SHA Scheffler Helbich Architekten is an innovative architectural office located in Dortmund and Berlin. SHA focuses on the design of commercial buildings in the areas of DIY stores & building material trade, bicycle trade, sports facilities, industry & commerce as well as administration.

1.

Challenge Introduction

Development of a software solution for the prediction of potential new building projects in the sectors of DIY stores, building material trade as well as bicycle trade.

2.

Challenge Details

Due to its extensive experience in the DIY & building materials and bicycle retailing sectors, SHA provides its customers with very comprehensive advice, also with regard to future space utilization and optimization. Within the scope of the Challenge, SHA would like to match its existing data-driven experience with publicly available data and information in order to learn in advance about the needs of a potential customer. In the future, this can take the consulting approach to a new level, in that a customer can be made aware in advance of a development that has just taken place at a location and the solution for this can be developed together.

In concrete terms, the challenge will involve the structured recording of public data such as the size of the plot, existing buildings (floor area), number of floors, gross floor area, small scale and clear height in the existing building stock, paved areas for parking spaces and deliveries, as well as the existing green spaces.

At the same time, it will be a question of recording the current capacity utilization, which will be obtained, for example, through mobility data, standing times on delivery, density and turnover frequency of the stored goods, etc. This information has to be linked to internal information / empirical values in order to indicate possible requirements to potential customers and to enter into discussions based on this.

The overall goal will be to develop an automated tool that alerts to planning and change needs at logistics and retail locations. One way to get there, the first step could be a tool in which a list of addresses / locations is entered to filter for potential candidates. In a second step, these locations, which are entered once, are to be checked regularly in order to identify future needs at an early stage and report them automatically. And in the final stage of expansion, the aim will be to use register entries to identify existing locations themselves, analyze them and report them accordingly.