How can you identify business process improvements with data visualizations?

Para se alcançar melhoria em qualquer processo o ponto principal é identificar seus objetivos específicos. Somente entendendo quais objetivos se quer atingir é possível definir métricas-chave que ajudarão a medir o progresso em relação a esses objetivos.

Data visualization helps to reach decisions faster and enables viewers to glean far better insights about patterns and trends. By presenting data in visually appealing charts, graphs, and dashboards, decision-makers can quickly grasp the key insights and make more informed decisions, providing their organizations a competitive edge.

Data visualizations can be powerful tools for identifying business process improvements by providing insights into trends, patterns, and anomalies in the data. Here are several ways to leverage data visualizations for this purpose: Identify Bottlenecks: Analyze Workflow Efficiency: Monitor Trends Over Time: Compare Performance Across Segments: Drill Down into Root Causes: Analyze Process Variability: Detect Anomalies: Track Compliance and Quality Metrics: Forecast Future Performance: Share Insights and Collaborate: By leveraging data visualizations effectively, businesses can gain valuable insights into their processes, identify opportunities for improvement, and drive continuous optimization and innovation.

I've learned to view data almost as a stakeholder. By crafting dashboards, I can dive into the data, spotting trends and outliers that might not be obvious. This deep dive often leads me to rethink my initial plans for visualizations. When I'm focused on enhancing business processes, analyzing data over time can highlight gaps that even the users might not notice. Charts act as a powerful lens, bringing the intricate details of processes into focus to help identify where we can get better. Remember, it's all about partnering with the data. As we work through it, we often find that our first ideas evolve, and that's okay. It's this collaboration with the data—and with our business stakeholders—that turns raw numbers into actionable insights.

In my experience, I was able to identify improvements trying to find some patterns and some anomalies in the client's business, I even performed unification of different bases to try to identify some pattern and be able to display this in a graph for use in the dashboard. Try to understand how difficult it is for your customer to have some information they need but don't have yet.

The simple and old method is story telling. Use data visualizations to tell a story. Clearly communicate the current state, challenges, and opportunities for improvement. Engage stakeholders by presenting visualizations in a narrative that highlights the need for process enhancements. Then consistently review and update the report. Regularly revisit your visualizations as you implement changes to evaluate their impact on the process. Adjust visualizations to reflect improvements and monitor ongoing performance. My most loveable strategy is to creating heat maps to visualize areas of high or low performance within a process projecting the "hotspots" that may require immediate attention.

While statistical/data visualizations are invaluable, it's important to remember that they're not the only tools at our disposal. Infographics can also play a crucial role in conveying complex data insights effectively, especially in presentations or handouts aimed at illustrating how data translates into business goals. For instance, using pictographs to represent changes, such as depicting only 2 out of 4 people needing to submit data due to a new ERP system, or utilizing pie graphs with infographics to showcase workflows. Even incorporating elements like speedometers can enhance understanding. Visualizations don't have to be confined to traditional graphs; exploring diverse formats ensures comprehensive communication of insights.

Mais uma vez aqui se ressalta a importância da identificação do objetivo pois as formas de apresentação mais adequada dependerá da situação que se deseja expor em relação ao objetivo traçado. Existem diversas tipos e formas de disponibilizar a visualização desses dados: Gráficos de Linha, gráficos de barras, gráficos de pizza, mapas de calor, diagramas de dispersão, Diagrama de Venn, etc. Tudo vai depender de como os critérios de análise podem ser melhor percebidos visualmente.

Effective data visualizations play a crucial role in conveying complex information in a digestible and impactful manner. Arranging the visualizations in a logical sequence to guide users through the data. Highlighting key data points or trends - colors play an important role. Adding interactive features for users to manipulate and explore the data - can generate more insights.

