Assessing the Organizational Value and Cost of Emerging Data-as-a-Service
(2026) MIOM05 20261Department of Industrial and Mechanical Sciences
Production Management
- Abstract
- In recent decades, organizations have undergone a fundamental shift from selling physical products to offering services and most recently, data-driven offerings. This transition has elevated data to a central organizational resource and given rise to new service models, most notably Data-as-a-Service, DaaS. While the costs associated with developing and maintaining data infrastructure are often measurable, the value internal DaaS generates remains difficult to quantify. This gap between value creation and value capturing represents a critical challenge as organizations become more dependent on data for operational and strategic decision-making.
The purpose of this thesis is to describe and analyze Data-as-a-Service internally in an... (More) - In recent decades, organizations have undergone a fundamental shift from selling physical products to offering services and most recently, data-driven offerings. This transition has elevated data to a central organizational resource and given rise to new service models, most notably Data-as-a-Service, DaaS. While the costs associated with developing and maintaining data infrastructure are often measurable, the value internal DaaS generates remains difficult to quantify. This gap between value creation and value capturing represents a critical challenge as organizations become more dependent on data for operational and strategic decision-making.
The purpose of this thesis is to describe and analyze Data-as-a-Service internally in an international organization and to identify the associated value and cost. The study is conducted as a qualitative, exploratory and problem-solving case study at E.ON, a large European energy company.
The theoretical framework draws on Kotler's Three Levels of Product, Product-Service Systems, PSS, Service-Dominant Logic, SDL, and frameworks for value creation, value capturing, and cost calculation. These theories are applied to two internal data products at E.ON: Korttidsprognos för fördelningsstation and Basdata med reläskyddshändelser.
The empirical findings reveal that both data products are best understood as service-oriented offerings where value is not embedded in the data itself, but in the augmented product, where the surrounding services such as maintenance, support and quality assurance ensure continuous and reliable data delivery. From a PSS perspective, both data products are classified as result-oriented, meaning that value is realized through operational outcomes rather than through access to the data.
A key structural finding is the phenomenon of value slippage within the organization, which means that the department creating DaaS is separated from the department that captures the value. The analysis also identifies that while some internal DaaS generates a relatively quantifiable exchange value, other data products primarily generate use value, making their economic impact harder to express in monetary terms.
Regarding cost, the study finds that the existing average costing model, built around a single homogeneous cost object, is insufficient for capturing the true cost of individual data products.
The study shows that the traditional ways organizations think about products, costs and value are poorly studied for internal DaaS. As DaaS offerings become more important, the absence of lacking valuation and cost allocation methods risks leaving critical offerings underfunded and underappreciated. Addressing this requires organizations to treat internal DaaS not as a technical function but as a strategic service with organizational impact. (Less) - Popular Abstract
- As society becomes increasingly digitalized, data has evolved into one of the most valuable resources within modern organizations. In the energy sector, enormous amounts of data are generated every day through electricity networks, consumption patterns and operational systems, creating major opportunities for improved data utilization. Despite this growing importance, organizations often struggle to understand how data-driven services create value and how their costs should be measured. This thesis investigates how Data-as-a-Service can be understood within E.ON and highlights the challenges organizations face when data becomes a strategic organizational asset.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/student-papers/record/9228723
- author
- Eldh, Linnéa LU and Rosén, August LU
- supervisor
- organization
- course
- MIOM05 20261
- year
- 2026
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- Data-as-a-Service, DaaS, value creation, value capturing, cost allocation, digitalization, data product
- other publication id
- 26/5329
- language
- English
- id
- 9228723
- date added to LUP
- 2026-05-29 16:02:08
- date last changed
- 2026-06-24 16:14:23
@misc{9228723,
abstract = {{In recent decades, organizations have undergone a fundamental shift from selling physical products to offering services and most recently, data-driven offerings. This transition has elevated data to a central organizational resource and given rise to new service models, most notably Data-as-a-Service, DaaS. While the costs associated with developing and maintaining data infrastructure are often measurable, the value internal DaaS generates remains difficult to quantify. This gap between value creation and value capturing represents a critical challenge as organizations become more dependent on data for operational and strategic decision-making.
The purpose of this thesis is to describe and analyze Data-as-a-Service internally in an international organization and to identify the associated value and cost. The study is conducted as a qualitative, exploratory and problem-solving case study at E.ON, a large European energy company.
The theoretical framework draws on Kotler's Three Levels of Product, Product-Service Systems, PSS, Service-Dominant Logic, SDL, and frameworks for value creation, value capturing, and cost calculation. These theories are applied to two internal data products at E.ON: Korttidsprognos för fördelningsstation and Basdata med reläskyddshändelser.
The empirical findings reveal that both data products are best understood as service-oriented offerings where value is not embedded in the data itself, but in the augmented product, where the surrounding services such as maintenance, support and quality assurance ensure continuous and reliable data delivery. From a PSS perspective, both data products are classified as result-oriented, meaning that value is realized through operational outcomes rather than through access to the data.
A key structural finding is the phenomenon of value slippage within the organization, which means that the department creating DaaS is separated from the department that captures the value. The analysis also identifies that while some internal DaaS generates a relatively quantifiable exchange value, other data products primarily generate use value, making their economic impact harder to express in monetary terms.
Regarding cost, the study finds that the existing average costing model, built around a single homogeneous cost object, is insufficient for capturing the true cost of individual data products.
The study shows that the traditional ways organizations think about products, costs and value are poorly studied for internal DaaS. As DaaS offerings become more important, the absence of lacking valuation and cost allocation methods risks leaving critical offerings underfunded and underappreciated. Addressing this requires organizations to treat internal DaaS not as a technical function but as a strategic service with organizational impact.}},
author = {{Eldh, Linnéa and Rosén, August}},
language = {{eng}},
note = {{Student Paper}},
title = {{Assessing the Organizational Value and Cost of Emerging Data-as-a-Service}},
year = {{2026}},
}