Reading time: 4 minutes | By Maarten Jansma, Account manager at Berkeley Bridge
The increasing pressure on organizations to make sound decisions faster and work more efficiently is driving organizations to make more use of scoring models. I dedicated last week’s blog to scoring models and how they come into being. This week I will discuss a few benefits of using scoring models and how it helps organizations achieving their goals.
Throughout this blog, I will be giving examples from the field of creditworthiness assessments. In many organizations, assessing the creditworthiness of new and existing customers is an integral part of the sales process. It helps them determine whether they want to do business with a customer, and if so, under what conditions. Scoring models lend themselves perfectly for answering these questions.
Scoring models (and their underlying scorecards) are built by domain experts. By effectively translating their knowledge into score based applications, non-specialist users are allowed to make sound decisions as well.
When assessing the creditworthiness of a customer, a variety of criteria is taken into account. Assessing a customer’s creditworthiness does not only involve checking their financials, it also includes the consideration of the sector in which it operates and the legal form it has, for example. Many data sources are available to support organizations in assessing a customer’s creditworthiness. The most used sources are Chamber of Commerce documents, third-party credit information and data from one’s own ERP system.
However, most sales departments still rely on the assessment of the available data by their respective finance departments. The latter has access to the necessary data and is familiar with the criteria (and rules) that are important in their decision making. Considering the necessity of this specialist knowledge, you should ask yourself to what extent it is desirable to make a sales employee responsible for assessing a customer’s creditworthiness, in the first place.
By effectively implementing ones decision-making strategy and the available data in a user-friendly application, non-financial professionals become instant decision makers. It allows them to make sound decisions, which are based on knowledge and expertise from colleagues in finance.
Because the criteria which are used to calculate a score are predetermined and defined in the scoring model, each score is calculated in an objective and uniform manner. Decisions are no longer subject to different interpretations or personal experiences.
The assessment of a customer’s creditworthiness can be rather arbitrary. One financial expert might feel a customer’s payment behavior is the most important thing to take into account, while another believes a customer’s net worth should have the most influence on the outcome, for example.
And how about a credit manager who is being asked to assess the creditworthiness of a construction company, while a few minutes ago he read about a construction firm that was forced into liquidation? I am pretty sure this will have a negative effect on the assessment and might even result in an unnecessary rejection of a healthy customer!
With a scoring model, gut feelings and guesswork are a thing of the past. Thanks to the fact that one’s decision-making strategy is implemented and only predetermined parameters are used, scoring models ensure objective, uniform decisions.
A scoring model allows organizations to individually identify key criteria and assign different values to characteristics, that are applicable to their own specific situation.
Decision strategies can vary greatly because no organization is the same. Organization A might think you should always avoid taking risks (low-risk appetite), while Organization B believes taking risk is inevitable if you want your company to be successful. Therefore, a generic method for assessing a customer’s creditworthiness will never perfectly match one’s decision strategy.
Scoring models allow organizations themselves to determine which rules must be followed and which criteria are taken into account while assessing a customer’s creditworthiness. Consequently, scoring models are ideal for organizations that want to make sound decisions in accordance with their specific decision strategy.
By standardizing the decision-making process through the implementation of a scoring model, sound decisions can be made faster or fully automated.
As noted earlier, most sales departments still rely on the finance department for the assessment of a customer’s creditworthiness. But what if the financial expert is not immediately available or (because of the complexity) an extensive analysis needs to take place first? There is a big chance your customer already ordered somewhere else, while you were still waiting for your colleague.
And how about customers that want to place an order in your webshop on a Saturday afternoon? Should they wait for your response on Monday? Or do you agree it should be possible to place an order without human intervention, while the webshop does all the work for you?
Not only does a scoring model allow non-financial professionals to make sound and fast decisions, it also offers opportunities to further automation of your decisioning process. Scoring models can be integrated with existing platforms, such as webshops and ERP systems. Highly efficient, also outside office hours.
Last weeks’ blogs were aimed at giving you some more insight into scoring models and the benefits of using them. Of course, there is a lot more to talk about, like how to capture expert knowledge and evaluating scoring models you have built. However, that is beyond the scope of this blog. If you are interested in further discussing how scoring models can help you share valuable knowledge throughout your organization and make it accessible for everyone, please send me a message. I am keen to learn your thoughts and happy to think along!
– Maarten Jansma, Accountmanager at Berkeley Bridge