Acting data-driven

The state of affairs in companies can be compared to a bulging refrigerator full of delicacies, unfortunately the only thing missing is the trained star chef for the appropriate preparation. So it's a matter of finding the right chef for you!

Currently, the focus of companies is on the procurement, collection and management of data: How do we get the data, how do we structure it, where and in which system do we place it usefully? These are important questions and considerations, however, those who want to be data-driven and digital should rather consider what they want to realize (cook) with it. Simply put, what is the purpose or reason you need the data? What results do you want to achieve? What decisions will it be used to make? How will the data be processed?

Once these questions have been clarified, it makes sense to think about what data you really need.Is it the maintenance of machines that you need to keep running, personalized advertising that you want to play out in marketing, or planning processes in controlling that you want to run through with different scenarios? What is the result that you can optimize with the help of this data?

If you start with the question of purpose and reason, it is much easier to hypothesize about which data might be relevant.In the course of this, it also quickly becomes clear how and where the relevant data you need comes from: firstly, through the collection of business activities within the company or secondly, through external acquisition.

Metacommunication of the data

Once the business outcomes are defined and the data set is appropriately prepared and released, further opportunities for using the data and implementing insights often become apparent. In some cases, it is even so clear that this newly acquired information can be processed and used directly.

In the past, the approach and communication was divergent: collect as much data as possible, use it to gain new business-relevant insights, and the more information you get, the more data you need. Today, the view is completely different and the desired outcomes are prioritized rather than the amount of data.

Techniques for analyzing data have evolved rapidly and different types of data are now available in almost unlimited quantities. The metacommunication of data has had a positive evolution. It is not data that leads to insights, but very well defined outcomes that require corresponding data.

The clever game with location data

A furniture store from the Ruhr area wanted to attract potential customers to their store rather than the stores of the surrounding competition. The idea was that if they offered targeted cross-promotional offers, they would better understand where customers go or spend their time before and after a visit to their furniture store.

The strategy plan was in place, now it was time to get the relevant data. The in-house furniture store app collects location information, but only if it is turned on in the settings of the respective mobile device and the GDPR has been accepted. However, most people allow various apps to share location information only "when using the app" and this happens mainly from home or directly in the store.

For this reason, the furniture store partnered with a mobile gaming provider that uses real-time data of a phone's latitude and longitude. The furniture store analyzed this data and found that customers were visiting either the nearby car wash or discount grocery store before and after their visit. Using a targeted co-promotion between these three companies, customers could now be persuaded to return to the furniture store again. The successful co-promotion also asked for new insights that could be played out in new ways, e.g. a discounted car wash service for as long as the visitors stayed in the furniture store.

Breaking down data silos for digitalisation

One thing should be clear to us by now, data belongs where it is needed to support decisions. In the past, we have produced vast amounts of data silos, now the task is to break down these silos and use the data where it enriches the value chain of companies. Data-driven companies don't collect data, they use the right data. A full fridge is not a five-course meal. Cheers...

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