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The following article was published in our article directory on October 18, 2019.
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TAPPING SOURCES OF ANALYTICAL VALUE FROM IOT DATA

Article Category: Advice

Author Name: Kumar Singh

It should be stale information to you by now that analytics can add value in a multitude of areas within your organization. This also extends to Industry 4.0 ecosystems, where the real value is in leveraging the data that is generated by the devices. The initial step, before you start applying analytical methods on this data, is to understand what are the opportunities to create value using this data.

In this article, we will explore few sources of value that can be explored leveraging IoT Data.

Optimize your customer expereince: Condensing data transmitted from connected products to feed into actionable insights can create instant value for companies, including manufacturers, their customers and their customer's customers.

This can take personalization and customer segmentation to a whole new level, thereby directly leading to increased sales and revenue.

Optimize your product performance: A connected product, bought to life by software, can offer much more value than non-smart hardware.

A good example is my Rachio sprinkler system. Having used it for one season, I can't imagine using the version I had earlier. Not only it decreased my water usage by 60% (monitors weather, local soil saturation etc.), it also provides me functionalities that only a smart system can do. It also provides me historical analytics that can further help me fine tune water consumption in my yard by zone.

The key here is to define the value optimally, for each manufactured product.

I have created a framework for this that I will share in a seperate article.

Optimize workforce : Iot data can help with human resource management in Industrial sectors. On top of these workforce benefits is safety. Wearable tags reduce safety issues in Oil and Gas industry Similarly utilities companies can use data from monitoring sensors to forecast pipe ruptures, keeping engineers safe.

On top of workforce benefits is workforce efficiency optimization.

Applying analytics to worker tags data can not only increase safety but also optimizes oveall downtime by better optimizing complex field intervantions.

Optimize operational efficiency: This is obviously one of the most touted benefits of applying advanced analytics to raw IoT data. As an example, consumption of water, energy and raw materials can be fine-tuned to a minimum by applying data analytics, while logistics fleets inside and outside manufacturing plants can be brought to maximum productivity and machinery cna be maintained according to efficient schedules.

Optimize product and services portfolio: Data generated by IoT sensors allow your to create new value propositions. I have posted about this earlier on linked so reproducing that post below:

"The power of IIoT gives manufacturers a chance to offer Analytics based services around their physical hardware.

While companies are begining to draw more and more accurate conclusions from data insights produced across their own functions and processes, the time is ripe to take it to next level.

Leveraging IIoT, they can gather data insights from products being used in the field, translate this into services and make this a mainstay of their value creation. Nothing is off the table – even something as simple as a Toothbrush. IIoT enabled brush can capture your brushing habits like frequency, duration, motion etc. and then every 3 months a dentist emails you feedback on your brushing habits. Imagine the kind of premium this value add service can allow you to charge on the MRP of the Toothbrush.

Give me any manufactured product and I can tell you an associated IIoT generated data based value add service. What this means is that opportunities are unlimited. Organizations that make the first move on this will have the benefit of collecting more data in the form of customer response and feedback, further enhancing their offering and will therefore always maintain a first mover advantage."

Keywords: Analytics, IoT, IIoT, Manufacturing 4.0, Industry 4.0

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