Data Analytics Enhances Enterprise Wearable Devices

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4Q 2017 | IN-4832

Data analytics provides companies with insight into the data that devices and sensors collect, rather than just providing a long stream of real-time raw data. This raw data is often overwhelming and does not provide a company with any actionable information. Data analytics adds value to this data by showing correlations between data points, making predictions on what will happen based on the current data, and prescribing actionable measures that allow the company to prevent, mitigate, or ensure an outcome. As the presence of wearables within the workplace continues to increase, so does the amount of data that they collect. Companies are now looking into how to get this actionable analyzed information from wearable devices, alongside the other devices and sensors that are in use.

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Wearable Data Analytics Provides Companies with Actionable Information

NEWS


Data analytics provides companies with insight into the data that devices and sensors collect, rather than just providing a long stream of real-time raw data. This raw data is often overwhelming and does not provide a company with any actionable information. Data analytics adds value to this data by showing correlations between data points, making predictions on what will happen based on the current data, and prescribing actionable measures that allow the company to prevent, mitigate, or ensure an outcome. As the presence of wearables within the workplace continues to increase, so does the amount of data that they collect. Companies are now looking into how to get this actionable analyzed information from wearable devices, alongside the other devices and sensors that are in use. 

What Insight Analytics Brings to Enterprise Wearable Data

IMPACT


Different types of wearable devices collect different types of data. Often this raw data is only useful to show the user current readings, but data analytics provide further information, such as how the readings have changed over time, when a dramatic difference is detected, what will happen in the future, and how to change this. There are many insights that data analytics can bring to enterprise wearables, including:

  • Patient Vitals – Wearable devices are often used in healthcare to track patient vitals. Without data analytics, healthcare professionals are faced with long streams of real-time vital information from a large number of patients. Data analytics helps to predict if/when a patient’s health will deteriorate based on subtle changes in their condition, and sends alerts sent healthcare provider when necessary. With access to this information, healthcare professionals can treat the patients most in need of care quickly and potentially avoid fatal health deterioration.
  • Worker Fitness – Wearable devices that collect fitness data are increasingly being used in the enterprise area to track activity levels of work, either for health insurance purposes, to track their health or to ensure that workers are productive. In the latter point, data analytics can determine how much work an employee will complete throughout the day at their current activity levels and provide insight into how to improve their productivity. This ensures that the workforce is efficient and completing the work that is required.
  • Workflow – Many wearable devices offer workers the ability to log the work they have completed. While this raw information is useful to the company (as it shows what work has and has not been completed), data analytics gives the company insight into how to improve productivity. Analysis of the data identifies how long it will take to complete a set number of tasks at the current rate, and how to adjust the workflow to reduce the time.
  • Marketing – Retail companies use data analysis from customers’ wearables to provide them with personalized offers. For example, if data analysis of a customers’ fitness trackers shows that in general, he or she is more likely to be active at lunchtime, personalized offers could be sent to encourage the user to walk to the store. These offers can also be more personalized based on analysis of individual shopping habits, with offers and recommendations being sent directly to the user when they are near the store. This helps to increase sales and improve customer satisfaction.

The Future of Enterprise Wearables and Data Analytics

COMMENTARY


Wearable devices are becoming more popular within the enterprise market due to their ability to provide workers with access to hands-free information and communication. This hands-free form factor saves time, preventing workers from needing to access a separate device, which helps to improve productivity. As the benefits behind this technology continue to become more well-known, an increasing number of companies will look to adopt wearables to aid workers and improve productivity. This will lead enterprise wearable device shipments to increase to nearly 118 million in 2022, up from 38 million in 2017.

As the number of wearable devices increases, so will the amount of data that they collect. Companies adopting the technology will look to find ways to gain further benefits from the devices and their data. As data analytics can provide more actionable information, allowing vital business decisions to be made quickly, more companies adopting the technology will consider the possibilities of adding this further layer to their solution. The companies that offer the analytical capabilities, such as Catapult Sports, Emu Analytics, Sentrian, and Vivametrica, will investigate how to improve their offerings moving forward, entering into partnerships with vendors and clients to create custom made solutions that provide clients with what they require.

Due to the potential fragmentation in this space, more data companies will offer clients the ability to combine data sets from numerous different types of technologies, devices, and sensors, to provide a complete solution. Data monetization will also become more popular, with monetary benefits including those indirectly associated with improving productivity and workflow, as well as the ability to sell data collected from devices to provide others with information into user habits.

At its core, wearable data analytics is another way of looking at wearable devices and the potential value they bring to users and implementers. The direct benefits for a consumer are well-understood, and the benefits for an enterprise worker are catching up in familiarity, but the long-term benefits of the data collected during use is less explored. With the enterprise wearable device adoption uptick ongoing, the capability and value of both direct device usage and its associated data compounds. 

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