Goal
Enhancing the conditions for Data Science to drive organization-wide data-centricity.
Solution
Evaluating the current state and setting strategic direction for data infrastructure, data governance, and expertise — together with eoda as a partner.
Result
Identifying required actions and implementing concrete measures to guarantee efficient and secure data use company-wide.
Challenge
successfully address the ever-increasing complexity in the transport and utilities sector, digitalization and data-driven decision-making are becoming increasingly important for Kasseler Verkehrs- und Versorgungs-GmbH (KVV).
A key piece of this puzzle is KVV’s newly established in-house Data Science team.
Goal
KVV’s goal is to improve the framework conditions for Data Science in order to achieve an organization-wide increase in data-centricity. A concrete starting point on this path is the professionalization of working conditions for the newly established in-house Data Science team and the removal of existing obstacles. This aims to make Data Science and analytics processes more efficient and scalable.
Solution
Strategy, Know-how, and Infrastructure: KVV recognized early on that to achieve its goals, it must unlock existing potential on multiple levels. For this purpose, it relies on the holistic empowerment approach of the Data Science and AI experts from eoda.
Infrastructure Assessment as a Starting Point
The collaboration began with an assessment of the current state of Data Science and analytics infrastructure and the development of a target vision for the future IT environment.
What tools are in use? How are the data flows and processes structured? Together with representatives from the Data Science team, various departments, and KVV’s IT service provider, the current state of the Data Science infrastructure was analyzed. Existing data value chains—from raw data to finished data products—were identified. Creating and visualizing these data value chains helps to understand the steps the team goes through and where optimization potential lies.
For designing a Data Science infrastructure tailored to KVV’s individual requirements, the eoda experts also rely on formulating user stories. These user stories enabled a clear structuring and prioritization of the requirements and wishes of the various stakeholders.
Besides technical obstacles, organizational challenges also emerged during the assessment with eoda. These concern specific workflows within the Data Science team, as well as company-wide framework conditions—from the introduction of new software to the availability of IT resources.
Determining the Data Science Maturity Level
To classify current capabilities and processes, the eoda experts determined KVV’s Data Science maturity level based on these insights. The result: initial structures for Data Science are in place, but a comprehensive integration into the company is still lacking. Data Governance plays an important role in this context.
Development of the Target Vision
To overcome existing technological hurdles, eoda developed the target vision for the future Data Science infrastructure. This focuses on introducing version control, automation through pipelines, and a scalable deployment strategy.
Beyond the assessment, eoda supports KVV in knowledge building (R & DevOps) and strategically in developing Data Governance. This governance aims to improve data discoverability and establish clear ownership responsibilities.
Result
KVV has recognized its data potential and aims to unlock it with its own Data Science team. However, as in many companies, organizational and infrastructural deficits still prevent the full exploitation of the available data potential.
With the support of eoda, KVV has identified the necessary areas of action and initiated measures to ensure meaningful, efficient, and secure data usage throughout the entire organization.
Get started now:
We look forward to exchanging ideas with you.
Your expert on AI strategy:
Dr. Martin Bober
empowerment@eoda.de
Tel. +49 561 87948-370
