Last week I published my new book: The New Oil: Using Innovative Business Models to Turn Data Into Profit. The book describes five Business Model Patterns to leverage the value of data in organizations. Each of these patterns is explained using the Business Model Canvas and illustrated by real life examples from companies such as Google, Nike and Samsung:

1. Basic Data Sales

Companies create data in their primary process, package this data into a feed and sell it in a single transaction or a subscription. One example is that of bank, selling benchmark data about financial transactions to retailers ("people who shop at your store spend, on average, twice as much at your competitor's stores in the same month.")  

2. Product Innovation

Companies create new products or services based on te data they generate in their primary process. One example is that of a car leasing company offering 'fleet management services' based on the GPS locations and other sensor data from cars.

3. Commodity Swap

Commodity providers offering their original products (electricity, water, telecom etc.) at a large discount or even for free but charge for services provided in combination with the commodity products. One example is that of a telco providing calls for free in order to collect data through smartphones on which it sells location based services at a premium.

4. Value Chain Integration

Two companies exchanging (usually sensitive business) data to integrate parts of their value chains in order to save money or optimize business performance. One example is that of a soda brand and retailer exchanging real time point of sale data in order for the softdrinks manufacturer to produce and deliver their goods just in time, saving money on inventory and logistics.

5. Value Net Creation

Multiple companies sharing the same customer exchange data in a 'value network' with the aim to provide unrivalled service to the customer. One example is that of an advertising agency coordinating the exchange of data from airlines and hotel chains to provide extreme targeted advertising, placing ads for available hotel rooms at exactly the destination and travel date of a traveller on pages he/she visits online.

The New Oil describes why data driven business models are relevant now, how the Business Model Canvas helps to identify opportunities and how the canvas and lean startup principles help your organization to get started.

The New Oil is available on The New Oil: Using Innovative Business Models to Turn Data Into Pro...

Please feel free to add comments and suggestions about the Business Model Patterns. I would appreciate your ideas and additions very much!

Best Regards,

Arent van 't Spijker


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A nice view on how versatile the BCM is. Basically this is a part of using the Capability framework. A Capability consists of four corners: People, Systems, Process and Info (Data). You can basically apply the BCM on any of these four pillars. People: how to get the best out of them and what they want to achieve. Systems: where they provide value, re-use, unbundle etc. Process: value of a process and who is involved, where it breaks down, and Info: Data as described in the article above/book.

Well done!

Hi Paul,

Thanks for your comment and compliment! What I find interesting in your capability approach is that data for some companies represents both the Data-aspect as well as the Systems-aspect. Since data can be used as an instrument to determine how or where to provide value, re-use and unbundle, with new data as a result. Int his way, data becomes a fluid asset: both the tool and the raw material. In y book I call this phenomenon 'Reciprocity'. It underlines both the versatility of data and its power to transform current economic principles.



Good food for thoughts!

I've been thinking how to conceptualize and explain the value of business data in general. A simple drawing would help, but I'll try to explain the idea.

Conceptually, I consider the business data to be an intangible resource for companies, which can cloned (almost) without variable costs, as long as the users of the data have means to access the data. The initial gathering and the maintenance of this business data require efforts and generates costs, which are fixed by nature and does not depend on the usage of the gathered data. Following this idea, financially the gathering and sharing of the business data make sense, if the reuse of the gathered data outweighs the effort needed to gather and maintain the data.

For example, if the initial gathering of the customer address data for 1000 customers would require 100h initial work effort and then yearly maintenance of the same data additional 10h/year effort, then we can calculate a break-even point for "investing into address data", assuming we also know where it is reused. Assuming this data is reused to process 1000 invoices yearly, saving 100h of manual work yearly of finding the address manually for each invoice separately, then we end up with break-even with little over a year. If we could reuse the same address data also to send out 1000 yearly marketing letters to the same customers, then the break-even point would roughly halved.

This kind of thinking enables business case calculations for master data investments, even when the master data itself does not usually create value directly, but only through the business activities where it is reused. Obviously, some sort of "IT" is needed to provide a shared repository for the data and means to access it.

This idea can be also embedded into the original business model ontology by defining the business data to be one type of an intangible resource and by assigning the "IT" the support activities of storing and providing access to the data, enabling the reuse of the data.

I guess I need to read the book, but I wonder if you have conceptualized the role of business data in some way?

Best regards,

Ville Alkkiomäki

Hi Ville,

Thanks for your reply! Your line of thought is correct but it will, in practice, have a hard time drawing management attention for the intrinsic value of data. You are right in the sense that data is an asset. However, you are trying to express that value by building a business case for improving existing situations (such as 'sending invoices') and management will usually check a business case on these issues by the technology supporting that improvement, rather than the data.

In my book I emphasise that data has value for new customers outside of your own company (eg. an insurance company can sell its analysed data on particular vehicle damages to car manufacturers who can then build safer cars). To do so, they can use the business model canvas to find new 'data driven' business models. My book describes five business model patterns for such data driven strategies. 

Senior management will much quicker acknowledge the value of data as a solution to somebody else's problem, which has a far bigger potential upside (economies of scale, just like you mentioned, data can be copied without much variable cost) than internal solutions.

Please let me know how you like the book and if it answers your ideas.


I totally agree with difficulty of the concept and that is the very reason why I'm looking for concrete examples with real numbers and euros. There are some persons also in the senior management, who understand the idea, but it might be worth trying indirect approach through customer-centric questions to identify also the in-house value of data.

However, I can image how that discussion will end up with further business opportunities in providing full services instead of just data. (Selling an invoicing service instead of address information for invoicing)

But whether the problem being solved is in-house or customer's, you still need to understand how it creates value. Even data is easier to sell, if you know what it can be used for(?)

Anyways, I guess you have sold at least one book. :)

- Ville

Hi Ville,

Thanks ;-) And I would appreciate to learn how you liked it once you've read it. Feel free to contact me.



Hello again,

I was hoping to find at least some examples from the book how data is used by companies to make profit, but the book turned out to be an encyclopedia on this matter. :)

Good book and definitely worth the money!

- Ville

Hi Ville,

Thanks for the compliment! I'm glad I could be of help.

Could I ask you to write a short review on

I also regularly post articles about this topic though Twitter via @avantspijker. Feel free to follow me to pick up the links.




Hi Truong,

Thanks. Feel free to ask if you need more information.



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