Lukas Feuerstein Rotating Header Image

Survey/Feedback Data-centric business models

I currently write my master thesis on “Success factors of data-centric business models” at University of Regensburg (Germany) and in cooperation with Detecon Consulting.

Data-centric business models try to describe emerging business models that are mainly based on leverage data and information exchange with users, communities and partners. As we have observed, companies that adopt a data-centric business model such as Google or Amazon, generate most of their revenues from handling and processing of data or information.

A in depth overview over the methodology and also some examples for data-centric business models such as nike+, Goldcorp, social media aggregation and restaurant reviews can be found in the presentation here.

My current research approach is to develop several case studies based on expert interviews, that are furthermore using the “business model framework/template” (@all thanks for the great and comprehensive work on the book that is released now  – Preview there ) for analyze the overall business model.

Since the focus of my thesis is mainly on information and data-products we have created a framework called “Information Value Chain”(IVC) that is especially targeted at data and information processes of a business model.

The information value chain

In evaluating the IVC as framework analyze data-centric business, we address further questions:

  • What are the key success factors of data-centric business models?
  • How does the information value chain (IVC) help to derive strategic options related to data-centric business models?-
  • What data is marketable and how does it need to be processed and presented?

For a quantitative evaluation of the IVC I’m conducting a online survey. Survey Link
The survey is confidential and will take approximately 5-10 minutes.

It would great if you are able to participate or can give me some feedback, random thoughts and comments on the information value chain approach. Also forwarding to some experts, colleagues etc would be great.

Your benefit to participate is that each participant gets a copy of the aggregated results and final findings of my thesis.

Furthermore, if your company is marketing any informational or data-products. I would be thrilled to ask you some questions in a short 15-20 minute telephone interview. Please leave your contact details in the survey or send it to me via email: Lukas.feuerstein/at/

Thank you al lot.
Kind regards and looking forward to the “business model generation” book

Here some the short characteristics of the several steps of the Information Value Chain (IVC)

1. Data generation/acquisition describes the generation/source of data.
- Is data generated externally through users?
- Is data acquired from partners or users?
- Is data generated internally?
- Structured vs. unstructured data?

2. Storage and representation
- Is the data stored persistently and in a computer oriented way?
- Does the company that stores the data originally own the data (in contrary to pure integration services like Salesforce)?

3. Aggregation and processing
This information value chain steps tries to aggregate and consolidate theData. Furthermore it focuses on the creation of semantic links between data (categories, hierarchies etc.). Also, data is transformed and restructured.

4. Information generation and integration (Mashup)
- Data from different types and sources (internal or externally, structured and unstructured) are mapped, combined and mashed up.
- Integration of value offer of 3rd parties in order to enrich the own data and expand the customer value.
GoogleMaps for examples integrate address data from the GoogleSearch Index with map data and therefore improve the user interface and add value.

5. Analytics and application.
- Evaluation and analysis of the information (e.g Search)
- Adaption into concrete situations (Recommendations, context sensitive ads).
- Personalzation (users adaptive evaluation of data)

6. Presentation and provisioning
- Presentation of the information to the customer and provisioning of the created data and products
- device adapted display of content

Thanks for your comments.
Survey Link

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  • lfeuerstein

    Hi Patrick,
    I highly appreciate your comment so thanks for that.
    I’m aware that the blog post /thesis hypothesis are provocative and it will keeps me busy to prove my thoughts...

    So far, my working definition/approach is that data-centric business models in contrast to usual IT business models is determined by the focus the “value proposition” side of a business model. Certainly, a data-centric approach also has side effects on value architecture, operations excellence and revenue models (using your approach to describe business models Stähler 2002).

    Bringing up your Zara example, they are mainly using IT and data to improve their logistics and operational efficiency. Its main business focus is still retailing (of trendy fashion) and based on vertical integration. Zara certainly utilizes data generated through logistics and processes to improve operations - but this data is only used indirectly in the value proposition towards customers eg. better price, faster delivery etc… I assume that they are also capable to collect POS data to make predictions and determine customer’s behaviour but only on a minimal scale (through their reward program?) and less accurate and complete then companies like Amazon.

    Contrasting Zara with Amazon, we can observe, that Amazon is superior in operational performance and logistics as well. Furthermore it is important to realize, that Amazon’s profit is mainly derived through transactions/commission from selling goods like books etc. (that would be your “revenue model”) and exploiting the long tail.
    Additionally its IT infrastructure/platforms are certainly outstanding. Nevertheless strategic moves, especially the recent cloud computing/web service efforts are demonstrating that Amazon is commoditizing its IT infrastructure. Even competitors can now connect and use parts of the platform (pay per usage). This strategic orientation in my opinion demonstrates that the value of IT as a strategic asset in a long term perspective is decreasing.

    My main data-centric point is however, that amazon’s advantage over other competitors is their data-centric capsule around their core value proposition (efficient, cheap processing of transactions, coordination of seller to buyer, logistics) and the integration of the customers.
    Amazon is through its position as intermediary uniquely able to gather direct (reviews and ratings) and indirect (transactional data such as checked out items and clicks) data from customers. But even more important is Amazon's ability to use analytics on top on that and to put this data to work. Through its mass of accurate customer behaviour and preference data (which in my opinion the most valuable strategic asset), Amazon is able differentiate from competitors to make personal recommendation that enhance the value offer and decrease information asymmetries favouring the buyer side.
    Hope this make sense so far – hope to give some update soon as I’m innovating and improve my definition.

  • I am a little bit surprised about this topic. To call amazon a data-centric business is quite far fetched. Yes, every logistic firm must be a master in data management but the success of amazon is not the data management alone. It is the whole customer-centric business model that makes them strong. Of course, they have a great IT to support their business model but still that does not make them a data-centric business. Then you would call Zara a data-centric business as well since they whole logistic and procurement depends on their strong IT system.

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