Short answer
When designing Big Data solutions, consider developing specific innovation service strategies that clearly define how value will be created and captured, and how stakeholder networks will be managed.
- Field
- Innovation & Design
- Source
- Technovation (2018)
- Method
- Multiple-case study analysis
- Evidence
- Moderate effect
Companies providing Big Data solutions can leverage this technology to develop distinct innovation service strategies, influencing how they create and capture value. This innovation & design research insight is drawn from a 2018 study published in Technovation. Using Multiple-case study analysis, researchers explored how this design variable affects real-world outcomes. The key design takeaway: When designing Big Data solutions, consider developing specific innovation service strategies that clearly define how value will be created and captured, and how stakeholder networks will be managed.
Big Data fuels innovation service strategies by provider companies
Companies providing Big Data solutions can leverage this technology to develop distinct innovation service strategies, influencing how they create and capture value.
Technovation · 2018
Key Findings
- 01Big Data enables provider companies to develop unique innovation service strategies.
- 02The network of stakeholders significantly influences the design and implementation of these strategies.
- 03A theoretical framework for value creation and capture using Big Data was identified.
Application
Design takeaway
When designing Big Data solutions, consider developing specific innovation service strategies that clearly define how value will be created and captured, and how stakeholder networks will be managed.
How to apply
When developing a new product or service that utilizes Big Data, explicitly map out the potential innovation service strategies and how value will be exchanged with all involved parties.
Project actions
- 01When researching Big Data, think about how it can be used to create new services, not just analyze existing data.
- 02Consider the entire ecosystem of users and providers when designing a Big Data solution.
Method & Evidence
Variables
Strengths & Limitations
Strengths
- +Provides a theoretical framework for value creation and capture using Big Data.
- +Identifies specific innovation service strategies employed by provider companies.
Limitations
The findings are based on a limited number of case studies, so they might not apply to all Big Data provider companies.
Reliability & validity
The use of multiple-case studies enhances the external validity of the findings by providing a broader perspective than a single case. However, the qualitative nature of the data and the potential for researcher bias in interpretation could affect reliability.
Think critically
To what extent can the identified innovation service strategies be generalized across different industries and types of Big Data providers?
Design Principles
"Leverage Big Data to define and implement distinct innovation service strategies that optimize value creation and capture within a stakeholder network."
Understanding how Big Data enables new service models is crucial for design practitioners. It allows for the development of more sophisticated and value-driven offerings, moving beyond simple data analysis to integrated service solutions.
What This Means for Your Design
Companies that sell Big Data services can use data to come up with new ways to offer their services and make money, and the people they work with (like partners or customers) can affect how they do this.
How to use in your project
- 1.Use this research to justify the development of innovative service models based on data analysis.
- 2.Discuss how stakeholder collaboration is essential for the success of data-driven service design.
Add to My Project
Quick Cite
Paragraph starter
This research highlights that Big Data can be a catalyst for developing distinct innovation service strategies within provider companies, enabling novel approaches to value creation and capture. The study's findings underscore the importance of considering the influence of stakeholder networks in the successful design and implementation of these data-driven service models, offering a valuable framework for understanding the strategic application of Big Data in service innovation.
Source
Technovation
Creating and capturing value from Big Data: A multiple-case study analysis of provider companies
journal · 2018
View sourceQuestions About This Research
- What does the research say about big data fuels innovation service strategies by provider companies?
- When designing Big Data solutions, consider developing specific innovation service strategies that clearly define how value will be created and captured, and how stakeholder networks will be managed. Evidence: Technovation (2018).
- Why does "Big Data fuels innovation service strategies by provider companies" matter for design?
- Understanding how Big Data enables new service models is crucial for design practitioners. It allows for the development of more sophisticated and value-driven offerings, moving beyond simple data analysis to integrated service solutions.
- How can designers apply this research?
- When designing Big Data solutions, consider developing specific innovation service strategies that clearly define how value will be created and captured, and how stakeholder networks will be managed.
- What were the main findings?
- Big Data enables provider companies to develop unique innovation service strategies.. The network of stakeholders significantly influences the design and implementation of these strategies.. A theoretical framework for value creation and capture using Big Data was identified.
- What research method was used?
- Multiple-case study analysis.
- How strong is the evidence?
- Evidence strength is rated Moderate effect, based on a 2018 journal from Technovation.
- What should I do differently in my next project?
- When developing a new product or service that utilizes Big Data, explicitly map out the potential innovation service strategies and how value will be exchanged with all involved parties.
- What are the limitations?
- The study is based on a multiple-case study, which may limit generalizability. The focus is on provider companies, not end-users of Big Data solutions.