Online stores are completely transparent, retailers know their customers, where they click and where purchase decisions are made. They can analyse all happenings and systematically optimize the shop.

Compared to online shops, brick-and-mortar stores are almost black boxes. But technological progress enables a digital twin in which the store and processes become transparent and can be controlled efficiently and targeted.

The potential and use cases for digitizing brick-and-mortar stores are enormous. There are two main groups of data that can be collected and used to improve store performance:

1. Digitalization of the building and equipment

Building Information Modeling (known as BIM) collects all the data of a building: the 3D building model including all objects, which can be building infrastructure, furniture, equipment and so on. Two types of data are collected:

• Static data, e.g. what type of cooling system including maintenance cycles, and
• dynamic data from the IoT such as the temperature of a cooling system.

All building data is summarized as Retail Information Modelling (RIM).

Use Cases are predictive maintenance, inventory management, asset management, building automation etc.

2. Process digitalization tracking all movements of articles and people

While RIM is digitizing the building and infrastructure is the digitalization of processes tracking all movements of people and articles in a store, e.g.

• People tracking and heatmapping.
• Articles:
  • Inventory/SKUs: assortment, quantity, quality and place (planogram).
  • POS data about all transactions and sales.
  • Prices (Electronic shelf labels).
  • Promotions (e.g. with digital signage).

The digitalization of the processes makes all movements transparent which enables a data-driven store optimization to increase the effiiciency and turnover in a store.

The following graphic shows the digitization possibilities of a store to create a digital twin:

The autonomous store where all processes in a store are automated is the final stage of a smart store. At the moment only semi-autonomous stores are possible, no store can be run without people yet.

Semi-autonomous stores are characterized by self-checkout, either through Grab & Go systems such as Trigovision, Aifi or Amazon Go or through self-checkout systems such as shopreme Scan & Go. Grab & Go has the disadvantage that it requires a lot of hardware such as cameras, which makes it difficult to scale the system, and that the technology is currently not 100% reliable.

When there is no staff on site, the building must be managed and controlled automatically. Required technologies are for instance

• a controlled door opening system adapted to the opening hours,
• climate control to ensure the optimal temperature in the room,
• triggering fire alarms,
• alarms in the event of a defect in the cooling system,
• etc.

The pioneers of smart stores are the already widespread self-service boxes, such as the All-In-Box we have built at Umdasch. Smart and semi-autonomous technologies work on about 12 square meters, now it is a matter of transferring the technology to common stores. This step is becoming indispensable as retailers face challenges such as staff shortages and the pressure to increase cost efficiency.

Umdasch Group Ventures is researching the technologies and use cases for smart stores. We bring the optimal conditions for this, as the Umdasch Group, in particular Doka and NeoTwin, has a lot of expertise in the building life cycle and its digitalization. By merging these competencies with our many years of experience in retail and shopfitting, we become the enabler for Smart Stores.

In addition, as one of the market leaders for Scan & Go, our joint venture shopreme contributes its expertise in self-checkout and the digitization of store processes.

Acting in a professional ecosystem like this we want to drive the development of smart stores.