EnBW, Energie Baden-Württemberg AG, is working on new business cases. One of them enables senior citizens to live a self-determined life within their own four walls for a longer period of time. The developed system detects irregularities in electricity consumption that can indicate emergency situations and alerts local care services.
The team around that specific business case has been put together from different areas of EnBW, Energie Baden-Württemberg AG, one of the largest energy supply companies in Europe.
They had already established research practices and conducted occasional user interviews.
Above all, the team needs qualitative feedback on the use of the product itself.
To gather this feedback they decided for an alternated phase system. In the interview phase, they set up regular interviews with seniors for one side of the product as well as with on-call services for the other side. After collecting enough valuable data and insights they switch to the work phase.
During the development, Swenja joined the team and was faced with a lot of previous interviews and the task to find a way to make them comparable.
Up to now, the documentation was mainly displayed using Excel tables, which meant that only a few insights were actually documented.
Immediately after Swenja had gained an overview of the research, she realized that documenting the interviews with Excel would not be effective because it led to too many time-consuming inquiries about the meaning of the insights.
In addition, a lot of knowledge was lost because documentation was too cumbersome.
When searching for a tool, three things were especially important for the team:
The tool should help the colleagues to carry out the evaluation in a structured way.
Conversations and interviews with seniors are a challenge even for experienced researchers. The conversations are usually not very structured and the test persons often deviate from the topic and start to talk.
Therefore the evaluation has to be very flexible. The evaluation must allow for quick and flexible changes to the scope of the evaluation during the analysis.
Link insights to interviews
It has to structure the results flexible and individually. The interviews with the two target groups seniors and on-call services are very different, but the findings must still be combined and evaluated.
The focus is always on the link to the raw data. Since the interviews are so different, it can often happen that in apparently unimportant statements important findings are found again later.
Easy onboarding experience
During the introduction of the tool, Consider.ly helped to find a suitable structure for the research and to make the tool known within the team. consider.ly was completely adaptable to our structures and proved to be very flexible.
The built-in chat function, which provides a direct line to consider.ly’s experts, allowed new colleagues to be quickly onboard.
How consider.ly helped
The positive effects of consider.ly on research could already be observed shortly after its introduction. Research that had previously only been superficially evaluated in Excel was now analysed in a structured manner and the results prepared for the team. This had the advantage that significantly more findings could now be derived per interview than before.
The interviews themselves are now stored centrally and can be viewed by all colleagues. Since the distilled insights are directly linked to the interviews, no knowledge is lost. Interview parts that seem rather unimportant now, can be reviewed and cross checked with future research in just a few clicks.
The consider.ly interface also allows us to create new tags or change existing ones while the data is still being analyzed. This ensures that we can start early with the analysis and develop our framework on the way
The handling of insights has also changed: The insights created are now directly compared with the team’s hypotheses. This way it can be determined directly whether a hypothesis is correct, requires further research or can be rejected.
The link to the original data is very important. With such an important topic as medical emergencies, the exact wording of the respondent is important so that the team can implement the Insight correctly.
With consider.ly, all interviews are systematically analysed and the results are processed into an ever growing Insights repository, which grows with every interview. consider.ly is one of the foundations of our product management.