User Tools

Site Tools


10a.002.JYU_WP8 - Decision Intelligence for Mission Critical Business Decisions

Project - Summary

Decision intelligence uses applied data science, managerial science, and social science to develop holistic solutions for enterprise-wide decision-making. It requires a good understanding of the business problem, alignment with the business team, an iterative work process, a robust data science platform handling the data governance, model accuracy, assumption validation, and data visualizations. Data-driven approaches in, e.g., business analytics, could enable businesses to react rapidly to changes in their business environment (Zamani et al., 2022). However, businesses face challenges in developing a data-centric organizational culture with supportive business models and a collaborative environment (Immonen et al., 2014). They struggle with applying decision intelligence due to, for example, fear of change, poor data quality, or competence in providing value (Figalist et al., 2022). We build upon the work of the previous two projects by examining challenges around insufficient data and will concentrate on means to automate decision-making in meaningful and sustainable ways. The application domains include organizations in a broad spectrum of industries with data available for supporting their decision-making, such as software companies, financial services, and transportation. However, in order to adopt decision intelligence successfully, a data-centric ecosystem needs to be in place for a sufficient amount and quality of data. Further, the ecosystem should have achieved a certain level of maturity to gain the benefits of the data-centric mindset. Thus, we utilized ecosystem thinking to support value creation and used domain-specific modeling to increase ecosystem maturity. The project has been continued until the end of February 2023. Currently, the project is in its final analysis and documentation phase.

Project - Team

Team Member Role Email Phone Number Academic Site/IAB
Pekka Abrahamsson PI 358 40 541 5929 University of Jyväskylä
Joni Kultanen Researcher 358 40 628 1871 University of Jyväskylä
Gabriella Laatikainen Researcher
(Until 12/2021)
N/A N/A University of Jyväskylä
Anssi Sorvisto Student N/A 358 44 285 2431 University of Jyväskylä
Taija Kolehmainen Student N/A N/A University of Jyväskylä
Jukka Lassila Project Mentor 358 50 1810 Multimentor Oy

Project - Novelty of Approach

Human interaction and performance and business strategy execution data both present new domains for Machine Learning applications. The problem is approached from an ethics viewpoint using ECCOLA – a Method for Implementing Ethically Aligned AI Systems (Vakkuri et al., 2020) in the design and implementation phase of work packages 8 and 9.

Critical business decisions, strategies, and analysis methods have been actively investigated in earlier CVDI projects and in the literature. Decision intelligence is an emerging topic in optimizing tactical, strategic, and operational decision-making with strong data science foundation. It can provide high-level guidance, but new methods are required to align complex business problems with organizations' strategic objectives and optimize different operations fields for profitability, quality, and productivity. We investigate how to align decisions on complex business problems with organizational strategic goals through ecosystem thinking, modeling, and automation. Next, we understand the building block of a data-centric organizational culture, how to develop one, how to build an ecosystem of such organizations, and finally, how to utilize data-centric ecosystems in making more optimized strategic decisions for improved business capabilities. By combining strategic analysis and future-perspective firm interactions in our modeling approach, we can form an understanding of the impact that business decisions have at an ecosystem level (Battistella et al., 2013). Further, we contribute to a need to form a governance-level understanding of an ecosystem before developing an informed decision-making strategy (Talmar, 2020).

Project - Deliverables

1 PoC on data enhanced decision making for mission critical business problems
2 Method for business problem alignment with organizational objectives
3 Case study on implementing decision intelligence in real-life cases
4 Reports on the development of the PoC (Incl. ML and optimization models), and business problem/org. objectives alignment method
5 Article on the case study

Project - Benefits to IAB

Academic publications

We are finalizing two academic publications by February 2023:

  • Case study on modeling data-centric innovation ecosystems, their design, and governance
  • Research paper on data-centric innovation ecosystem design and development

The first publication will be qualitative action research on ecosystem design and development by applying the theory of digital innovation ecosystems and using data-centricity and decision intelligence as two lenses to drive progress.

The second publication will be a qualitative single-case paper on utilizing the Ecosystem Governance Compass in designing a data-centric ecosystem. In the paper, we will evaluate how well the method can be used in the task and seek to answer the questions about the role of modeling in designing a data-centric ecosystem. Beyond validating the method, we will also attempt to identify possible shortcomings and further directions for developing the tool from the perspective of data-centric organizations and ecosystems.

Seminar on Data, Ecosystems, and Business Analytics in October 2022

Our team and the collaborating company will share the insights from the three last projects with a wider selected audience in October 2022. The seminar has research and company speakers and a workshop session with businesses and financiers who share an interest in utilizing data and developing ecosystem thinking. The event will also prime further industry collaboration.

New ecosystem development venture

During our research, we discovered a need for further research and development of ecosystems to be more data-driven and have better situational awareness. According to a report by McKinsey Global Institute the value of open data will influence trillions of dollars in value creation globally (White et al., 2021). We began developing a new kind of venture around a consortium of companies interested in developing continuous business analytics to support real-time business analytics and open data generation, which is an essential factor in producing decision intelligence. According to a study (John et al., 2022), open data and development in other forms of analysis improves decision-making and innovation through products and services and unlocks data-driven opportunities. We give no value to the analysis if it cannot influence the decision-making process.

From the research, firstly, we are sharing the basics of being a data-driven organization and how it affects situational awareness.

Project - Documents

projects/year10/10a.002.jyu_wp8.txt · Last modified: 2022/10/04 08:25 by sally.johnson