It's all to easy to make decisions about your department based on a seat-of-the-pants feelings. In fact, we'd venture to say it's the norm. But due to advances in technology and systems in recent years, most credit departments are sitting on a goldmine of data. The trouble is, putting that data to good use is often challenging. This article focuses on ways that you can capture this data to help you make better decisions.

True professionalism involves gathering the facts, not to justify what you want to do, but instead to fully understand what is needed to help you achieve your organization's goals. Without that, you'll make decisions that are likely to have unintended consequences and performance shortfalls.

The term consultants are using these days to describe "putting data to use" is analytics. So we're going give you a methodology to take data that's just sitting there and make turn it into useful analytics.

The Analytical Advantage of Automated Systems
Automation provides transactional transparency to the order-to-cash process, often allowing you to monitor every item as it passes through your system.

It's one thing to see your data (the transparency or visibility part). But it's an important step further when you begin to use that visibility to better control and act on the data. That's putting "analytics" to use.

With automation, you can both see the big picture and drill down to isolate specific data elements.

Automation Brings Greater Productivity Along With Added Benefits
Analytics can give you greater context and detail, allowing you to focus in on things previously unobserved. Without the context, more data only adds to the confusion. Context, plus data-driven analytics results in clarity.

Credit and collection automation is usually justified by the productivity gains it provides, but indirect benefits buried in the transactional data it collects can be worth just as much or more. Your analytics will allow you to focus on two primary objectives:

1. Forecasting - The visibility provided by automated systems facilitates data analysis that can more fully identify risks both in terms of customers and system weaknesses.
2. Optimization - The ability to predict performance facilitates decisions designed to optimize process efficiency, working capital, compliance, and service quality in a cost-effective manner.

Visibility Plus Graphics Provides the Foundation For Achieving Control

The ability to see what is going on so as to forecast outcomes and then optimize results is how you gain control. Automation tools improve control over processes and information, aiding compliance by enforcing policy and adherence to proven best practices.

Six Steps to Better Credit Management Decisions
So now that many credit departments are awash in data from their automated systems, how can you mine the intelligence captured by these systems? The simple answer is to implement an analytics methodology. That involves the application of mathematical and statistical methods to organizational decision processes, and will require that you start with a blank slate in terms of how you think about risk and performance metrics.

Here are six steps to help you re-define your analytics.

1. Define the problem: It is not enough to identify the problem. You must also define it. The key to this is asking the right questions. If you jump right to the obvious answer, very often you will miss something important. Defining the problem means that you not only know what the problem is, but also understand it in its entirety -- its cause and its effects.
2. Clarify all pertinent issues: Nothing happens in a vacuum. Priorities and resources will temper almost every issue. So do the personnel involved and your company politics. Whereas you define the problem in a micro sense, you'll also need to look at the big picture (the "macro" view) so you can understand and anticipate the direct and indirect impact as well as the historical and organizational context.
3. Collect and organize the data: It goes without saying that an analytics methodology will involve data collection, but how the data is organized and presented will determine to a large extent how useful it will be. This is where some statistical skills can help. An understanding of basic concepts such as correlation, validity and sample distribution will help you determine what data you should collect and how you should organize it.
4. Build projections: Based on the data you collect, you can then create models to help you project the effects of any changes you might implement. This allows you to say 'what if' and then see a projected result. If you have done a good job clarifying all the pertinent issues there is less likelihood unexpected consequences will impact your projections.
5. Act on your decision: Deciding what to do and then doing it are really two different things. Acting upon your decisions will often involve more than simply making a choice. Many decisions will be multi-faceted and some will require considerable implementation support both in terms of preparation and perseverance.
6. Monitor the results: Once a decision has been made and implemented, it is important that you make sure it has produced the desired results. Monitoring results affords the opportunity to both learn what works and to make additional adjustments to your decision geared at optimizing outcomes.

It is one thing to recite these six steps, and quite another to apply them within a receivables management context. The following chart should help you better understand how to implement an analytical methodology in order to drive better credit management decisions.

Implementing an analytical decision methodology is not unlike learning to solve the word problems that frustrate many algebra students. Once you learned how to translate the facts presented in the word problem into a mathematical formula, solving the problem itself was not especially difficult. Likewise, reaching conclusions based on data is usually not difficult if you employ the appropriate analytics. Get the first four steps right, and the best decision will usually manifest itself in due course.

By working through the steps of this methodology, you should uncover key performance indicators and other metrics that are not in the traditional credit manager's tool kit. As in the example provided, while DSO indicated a problem, it did not define it. Other metrics are required to clarify the situation and still others to map out a solution that can monitor to ensure your goals are achieved. The ability to analyze and react appropriately is what ultimately puts you in control, and that is a good place to be.

The Scenario: DSO at ACME Widgets has slowly but steadily been rising for the past 12 months despite level sales volumes. The credit department staff is made up of six veterans who have all been in their positions for at least 3 years. Staffing has not changed during that time frame. They implemented collection workflow automation software about three years ago resulting in a large drop in DSO over the next 12 months.

Editor www.highako.com Highako.com is a video-first microlearning platform trusted by over 10,000+ Credit and Collections professionals. Drive skill growth with role-specific, expert video lessons. Measure practical expertise through hands-on assessments. Connect and collaborate with the largest credit community and get access to ready-to-use templates.

Explainer   10 Min Read Five Brilliant Responses to Diffuse an Angry Customer

Explainer   10 Min Read Empathy in Trade Credit is Good For Business

Explainer   10 Min Read A Complete Customer Visit Preparation Checklist :Onsite