(US & Canada) | Quality Data Is the Building Block of AI — North Dakota Information Technology CDO

Kim Weis, Chief Data Officer at North Dakota Information Technology, speaks with Bob Audet, Partner, Digital Solutions - Data at Guidehouse, in a video interview about developing a state-wide data strategy, the engagement and support of senior officials, the drivers and challenges, the role of cross-agency collaboration, and having the right vendor support for implementing a successful data strategy.

Weis begins by stating that data has historically been seen as an IT function, especially in North Dakota. She adds that the office of the CDO in North Dakota falls within the purview of North Dakota Information Technology.

The placement of the office has led to great opportunities as well as challenges as the CDO office has been working to develop a state-wide data strategy. When it comes to the future state of technology and data solutions, Weis shares that the organization is in an advantageous position because of the established relationship with colleagues in IT.

Ensuring solid collaboration with agency stakeholders was the key to developing data strategy, says Weis, which in some cases meant building new trusted relationships on the data side. She adds that having a long-standing relationship with stakeholders who know their data best has been critical to building a modern data culture.

Highlighting the engagement of senior-level officials in building the data strategy, Weis acknowledges the administration of the current governor. She states that technology and data have been focal areas in the cabinet under his leadership.

Additionally, Weis notes that the governor has been the strongest supporter of modernization, driving insights, and data-driven decision-making. She confirms that he is focused on fostering the purpose of serving the residents of North Dakota to improve outcomes.

Being a government data practitioner for two decades, Weis shares her first-hand experience of the challenges that led to building the state-wide data strategy. She recollects what the lack of data governance and collaboration meant and how it drove the need for modernization.

To address the challenges, Weis and her team preached the need to invest in data, which at times was a struggle as data was not a priority. However, the governor and his cabinet’s support helped them spread awareness around not just data but quality government-trusted data.

Also, as a consequence of COVID, everyone felt the need to have quality and trustworthy data, she notes.

Moving forward, Weis maintains that the growing awareness of the role data can play in running organizations and businesses has naturally paved the way for a data-driven state of things. Moreover, the explosion of AI also has a critical role to play in this. She states that many agencies want to jump onto the AI bandwagon but in some cases, they cannot comprehend what it means.

Therefore, when the agencies realize the true benefit of AI and understand that quality data is the building block of AI, that sparks awareness and makes them data advocates.

Next, Weis discusses the engagement of other state agencies throughout the development of the data strategy and remarks that the engagement is essential for its success. Without engagement, she says, the state-wide data strategy would not be meaningful or helpful to agencies.

Emphasizing engagement, Weis affirms initiating the data strategy by collaborating with two massive state government organizations: Health and Human Services and the Department of Public Instruction.

After the completion of the data strategy and the start of the execution phase, Weis and her team began socializing the strategy and roadmap extensively. She recalls that the conversations that followed brought out the pain points and how the data strategy could directly benefit the agencies.

In the course of the journey, Weis mentions educating agencies on the strategy and their need for participation. Furthermore, she confirms partnering with solid vendors to support the efforts with expertise and help with organizational change management and communications.

In conclusion, Weis states that data strategy is not a one-and-done project but rather an ongoing need. She envisions a future when data is not considered a separate creature but a part of the organizational fabric and decision-making process.

​CDO Magazine appreciates Kim Weis for sharing insights on her data strategy with our global community.

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