Do you also know this from your company? You want to evaluate a topic, use data for analysis and decision making. You know that this data exists but accessing and evaluating it is time-consuming. BI and data warehouse systems improve the situation, but there is still a huge treasure of data that many companies only use in rudimentary form: for example, unstructured information from customers in mails, texts, or social media.

When companies use data, they often build on existing structures. Opening new data structures is often costly and does not offer any immediate added value. At the same time, new technologies such as social media and chat bots are being piloted and used in peripheral areas. This pragmatic approach makes sense in principle, but it is also important to be aware of the different data uses and data sources.

An exercise in the DataValueThinking workshops is to name different “data zones” in the company’s data lake. Here, a distinction is made between data that is in direct access and awareness, data that is already in use but is difficult to access, and data treasures that are hidden. The next step is to discuss what a salvage of data treasures from the depths of the company could achieve.

Customer Feedback, Language or Text – a Data Treasure

In our workshops we often encounter unstructured information contained in mails, letters, social media, and other correspondence as such treasure. Customer orientation? What the customer wants? How satisfied is he? Yes, you can query it. But who does not know the tiresome customer surveys that you click on rather listlessly, if at all? At the same time, you can recognize the customer’s satisfaction through tone of voice, choice of words and content in the interaction with the customer and often a good customer addresses his wishes directly to the company. There is a growing range of speech recognition and interpretation systems on the market that convert unstructured text into structured information and thus make this valuable information accessible.

At the same time, many texts are created and edited within the company. This content can also contain a data treasure. A common example of this is the handling of error messages. Meaningful analysis not only speeds up future error handling, but often access to this information provides a value or service in itself. Another example: CRM systems in which customer inquiries are stored and a higher-level evaluation of the most important topics could be useful.  

However, the introduction of these systems can be costly. Training the terms of your specific industry and language is an important and intensive exercise. It is also important that the software recognizes which information is relevant in which context. To ensure a pragmatic introduction and use of these systems and thus of the data sources, it is important to think about initial usage scenarios and evaluations. At the same time, the systems should be expandable.

Of course, it is not enough to point out ideas and observations in workshops. It is also important to provide suggestions for possible solutions based on real world experience. Here we also make use of our technology partners, who in turn use the results and presentations of DataValueThinking for their own positioning. A good example is our partner Insaas. Insaas is a software solution based on artificial intelligence to evaluate large volumes of customer voices and communication content. This expertise and technology enables companies to understand customer needs and make customer orientation measurable. The automated analysis of opinions and moods allows product and marketing experts to identify critical issues and align products and services more directly with end customer expectations.

Insaas shows very clearly how important it is to use data from the different areas of the company or the different data zones in a short video

Insaas represents just one way to use data sensibly to increase the value of the company and streamline its operations. In addition to technical solutions and products, a prerequisite for this is to anchor the data culture in the company. Use the methodological framework and creative approaches of DataValueThinking to unlock the hidden values of the data treasure in your company. Learn more about DataValueThinking.

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