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The old adage ‘turnover is vanity, profit is sanity’, rings true in multiple other areas. A similar sentiment is heard in golf, motorsport and many others that I can’t even think of – Vanity vs Sanity.

It can also be applied to data and would go something like this… ‘volume is vanity, actionable insight is sanity’. This is the point right? There is simply no point at all in hoarding huge volumes of data. We hear things like ‘data is the new oil’, putting the importance on volume but also quality. But the truth is there is no point to data if it can’t be used to create value. Data must drive action otherwise it’s is simply, well, vanity.

With the Internet of Things seen as a means of collecting new levels of data, connecting billions of ‘things’ collecting and streaming huge volumes of data to businesses of the future, the question of how this data will be used to drive action is becoming ever important.

Converting raw data into actionable insights

A data output from an IoT device will read something like: {“ID”: 1, “IMEI”: 123456789012345, “DATE”: 1559309199, “LAT”: 52.246292, “LONG”: 0.412697}.

Clearly, this data is completely useless to us as human beings (unless you are proficient in one of the many coding languages). So first and foremost, data needs to be interpreted. But even then, it would just be a dot on a map with a temperature reading, etc.

To convert this string into actionable insight, other inputs are needed. For example, where is that dot in relation to its destination? (if it’s travelling) or is the temperature too hot for the product? All of this is achievable through software and algorithms. Physical places can be input and algorithms help to provide insight as to how far away a sensor is, the sensor can be allocated to particular inventory so it’s clear what is being monitored, helping to give more meaning to temperature, etc. and thresholds can be input stating a tolerance range.

Now, the initial data string could mean that the sensor (and more importantly, what it’s sensing) has arrived somewhere, gone over temperature, etc.

Sweating Data

Ok, so we’ve all heard the phrase ‘sweating assets’ before right? Well, data is an asset, the right data is an even more valuable asset and the beauty of data is the asset value can grow over time as the same data is repurposed and used to drive other insights.

In the example above, we show how the use of sensor data can be used to provide an actionable insight such as something being successfully delivered. In this example, the value of the raw data increases.

Going one step further, that same data that can be used to ‘clock in’ an asset such as the supply chain handling unit carrying the inventory. Now, the asset is recognised as ‘dwelling’. When that asset leaves that particular site, be it and depot or a store, it will have recorded a total dwell time. Same data, two applications.

Moving further still, that same data can now be stored (as dwell time) and used in the future to help build historic trend analysis to help business predict utilisation and better manage their assets.

Separating the wheat from the chaff

So yeah, volume is vanity, actionable insights are sanity. The challenge for IoT solution vendors is to turn the huge volumes of data collected into actionable insights, providing real value to end users. To filter through reams and reams of data volume, picking out the good bits and using that data to grow value.

But surely data volume is useful for say AI companies? Well, yes and no. Volume has the potential to paralyse companies. Highly skilled individuals sorting data into the appropriate data sets to analyse can be hugely damaging to productivity.

Entopy turns data into actionable insights. The notification centre will provide alerts via push notifications to tell operators when action needs to be taken. It provides analysis of productivity and trends giving a real-time picture and historical data points to add context. Over time, these insights will move to become predictive, using past data to help predict what will happen moving forward.

Not only this, Entopy has developed an API suite that enables the extraction of raw data but critically, the extraction of processed data after it has gone through our engine. This enabes dwell time analysis the be extracted and could be a very powerful tool for AI vendors for example. This will save huge amounts of time and allow business right across the spectrum to focus on what they are good at.

Interested?

Get in touch today: info@entopy.com


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