Cohort for DSO/DPO Analysis

The standard way to look at DSO Analytics is by grouping customers/invoices into broad ageing buckets of payment duration in days. While this is standard, it does not give more information around the following

1. How are our customers paying us?
2. Are they paying us on time?
3. What is the average payment duration?
4. Is there is a sweet spot when it comes payment duration or when it comes to month of raising an invoice?
5. How efficient is the cash flow compared to the outstanding?
6. What is the optimal payment term that has worked for us?

As executives, when data is analyzed its hard to keep focus on just 1 metric alone. Businesses are so interdependent that Customer Payment Duration is directly related to the type of customer, how we invoice the customer, how we priced, payment terms etc. So, more dependent metrics are brought into the context of analysis, decision making can be lot more effective. The correlation or the ability to bring varied metrics together requires a common framework and platform to bring these all in.

Lastly, traditional Enterprise Performance Management Platforms help in bringing outlier management reporting metrics. While standard management KPIs are very much needed, we at QuarkCube believe that any metric, right from operations to Finance to Business which could help in decision making should all be brought into EPM platforms so that effective, managed decisions can be made.

In the sample attached, we have 7 types of data coming in - Month on Month Invoice Raised, Cash Flow Restated (not actual), Payment Days, % Outstanding, KPI Tiling to expectations and Zoning Flow. As an executive, we might be interested in understanding, when do most of our payments come from customers (50% or 75%) - to answer that we need this all coming in properly, on time and with accuracy.

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