How can you visualize ERP data analysis to make it more accessible for stakeholders?

For effective ERP data analysis, start by identifying key metrics and KPIs crucial for stakeholders' decision-making. Develop interactive dashboards presenting essential data trends and comparisons using charts and graphs. Enable stakeholders to explore data segments with drill-down features. Use time-based visuals for historical insights and geographical representations to highlight regional performance. Incorporate predictive analytics for future trends and offer context through narrative elements. Ensure mobile compatibility and provide training and ongoing support for better understanding. Encourage feedback to continuously enhance visualization usability.

Let's simplify ERP data with quick insights: 1. Dashboards: Command centers for a quick overview. 2. Visual Masterpieces: Turn data into easy-to-understand charts and graphs. 3. Color-Coded Guides: Heat maps highlight trends with colors. 4. Zoom In/Out: Magnifying glass for detailed exploration or big picture view. 5. Bite-Sized Visuals: Infographics tell stories in a nutshell. 6. Data Storytelling: Treat data like a story to understand the journey. 7. Mobile Accessibility: Ensure visuals work seamlessly on your mobile. 8. Collaborative Tools: Virtual spaces for group discussions and analysis. 9. Personalization: Customize your view, focus on what matters to you. 10. Learning Support: Quick training sessions available for any questions.

Gone are those days where stakeholders are dependent on canned reports! Now a days ERPs are equipped with Control towers / workspaces which drives the day for each stakeholder to do what is the insight for their functions, what are actions to be taken, what is alarming, key metrics, collaboration so on and so forth.

I used to work with a large nuclear power generator that combined their SAP data with definitive KPIs and analytics that were shared on 70-in screens in the hallways and cafeterias for all of the senior managers to see on a daily basis. Mostly related to supply chain, the constant visualization of their burn rate made everybody acutely aware of overhead and down time that was being built on unproductive tasks.

Management Information System (MIS) and Decision Support System (DSS) are the most important and the final step of an ERP implementation. It is like the Iceing & Cherry on your Pastry. As said, ERP has voluminous data and consolidated view is this very essential. The dash board can be like this: AR, AP, Procurement and Sales and price movements, Order position, Inventory, Cash Flow, Contribution & Profitability, Repeat orders, Lost customers and opportunities. We can also fix KRAs & KPIs, Projections for different business functions and compare Actuals Vs Projections. These can be individual dash boards and will be quite easy will save loads of unproductive time of the management and with live data.

The significance of consistency cannot be over emphasized. Time overtime are policies, practices and rules change. They often result in inconsistent numbers being drawn. It is the responsibility of financial planning analysis and reporting team twin sure that the data being presented for visualization is consistent.

Standardization is crucial for effective data visualization and dashboards. Consistency across different reports not only creates a sense of familiarity but also facilitates easy understanding for stakeholders. When there's a standardized design, management can quickly grasp and interpret the data without being overwhelmed by varying formats that might distract from the information presented. Moreover, a standardized design lends professionalism and reliability to the data being communicated. It allows for easier comparison between different reports and ensures that the focus remains on the insights rather than on deciphering the visual elements. Presentation and design skills play a pivotal role ultimately aiding informed decision-making.

Most of the times the tool capabilities dwarf the user operability. This makes developers design fancy charts with no scale and legends and flashy colourful graphs. While the visuals may be highly impressive, the user might get distanced from the solution. Hence, the basic design principles and consistency is ever so important. The key objective of any visual is for users to derive insights and make data driven decisions. For that to happen, the fundamentals of graph still need to be taken care while addressing aspirations of design aesthetic.

Start by choosing intuitive chart types like bar graphs for financial data, line charts for trends over time, and pie charts for market share or segment distribution. Employ a cohesive color scheme to differentiate data sets while maintaining visual harmony. Utilize interactive elements like hover-over tooltips for detailed data points and filters to allow stakeholders to customize views according to their interests. Ensure that all visualizations are labeled clearly with legible fonts and include a brief narrative or bullet points to summarize key insights. This approach not only makes the data more digestible but also helps in highlighting the most crucial information, aiding stakeholders in making informed decisions.

There is no need to re-invint the wheel ! Keep the reports simple. One thing I actually found helpful, users are used to reports in Excel and powerpoint. * Hence the closer the reports format to Excel and Powerpoint the easier they will read them. * Allow between 3-6 reports to be on the main screen of managers and high users. * Always let the time scale of the repot to be customizable ( hours, days , weeks, months) and to be imported for the period as well. * Colors are always helpful for story telling.

