How buyers benefit from costdata®.

Initial situation
‍Acustomer from the mechanical engineering industry received several offers for stainless steel components from different suppliers. As prices for metals fluctuate widely, it was unclear whether the prices offered were competitive. To ensure they were getting a fair deal, the customer decided to compare prices using costdata® market data.

‍Challenge
‍Oneof the quotes was €3.50/kg stainless steel. Without a reliable source of comparison, the customer could not be sure whether this price was in line with the market or whether he had room for negotiation.

Solution
By accessing the costdata® market data, the customer was able to immediately compare the quoted price with the current average prices on the market. He discovered that the average price for stainless steel in the database was €3.15/kg - the offer was therefore higher than the market price.

‍Result
‍Withthis knowledge, the customer went into negotiations and pointed out the market price difference to the supplier. This led to a successful price reduction of 10%, resulting in a new price of €3.15/kg. By using the costdata® data, the customer was able to strengthen its negotiating position and convince the supplier.

‍Conclusion
‍Thanks tothe precise data from the costdata® database, the customer was able to make a well-founded price assessment, avoid unnecessary costs and secure competitive pricing. In a short space of time, he achieved sustainable savings for his company.
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Initial situation
‍Acustomer from the consumer goods industry was looking for a supplier of plastic components required for the production of packaging. Due to the volatile prices in the plastics industry, it was difficult to realistically assess the incoming offers from suppliers. To make sure he did not accept inflated prices, the customer used costdata® market data to compare prices.

Challenge
One quote for polypropylene was €1.80/kg. Without accurate comparative data, it was difficult for the customer to assess whether this price was fair. He was faced with the challenge of making a decision within a short period of time, as the supplier was pressing for a quick response.

Solution
With the help of costdata® market data, the customer was able to immediately compare the price for polypropylene with the current market average. He found that the average price for polypropylene in the database was €1.65/kg. The supplier's offer was therefore slightly higher than the market price.

Result
Armed with this information, the customer went into the negotiation and pointed out the price difference to the supplier. Although the difference was not significant, he used the data to achieve a reduction to €1.65/kg - exactly in line with the market average. This small adjustment enabled the customer to avoid unnecessary additional costs, which would otherwise have added up considerably with the large order quantity.

Conclusion
Thanks to the precise data from the costdata® database, the customer was able to react quickly and soundly to its supplier's offer. He was able to fend off an excessive price demand and ensure pricing in line with the market. In this way, he was able to achieve short-term savings and secure long-term competitiveness.

Initial situation
A customer from the mechanical engineering sector was looking for a new production machine to expand its production plant. He had received several offers from different manufacturers, which differed greatly in terms of price, technology and technical specifications. In order to make the best investment decision, the buyer used costdata® market data to compare the machines comprehensively.

Challenge
The offers not only included different acquisition costs, but also varied greatly in terms of consumption costs, floor space and connected loads. The buyer had to consider not only the purchase price, but also the total operating costs of the machine over its lifetime. It was challenging to weigh up these factors efficiently, as each machine offered different technologies and specifications.

Solution
With the costdata® market data, the buyer was able to directly compare the different model names, technical specifications and purchase costs of the machines. In addition, he used the information on consumption costs, floor space and capacity costs to carry out a well-founded total cost analysis. He took into account not only the acquisition costs, but also the long-term operating costs in order to find the most economical solution.

Result
By comparing the various machine offers, the customer realized that a machine that seemed more expensive at first glance was the more economical option in the long term due to significantly lower consumption and operating costs. With this knowledge, he was able to make the best investment decision, optimizing not only the short-term purchase price, but also the long-term operating costs.

Conclusion
Thanks to the comprehensive data from costdata® , the buyer was not only able to compare the purchase costs of different machines, but also to include all relevant operating costs and technical specifications in the decision. In this way, he made an informed decision that led to long-term cost savings and better utilization of production resources.