Innovation with data and AI requires more than just safeguarding privacy risks. Especially when things become complex—where ethics, human rights, and compliance intersect—it is essential that the right people come together and engage in meaningful dialogue. A DPIAMA combines a DPIA and an IAMA, bringing business, development teams, and compliance together at one table.
In our High on AI-podcast, we talk through the real world stories and use cases of business and organizations successfully introducing AI into their everyday work lives, to do all the things AI promises to do, can do and more.
Because visualizations within organizations can be created in many ways, the search for the right form is on. Design choices affect the outcome. The content may be seemingly identical, while a powerful design ensures that the message is better understood or comes across better. The following six tips will help in the choice of design. Tip 1: Choose a clear target audience for the visualization A director does not want complex Excel sheets, while others want to study the details. Therefore, match the message to the target audience. If the target group is organization-wide, make sure it is accessible to everyone and keep it as simple as possible Tip 2: Choose the setting in which the visualization should land Is it a report from tooling, the report and presentation of a study, a communication message, a drawing on whiteboard or flip chart, a supplement to a quotation, the setting gives direction to the design. A communication message should only be about the message, while a visualization in a quotation should be visually appealing and also support content Tip 3: The art of omission Ask whether it is really necessary to present certain information. The more information is left out the more focus there is for what is left. This makes a discussion much more specific and gets people thinking in a more focused way Tip 4: Within visualizations, use figures instead of text If, within a visualization, a word or phrase can be replaced with a figure, it is easier to understand and sticks better. This works the opposite way if the chosen figure is not sufficiently clear, then discussion and ambiguity will arise Tip 5: Provide overview within the field of view For example, an infographic fits into one page, but if there is a lot on it, the message is lost. On the other hand, if there are more visualizations for the same topic, ask yourself if it cannot be combined in clickable selections, for example Tip 6: Use lots of color Dark colors are more likely to be boring. Bright colors appeal, but are not always easy to see or it is childish. Therefore, when adding color, always make sure it is the right shape and accessible Extra tip: Contact for more considerations for creating powerful visualizations
Data is increasingly put in order as a result of attention to data management. It is forgotten that this leads to improvements in the primary and supporting processes, resulting in fewer errors and higher effectiveness. These process improvements, in turn, ensure that the data quality increases, resulting in a self-reinforcing effect. So, after putting the data in order, don't forget to improve the processes. More and more organizations are serious about data management. This is to comply with the AVG (General Data Protection Regulation) but also because they can realize ambitions such as information-driven work on the basis of data. When complying with the AVG, the focus is on what data may and must be retained and who has access to this data. With information-driven work, it is mainly the search for data on which control can take place. As a result, data has increasingly been put in order. In other words, an inventory is made of the data present within the organization, because there is often no overview of it, and then it is placed in a suitable location with appropriate authorizations. But all too often it is forgotten to make better use of this data in the primary and supported processes. An example of this in the primary process is putting client files in order in a healthcare institution. The added value of this becomes much greater if one then looks at how this data can be used effectively and efficiently by employees. What information do they need in order to best help the client in specific cases? How can we ensure that precisely this information is easily and quickly extracted from the file. Another example is the deployment of steering information. Based on this data, the quality of the capacity management of employees in support processes can be examined, or where in administrative processes the greatest delays occur. This often turns out to be low-hanging fruit because it takes little time to identify improvements. If process improvements are achieved in this way, this also leads retroactively to further strengthening data quality. After all, when processes have fewer errors and are more effective, data quality also increases. This creates a self-reinforcing effect. If you want to know where data-based process improvement can be achieved for your organization, please contact me.
Governments want to work in a data-driven way, using data to design policy and implementation more efficiently. This starts with making the data accessible, offering insight into the data and thereby telling the story. Data visualization and dashboards offer a low-threshold method for this, and directly help to work and steer in a data-driven manner.
More than ever, technological developments are bringing with them a variety of possibilities. Because more is possible, organizations also need to know more about it to determine what to do or not to do. In most cases, developments can work for you, but thorough preparation before starting projects is recommended to avoid disappointment. So what should you look for when starting a project with an Internet of Things (IoT) component?