Never before have we been so inundated by data. And it is because of this influx of data that companies are looking for better-substantiated and clearer insights into their business. Insights that these companies can rely on to take crucial decisions, including in relation to customer acceptance. A carefully balanced decision model is the tool that makes it possible to take all of that data and implement a uniform and efficient policy on customer acceptance.
The way a decision model works is quite straightforward. It provides an outcome to act on or a recommendation about a specific question by taking account of the parameters set out in a decision tree. In the context of B2B, a decision model is a great thing to have to streamline and optimise a company’s policy on customer acceptance.
In the process of accepting new customers, the decision model is an application that a company or organisation uses to translate its policy into a clearly defined set of business rules. These rules – for example about the payment behaviour and creditworthiness of (potential) customers – are set down in a decision tree and feature specific checkpoints. The model then provides an answer to the question of whether doing business with certain customers/prospects fits into the company’s business processes.
Plenty of other benefits flow on from using a decision model in the customer acceptance process. In this blogpost, we will limit ourselves to the six most important ones.
The speed with which a business relationship is assessed with a decision model is amazing. Some companies require hours and even days to evaluate a customer. So much business data needs to be analysed and interpreted – and only a few specialists are trained to do the work. So it is no wonder that the customer acceptance process can be time-consuming. But this is no longer acceptable. Today’s demanding customer simply won’t wait and wants immediate assistance.
A decision model takes no more than one minute to screen a company from top to bottom. Which means the user has an immediate answer. Certainly this will be of great interest for the salesperson out on the road. Because they can find out straight away whether they should spend their time targeting a particular prospect or not.
A decision model bases its logic on specific information at any time to reach the same conclusion. The parameters are set, so all companies always go through the same automated screening process.
But with ‘human’ checks, indirect factors may frequently have an effect on the way a customer or prospect is screened. These factors include the person’s character, the mood they are in at the time and any differing level of knowledge they may have. Which means that the way they gauge the data of the (future) customer will always leave a certain amount of room for interpretation.
All of the checks carried out by a decision model are performed efficiently and uniformly. The parameters are set in advance. This means there is no possibility to interpret the result generated by the decision model. The model produces an unambiguous recommendation.
This means that a company or organisation is no longer dependent on a select small group of experts to analyse and interpret data. The result produced by a decision model can be integrated directly into the work process, regardless of the position or level of expertise of the employee using the decision model. Additional justification is not required. Everyone can use the decision model and get an immediate recommendation.
With customer acceptance, a decision model is able to assemble and analyse numerous sources and databases. All of the values and scores are weighted using parameters set in advance (called checkpoints). A decision model will take account of the threshold values set when evaluating a company.
The aspects that can be screened by the decision model are far-ranging and may differ from country to country:
Any company may itself define the threshold values of the parameters – or checkpoints – in advance. This enables the decision model to take decisions that fit in entirely with the company’s risk appetite. If you want to play it safe, you will opt for more strict parameters than with a company that aims to grow at all costs and is prepared to take a higher degree of risk.
The decision model always makes a recommendation based on this risk appetite. If a customer or prospect meets all of the conditions set, then the decision model will give the company a positive evaluation. That means this (possible) business partner has passed the test and in this case has scored well on all the checkpoints. So the company can be accepted. If not, there are two possibilities:
Decision models also make it easier to evaluate and optimise the customer acceptance procedure. It may well be of interest to take a closer look at rejected customers or prospects after a period of time. For instance, what has happened with these business contacts in the meantime? If they have gone bankrupt, then the rejection was justified and the settings for the decision model are correct. If not, then the checkpoints can be reviewed.
The decision model examines the extent to which it makes sense to do business with a certain company. Factors such as the company’s credit limit, payment behaviour and financial health will be looked at. If it is possible to detect specific risks based on this data, then it is also just as possible to uncover opportunities, too.
Comparing the recommendation of a decision model over a number of periods – for example every quarter – can deliver valuable new insights. A company in a healthy situation will quickly take on the ambition of using that potential to implement a growth policy.
If you want to find out more about the Graydon Decision Model, download our e-paper that demonstrates in detail the value of using decision models for customer acceptance: