It is vital for a company to avoid making a loss (or disappointing profits). This is why continuous management of profitability is necessary. Managing for performance is easy when costs are constant, easy to estimate, or when the difference between selling price and cost is large.

As soon as sales prices have to be lowered due to competitive pressure, costs start to increase, show great variation, are not properly estimated and/or are unpredictable, managing for profitability becomes a major challenge.

Historical data does not guarantee the future

Traditionally, companies have used methods that can be summarized in the terms pre-estimation, post-estimation, and variance analysis. The pre-estimation is all about the expected costs. The post-estimation on the actual costs. And the variance analysis provides insight into things like price and efficiency differences. There is nothing wrong with this way of working in itself. What is wrong with it anno 2021 is that in practice this approach has far too high an “accountancy” character. By this we mean, that the variance analysis is not carried out frequently enough and is mainly based on data from a too distant past that does not provide sufficient guarantees for the future.

Self-learning algorithms help with profitability optimization

The Quotation Factory is working with its clients to find a much better approach to this. Through far-reaching digitalization, simulation and the application of self-learning algorithms, steering for profitability becomes a process that:

  • Is strongly data driven => high frequency of metrics at many data points;
  • Is self-learning => use the most recent facts to estimate more realistically;
  • Is focused on discovering trends => finding patterns and predicting the (near) future.

This allows the entrepreneur to make the necessary adjustments and improvements within the quotation process at the right time and with more certainty. In a number of cases, those improvements can even be made autonomously and directly by the software (Quotation Factory in our case) itself.

Enormous improvements in estimating production time and material consumption

The video below is an inspiring conversation between Wim Dijkgraaf (CEO) and Lotte Noteboom, artificial intelligence specialist at the Quotation Factory.

They address the vast improvements that can be achieved in estimating production times and material consumption. The Quotation Factory can in fact recently learn from information from the production process itself. As a result, it is expected that differences between pre- and post-estimation can be largely eliminated. At least in terms of production times and material consumption. This minimizes differences between quotation and reality. Machine Learning is the technique that makes this happen.

Be sure to get in touch if these unique opportunities can add value to your business! The perfect Proof of Concept during the vacation season…we’re here to help.