Beyond DSO: Rethinking the AR Maturity Journey

As a finance leader, concerned with Accounts Receivables, DSO will mostly feature at the top of your metrics-to-measure list. For decades, it’s been the gold standard. And, critical to unlocking cash and reducing borrowing.

But the game has changed. And, how.

In today’s volatile economic climate; payment terms are fluid, credit behavior is psychographic, and revenue predictability is slipping. DSO alone no longer gives you the full picture. Neither does it tell you where you stand in your AR maturity journey.

Why is the AR Maturity Journey important?

Modern AR isn’t just about getting paid. It influences financial health, liquidity, and enables you to make sharper working capital decisions. And, no - it’s not just about buying the latest tech. It’s about rethinking how AR fits into your overall finance strategy.

It’s time to reflect, recalibrate, and rise.

Here are the five stages of AR maturity; driven by real-time visibility, seamless collaboration, higher productivity, and accurate predictability.

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Stage 1: Manual and Reactive

At the moment, you are probably spending over 60% of your time driving processes that can easily be automated. Your team lives inside clunky and error-prone spreadsheets. There are always multiple emails flying back and forth for the same customer accounts. Payment reminders are late, and so are payments. Managing and resolving disputes on time is an uphill battle. Chaos reigns supreme within individual inboxes.

Is this common across the US?

‍According to a study, 53% of mid-market B2B firms are still juggling AR in spreadsheets, and 94% of the spreadsheets contain formula or data errors, leading to delayed payments and increased collection costs.

Want to take the first step?

‍Inorder to go from manual and reactive, to a AI-enabled, proactive approach, AR first needs some form of structure.

First, identify the current bottlenecks such as spreadsheet mapping of AR data among others, and streamline this process through AR tools. Next, create SOPs for everything - right from what your reminder emails would look like, to how dispute management can be done such that, your overdue % comes down, while NPS scores go up. Inconsistencies in AR processes and workflows creates an uncontrollable, unsustainable path, going forward.

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Stage 2: Standardized, but Siloed

At the moment, you have SOPs governing how collectors can reach out to customers, the templates they ought to use, and there are minimal ad-hoc tasks chasing basic processes. Visibility has improved through the use of dashboards, but this visibility is only available to the AR team. At the same time, collaboration between teams is still a pain.

Why is this happening?

Well, as companies scale, volumes spike, and when that happens, the cracks show. Teams scramble. AR doesn’t talk to sales or customer success. The data exists. But, it resides disconnected across teams and systems, leaving minimal scope to use the insights to power strategic decision-making and actionable change.

How to proceed further?

To truly elevate how AR, sales, and CS functions collaborate, there needs to be a step-wise approach. While leveraging AI-driven platforms is key, a little bit of groundwork is required prior to that. Firstly, all systems, from your ERPs, to CRM and CS tools need to be unified and powered by real-time APIs and an event driven architecture.

Well, by analyzing data better and more holistically, any late payment for example would trigger coordinated actions, across each of these systems.

Further on, ML models can come, analyze each of the macro-signals against existing customers, and automate notifying sales and CS, in case any action is required. This high-tech orchestration not only breaks down silos but transforms the AR function into a powerhouse that drives smarter, faster, business outcomes.

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Stage 3: Automated and Segmented

At the moment, you’re automating a lot of the routine AR processes. You have mapped and identified customer cohorts. Reliable payers receive minimal follow-up reminders, while you adopt a more proactive engagement strategy with your riskier customers. Disputes are also categorized and efficiently channeled to your collectors.

But the process isn’t intelligent. It’s a standardized, rule-based system which cannot analyze changes, or patterns.

Around 44% of US companies have automated a few AR tasks, while another 33% are still mostly manually doing AR. What’s the result? According to a Bloomberg article, $1.76 trillion  of working capital is still trapped inside US balance sheets.

What needs to be done?

Since the process isn’t intelligent, layer in analytics to understand which cohorts consume more collector hours, and what needs earlier intervention. Start by embedding AI to identify cohorts who have a higher pay risk. Further on, segment workflows based on the risk profile, and payment patterns. To keep checking if you’re on the right track, identify metrics like DSO, CEI, ADD, and cost-to-collect on a cohort level, so that you can adopt a more targeted, data-driven dunning strategy.

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Stage 4: Predictive and AI-Enabled

This is where it gets really interesting. You’re currently at a stage where AI models are helping you flag who’s most likely going to pay late, even before the due date hits. You’re not reacting anymore, but instead shaping outcomes. AR has become a cash-flow signal, not just a collection arm. This is simply brilliant.

What are you gaining month-on-month?

‍90 to 95% accuracy in cash flow forecasting. At the same time, reconciliation accuracy increases to over 80%, virtually eliminating unapplied-cash headaches.

Instead of reacting to an overdue invoice, the AI model flags bad debt beforehand through micro-signals such as payment method drifts, early discount payments which were missed, invoice splitting, micro-payments, and the list goes on and on. This helps your collectors prioritize specific accounts before an invoice ages, without compromizing on the overall customer experience and leadership.

What more can you do?

‍While your AI models help you predict better, go one step further in terms of customer experience, and provide a integrated platform for your customers to reach out to you. A one-stop shop for disputes, payments, and any form of communication.

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Stage 5: Strategic and Integrated

At this moment, you have a strategic and integrated AR platform that is visible across teams, is predicting cash flows using AI models, and is fully connected across the order-to-cash (O2C) cycle. Sales and collections teams know which customers are at risk. Customer Success has visibility into billing issues. Treasury teams rely on AR data for real-time liquidity planning.

Customers are able to self-serve, and view invoices, payment statuses, make payments, and have a significantly improved experience. Due to this, there are reduced follow-ups, and less administrative burden on finance teams, allowing them to focus on what matters.

What does each of these steps change for you?

The leadership gets answers, not just reports. At the same time, receivables data now flows across the entire O2C continuum, and AR becomes a forward looking liquidity signal.

Simultaneously, sales teams enter the renewal stage with more inputs on live credit signals, while CS teams notice billing frictions before the NPS dips. Similarly, treasury teams get accurate predictability on the customer’s likelihood to pay, using AI models, tightening cash flow forecast confidence.

The Hackett Group reported that digital world class finance teams run at 47% lower cost than peers, and 44% are likely to be ‘valued business partners/customers’.

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Where are you on this journey?

Not just in terms of software adoption or automation, but in terms of how well your finance teams understand and act on the why behind late payments. If you’re still only measuring DSO, or don’t have AI embedded into your AR processes, or aren’t analyzing customer cohorts from a 40,000 feet view, it might be best to zoom out and look at the big picture.

Ask the tough questions like:

• Do we have visibility over collection velocity?
• Do our processes help us identify the customers and cohorts that are blocking our cash inflow?
• Are we incurring high costs to collect cash, and are we basing our cash flow forecasts on guesswork?
• Do we have an intelligent, fully integrated process that enables collaboration between concerned teams?

To understand where you are, in your AR Maturity Journey, schedule a call with our in-house AR expert.