Struggling to convey GIS software challenges to non-technical stakeholders?

When one has to talk about Challenges in GIS Software with a nontechnical stakeholder, results need to be the focus and not the technical details of the problem. Emphasise how GIS can enable the virtualisation of complex data to help drive informed decisions. Such challenges would include integration issues that may affect the accuracy and time appropriateness of results. Finally, quantify the bottom-line impact of such challenges on project timelines and resource allocation to ram the point home of why effective GIS management is necessary.

To illustrate, imagine GIS layers as a stack of transparent papers, each containing different information about a city—one layer might show roads, another buildings, and a third parks. When you stack these layers together, you can see how they interact, such as where roads intersect parks. This visualization helps stakeholders grasp the power of GIS in combining various data sets to make more informed decisions.

For example, in urban planning, if outdated or inaccurate data is used to map flood zones, it could result in buildings being constructed in high-risk areas. This can lead to significant financial losses and endanger lives when floods occur. By stressing that high-quality data ensures precise and reliable GIS analysis, you highlight its crucial role in avoiding such costly errors and making well-informed decisions.

For instance, an organization may invest in a powerful GIS software, but without adequately trained staff, the tool's full potential won't be realized. This can result in underutilized resources and missed opportunities for insights and efficiencies. Emphasizing the importance of continuous training ensures that the team can effectively use GIS technology to meet organizational goals and adapt to new advancements in the field.

For example, an organization might currently use GIS for basic mapping and spatial analysis, but future advancements in AI and machine learning could offer more sophisticated predictive analytics. Planning for scalability ensures that the GIS infrastructure can accommodate these future capabilities, providing long-term benefits and maintaining a competitive edge. By illustrating the need for ongoing investment, stakeholders can better appreciate GIS as a continuously evolving asset.