Data collection, the basis for a successful billing process

The quality of the billing process is dependent on the correctness of the information available. Without good data, it is not possible to create correct invoices. This has many implications on downstream processes, but also on customer satisfaction and cash flow. Garbage in, garbage out.

These data come from somewhere. Often from multiple proprietary systems, and frequently also from third-party systems. Typically, they have to be pre-processed before they are useful for the actual billing. This process, data collection, can be complex. Many companies therefore struggle with this side of the billing process. Conversely, when this section is well organized the first step towards a smooth billing process is taken.

This is part two of a series of blogs by FIQAS about billing process optimization. In this blog we will address the issue of how to successfully organize the important process of data collection and discuss some challenges you will encounter in practice.

The start of the billing process

The billing process is preceded by other processes such as acquisition, ordering, product activation, connection and delivery / fulfillment. Errors and omissions in these processes affect billing, so it is important that these processes are well established.

These processes generate various kinds of data relevant for the billing process. Customer data (personal and business information), contract data, product data (codes, descriptions and prices), order data (numbers, product codes) and other transaction data, usage in particular.

In a very basic scenario this information is registered in one large ERP system, that also supports billing. However, this approach has some major disadvantages. It typically leads to very inflexible situations where it is difficult or impossible and usually costly to implement changes.

In a real-life situation various separate source systems are commonly found that provide data to the billing system. This will vary by industry. Companies in the telecommunications industry, for example, are dependent on network operators such as KPN, Vodafone and T-Mobile for their usage data (in the form of CDRs Call Detail Records or IPDR, IP Detail Records).

To collect all this information and make it fit for the billing platform an automated process must be set up: data collection.

Collect, convert and consolidate data

Modern technology offers sufficient possibilities to transfer data from one platform to another. Which interfacing possibility is to be preferred in a particular situation – the choice is roughly between an API, a simple file import or a hybrid solution – depends on several interrelated parameters. What are they?

  • The timing of the process. Are data required in real time, is near real-time sufficient or may they be delivered at a lower frequency?
  • The number of records. The larger the amount of data, the more important the dataload spread is in view of system performance. Are the data supplied in bulk, or not?
  • Reciprocity and complexity. Should the billing process return data to the source system? To cite a typical example, when data are supplied in bulk, the frequency with which this occurs can be lower than when data is received on a real-time basis. For the latter an automatic link between the two systems will be more appropriate.

Typical data collection challenges

The data collection process has its own challenges. A few examples.

Data are not always 100% complete

The starting point for the billing process is that the source data are correct and complete. The more source systems, however, the more complex the data collection, not only technically but also organizationally. In businesses where the data is taken from a variety of sources it is almost or even completely impossible to have relevant data 100% complete when billing starts. Even so, the process should continue, as the invoices must go out. Therefore the billing process and platform should be able to deal with non-billed usage and any other unprocessed elements from previous periods.

Telecom mediation: conversion of large amounts of raw data (real time or near real time) to usable data for billing

Mediation plays a central role in data collection for telecom . Mediation is the crucial and complex step after retrieving the CDRs or IPDRs, in which raw usage data are converted, made uniform and consolidated to data types that are usable for the next step in the billing process, the rating/pricing. Given the large numbers of usage records, it is important that data is read by the billing system directly and with high frequency (real-time, near real-time, but at least once per day), from the provider’s switch or switches. The mediation platform can be included in the telco’s set-up, but also be part of the software from an external billing services provider.


Data collection - mediation

Design the data collection process carefully

Finally, a challenge that emerges in any automated process. The data collection process should be well thought out. A number of items must be accurately mapped out before setting up the process:

  • what data does the billing process require?
  • which system should supply them?
  • how can the data structure be mapped to the structure of the receiving billing platform?
  • how are usage data mediated?
  • which other data preprocessing is required and when and where should this be done?
  • what infrastructure is needed in order to ensure the safety of the process?


Furthermore, it is of paramount importance to ensure a flexible design of the data collection process, using a rollback mechanism to allow for error correction. Not least this process, with all its dependencies, should be subject to very strict testing. If all of this is properly taken care of you have a solid base for a healthy billing process. This keeps customer satisfaction intact and ensures a reduced administrative burden. For example, because there is less need for credit invoices. Sound billing processes create an optimal cash flow.

Flexible data collection keeps ‘garbage’ out of the invoicing

Data collection is a process that enables proper automated checks to prevent the billing process is fed with ‘garbage’. In the data collection process capabilities for automated error correction can and must be built in. If problems are solved at the start of the billing chain fewer errors will have to be restored afterwards. The investment in a thorough analysis and appropriate technical solution will pay off in a smooth billing process with few errors that contributes directly to customer satisfaction and a maximized cash flow.

Other topics and why this series?

Other topics in this series:


The FIQAS specialists have a wealth of experience in organizing, executing and optimizing billing processes. The business cases that we see are often narrowed down to one or two of the above aspects. With this series of articles we try to do justice to the bigger picture. In part three of this series we will focus on the processes and best practices concerning rating/pricing.

Erik Henselmans
Hillebrand Kuypers

FIQAS is an authority on invoicing processes, established in 1989, with renowned international customers and operating from Aalsmeer (greater Amsterdam area).

Tagged: Billing, Facturatie, Facturatie, Rating, Telecom billing, Telecom billing