A data culture is not a theoretical concept, but a practical comprehension of business and how to enhance it using data and AI. Such a culture can be cultivated within an organization, and those who recognize the importance of data tend to be the most productive contributors.
Top Reasons for Not Starting Data and AI Projects
In our conversations with clients, we regularly explore the challenges they encounter when initiating AI projects. The feedback typically falls into four categories: A) resourcing, B) data and technology, C) organizational culture, and D) project management. The majority of responses highlight getting buy-in from the management and business as the most significant obstacle. This finding is not a big surprise, as companies have struggled to implement truly effective data management and governance processes.
In the past, efforts to tackle these issues through data governance have resulted in complex bureaucracies and inflexible rules. However, culture goes beyond just rules and regulations; it is embedded in the behaviors and attitudes of the people within the organization. Interestingly, the lack of technology or data is no longer a major issue. The real challenge is to convince the business world that IT-driven data development is becoming a bottleneck and preventing companies from achieving the benefits of data and AI.
If Data is a Core Product of the Business Process, Why Does it Need Separate Governance?
The Non-Invasive Data Governance (NIDG) approach, first introduced by data governance expert Robert S. Seiner, offers a refreshing paradigm shift from conventional data governance methods. Its main advantage is the ability to weave governance practices into the existing organizational fabric without major disruptions. Traditional methods often necessitate extensive modifications to workflows and systems, leading to higher levels of resistance among stakeholders and prolonged implementation times.
In contrast, NIDG leverages and formalizes existing roles and processes, enabling faster adoption and quicker realization of benefits. This approach not only fosters enhanced collaboration and communication across various departments by promoting a shared sense of accountability but also offers superior adaptability to evolving business needs without the need for substantial investments in new technologies or methodologies.
Characteristic
Traditional Data Governance
Non-Invasive Data Governance (NIDG)
Data Culture is Persistent, Bureaucracy is Not
In conclusion, the desire for effective data management is universal, but the aversion to additional bureaucracy is equally strong. To achieve successful data management, it is essential to cultivate a data culture within an organization. However, imposing a data culture is not feasible; people must understand the importance of data and its impact on their work.
In our experience, the most effective way to foster a data culture is through training, working on business-relevant use cases, and collaboratively developing necessary data management processes.
By taking this approach, organizations can establish a culture that values data and incorporates it into daily operations. Unlike bureaucracy, which can be easily dismantled, a strong data culture is persistent and enduring, providing long-term benefits for organizations seeking to thrive in the data-driven world.
Business Buy-In
To achieve successful data management, businesses must take on a more active role in leading data initiatives and move away from traditional IT-focused models towards a more collaborative approach.
Use of Existing Organization
The Non-Invasive Data Governance (NIDG) approach leverages and formalizes existing roles and processes within an organization, enabling faster adoption and quicker realization of benefits while minimizing disruptions.
Use Case Driven Training
A strong data culture, fostered through training, business-relevant use cases, and collaborative development of data management processes, is essential for effective data management and provides long-term benefits for organizations seeking to thrive in a data-driven world.
