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The Internet of Things is all about connectivity; connecting your assets to the internet, connecting your employees, connecting workers to the assets, and connecting you to your customers. That’s a lot of connections. What drives these linkages?
Data, of course. Data is inherent to your IoT system, and the data collected can make or break your project’s success. But data without any context is meaningless. Without specific functions or particular business decisions in mind, your data won’t effectively capture IoT’s real value.
Enter analytics. Analytics is the driving force behind IoT systems. Without a precise analysis of the data, it may as well be going straight into the bin because you’re not using it to its full advantage. But how do you figure out what analytics you need to create meaningful business decisions?
You might be inclined to jump ahead and think about how you take all this raw data – from logs, applications metrics, and device data – and turn that into actionable insights through a lengthy automation process. You wouldn’t be wrong to think this because this is another step in the IoT journey.
Before you dive into the specifics of data collection, you must have a clear strategy in place first to tie your project together. As you collect data, be it telemetry or images and video, you need to have a process that caters to the demands as it grows because your data will inevitably grow and provide you with further insights.
When we set out to create an IoT project with clients, we must first look at the organization’s overarching goals to ensure the analytics we run on the data produces the results we need. Before getting carried away, you must first figure out what you want from this project, what stakeholders want to improve in the business, and how this can be mapped to current company processes.
By clearly defining what you want to achieve, you will be less likely to steer off the right path. If things aren’t going according to plan, you’ll know to revert to other areas because you have the right strategy in place.
1. Reduce Operating Costs
Heating and lighting, power, and demand charges all add up in the operational costs and, over time, can drain companies of profits. These ongoing challenges are vital for IoT adoption within all organisations because the data provided can almost instantaneously highlight problems.
By calculating how much is spent or wasted on your buildings’ energy, you can quickly put steps in place to eradicate or lower these costs. Implementing ventilation control systems and light and heat controls are one of many outcomes for securing overhead expenses.
2. Mitigate Risk
Predictive maintenance is a big buzz word in the manufacturing industry right now, and for a good reason. By adopting a maintenance system that ensures machines and equipment are only assessed on an as-needed basis, organisations can save millions in unnecessary spending. A maintenance programme provides you can predict the likelihood of machine failure even before there are signs of wear and tear, so you can save downtime and continue to produce your goods and keep customers happy.
3. Increase in Revenue
For many IoT projects, starting small to play the long game usually works best for companies. The first project could involve collecting data, then add analysis to begin aiding critical decisions. Focusing on revenue comes even further down the line but should be considered from the offset.
Through big data analytics, you can not only monitor your machinery and environment to reduce overheads or make predictions, but you could begin tracking customer usage of your products. This new revenue stream can allow you to build on data you already have, such as demographic or time information, to lease out products rather than selling them outright. Therefore you have greater control over these products and can get more value for money instead of selling them off as one item. Airplane engine manufacturers have started doing this, where they lease their engines instead of selling them outright and only bill on usage.
Although you might aim to have a system that turns the lights on in your building when workers walk in, you should be digging deeper with your analytics. At what time of day are the lights used the most? Do you need the lights on in all areas of the plant or room? When you start to get resourceful with your analytics, you’ll be surprised with what you can find.
Democratising your data and analysing it for the given context while also making it available for more of your shareholders and customers to use will help your organisation get more out of the data they create.
The additional data provided by IoT only enables organisations to generate real-time insights that benefit them in the pre and helps to foresee future business trends in advance. Of course, it matters what data you bring into the business in the first place, but if you can match your critical goals with an analytics strategy, you’ll reap the rewards of a fluid IoT system.
Brian McGlynn, Davra, COO
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