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Technical

Using analytics to reduce days sales outstanding: accounts receivable analytics Logo cima

  CIMA & Infosys |   Free |   Infosys |   Sep 2014 |   Thought leadership

This paper, produced by Infosys in association with CIMA, alerts finance professionals to new ways of using data to improve cash flow and ensure the value of the organisation is maintained.

There is untapped potential in the enterprise data captured in business, particularly in relation to the management of accounts receivable. While there is excitement about the potential of utilising new forms of data, finance professionals should take advantage of the data readily available to their business to improve the analysis and management of accounts receivable.

Business analytics can add much value in terms of improving cash flow, reducing delinquencies and mitigating losses. Understanding how to apply an analytics framework to business processes can move data from being informative into actionable insights.

Topics covered:
  • Management accounting: Technical: Management reporting & analysis: Financial analysis, Advanced

7 Comments/Reflections

Eoin Campbell

Eoin Campbell Jul 2023

Provides much to think about.
Importance of share of wallet and thr wider relationship with the customer.
Can we deal with riskier customers what would be the result.
Usesful benchmarks for comparison and to set targets
Sacheen Bhatia

Sacheen Bhatia Apr 2016

This article was useful in understanding the role of big data in the management of accounts receivables and provided interesting facts around the order to cash cycle.
Senadhi Vithanage

Senadhi Vithanage Dec 2015

I was able to gain some useful insights into how to leverage analytics to manage the AR function better.

Senadhi Vithanage

Senadhi Vithanage Dec 2015

I was able to gain some useful insights into how to leverage analytics to manage the AR function better.

Daniela Hulpus

Daniela Hulpus Jun 2015

The article has given me some ideas on how I could improve our BI system in order to better answer to the organization's needs and enable us to become more predictive in terms of our customers' payment behavior.