This is where you need to open up your perspective and invite an artist into the team. I have worked over 25 years with data. I understand how to organise and categorise the data to make it more accessible. I do not have the brain that allows me to make the most impactful visualisations. It takes a village to create visual storytelling that is impactful for a variety of stakeholders

If the visuals don’t progress the underlying data to information to insights, the value of visuals is lost. They just remain for the sake of only. It’s is absolutely important to know the purpose of your dashboard, the target audience and the impact of decisions your target audience would be making based on the story that your dashboard narrates. If the visualisation cannot let the data talk and describe the hidden facts, it wouldn’t serve any purpose. Visuals has the ability to connect the dots and deliver powerful insights that isn’t possible with data represented as-is.

Use a dashboard with interactive elements like graphs, heat maps, or trend lines to depict these metrics. For instance, a line graph could show sales growth over time, with different colors representing various product lines or regions. Incorporate a geographical map to display regional sales distribution, enabling stakeholders to instantly grasp market strengths and areas for improvement. By integrating real-time data, stakeholders can interact with the dashboard to explore different scenarios or time periods, making the data story dynamic and relevant. This approach not only simplifies complex ERP data but also empowers stakeholders to make informed decisions based on clear, visual insights.

Telling a compelling story with data involves several key steps. Begin by understanding your audience and what message you want to convey. Structure your data into a coherent narrative, using a clear beginning, middle, and end. Choose impactful visuals, such as charts or graphs, to illustrate key points. Provide context to help your audience interpret the data, and use annotations or callouts to emphasize important findings. Use a narrative arc to guide your audience through the data, making it relatable and engaging. Finally, practice simplicity, ensuring that your data visualizations are clear and concise, allowing your audience to grasp the story without unnecessary complexity.

"The only thing worse than no data is Fake data" If the ERP system is spitting the wrong data out it can lead to catstrophic results ! Simply because it could lead to moving the whole company resources in the wrong direction. It's not umcommon for ERP system admins to lie with statistics! just to give a good image. Sometimes employees learn how to do that themselves and manipulate the data to make it paint the picture they want to it to paint. So as a system designer, user or admin , be careful with how data is represented and while I advised in the previous article for customization. It must be done with the idea of possible manipulation in mind. I will discuss statistics manipulation in the next article due to characters limitations.

I believe that AI powered visualization tools are the future of decision making. It is crucial to view raw data in a graphical format as it gives quick insights about performance, gains, losses, and/or market share. Drilling down is very useful to understand in more details a certain phenomena. However, I believe, the decision maker needs also more forward looking information, like for example, expected performance, market landscape behavior, customer experience evolution, and supply chain networks dynamics. Such info can provide deeper insights that should help improve organizational performance and even strategy review.

1. Create interactive dashboards that display key ERP data analysis metrics in a visually appealing and user-friendly format. 2. Utilize data visualization techniques such as charts, graphs, and heatmaps to present complex ERP data analysis in a simplified and intuitive manner. 3. Incorporate drill-down capabilities, allowing stakeholders to explore specific data points or categories for deeper insights. 4. Use color coding and visual cues to highlight important trends or anomalies in the ERP data analysis, enabling stakeholders to quickly identify key information. 5. Provide clear and concise data summaries or narratives alongside the visualizations to provide context and enhance understanding for stakeholders.

Data analysis for stakeholders involves creating clear, concise, and interactive dashboards that highlight key metrics and trends. It's also beneficial to include filters and drill-down capabilities, allowing stakeholders to explore the data at different levels of granularity. Real-time data visualization is particularly effective, as it enables stakeholders to see current performance indicators and make informed decisions quickly. Additionally, ensuring these visualizations are accessible on various devices, including smartphones and tablets, can increase engagement and accessibility for stakeholders who are often on the move.

It’s also very important to highlight how the new era of GenAI harnesses the power of artificial intelligence to enhance data visualization with (ERP) by creating intuitive, dynamic visuals tailored to specific datasets and user preferences. GenAI can quickly identify patterns, trends, and outliers, transforming complex data into accessible, insightful charts and graphs. This facilitates informed decision-making, reduces the cognitive load on users, and helps teams understand vast amounts of ERP data at a glance. GenAI also ensures visualizations are not only accurate but also aesthetically pleasing by automating the design process, leading to more engaging presentations and reports.

While some may argue that data visualization is not an essential component of an ERP system, I firmly believe it plays a crucial role in streamlining decision-making across all organizational levels. An ERP system effectively integrates various facets of an organization, from data entry clerks to the CEO, and it's imperative to provide each level with features that align with their needs and responsibilities. Data visualization serves as a valuable tool for management and top management, enabling them to extract meaningful insights from data and make informed decisions that drive business success. The type of charts and data segmentation employed should be tailored to the specific purpose of the visualization.