The ability to streamline processes and improve strategy by leveraging big data has been transformative for businesses. Finance departments – where systems are often based on less than efficient multiple mixed ledgers – can derive value from a combination of all the data that a company has on its customers and the analysis that can be drawn from it in terms of actionable insight and time savings.
But if, as in many organisations, existing processes are entrenched and silos exist that only serve to fragment information held within different departments, an approach has to be developed that can bring the data together to provide a 360° view of the customer and be transformed into vital analysis?
The value of actionable analysis that can inform business strategy cannot be underestimated, so managers initiating big data projects should focus on easy wins. This might be around data that can analyse trade payment behaviour, for example. With an overview of the characteristics of customer payments, credit managers can then form a case-by-case view on credit limits and access. They are in control and can bring silo teams and departments together, to collaborate and combine efforts for optimum return.
And it’s not just credit managers, but all levels of staff from sales directors through to CFOs who can use the analysis derived from big data to make good financial decisions, and encourage board-level endorsement to extend big data projects more broadly.
Silos exist, of course, because individuals and departments lack the appropriate mechanisms and incentives to share data. But many credit managers, who rely on shared data from across the organisation, are increasingly working towards an enterprise – wide smart risk culture – a way for their company to become more tolerant to financial risk – so they are already invested in bringing together the entire organisation.
This is reflected in the latest Credit Managers’ Index from the Chartered Institute of Credit Managers which highlights just how much the role of the credit manager has changed in recent years. 41% said that they not only had additional responsibilities, but were increasingly being called upon to make strategically important decisions.
In practical terms big data has much to offer in support of credit management functions, for example:
With visibility across the entire organisation, questions can be answered that inform important business decisions. Big data intelligence arms companies so they can assess customer risks and focus sales efforts on the strongest, high value opportunities that deliver fast, full revenue recognition.
Sales teams will be tangibly more productive and the company will be focused on maximising profitable sales. This data can also be leveraged to guarantee bank credit and reduce borrowing costs.
From delivering analysis that can help in asset recovery through to giving an overview of a customer’s payment behaviour, big data removes the guesswork for credit managers and FD’s, builds an accurate picture of the financial opportunities and pitfalls and allows organisations to manage risk according to their own particular appetite.
Tinubu Square : How important do you believe analytics has become to credit managers and finance departments over the last few years?
Guy Thompson, Credit Risk Manager EMEA & APAC: I get concerned when people just throw numbers and statistics around, or try to extract data without paying attention to what it means and what it tells us. We have to use analytics to provide us with information that we can make sense of and that we can use. DSO is a perfect example of this – everyone has a rough idea of what DSO is (but not how it is calculated) but does the salesman know what it means? We have a job to do educating and informing people that we work with in a meaningful way, and not just drowning them in numbers. Analytics therefore is crucial, but only when we can derive information and intelligence that is relevant.
When I talk to other credit managers I get the impression that many are not using fit-for-purpose tools. They are doing more analysis, but not necessarily using specialist software. There’s a problem with this because whilst standard spreadsheets are fine, they can be set up by one person in a particular way, but how are other people expected to use it, and add to it? I think that analytics tools need to be fit for the job, provide you with the information you need, be reliable and allow team members to be able to input and extract data.
T.S. : In what functions that you deal with do you think that analytics can play a crucial role?
G.T.: If you are analysing the right data then it will be useful across all functions, but it’s important to be selective in what you are analysing. Payment behaviour, for example, is fundamental. How does the customer pay us and how does he pay everyone else? Analysing this will give you a picture of exactly where you stand with the customer and how much, or how little he values you. It’s about tracking normal behaviour and acting on abnormal behaviour. If a customer always pays 15 days late, and that’s ok for me, but if he starts paying in just 5 days, or worse, stretches it out to 30 days late, I would want to understand why and what the significance was. Using analytics, you can spot this change in behaviour early and then discuss these findings with the sales force, for example, and combine your knowledge before making a decision about what action to take.
Without analytics you are simply inputting data and producing graphics which takes a long time, and whilst you don’t have to have everything in real-time, you do benefit by tracking behaviour and trends on a regular basis.
T.S. : Do you think that credit managers can drive the adoption of big data in order to use analytics more effectively?
G.T.: Credit managers should be in a position to drive technology adoption. We are in a pivotal role. The big change for us in recent years is the professionalization of our industry, and our value is being recognised higher and higher up the company, so we have a much more positive role in the organisation. The buzz phrase of the moment is ‘trade working capital management’ which puts receivables, and us, in the spotlight.
Many companies have already invested in big data systems, but once installed they have to be managed and utilised and this provides credit managers with an opportunity. We can get our hands on all this information and use it to drive the business. What does it tell us about sales, what does it tell about the profit margin on different customers? Having the right tools to make sense of it all becomes crucial.
T.S. : Do you think there might be barriers to adopting big data as a result of company size, or more likely company culture?
G.T.: Big data can be adopted by any company, and using analytics is as appropriate to a small organisation as it is to a huge conglomerate. It’s about going back to basics and understanding the customer. In fact, someone who runs a small business is much more likely to benefit by having a good understanding of the payment behaviour of a customer because the loss of that customer could be very significant.
T.S. : Do you believe that it is a big challenge for credit managers to encourage use of new technology to deliver this level of analytics or that the potential return on investment is so strong that it increasingly has board approval?
G.T.: The door is slightly open for us to be ambassadors for technology. We all have the same issues, regardless of what sector we are in, but because there is such a focus on trade working capital, and its importance is recognised at board level, we do have the opportunity to demand the right solutions to help us do our jobs.
T.S. : In your international experience do you see a change in the role of credit managers, particularly where the adoption of technology is concerned?
G.T.: We sit here right in the middle of the organisation, so our ability to influence the business is great. We communicate with everyone from finance controllers to sales people, from order takers to IT managers, and we are ideally positioned. The culture is changing and if the new breed of credit managers is prepared to grasp the opportunity we can argue the case for making sure we have the tools we need to do our jobs effectively.
Founded in 2000, Tinubu Square is a software vendor,
leading expert in trade credit risk management. Tinubu
Square enables organizations across the world to significantly
reduce their exposure to risk, and their financial, operational
and technical costs with best-in-class technology solutions and services.
Tinubu Square provides IT solutions and services
to different businesses including credit insurers, receivables
financing organizations, and multinational corporations.