According to my observations, heat maps and scatter plots help us enormously. Utilizing them is what makes the difference. I love ecommerce data which is why I like talking about it. Heat maps: Heat maps can be used to show where customers are clicking on a website, indicating which areas are receiving the most attention. This information can help optimize the website's design and layout. Scatter plots: Scatter plots can help identify any outliers in the data, such as unusually high or low sales figures. It can also help identify any correlations between different data sets, such as sales and website traffic

Die Anwendung der IBCS Regeln (International Business Communication Standards) von Rolf Hichert & Jürgen Faisst haben sich stets als sehr zielführend erwiesen. Die Regeln können in die sieben Bereiche von SUCCESS gegliedert werden: SAY - Convey a message UNIFY - Apply semantic notation CONDENSE - Increase Information density CHECK - Ensure visual integrity EXPRESS - Choose proper visualization SIMPLIFY - Avoid clutter STRUCTURE - Organize content Nur ein erstes Beispiel wie hilfreich die Anwendung der Regeln sind. Zeitliche Verläufe werden immer als Säulendiagramme dargestellt. Strukturelle Vergleiche immer als Balkendiagramme. So hat der LeserIn, ohne das man sich mit den Daten beschäftigen muss, einen Indikator um welche Daten es geht.

If your organization has a brand template, it's always best to utilize that. When you create familiarity, whether it be color palettes or fonts, you reduce barriers to adoption. Also, it's easy to put too many visualizations so its good to follow the rule of three. If you have more than 3 measures, its best to create a filter or parameter to limit how many are visible at one time. I had a dashboard that had one measure but for 10 separate years, rather than display all 10 years at the same time, we created a filter with the most recent 3 years as a default. On some charts we even added a toggle to hide all measures so that only key data points were displayed. We also try to avoid acronyms or initials as much as possible.

Using best practices when designing your visualizations is key to understanding the insights quickly. Making sure you are using proper font and size to call out your KPIs, making sure you are using color effectively to aid in your analysis, and not overloading the user with data are just a few. Designing a dashboard is like reading a good book. It should have a well defined beginning, middle, and end and keep the user engaged in the story you are trying to tell.

Designs angelehnt an eine CI, Stock-Designs des Tools, IBCS; es gibt viele Möglichkeiten Datenvisualisierungen ANGENEHM darzustellen. Dazu gibt es standardisierte Regelwerke, Vorlagen, Add-Ins oder externe Tools.

Knowing your audience matters the most, Before creating visualizations, consider who your audience is and what they need to know. The visualization should convey information that is relevant to them. Use colors that are easy to read and ensure that they contrast well with the background. Use different colors for different data sets and avoid using too many colors in one chart.

Take a peek at your historical data using tools like line graphs or pair graphs.Those can help to identify any recurring pattern, weird outliers or gaps in the data. By doing so,maybe you notice a surge in orders from a demographic you never even thought about targeting before.

Leveraging the entire time series data from the business process workflow enhances the comprehension of time allocation for various tasks and processes. Drawing from personal experience, I've focused on enhancing business processes related to Service Desk turnover time and operational metrics. By extracting data from the Service Management system, we analyzed the duration of each task within the service ticket workflow. We developed numerous visualizations depicting time spent versus average time and target time. Additionally, insights into overall ticket submission rates and peak ticket influx times aided in identifying factors shaping our approach to customer service delivery.

After creating data visualizations, analyze them for insights to identify areas for business process improvement. Look for patterns, correlations, gaps, anomalies, or opportunities that highlight strengths, weaknesses, or potential enhancements. For instance, you may find a product with high demand but low profit margin or a customer segment with high churn and low satisfaction. These insights enable you to generate hypotheses, questions, or recommendations for refining business processes.

By leveraging data visualization, we can pinpoint bottlenecks in the supply chain by visualizing inventory turnover rates across different locations. Additionally, analyzing customer journey data through interactive dashboards can reveal areas for enhancing user experience and increasing conversion rates. Visualizing sales trends over time allows us to identify seasonal patterns and adjust inventory levels accordingly, optimizing resource allocation. Moreover, creating heatmaps of customer demographics can aid in targeted marketing strategies, enhancing customer engagement and loyalty.

