Sitting on a pile of digital gold

Pause for a second. Think about your organisation; mentally visualise your processes and perform a quick inventory of all the data which you collect. It might be a scribble on a form or a record in a database. I bet that you have a lot of that. Now think more in-depth about your operations and at all the data which you are not capturing. It might include the list of people that walk into your shop or maybe the location of your delivery vans. I am pretty sure that you can think of loads of uncaptured data.

Did it dawn on you that you are sitting on a pile of digital gold?

And the worst part of this is that most probably, you are not doing much with your data. You might be generating a report here and there, but that’s pretty much it. Of course, this is a missed opportunity because only by measuring your processes can you manage them efficiently and effectively.

In this day and age, data is considered by many as being the new Gold because it is the primary fuel for our intelligent software. It is highly, pervasive; you can collect it from anywhere, and with the proliferation of digital devices, the availability of information is increasing. Just two years ago, 90% of all the data in the world did not even exist! Because of this, the problems we are facing today are various.

First of all, we are creating large volumes of data daily. Computers, wearables, mobile devices and all sorts of sensors are producing 2.5 quintillion bytes of data every day.

To visualise the scale of this, if we had 2.5 quintillion pennies, we could cover the entire surface of the earth five times! When you generate so much data, the issue shifts on how to manage it, and that is where Artificial Intelligence (AI) comes into play. The only way to process it is by using AI algorithms capable of digesting large volumes of data, identifying patterns and making sense of it.

As an example, take the manufacturing industry, having hundreds of machines operating at the same time. The amount of data which they produce is enormous.

Only an AI is capable of analysing it in real-time, propose prescriptive maintenance, predict future faults and optimise the running of the plant autonomously.

Second, not all data is adequate for computers. Around 80 to 90% of the data found on the internet is unstructured data, thus needing further processing before a computer can use it. Once again, even though AI is far from being perfect, it can manage to process this unstructured data automatically.

Stock traders monitor local and international news to try to predict fluctuations in the market. But there are hundreds of new channels, some of these are official while others are not. All of them use natural languages (like English, Spanish, Mandarine, etc.) which is unstructured and not understandable by machines. Because of this, AI systems can parse the different news feeds in real-time, translate the text, summarise it and extract the polarity of the news item thus giving stock traders a good indication of the market’s reaction to the particular news item.

Third, one of the internet’s most significant malaise is the lack of reliable or trustworthy data. Here too, the only way to check this data is by using automated techniques.

Newspapers need to harvest stories from various news sources, and it is not always easy to distinguish between fake and real news. Automated systems are capable of doing so with a high degree of accuracy. They can quickly identify the source of the news items, compare it to a list of reliable sources, extract snippets from the text and verify its integrity through other online sources.

Fourth, the production of data happens at the speed of light. Furthermore, you would never have a single source of data, but you would have to deal with several sources of live data simultaneously.

Imagine if you’re operating a network of CCTV cameras. Having a human watching all the feeds is slow, boring, error-prone and tedious. But an AI can analyse the various feeds simultaneously 24/7 and in real-time, thus raising alerts promptly.

Fifth, data on its own has no value. In a world overloaded with sparse data sources, data only becomes valuable once we augment it with other information and use it correctly.

An automated traffic lights system isn’t much of use if it doesn’t have a camera monitoring the state of the traffic and deciding when to switch the lights. But the combination of a camera system together with intelligent traffic lights makes all the difference and saves commuters precious time waiting for nothing.

As you can see, data is critical in the world of today. We have seen how its use has made processes efficient, reduced errors and brought value to the organisation.

So if you are sitting on a pile of digital data, don’t let it gather dust because if you don’t use it, its a missed opportunity for your organisation. Its as if you have vast reservoirs of fuel, but you’re hesitant to buy a car.

Don’t lose time, consult with an expert, explore what you can do with that data, take the plunge and start boosting the engine of your organisation.