How to maximise profit margins with AI

massimizzare margini di profitto

Analysing pricing choices and the margins they generate allows companies to understand and identify where revenues and margins are most efficiently expanded or where they are most easily lost for each product, customer or transaction type, as discussed in the article on Price Waterfall analysis.

To do this, it is necessary to possess a large amount of data coming from different sources and it is also necessary to possess the technological instruments which allow the above-mentioned types of analysis to be carried out, and finally, it is necessary to possess advanced forecasting instruments capable of going beyond a simple static forecast model for revenues and profits. The use of artificial intelligence in pricing is the perfect enabler to perform these analyses in an increasingly innovative and high-performance way.

What can be done to reduce margin compression?

Structuring prices or contracts in such a way that they can be adjusted for any increase or decrease in costs or for market and competitive pressure. If such a structuring is not applicable, strategic and timely changes can be introduced to temporarily increase prices in response to short-term or more dynamic scenarios. Set up your data flow, processes and systems to enable automatic recalculation of pricing in downstream transactional systems, such as in the resource planning phase and in the monitoring phase of digital purchasing platforms.

The difficult situation resulting from the deployment of Covid-19 has resulted in a major change in supply chain structure and increased costs, which at the same time provide an opportunity to introduce this new approach to the market and make it known to consumers. So what can be done to reduce margin loss?

  1. Use the Price Waterfall structure to identify and analyse the profitability drivers of products, customers and transactions. And use them in negotiation processes.
  2. Incorporate this insight into the lead-to-order process, integrated with resource planning (ERP) and CRM systems.
  3. Provide comprehensive pricing and profit guidance for use in sales negotiations.
  4. Eliminate the possibility of customer service overriding prices in the resource planning system without approval.
  5. Measure volumes and revenues against contracts and use this data in the future.
  6. Use volume incentive rebates with the necessary technology support, as they are often difficult to manage without a platform to set and control them in an automated, real-time manner.

So, what is often observed in various markets is that the most obvious margin losses occur when the speed at which conditions outside the organisation change is greater than the speed at which the company reacts to these changes. This requires a high degree of business agility, but especially in pricing to positively affect profits. Only this responsiveness can help reduce margin compression or loss. To make this possible requires people and resources, but also processes and systems that can be automated to the level needed to respond quickly to changes in costs and the dynamics of the market and competition.

Artificial intelligence applied to pricing may be the most effective tool to achieve this. Digital transformation, the use of AI, is now a vital step in equipping companies with the agility needed to compete in the market today and avoid losing margins in the future.


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