Design driven data productizement process
Jarkko Moilanen (PhD)
My economics oriented 2nd Ph.D. research is focused on the design driven data productizement process, which binds together data products and data strategy in companies. It also includes data product family and lifecycle concepts. My intention is to define the productizement process and then pick spots in the process and do research and write articles on those. Of course I will not be able to cover whole process and the missing spots are limitations of the research and reserved for further research.
Data Monetization as the playground
Data monetization can be seen to include enhanced decision-making support through a better, more effective use of data; creating a unified understanding of data and a harmonised view of all relevant data; creating conditions for data-driven work and thereby becoming a digital company; increasing process efficiency; and building common objectives, benefit concepts and mindsets when dealing with data.
Focus on data products
Although all of the mentioned have value, focus in the research is in data products which are sold as commodities. Data product content is raw data or results of analysis process which might include AI or not. The content of data products is wrapped around with product element such as pricing plans, conditions, versioning, attractive name and description to mention a few. One of the fundamental aims is to define data product as accurately as possible. The added value is in the data which is packaged into easy to understand, buy and consume data products.
Data Product Toolkit
Data owners lack tools and skills to design data products. Furthermore, before data products can be built on top of a platform, those need to be designed. Platform might even offer testbed or simulation tools to test data products before production level publication. Thus, the results of the research are used into development of Data Product Toolkit, which offers canvases and other tools to design and manage data products, product lifecycle and product portfolios.
Data Products and Platforms
Data is increasingly not purchased as a batch or a dataset. Instead data consumer is purchasing access to data. One reason for this is the success story of subscription economy. We’ve seen this with Netflix and Spotify, but also in getting access to cars and other commodities instead of buying one. The purchased data product is stream of data which is either retrieved on customer request or pushed to customer upon changes in content. This resembles more a service than product in the pure format. More often “data product” is consumed via productized APIs. Consumers are not buying APIs. APIs provide modern access to discover, purchase and consume given data products.
Currently only scalable option to deliver data product content to consumers (apps) are APIs. Just as data has to be productized, also necessary APIs must be productized. Commonly data owners lack skills to productize APIs, market place to sell goods in. Thus we need a third party - platform, which will offer productized APIs to access productized data products with modern plans including subscription.
Below you'll find my planned articles to be written. I am more than happy to have coauthors since that enables more fluent authoring experience, multiple viewpoints, fresh ideas, fruitfull discussions and other benefits. I use Overleaf in the writing and that is not negotiable. Take a look at the article candidates and contact me if you want to participate in the research.
I am also publishing some of the results and materials as videos. In addition to that I will gather a curated list of academic materials for others to use. You can find those from Materials section.