Bridging the Organizational Gap: The Role of Connectors in Data Science Projects

Connectors are emerging as a crucial link between departments in data science projects, addressing organizational gaps that hinder success.

Data science has become a critical tool for improving decision-making and operations in organizations. However, many data science projects still fail, and even successful ones often face delays and high costs. The root cause of these challenges lies in the organizational gaps that exist between teams. To address this issue, a new role has emerged – the connector. Connectors bridge these gaps, facilitating the development, application, and scaling of data science projects. In this article, we explore the importance of connectors and how organizations can effectively manage this new type of data professional.

1: The Organizational Challenges in Data Science Projects

Data science projects face several organizational hurdles that impede their success. Firstly, data science has often been treated as an add-on to the organizational chart, rather than an integral part of every team. Secondly, there is a fundamental tension between line managers who seek control and predictability, and data scientists who disrupt established processes. Lastly, many companies expect data scientists to handle a wide range of tasks, from understanding the business to dealing with data quality issues, which can lead to a lack of focus on critical aspects of the project.

2: The Role of Connectors in Closing Organizational Gaps

Connectors are individuals who fill the organizational gaps in data science projects. These roles have existed in various forms, such as systems analysts, business analysts, and data engineers. However, simply adding connectors to the team is not enough to address the underlying issues. Connectors must facilitate communication and understanding between line managers and data scientists, deal with data quality issues, and ensure coordination and progress towards project goals.

3: Steps to Effectively Manage Connectors

To effectively manage connectors, organizations should follow three key steps. Firstly, they need to define the data science project process and identify the people involved at each step. This ensures that all relevant stakeholders are included and their roles are clear. Secondly, organizations should evaluate where connectors can make the most impact by identifying the gaps and areas of miscommunication. Connectors can help in framing the problem, translating between business and technical teams, dealing with data quality issues, and keeping track of progress. Finally, organizations need to clarify the specific roles for connectors and put them in place. This includes assigning connectors to individual projects and considering program-level connectors to bridge the gap between data science and the rest of the business.

4: Examples of Successful Connector Roles

Several organizations have successfully implemented connector roles to improve their data science projects. Regions Bank, for instance, has data product partners who function as both data product managers and partners with the business. These partners bridge the gap between data science and business needs, ensuring the successful implementation of data science projects. The Federal Statistical Office of Switzerland has a data science bridge that coordinates various statistical functions and ensures collaboration and positive business impact. These examples highlight the effectiveness of connectors in overcoming organizational gaps.

Conclusion:

Data science projects often face organizational challenges that hinder their success. Connectors play a crucial role in bridging the gaps between teams, facilitating communication, and ensuring the smooth implementation of data science projects. By defining their roles, evaluating their impact, and putting them in place, organizations can effectively manage connectors and improve the overall success rate of data science projects. The role of connectors is vital in ensuring that data science becomes a valuable tool for improving business performance.


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