A 2019 report by Gartner stated that “culture and data literacy are the top two roadblocks for data and analytics leaders”.
At KNIME Data Talks, five German companies described their journey towards becoming data-driven enterprises and the techniques they are using to tackle the challenges along the way.
There are quite some hurdles to overcome. Data analytics can prove too complex and too difficult to manage when capacities are limited. In medium sized companies, for instance, data scientists are few and far between and often work alone. Data analytics processes frequently prove to be difficult for other departments - Development /Ops/Product Management - to understand and integrate into their own work. So how can these issues be solved?
Implement a Visual Workflow Environment
At the WIMEX Group, data science techniques have been used successfully for many years already in Controlling and BI. Their journey towards a data culture was made easier when they started implementing a visual workflow environment. This helped increase not only understanding of the data science processes but collaborative work across departments.
More recently the company has been applying their data science knowledge to more advanced analytics for smart farming. They are using AI workflows in KNIME software to evaluate weather information, soil moisture data, and network automated information into intelligent systems. Greater knowledge about the soil, for example, is crucial in being able to predict the potential yield of a crop.
Another way to make the journey towards a data culture easier is to find a software for analytics and automation that fits the needs of users. At internetstores GmbH, they identified the different user types in their companies and found a data science tool that can be used by them all.
“It’s not dedicated to developers, data scientists, or engineers only”, said Ingo Geisel, data scientist at internetstores GmbH, “It can be useful for anyone working with data. Just give it a try!”
Set Up Data Science Knowledge Channels
internetstores set up various knowledge channels e.g., brown-bag sessions, newsletters, success stories, and they also have a support user group in place. The company has been able to not just continue using KNIME software successfully but also expand usage to more users across the business for more use cases and incorporate more features. Since the additional integration of KNIME Server, they have reported even greater returns on the time invested to empower their employees with data science skills. In the near future they will be doubling the number of users working with KNIME. The fact that the Analytics Platform can be used by anyone working with data - not just developers, data scientists, or data engineers makes it a powerful tool on their road to becoming a more data driven company.
Establish a Community
Founding and establishing a proactive data community empowers employees with data science approaches to solve use cases themselves. There is a strong community network at Siemens used by approximately 6,000 users. They are now able to reduce manual work with automated workflows and perform advanced analytics with KNIME software. Accessibility to their Data Vision program and attending on-site and online events enable colleagues to learn new AI tools, share use cases, and follow the newest projects and challenges in the company. From the start of the data culture journey, Siemens reported it takes only 8-12 weeks for employees to become proficient at using data science in their work.
The experience of the companies presented at KNIME Data Talks shows the true value of investing in becoming a data-driven enterprise and thus improving efficiency and enabling informed decision making.
Now Watch the Presentations
Below are links to three recordings from the KNIME Data Talks event, of the presentations by Ulrich Wagner (WIMEX Agrarprodukte), Ingo Geisel (Internetstores GmbH) and Matthias Stephan and David Wroblewski (Siemens AG) as they describe the journey their organizations have taken to establish a data-driven culture.
Note: The talks are in German with English subtitles. If the subtitles don't display automatically, simply turn them on by clicking the captions icon, which is to the left of the volume settings.
How are data analytics used in a medium-sized family-run agricultural company? Ulrich Wagner describes how WIMEX Agrarprodukte has established using KNIME as their data analytics tool successfully for controlling and BI plus AI.
KNIME can be useful for anyone working with data, just give it a try! Ingo Geisel from internetstores GmbH tells us how the company moved from an individual solution used by a single practitioner to a cross-functional user group and explains how setting up knowledge channels geared to specific user types helped.
DataVisions is an initiative at Siemens to empower colleagues with data science methods. David Wroblewski and Matthias Stephan use this coaching approach to train teams and support them in solving their use cases themselves. A strong community network enables them to develop skills easily and learn to use advanced automation and analytics with KNIME software.