Analyze Your Data Visualization for Insights: Conduct thorough analysis of the visualized data to uncover patterns, trends, and outliers. Look for correlations, causations, and anomalies that may indicate areas for improvement in business processes. Use interactive features and drill-down capabilities to explore data at different levels of granularity and gain deeper insights. Leverage statistical analysis and data mining techniques to extract meaningful insights from complex datasets.

Do remember that you might be challenging the status quo and that's not easy to hear. Business operators, managers & heads will be worried about how any criticism of existing business processes will make them look. If not managed properly, there will be fierce resistance & the suggested process improvements, however valid will never take off. Some suggestions are to 1. Keep it impartial & devoid of any emotion 2. Focus on the business issues & not the people involved 3. Instead of 1 final presentation or report, run multiple mini consensus-building sessions with key stakeholders. They'll guide on how to present the information effectively (terms to use, colors, icons, relevant KPIs, pain points etc.). This will lead to successful outcomes.

Keep visualizations simple and focused on the key message you want to convey. Avoid cluttering the visualization with unnecessary data or graphics. Another thing you can do is avoid distortion graphics that distort the data by changing the scale or aspect ratio can be misleading. Make sure to use accurate and consistent scales.

originally you thought the graph and visualization you design is clear, however it might be very confusing for those business users as they are not so deep/familiar like you, make sure you involve them throughout the design life cycle, perhaps the pilot group really helps, since they are the primary user, communicate *3 and change according to their suggestion if applicable.

When communicating your data visualizations and insights, tailor your approach to your audience and use storytelling techniques for impact. Provide evidence, context, and rationale for your insights, inviting feedback and discussion. Present your findings in reports, presentations, or dashboards, incorporating narratives, charts, and interactive elements to engage and persuade your audience effectively. By adapting your communication style and format, you ensure your message is compelling and memorable, fostering informed decision-making and action from stakeholders.

Storytelling Techniques: Craft a narrative around your data to make it more engaging and memorable. Start with a clear storyline that highlights the problem or opportunity, the data analysis process, key findings, and actionable insights.

Process mining is a set of techniques for the analysis of operational processes based on event logs extracted from company dbs, information systems, or business management software such as ERP, CRM, electronic health records ... The process mining tools present processes visually, simplifying exploration & inefficiency identification. They give organizations an X-Ray visualization, facilitate interactive examination of every process step, aiding in inefficiency detection & resolution, leverage machine learning for root cause analysis, offer recommendations and alerts for corrective actions to tackle inefficiencies like rework & manual tasks, ultimately enhancing lead time, cost-effectiveness, & customer satisfaction.

No matter your role or title within an organization, data visualization is a skill that’s important for all professionals. Being able to effectively present complex data through easy-to-understand visual representations is invaluable when it comes to communicating information with members both inside and outside your business.

When considering data visualization and analysis, it's essential to keep ethics in mind. Ensure data privacy and security are upheld throughout the process, especially when dealing with sensitive information. Additionally, remember that data visualizations are tools for understanding and decision-making, not an end in themselves. Encourage a culture of data literacy within your organization, where stakeholders understand how to interpret and apply insights from visualizations responsibly. Finally, embrace creativity and innovation in your approach to data visualization, exploring new techniques and tools to unlock deeper insights and drive business success.

Begin by understanding your business goals and the specific metrics relevant to your processes. This clarity helps in selecting the right type of data visualization, tailored to highlight key aspects. When applying data visualization best practices, focus on clarity and simplicity for easy interpretation. During analysis, look for patterns or anomalies in the visualized data. Identify areas where processes may be slowed or improved. Use these insights to communicate actionable recommendations, fostering a data-driven approach to enhance business processes. Effective communication ensures that stakeholders grasp the findings and collaborate on improvements.

Data visualization can help businesses: Interpret complex data Draw conclusions Make informed decisions Identify correlations Spot patterns, trends, and outliers Uncover hidden insights Forecast potential outcomes Present data to non-technical audiences