Willand Brienen, product owner at Onguard
Data, and the insights it reveals, can offer organisations a vast number of benefits. For example, data-driven credit management can help to reduce the days sales outstanding (DSO) and allow credit managers to create a better understanding of risk profiles. However, while the benefits that data insights can bring to a business are substantial, buying a credit management solution doesn’t automatically make a company data-driven.
As such, credit managers shouldn’t be fooled into thinking that simply implementing an off-the-shelf credit management solution will be the key to successfully harnessing data insights. First, they have to choose the right solution; and even then, there are still a number of important considerations to take into account in order to secure a successful outcome.
So, how can credit managers tap into their company’s data goldmine to glean insights – and better prepare for the future?
Lesson 1: Use the data you’ve got
Almost a third of organisations have a wealth of data to draw from – but they aren’t maximising its potential.
Despite this, many companies have a clear appetite to become more data-driven. Reducing costs and increasing efficiency are big factors in this, but according to our recent research, over 20% of businesses also hope to use their consumer data to personalise customer communications and improve overall satisfaction.
For maximum return on investment, it’s essential for businesses to utilise data from their own consumer base, such as customers’ risk profiles and payment behaviour. External data is not only expensive, but profiles based on your own customers will also tell you more about future customers than data from other companies. The risk profile scores that you draw up based on internal data will therefore have greater predictive value.
By leveraging this data to better effect, organisations can benefit from enhanced sales, improved products, better finances and targeted marketing – offering a better service, boosting customer satisfaction and improving relationships. Should they wish, businesses can then also proceed to take the step to combine both internal and external sources later down the line.
Lesson 2: Use AI to maximise your follow-up actions
Increasingly, businesses are starting to leverage Artificial Intelligence (AI) to harness valuable insights – but perhaps more importantly, it can also be used to determine how best to follow up with customers. This, in turn, can help improve relationships – whilst also using predictive capabilities and a deeper understanding of customer behaviour to minimise non-payment risk.
Data-driven insights are vital in helping to improve the forecasting of cash flow. AI can both support this process and advise on the best follow-up action. For example, it can help determine which customers would respond better to a follow-up phone call, or when it might be necessary to start collection proceedings immediately. Using individual insights based on consumer history, AI can also help identify the best time to contact specific customers, preventing you from making unnecessary calls if the customer is known to be unavailable. Not only will this dramatically improve operational efficiency, but if customers are approached in the right way, at the right time, it will also serve to enhance customer relationships and bolster retention.
Lesson 3: Leverage existing interfaces
Many credit management solutions offer standard interfaces. These can be linked to other systems and applications to improve efficiency – saving time on development and eliminating the need to re-test. By using existing APIs, businesses can benefit from tried-and-tested solutions that have already undergone comprehensive testing, so they can be sure that it works with their existing software.
For maximum ROI, organisations should choose an order-to-cash solution that offers as many interfaces that are relevant to their credit management processes as possible.
Lesson 4: Start small
As a credit manager, becoming fully data-driven will come with its share of challenges – but in an increasingly data-centric world, it’s vital to embrace this changing landscape. From companies using their own data and existing APIs, to implementing AI tools for determining follow up steps, becoming data-driven is the clear future of business operations.
Agility is key, as is taking small steps and using tools that enable you to incrementally expand your data-driven capacity. By linking the two most relevant sources and then expanding this further, this will immediately identify whether what you are doing is adding value – and where improvements can be made. By first analysing your data and determining which parts are most relevant, you can ensure that you don’t include any unnecessary information that may hinder results.
More and more financial departments are becoming data-driven, and by adopting this approach, credit managers and businesses alike can become more successful and more efficient, both now and for the future.
