In the age of the information economy, data is the most critical asset of any enterprise. Between 2015 and 2018 Big Data adoption in enterprises soared from 17% to 59% – but the amount of unstructured data generated can mean companies becoming overwhelmed and not knowing what to do with all of this potentially valuable information.
We say ‘potentially valuable’ because it is only valuable if it is effectively analyzed and then used to support your company’s ambitions. According to Gartner, fewer than 50% of documented corporate strategies mention data and analytics as fundamental components for delivering enterprise value. But, Gartner also predicts that number will rise to 90% by 2022 , as more and more companies understand the critical role of data as an asset and analytics as a competency in taking faster and more reliable decisions.
Knowing what to do with the data generated by your IoT solution can mean the difference between moving ahead of the competition or falling behind.
Where to Begin
Understanding and identifying what data you require is the first step in creating a successful IoT deployment. Depending on your needs, once you have that raw data you need to unlock its value, which means managing it, and then combining it with other data, such as product, sales, or customer data, as well as environmental data.
You then need to ask yourself how your business is performing. By analyzing your data, you can quantitively describe one or more functions of your business. The insights you get can be a key input for you, as a company, to improve processes and decisions. Using data in the decision-making process means you’re taking better and more efficient decisions because your decisions are fact-based – and no longer based on assumptions, instinct, or previous ways of working. You improve your business based on the knowledge you’ve unlocked from your data.
Do More with Your Data
Data isn’t just about fact description, though – it’s also about predictions. Predictive analytics are set to be the most common IoT data analytics use case, reflecting a gradual shift in emphasis from basic data preparation to actionable insights.
According to a recent report from GSMA Intelligence, while the majority of current IoT deployments use IoT data analytics, it is mostly used for data management and discover to perform basic statistical analysis. As companies expand their IoT deployments, though, the potential for data analytics lies in extracting targeted business benefits.
Take a company that needs real time data, such as a healthcare solution. A patient wearing a connected medical bracelet or wristband, for example, will generate data that allows you to start looking for patterns of usage and behavior. You can then begin making predictions and then take actions based on that data, whether it’s an alarm citing an emergency or addressing health patterns that need to or should be corrected.
Even more interestingly, particularly if we’re talking about healthcare, is data gathered from a wide swathe of people – this can be used for research purposes, which in turn could lead to medical advances.
Another example could be fleet management. Real time monitoring tells you things like location and travel routes, but data will also help you improve your processes, which means not just getting data on things like fuel consumptions, safety, and number of stops, but also to optimize things like employee schedules and vehicle maintenance. When it comes to public transportation companies, data is used to optimize route planning and keep the public informed in real time. From a longer-term perspective, a lot of planning and processes can be improved.
The long-term predictive possibilities are nearly endless: agriculture data allows you to see patterns in weather and climate over a number of years, while a utilities company can look at peak and valley usage.
The data generated by IoT has enormous potential to transform your business and relying on the knowledge built from data is crucial to being on top of the market’s changing demands. With analytics impacting everything from product development to identification of unmet demand and supply gaps, workflows and process are being transformed. This could be anything from operations management systems to hospitality companies using what they’ve learned about customers behaviors to improve sales and marketing operations.
IoT data has to be looked at in relation to other sources of data, and each data set has to be analyzed not just on its own but as part of the larger picture. By taking a deep look into everything in their current architecture and then defining how data will be integrated into their existing setup, companies can do anything from enhance pricing and user experience to optimized lead generation process, improve customer efficiency, and limit production downtime.
Why data matters
Having a clear data and analytics strategy is crucial to getting value from collected data. In order for companies to not get lost in the process – simply collecting data without knowing what to do with it – they first need to ask:
- What do we want to achieve with data collection?
- Do we have the resources we need to do this?
- How will we turn our data into insights?
- How will we govern the data in our company?
At the end of the day IoT is all about the data and what you can do with it to enhance your business. Having clear strategy will help you get most from it.