“Data is the new oil!”. There is probably not a single CEO out there who has not said this sentence before. In this blog post we want to give a little context to what this buzz-wordy phrase means and how we as a company use data insights to create business value.

In the first part of the essay we will look at general mechanisms of data-driven value creation. In the second part we will look into lidbot and how we use these mechanisms to create business value. First let us fully understand how data can drive monetary value for businesses. Therefore, we need to step back a little.

A few weeks ago, during my vacation in New York City, I came across a perfect example on how a company can use data: Amazon Books — a physical store of Amazon, selling books. The pure existence of these stores was astounding to me as book retailing was the very first industry which was digitized by the company back in 1994. By selling books online the company drove many bookstores into insolvency.

How Amazon Books uses data

Looking back the reasons are obvious. Online shops enable a much broader offering of products without renting tremendously large spaces in mostly expensive neighbourhoods. They also provide custom data-driven suggestions to customers (“If you liked this, you might also want this one”) to increase sales.

So why does Amazon suddenly open stationary shops — especially in one of the most expensive cities in the world? The reasonis: data! Apparently it does not need large book shops to fulfill customer needs.Amazon Books uses data to determine the books that aremost likely to sell in one particular store. The company has been around for ages and has collected a large amount of user data. Using this data, the company can create a slim and yet compelling offering of books in their stationary stores.

And you can see the influence of data insights yourself! I have been to two shops in NYC. Their collections vary in each location. Placed books are carefully selected by customer preferences in the neighbourhood. For example, the store in the shops of Columbus Circle (a huge luxury mall near central park) has — surprisingly — a huge kids section, while Amazon Books in midtown Manhattan offers a large collection of business books. Data-driven suggestions for customers are provided in the stores as well. Amazon Books also offers delivery of your purchase to your doorstep, in case you do not want to carry your bag around yourself.

All these innovations have one common goal: to provide the best customer experience within the smallest possible space.It sounds trivial but as it turns out you do not need to offer a customer hundreds of books to make him/her happy — just the ‘right’ one. With data, Amazon Books is able to decrease space and rental costs and subsequently increase its profits.

For most conservative retail companies all this sounds like science fiction. And yet, due to incredibly detailed customer insights it is a reality.

Data in the age of IoT

Until a few years ago, these data insights, at scale, were limited to customer-facing (aka B2C) businesses. From my perspective this rapidly changes with the (Industrial) Internet of Things (IoT). IoT is the sum of “objects with computing devices in them that are able to connect to each other and exchange data using the internet.” (Cambridge Dictionary). There is a popular misconception that business value gets created in IoT by connectivity alone — I disagree.

According to a study from Deloitte, value is created when information (read: data) is utilized to modify actions in beneficial ways. Ideally, this then creates a loop of further data generation that can be analysed again. The consultants call it the “IoT Information Value Cycle”.

In the IoT Information Value Cycle a business activity comes first. This can be anything from manufacturing goods to selling a product to customers. In our case, we are talking about efficiently emptying waste bins. In order to generate valuable data these analog activities are equipped with sensors. lidbot is an IoT hardware device that measures real-time fill levels of waste bins. We are using reliable, low-cost sensors that can easily beadded to waste bins. Data is generated with lidbot sensors.

This data is then analysed (typically in a cloud-based analytics engine) which produce data-insights. These insights, let’s say the finding that a waste bin is emptied to often, result in actions being taken (“data-driven decision making”). These actions then improve business activities and more business value is created.Of course, to enable data-driven modifications of business activities data, connectivity is needed in the first place.

However, business value is not created by data but by data insights that influence business activities. For this to work data integrity is an important building block. Therefore, we are deeply convinced of the IOTA protocol  –  a disruptive distributed ledger technology.

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