The Data Age: The New Industrial Revolution

Eleanor Barlow

We are currently in the middle of a data revolution so immense that if you research data analysis, the plethora of information readily available can be a little overwhelming. It is evolving everything we do, so it is important that businesses embrace it with open arms and strategic minds.

Data connections.

Our data age is, arguably, comparable to the Industrial Revolution in its impact and foreseeable imprint in history. It is providing new wealth, successes and change on a monumental scale; perhaps this nervous anticipation was felt by the Victorians when they were on the precipice of the movement?! The data age is so huge that it comes as no surprise that Data Science has been coined ‘the sexiest job of the 21st century’ by The Economist (but we already knew that!).

In years to come, human civilisation will look back on this era as the catalyst of when the lines between physical and virtual worlds blurred and allowed the first to have a phenomenal influence on the second, and vice versa. Faced with the wealth of available data, organisations are now capable of so much and are able to propel themselves in the marketplace.

However, this new data era is, perhaps, confusing. It might be because, on the surface, it appears so similar to what has been firmly established in business management for years. Businesses are aware of data analysis on the whole, but not the differing types of data analysis and its capabilities. We have been using some form of data to support our market and consumer insights and thoughts for a while now, and these have been consequentially informing our business decisions; however, as our technological abilities and data evolve, it makes sense that our analytical processes do too.

Data Collection 

With the introduction of Artificial Intelligence and Internet of Things, our capabilities are expanding at a rapid rate; something that would not have been imaginable when such data analytic technology was first conceived. With the assistance of smart technology, we are able to collate big data faster, on multiple servers located anywhere in the world. We also have access to data forms we previously could not access- such as voice and video. A wealth of qualitative data can be categorised easily through the help of automated programs where vital and relevant information is selected through a process of pinpointing keywords. Applying the data through a lens, qualitative data analysis can tell you pretty much everything about anything.

Our technology now allows businesses to connect to physical and virtual worlds in real-time and react swiftly. In addition to collating data that provides an in-depth profile of an individual customer, allowing for personalisation to be easily achieved, and subsequently predict consumer behaviour, businesses can also use this process to assess the comments of their competitor’s customers in order to understand how they feel and, consequently, win them over. It really is an exciting time to get your teeth into data analysis!

girl biting into an apple

Qualitative data analysis is, however, still a relatively fresh idea. As a result, it is frequently misunderstood and undervalued by many businesses on how to effectively implement it into their infrastructure. Subsequently, leading businesses to ineffectively utilise the power of data. 

Another trap that many fall into is thinking that simply collecting the data will somehow automatically improve their business. Some wishful thinking there! This is because data collection is relatively easy to do (if you have the right tools in place). However, in order to gain worthwhile insights from the data, it requires specialists with the expertise and technical capabilities to review the information against the business objectives. Even if you have the best data collection available on the market, human input is imperative to get the full value from the process.

(Read ‘The Cruciality of Due Diligence and How to Train the Machine‘ for more information on data collection and how to get the best insights). 

Steam Industrial Revolution

Much like the new machinery of the Industrial Revolution required people to work the machines and utilise idea generation in the creation of products, the data analysis process needs people to monitor the programs, ensure the accuracy of the inputted data and conduct the analysis on the data findings. As helpful as computers are, human input is needed to understand consumer emotions, drives and behaviours so that appropriate strategies can be devised.

We forget, as smart as technology is, it isn’t capable (just yet) of the same way of thinking that us humans are. The amazing thing about technology is that we can collaborate with these powerful machines to expand our capabilities further than ever before. If the human mind is not put into the equation, however, the process is utterly worthless. Most importantly, qualitative data analysis thrives when there are specialists trained in this area of study and know what they’re looking for. Without experience, many outside the field of data analysis, fail to pick out the relevant information under the mountain of data (and trust us, there is a lot to wade through!). 

Many believe that big data has more insights but, in actuality, it just means that there are more hay stacks to wade through in order to find the needle. Additionally, these experts have no bias, thus ensuring the insights are reliable, constructive and not influenced by the status quo.

Here at Pansensic, we specialise in qualitative data analysis, working on projects for a range of clients across a multitude of industries. We understand the importance of data analysis in the development of not only the business world but civilisation as a whole, and this is why we are always at the forefront of developments in the field. 

We don’t just summarise data, we provide a real depth of insight that is more granular, more accurate and more actionable to companies all around the world. 

Get in touch with us today, ask for a demo, or just have a chat, to see what our data analysis can do for you. 

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