Sourcing and Procurement

Are you utilizing data effectively to drive synergies between procurement and finance?

When one thinks of ways to measure the effectiveness of cross operation between procurement and finance, more than a few methods come to mind. PO Compliance rate, discount utilization, number of active vendor accounts, among others, are some of the indicators.

However, the business metric of impacting Payment on Time reflects the level of synergy between procurement and finance the best. In this article we will look at one of the resounding examples of how BI reports and Data Analytics can be leveraged to gain a clear perspective on the cause and effect relationship between the two departments.

Payment on Time is one of those business metrics that allows companies to exercise control on the end-to-end procurement process. Higher the percentage of payouts made on time, better the supplier relations and discount utilization, while a lower percentage would denote better cash flow. Balancing between the two ends, in a manner that suits the particular needs of a company best, is of key interest here.

How to maintain this balance across multiple locations and levels of engagement, while ensuring high supplier satisfaction? A bird’s eye view of the overall situation and the ability to investigate and analyse setbacks from a single application would be a good start, right?

Before we go into the details, let’s get one point out of our way at the outset – Payment on Time metric is not a new concept, but is fundamentally a basic one. But understanding the dynamics of such a metric is quite often like diving into murky waters, especially without appropriate methods and technology applications. For every timely payment invoice generated, there are numerous factors in the background at play to make it happen, and many of them outside the of realm of finance. Infosys BPM worked with one of its clients – a leading air conditioning and refrigeration company – to maintain and structure the process of understanding the metric with the use of data engineering and advanced analytics, in order to mitigate the risks of late payment patterns.

The collaboration with the client began with a benchmarking exercise that covered 10 different Invoice-to-Payment (I2P) metrics. In order to collect and combine these metrics properly, we had to make sure we compared apples to apples and thoroughly understood the processes put in place. How to distinguish invoices posted automatically from the manual ones? How to separate travel and other purchase-related expenses? How to track changes on each document? These straight forward questions often do not have a straight forward answer, especially when there are number of other small exceptions one needs to consider. After much deliberation we set out good grounds to introduce a near-live reporting solution to track Payment on Time for 18 different client affiliates.

However, building such a platform was not the end all, as clients now closely scrutinize the solutions for return on investment. The dashboards we created were only the equipment. So, we went a step beyond the usual to deploy the best of our gray matter to pin point the areas and means of improvement for the client.

Analytics is not automation of reporting; it is augmentation of business case detection.

We adopted a lean approach. We automated data extractions using VBA scripts to place the data in a specified a folder. As for the data, we took 5 SAP transaction downloads and 3 mapping files to set base for calculations and visualizations in our dashboard. Additionally, we designed for transformation of all data within Power BI itself, which is usually done with the support of a big-data software. We ended up with 15 different tables within Power BI that allowed us to proceed with visualization of client’s AP process and dependencies within, without bearing any cost related to additional SQL server space.

The areas of AP process we integrated to the dashboard:

• Basic paid on time/paid late/paid too early overview for all company codes in the scope of the project
• Drilling down of the above with vendor details
• Investigating into the root causes of late payment (e.g. late receipt, short payment terms, payment run missed, etc.)
• Missed discount analysis
• Posting inaccuracy overview

As a result, we defined two crisp business cases, found further areas of improvement, and deployed the dashboard for Accounts Payable operations by training and producing a detailed users’ manual. By changing the settings in SAP that followed our lost discount analysis of previous years, we were able to bring the client to break-even point within 3 months after implementation.

Second business case was the full visibility on payments issued less than 14 days before due date, which included 7-digit payments issued as early as 60 days before the due date. This helped in tracing system errors and in averting unwritten business practices, in order to give a noticeable boost to free cash flow. These analytics can be run every day, without over-stretching resources.

Our solution did not claim to boost the client’s PO compliance or increase their POT overnight. But we did impact a massive change in organizing the analytics process behind it, which is the fuel for all meaningful transformations. The solution gave our client easy access to valuable insights needed to drive change in both finance and procurement. Infosys BPM, as one of the leaders in the space, anticipate that business intelligence and advanced analytics will soon shed its novelty in corporate circles to become a permanent fixture in service delivery. Given its over-arching advantages, it is only a matter of ticking time.