The Internet of Things (IoT) is essential in today’s modern, digital business world. According to a recent study, IoT implementation is a top priority for the large majority (98 percent) of businesses. In fact, 25 percent of them said it was the most important initiative, even above boosting production capacity, upping revenues or launching new products and services.
However, successfully implementing and integrating IoT into a business is easier said than done. In the Vanson Bourne survey, 90 percent of respondents admitted that their organization is seeing challenges and barriers.
Below are the top three common pitfalls that hinder successful IoT implementation—and how organizations can take the steps to overcome these barriers effectively:
1. Failure to Establish a Clearly-Defined Business Case
It’s important not to implement an IoT initiative for its own sake. To derive real business value from an IoT initiative, you need to build a identify a compelling case for why an organization needs an IoT program. This helps the organization to discern what the ultimate goal for the program is (e.g., boost efficiency, productivity or profitably) and which data is the most important to look at—otherwise, it’s hard to identify what success with the initiative looks like, to measure progress towards the initiative’s goal and to figure out what is working or what needs to be changed in order to complete that goal.
2. Lack of Appropriate Staff
IoT requires a team comprised of a mix of experts across IT and operations to work together. While each member has a vested interest in leveraging IoT to help the overall business, their various backgrounds (technical, operational, management, etc.) will help to answer key questions regarding the goals and objectives of the IoT deployment, how the team should approach the deployment and what constitutes success. The best teams have an equal mix of those who have deep technical knowledge and those who have an intimate understanding of business processes and the company’s bottom line objectives.
In fact, many organizations are now creating centers of excellence (CoE) to support the progression of their IoT implementations. At its core, a CoE is a central governance structure that provides leadership, best practices, and support for any business initiative. A CoE also allows these disparate technical and operational groups to quickly align on the initiative and openly collaborate, discuss and sort through any roadblocks or challenges along the way. Once the individuals who should be involved with the IoT initiative are determined, it’s wise to set up a CoE right away to make sure the program stays on track and delivers the best results possible.
3. Inability to Connect, Gather, and Understand the Data
Everything in the IoT ecosystem has value. From internet-connected forklifts to wristbands and smart buildings, each possesses layers of data. In order to derive any sort of value from the vast amount of structured and unstructured data generated from connected equipment, organizations must have the correct systems in place to ensure they can collect, process, and subsequently act upon that data.
What often occurs when organizations start to undertake an IoT project is they assume device connectivity. In actuality, this is not the case, especially as more and more devices become connected and make the IoT ecosystem more complex.
To get a simple idea of how this might look, let’s consider a connected saw. As the saw functions, a certain pattern of current draw results each time it is used to cut. This can be used to calculate the number of cuts the saw has performed. When the business notices excess current draw, this can be an early indicator of the blade starting to wear. When this data is integrated into the business’s operations systems, it will trigger an event to order an additional blade to arrive in a timely fashion, avoiding machine downtime. Enabling the business to order on time is just one example of many where IoT helps improve overall equipment effectiveness. An additional example includes helping the machine operators optimize equipment performance by sharing insights derived from sensors and enabling operators to use the tool more effectively at optimal angles, temperature conditions, the right intervals, etc.
Another example would be to consider a connected motor. As the motor functions, the data collected from the motor’s sensors can let the company know when the motor is going to fail and predict when it will need to be repaired or fixed.
Now, imagine the same motor is installed on an elevator that’s been outfitted with its own IoT sensors. The sensors keep track of how often the elevator is used and which times of day experience greater elevator use. Using the combined data from both devices, the organization can schedule preventative maintenance tests based on when the motor will likely fail, and they can perform the maintenance at a time that would be least disruptive to the majority of people who use it.
As organizations add more devices to their ecosystem, however, what often occurs is that a variety of different solutions are required to connect all these pools of data together. As IoT ecosystems evolve, it’s important to leverage a comprehensive platform that enables data to flow between all connected devices. This enables business leaders to better parse through that data, to determine which data could add business value and then to integrate that data throughout the organization.
At the end of the day, the successful implementation of IoT boils down to intelligent data processing. The organization that understands exactly what it’s aiming to accomplish with its IoT initiative, which people are the best to work towards that objective and the importance of enabling device connectivity in order to identify and act on the right data will come out victorious.
Written by Yasir Qureshi, senior director of strategy and business development in the IoT and Analytics branch at Software AG.