It’s not about having sustainable ambitions, it’s about creating sustainability data that is one of the biggest challenges for big corporations. The ‘why’ in this story is clear as daylight; it is the ‘how’ and ‘what’ that is nagging them.
In the last years, I’ve learned that creating consciousness isn’t a problem. I’ve seen lots of highly motivated people, from the top to the bottom of the company, who want to make a difference.
People are also willing to change their behavior. From traveling by public transportation to keeping records on CO2 emissions, there are lots of concrete examples that people aren’t the problem most of the time.
It is the process that is the problem. No, it’s the process and the systems, together, they’re the problem. And here is why: nowadays we’re used to the comfort of the 21st-century technology. From ordering pizza in two clicks on your smartphone to paying with your fingerprint, technology made a lot of things more accessible than ever before.
Now let’s focus on the corporate process and systems. Lots of organizations use spreadsheets to manage their sustainability data. Managing data in spreadsheets is prone to error. Especially for people who are not used to work in spreadsheets, this can be experienced as a spreadsheet-hell.
Now let’s go back to the highly motivated people I met in the last couple of years. They are talented when it comes to realizing sustainability. But when it comes to working in spreadsheets, that’s not their cup of tea.
This is what we’ve seen in reality: people start highly motivated and set ambitious goals for themselves and their organization. Then reality kicks in. They spend most of their time in spreadsheets, collecting, and managing data to measure, manage, and report. It’s spreadsheets all day, all night. Before they know it, those ambitions seem further away than ever. People start to get demotivated, and the job they signed up for isn’t what it was supposed to be. They were going to change their employer and world for a better place!
This seems unfair, right? That’s true, but there is a great lesson to learn here: being motivated isn’t good enough. It would help if you had valuable insights from your data. It would help if you had a useful overview of those valuable insights. And it would also help if you had a tool that enables you so to put those insights into action. That seems more like 21st-century tools, right?
In this interview, Jonathan Aardema talks with Prof. Eric Postma (professor of Cognitive Science and Artificial Intelligence at the University of Tilburg) about the why, how, and what of artificial intelligence applications. What do we see in practice, and what does science say about it?
Every year Tableau invites its most valuable partners to kick off the new year together. The theme for this year was Accelerate, so let’s get right to the point. This exciting event was focused on three main areas.
Keeping your skills up to date is crucial when you work with the newest technology. At Rockfeather, we challenge each other to be the best version of yourself. That’s why I attended the mastering DAX course. DAX (Data Analysis Expressions) is a formula expression language. Next to Power BI, DAX is applied in Excel Power Pivot and tabular models in SQL Server. Learn it once, use it tomorrow.