Lindab faced a decision whether to invest millions of Danish kroner in a new production facility to specific rustproof components. It was a new market for Lindab, who is an international group dealing with solutions to simplify constructions and improvement of indoor climate. But would such an investment be profitable? Would the customer base be sufficiently large and if so how should they address the market?
Our analysis gave Lindab the following insights:
- Precise knowledge about the customer base on a potential new market
- Saved millions by avoiding investments in a new product the customers didn’t sought-after
“We needed to know whether it would attractive for us to enter the new market,” tells sales director Puk Spencer from Lindab A/S about the reason for collaborating with ag analytics on market analysis and to uncover potential. The target group was companies within naval, foods, pharma, agriculture and contractors.
Lindab expected that the end users would sought-after specific rustproof components. But it turned out not to be the case. The end users knowledge were low and specific preferences none-existing. The end users wanted standardized rustproof component and expected that the systems they bought were functional and met the industrial standards.
– ag analytics understand our needs well. They are thorough, but on the same time quick and they are willing to optimize the process on the way, when it is necessary to secure the quality and to provide output we can use.Puk Spencer, Sales Director, Lindab A/S
– So we saved a couple of millions and a lot of time, Puk Spencer concludes.
On the use of analysis in the decision process, Puk Spencer says:
– We obtain greater security for going in the right direction when we invest, develop strategy or prioritize resources. We have e.g. earlier with ag analytics unveiled what housing associations had of renovations in their pipeline. That made it possible to optimize and use our resources better, because we could target our initiatives. Today it is clear that the predictions from ag analytics were spot on.