Chasing customers for money has been around since trade between one person and another started and surprisingly the word ‘dun’, which means to make ‘persistent demands for payment’, has been around since the 17th century pre-dating the early days of Dunn & Bradstreet by a couple of hundred years, if online sources are to be believed. So when we say dunning it means more than just reminder letters.
Standardised and ‘persistent’ collections processes have been around a while and if you think about it they have remained pretty much the same, a series of steps taken at various intervals after the invoice is sent or becomes due. No rocket science there, the type of interaction has of course developed as technology has changed starting with letters, telephone, telex for international, fax, text and email. Segmentation of customers has moved on from alphabetical to match the collections function resources, to splitting out residential, small business, national, major, strategic customers, gold, silver, north, south, risk categories, etc.
This segmentation is in a constant state of change in some organisations especially those aligned with the salesforce. The constant striving for increased collections and reduction of debt now means that the number of tools that perform these tasks and strategies has grown exponentially but at the heart of these systems and processes lies a single objective… to influence a customer’s behaviour, usually after the event, the event being the invoice. Of course some customer behaviour is fixed based in their processes for payment and the myriad of steps that seem to prevent the payment being made… some offshore accounts payable functions are a case in point! The ‘5 invoices at a time’ rule and never speaking to the same person twice are common credit controller experiences.
The development of systems which sent ‘automatic collection letters’ when a debt was overdue at pre-determined intervals was a huge step forward, even though in my organisation in the 1990’s there were only 3 reminder letters of escalating severity and the segmentation of the customer base was they either got the letters (residential and small business) or not (major accounts). The game changer in my department back in 1993 was linking this system to a predictive dialler, possibly the first in a collections environment, and with this came a 300% improvement in productivity. Suddenly customers at the bottom of the priority list with smaller values were being contacted for the first time despite the increased productivity the cost of the tool meant that we had to make the most of it! The telephone collections call centre was born as inbound and outbound calls could be blended at busy times and with the centralisation of collections activity and thousands of customers being contacted by relatively few credit controllers a day.
These tools were great for the smaller, non-disputed debt but for everything else it was still a laborious process of account reconciliation, query and dispute chasing. Additionally calls were made to customers who would pay anyway and the whole process remained essentially reactive, aside from the new customer welcome calls and pre-due calls for the much larger customers.
‘Know Your Customer’ is a simple statement but it has become an industry in itself, from confirming who your customer is to regulatory compliance, but from a collector’s perspective understanding your customer is about behaviour and this is the game changer of today. I mentioned in a previous article ‘Robot Wars’ (CM Magazine July/August 2017) that some software companies believe that 70% of the collections effort is wasted and we have all heard experienced credit controllers say things like ‘He always pays on the second of the month’.
This 70% wasted effort is because of the reactive nature of collections we issue an invoice and chase it regardless. The experience and knowledge a credit controller has about their ledger is critical. I knew a credit controller, we shall call him Jeff (this is his real name), whose knowledge of his section of the debtors ledger, customers, payment patterns, disputes was encyclopaedic and this knowledge ensured that his team hit their target, if not he knew why to the penny. His focussed approach to his ledger, knowledge of his customers meant that he knew when or if to call.
Understanding customer behaviour is now what drives the major corporations like Amazon, Facebook, retail loyalty cards and competition for customers is now across industry. We compare one service offering to another, for example remember when ‘allow 28 days for delivery’ was the norm, today we compare delivery times of unrelated businesses ‘If X can get this to me tomorrow why can’t you?’ this is a key factor in buying decisions everyone is in competition with everyone else.
The same has always been true of collections teams, everyone is in competition to get paid, chasing the customer for the same money, the question is whose strategies will win and gain a share of that finite pot and whose strategies will result in non-payment. It stands to reason that those companies who rely on systems, processes and strategies that are reactive will suffer, but those who understand their customers and are able to influence customer behaviour early in the customer lifecycle will be the winners, we need a system called ‘Jeff’. I mentioned in the article ‘Robot Wars’ that robotic automation can be implemented if there is a predicable outcome and the order to cash process outcome is just that, predictable, but to get to the automation stage truly understanding the processes and the behaviour of customers is critical.
Back in 1921 the word ‘Workflow’ was first was coined in manufacturing, I think I first heard this back in the 1990’s relating to credit control along with ‘Quality Action Teams’ but that is the genesis of where we are today, understanding processes and outcomes and making improvements to gain better outcomes but this is now what is being automated through artificial intelligence and Robotic Process Automation (RPA).
Currently we have a desired outcome, we want to be paid, and we try to influence customers to do just that. We know the outcome and in some cases, like Jeff, we know the customers behaviour. Predictive Analytics tries to predict the outcomes of our actions, but if we know the outcomes already and how we got to that point achieving our targets would be easy. Do this and get that. Back in the 1990s the systems capable of this sort of functionality were only for the large corporates, banks, financial institutions etc, and were hugely expensive like the predictive diallers mentioned above. These needed significant use with millions of customers to make the business case stack up.
Not anymore, you can rent space in a SaaS (Software as a Service) cloud based system, or pay per click, per account, per transaction. Cost of ownership of these systems has all but gone, organisations with access to the web can gain access to these systems, no more change requests to update the system for new legislation changes, corporate IT departments are getting smaller as they shift to on-line cloud based systems making home working easier.
Major corporates still have the big ERP systems but these are becoming the background engine rooms providing data for the smaller specialist systems used by the front-line credit controllers. Risk tools, diallers, collections systems, allocation tools, query management systems, workflow etc. This growth in specialist niche systems is fuelling the development of ‘aggregator’ systems that collect relevant data from different systems and present the information in one view to the user. The credit controller and the manager can now log into the office via a smartphone app and check on the performance of their ledger or team and receive alerts when customers pay or not, just what you need when you are on the beach or with the kids at Disney… actually that may be a welcome diversion!
With greater automation, more organisations gaining access to smarter systems that can predict behaviour and alter processes to gain the best possible outcome, being able to do more with less is becoming easier as we no longer need to waste effort on the 70% of customers who pay. Whilst these systems are with us now and the early adopters are experimenting with them, the 2nd and 3rd followers are waiting to see the impacts. Credit Management still doesn’t get the priority it deserves but when our accountant friends start to look at cost to serve again in the shared service centres especially those that are offshore this will come under greater scrutiny and questions whether offshoring has a long-term cost benefit are being asked now.
There is no doubt that ‘dunning’ for the vast majority of collections teams will continue in some form, but the decisions leading to the type and frequency of the dunning will be determined by outcomes of previous actions at a customer level, the segment of 1 not the many, having seen this in operation in a collections and query management functions of some CICMQ Accredited organisations recently, it is clear that Jeff may be safe for a while but re-training as a business and process analyst may be a good long term career move.