How can you use geographical data in your problem analysis process?

I have used geography data mapping sales, territory potential and market share. It really is about territory market share. Who is better a rep in Oregon who sells half a million in a territory of one million Or Rep in the state of New York who sells $2 million in a territory of $10 million? We mostly look at sales of reps. Very seldom do we look at territory share. If you look at big territories with low territory shares, you can raise your overall market share

You have highlighted the key aspects of importance of geographical data in decision-making and problem-solving process. I can add some more relevant points to consider: 1. Spatial Patterns and Trends 2. Risk assessment and management 3. Environment impact studies 4. Demographic analysis 5. Predictive modeling 6. Community engagement 7. Resource allocation Integration of geographical data into decision-making processes adds to depth of analysis, enhances informed decision-making, and opens up effective communication process with complex information.

One thing I've found helpful is that it can help us to see patterns and trends that would otherwise be invisible, and to connect the dots between seemingly unrelated events. I use this data to understand the world around me and make informed decisions. If you're not already using it, I encourage you to start. You won't be disappointed. The use of geographical data is becoming increasingly widespread. It is being used in a variety of sectors, including government, business, and academia. As per my research, I estimate the value of geographical data is growing rapidly. The global market for geographical data is expected to reach $250 billion by 2025.

Geographical data helps in understanding the spatial dimensions of problems. It allows for the analysis of patterns, trends, and relationships across different locations. In my experience, incorporating geographical data has led to more informed decisions, as it adds a layer of context that traditional data might miss, such as demographic trends, environmental changes, or logistical challenges.

Location! Location! Location! To understand any issue, one must have an understanding of the intended region. Particularly, if the product comes from a different sociocultural or religious background. Hence, for the issue to be successfully addressed, it is essential to understand these differences. Specially when considering the rapid changes occurring in the current environment.

Data tends to be most accurate to consumers when closest to their home. Gathering geographical data allows presentation of analysis in local, sub-regional, regional, sub-national, national, multi-national, global, etc. breakdowns. This provides much more value as conditions may differ widely from the consumer the farther that you get from their specific location. Gathering individual geographic location (with opt-in for privacy reasons) takes this even further as it enables expedited preparation of goods and services as the consumer gets closer to the business, or, for security purposes, as they get closer to their own home. The host of customized services that are enabled through geo-tagging, geo-fencing, and geo-location are endless.

Geographical data can be collected through various methods, including surveys, satellite imagery, GPS tracking, and public data sources like government databases. In recent projects, I’ve used tools like Google Earth and GIS (Geographic Information Systems) software to collect detailed spatial data relevant to the project’s scope.

My experience, collecting geographical data is a very complex and time consuming process, but it's essential. Here are some of the most common sources of geographical data I refer: - Census data - Administrative data - Surveys - Interviews - Observations - GPS data - Satellite imagery - Social media data - Open data platforms My advice when collecting geographical data (or any data in general), it is important to consider the following factors: - Relevance: relevant to your research question and the scope of your project. - Accuracy: The data should be accurate and up-to-date. - Reliability: The data should be from a reliable source and no reason to doubt its accuracy. - Ethics: Obtain appropriate permissions and consent to use the data.

Having vast amount of data doenot necessarily lead to a more accurate understanding of the issue. Sometimes numerous reports provide the same information not because the information is correct but because the various sources relied on the same inaccurate source. Therefore, to ensure a more objective and accurate data, various findings, which they themselves come from different sources, must be examined.

Analyzing geographical data is crucial for effective decision-making. Various methods and tools, from descriptive statistics to GIS and data visualization, offer options based on data type and complexity. Align your approach with the problem analysis process, ensuring systematic breakdown from problem definition to result synthesis. Incorporating spatial regression and hotspot analysis adds depth, uncovering hidden patterns. Embrace these techniques to enhance precision in problem-solving. #GeospatialAnalysis #DataInsights 💡🌍

Essential geo-data tools: Descriptive stats for data insights, correlation for predictive models (e.g., climate trends), clustering to identify similar regions, hotspot analysis for pattern detection (useful in urban planning), spatial regression to understand variable influences, GIS for data integration and visualization, and visualization software like Tableau/QGIS for clear data interpretation.

