People want to be mobile. In dense urban areas, bicycles are a great way to quickly get from A to B. And in many big cities, you don’t even have to own a bike, you can simply rent one. But for this to work, shared bikes should be placed where people need them. That creates a big challenge for bicycle rental companies, then the range of bicycles on offer is limited. For example, the urban infrastructure in Munich only allows a certain number of bike parking slots. On top of that, customers use the service very differently: some move spontaneously, others follow an hourly, daily or weekly routine. And even the weather plays a decisive role in usage and frequency. In sum, bicycle rental providers are facing many decision parameters and therefore require extensive data sets.
The Data Intelligence Hub is a simple solution to these problems – with sophisticated analytic tools and access to a wide range of information, such as personal movement or weather data. The Data Intelligence Hub obtains its extensive data sets from many open and commercial data sources. In case of bicycle rental, there is plenty of high-quality data from open sources such as population density and public infrastructures, such as the location of parks, schools and train stations. But often crucial information such as dynamic traffic flow data or the location of the customer at different times of the day is missing. On the Telekom Data Intelligence Hub this data is provided by Motionlogic. It helps to work out passenger traffic and movement flows based on mobile network data – of course, everything is secure and anonymous. A heat map can be derived from all this data on static infrastructure and real motion flows using the analytics tools of the Data Intelligence Hub. Switch it on, set up a project, create a workspace, select analytics tools, bring your own data and blend it with curated open and commercial data – all in one place on a Platform-as-a-Service, quickly and effectively – and of course in a secure manner with full control over data access and use.
This heatmap has many advantages. On the one hand, important behaviour patterns and trends can now be easily identified. On the other hand, a gap analysis is made possible: Where are bicycles missing when? Real bicycle usage data can be uploaded to the Telekom Data Intelligence Hub for this purpose and then projected onto the heat map as an additional layer. Now you have a quick overview of where and when bicycles are missing. Management can respond quickly with focused action; it can even verify the success of the response with the next refresh of the heat map. This is how success stories are quickly created with the Data Intelligence Hub Switch it on, set up a project, create a workspace, select analytics tools, bring your own data and blend it with curated open and commercial data – all in one place on a Platform-as-a-Service, quickly and effectively – and of course in a secure manner with full control over data access and use.