7 lis 2020
Pobierz Case Study


Food retailer that distributes exclusively organic certified products

• Currently 60 stores
• 550 m² is average store size
• Around 8,000 articles in the large stores

Denis Schulz  |  Category Manager

When did you start using Quant? Do you remember your expectations from that time?

After some years of working with Excel, photos from a camera and a sample rack (equipment) in a store, we took the next steps towards a “Professional Category Management (CM)”. The first employee took a CM course at GS1 and learned how to work with a planogram software. This was in 2015/2016 and so we talked extensively with different software vendors and finally, from our point of view, we stayed with the best software with the best price/performance ratio and decided to go with Quant at the end of 2016. We wanted a software that was easy to use, that would evolve, that would respond to our needs and that could reflect the diversity of our different stores. Of course, it should also be possible to connect our stores and we also appreciate the fact that there are access points for suppliers. All this was important for us, because up to now the health food trade was rather casual in comparison to the conventional food retail trade. We took the first steps in January 2017.

What were the worst obstacles?

When you start such a project, you naturally have “great expectations”. Everything should be done as quickly as possible, with low costs, low resource consumption and as little work as possible. And the question was how best to start. The biggest challenge was to record the status quo in the stores (shelf widths, shelf spacing, the number of shelves, etc.) and then map it in Quant. This was the most time-consuming part of the process and it took almost a year before we could create the first planograms.

How did you succeed in overcoming them and what were the first benefits you got?

In such a small organization as Bio Company, it is important to use resources wisely. We discussed a lot about the final way we want to go and how detailed we want to create the planograms. In the end, we decided to go for the more labor-intensive variant and we consciously accepted this. Today, we can create an individual planogram for every shelf, regardless of size, width and height, and for every store. Nothing is impossible and we know 100% which products are placed where. The informative value is relevant for all evaluations and is of utmost importance for future decisions. Local planograms can be created in this way and thus we can offer the customer on site a range of goods tailored to the location.

How long did it take you to publish first planograms to all your stores? Have you used Quant Web from the begining? How difficult it was for your stores to get used to it?

We launched the first planogram in January 2018 and the stores did not experience any implementation problems. The visualization of the shelves and the listing of details made it very easy to implement things.

Do you use integrated communication channels like Chat?

We are currently not yet using the internal communication tool. So far our proven methods have been established. But what we will use shortly is the photo confirmation. Our branches will all receive computer tablets shortly and after the implementation of the planogram they can create and upload a photo for confirmation.

Very important part of the whole project was integration of automatic data transfers from multiple sources like Bio Company ERP and DataNature. Could you briefly describe how do you use the data in Quant and what are benefits of such integration?

Every exact planogram needs good product pictures and exact product dimensions. Since our own merchandise management software does not provide this data, we have joined DataNatuRe. It was important to us and we appreciate Quant’s flexibility in providing an interface. So every day a matching of the software takes place. If we create new products on one day, we have the data (pictures, dimensions, XLPE size, etc.) available in Quant the next day.

You opened new stores using Quant. Could you describe the main benefits of having store planned in Quant prior to opening?

When we connect a new store to the network and the plans from the real estate department are available, the planning starts in Quant. The branch plan is taken over — it is very simple! We import the PDF and distribute the assortments accordingly. The big advantage of this is that we were able to shorten the implementation phase considerably, because the orders can be realized much more easily. Through Quant, we know the required quantities, which we order from the corresponding suppliers. To do this, we export the data via an Excel spreadsheet to our merchandise management software and then trigger the orders accordingly. The goods arrive at the store in the exact quantity. This saves us about three working days in the store and another two working days for the order.

What are your favourite reports and features?

Our weakness… we currently use the good analysis methods very little or not at all. But this is only related to the personnel and hourly resources. From October 2020, we are hiring a new employee who is almost exclusively responsible for „CM“ and then we can finally look at the shelf and space productivity across all stores. Store-specific sales analyses will also become even more relevant.

How would you rate the quality of the support?

I can’t report anything negative about the support. When you need it, you get help quickly. It goes without saying and is uncomplicated. A solution is usually available within a few hours.

What are the main results of the project so far and what are your future plans and targets in area of space planning and category management?

As a conclusion it can be said that with every new planogram we gain new customers and increase sales, as well as the turnover in the category increases. It is a reliable and easy-to-use tool.

Would you recommend Quant to others?

I will be happy to answer any questions you may have and I am also willing to give a demonstration. I can recommend Quant to any major retailer.


Possibility to create local planograms based on sales data


Store specific planograms

Opening new stores using Quant

Gaining new customers

Integration of automatic data transfers from multiple sources like Bio Company ERP and DataNature

Increase in sales and increase in the category turnover