Geographical data can be utilized: - To identify trends or anomalies to reveal market preferences or potential areas for expansion - Use geographical data to target specific locations. - Optimize the allocation of resources based on geographic demand. - Determine optimal locations for facilities, stores, or infrastructure based on geographical factors. - Evaluate the impact of environmental factors on specific locations. - Geographical data is essential for assessing and responding to natural disasters. It helps in planning evacuation routes, identifying vulnerable areas, and coordinating emergency responses.

Analyzing geographical data involves looking for patterns, anomalies, or trends across different locations. Using GIS software, you can overlay various data sets to identify correlations or causal relationships. For instance, mapping crime data against socio-economic data to identify potential risk factors in urban planning.

Analysing data is complex process, but essential part of my projects and decision-making processes. There are many different methods and tools available for analysing geographical data, and the best approach will depend on the nature of data, the research question I am trying to answer, and the level of detail I need. Few important steps I follow in problem analysis process. 1. Define the problem 2. Frame the problem 3. Break down the problem 4. Synthesize the results These steps helps me extract meaningful insights and answer your research questions. Here are few of my top of my list methods that I use to analyse data: - Descriptive statistics - Data visualization - Cluster analysis - Correlation analysis

When deciding on which tools to use for visualization, one thing to bear in mind is that there are some great open source options out there for geospatial analysis. Definitely check out QGIS which is a full-blown GIS or geographic information system. Also check with your IT department to see if they have an enterprise license for ArcGIS Pro. Esri, the company behind it, offer free and paid training online and in person. Finally, check out storymaps from Esri. These allow you to tell your story with maps, visuals, slides, and even video and sound.

Effective visualization is key to interpreting geographical data. This includes creating maps, charts, and 3D models that represent data in a clear and accessible way. Tools like ArcGIS, QGIS, or even simpler platforms like Google Maps can be used. I’ve found that well-designed visualizations can communicate complex data sets in an easily understandable format.

In my experience, when I preparing for data visualisation I always consider factors listed below - The purpose - The audience - The desired level of detail Next, there are many different types of visualizations that you can use to display geographical data, each with its own strengths and weaknesses. Some of the visualizations I have used in my projects include - Maps - Graphs - Infographics - Story maps Finally, I ensure I follow few important principles of good design such as using colours and symbols, Labels, context and interpretation.

Incorporating advanced GIS technologies like QGIS and ArcGIS into my solution architecture role has been transformative. My exploration of satellite imagery, drone mapping, and AI-driven analytics in ERP, CRM, and BI projects has led to innovative problem-solving approaches. This experience underscores the power of geospatial data in enhancing business intelligence, providing actionable insights, and optimizing operational efficiency. As a Senior Solution Architect, I leverage these tools to drive significant improvements in project outcomes, demonstrating the crucial role of cutting-edge geospatial technology in modern business solutions.

One thing I have found helpful is to seek guidance from peers and mentors. I surround myself with a network of peers and mentors who share my interest in data analysis. Further, I engage in discussions, seek feedback on my work, and collaborate on projects to gain valuable insights and expand my perspective. One more important advise is, mentorship from experienced professionals will accelerate learning and provide invaluable guidance.

One way to start with this is to familiarize yourself with basic geographical concepts, including coordinate systems, map projections, and spatial relationships. Understand the significance of latitude, longitude, and geographic coordinates, learn the fundamentals of Geographic Information Systems (GIS), understanding how GIS software works, how to manipulate data, and the basics of GIS analysis, Study spatial analysis techniques such as spatial queries, buffering, overlay analysis, and spatial statistics. These techniques are essential for extracting meaningful insights from geographical data.

Improving skills in using geographical data involves practice and continuous learning. Online courses in GIS, attending workshops, and following industry experts are great ways to enhance your abilities. Hands-on practice with GIS software and staying updated with the latest tools and technologies have been crucial in my own skill development.

I used the Standard Point Location Code (SPLC) in an Order Entry System fifty years ago and provided a daily report of open orders by SPLC for the shipping department. It only took them a couple of weeks to realize that they could consolidate their orders by location to save millions of dollars in shipping costs. In another application the location was used to obtain automobiles from the closest point available to improve delivery time and expense. These are just a couple of real life examples of the benefits of having location information available.

-Data Quality: Ensure the accuracy and reliability of the geographical data you use. Inaccurate data can lead to misguided conclusions. -Ethical Considerations: Be mindful of privacy and ethical considerations, especially when dealing with sensitive or personal location data. -Integration with Other Data Types: Consider how geographical data can be integrated with other types of data to provide a more holistic view of the problem.