having the ability to receive diagnostic and predictive data in real-time can be a game-changer, especially for companies who rely heavily on their equipment working properly and at full capacity. IoT data analytics allows workers to schedule downtimes that are convenient or know exactly what is wrong without having to bring in a technician to examine the machine. That all adds up to a less expensive and more efficient operation.
IoT data analytics can also be used to make customers happier and enhance their shopping experiences. By gathering data on the preferences of their audiences, companies can give customers what they are looking for and even know how much they are willing to pay for it. It can also gather useful data from product reviews, giving companies a better idea of what their customers are looking for or would like to see done differently.
Even though there are still significant challenges to overcome, IoT data analytics continues to grow and gain popularity. It has the ability to offer unprecedented insights that have never before been so readily available. It is reasonable to think that we will see a time in the near future where the general consensus is that its pros outweigh its cons.