11.8 Recovering dissemination costs

11.8 Recovering dissemination costs#

11.8.1 Free versus paid access#

There has been much debate over the years on whether NSOs should provide all their statistical data free of charge. The trend today is to provide access to data for free with some exceptions. As previously noted, official statistics are considered to be a public good, which in itself seems a reason for an NSO to provide free access to its data. One should also note that if collecting a fee requires more resources than the fee brings in, it is economically inefficient. Operating complex paywalls may be beyond the capacity of many NSOs.

If charges for data are made, they should be based on data extraction costs or the costs of expert work in compiling additional aggregations and linking of data for new statistics requested. It should cover costs, IT, and infrastructure required for the tailored service, not for profit.

There are still several paying models which include (extracted from ‘why people pay for data (🔗).

  • Metered consumption: In this model, a certain amount of data is free, and when you need more, you must pay for it. Within this model, there are a couple of options: one where rates are measured on a per dataset basis, and one where rates are measured site-wide, regardless of the dataset(s) being accessed.

  • Consumer classification: Charging different rates for various types of customers is a well-known business model. For government data, business consumers are most likely to be charged since they are probably using the data for revenue-generating purposes. Sometimes referred to as ‘freemium’, this model works by offering simple and basic services for free for basic users while more advanced or additional features are at a premium. The business consumers are paying customers that effectively subsidize free services for non-business customers.

  • Access methods: Purely from a technology perspective (computer memory, processing, and connectivity), downloading an entire set of data is generally less costly than asking for small specific pieces of it. Bulk data could be made available for free while application programming interfaces (APIs) could be fee-based. Charging to push data to a subscriber as it becomes available (rather than pulling it using bulk downloads or APIs) is another option.

  • Premium datasets: Similar to consumer classification, except instead of charging based upon who is accessing the data, costs are determined by what data they access.

  • Real-time or delayed access: This scenario is useful for transactional data where extremely recent data has greater value, but value decreases over time until it’s free. An example from the finance sector is stock market data, where companies pay a premium for real-time information (and invest millions of dollars to gain a millisecond lead over the competition), but within 15–20 minutes, the data is free and publicly available.

11.8.2 Role of data resellers#

The NSO is a provider of high-quality data that others can profit from by adding value. As more and more NSOs adopt open data policies (see Chapter 15.2.8 — Open data initiatives), data resellers can simply pull the data from NSO websites, re-package and re-sell it without having to engage in any specific relationship with the NSO.

In many countries, the private sector is already engaged in the dissemination of statistical data and information. In some cases, these are basic statistical information, and in others, the vendor provides a value-added service such as conducting further analysis of the data or integrating the data with other sources of information. While an NSO may not disseminate all statistical data, it does have an obligation to ensure that essential statistical information is provided to all society segments on an equal basis. Depending on national practices, an NSO may provide the information itself or assist the vendor in doing so.

The involvement of data resellers can assist in the dissemination of statistical information in several ways. Their marketing skills relieve statisticians of the task of interacting with the end-users of information, and by subjecting the data to thorough analysis, data resellers can provide additional constructive criticism of quality and presentation. They can also help NSOs assess demand for various types of data.

Value-added features of data resellers include the following:

  • High-frequency data delivery;

  • Multiple data delivery methods and formats;

  • Integrating multiple data sources into a single format;

  • High availability of data;

  • Adding on related data.

However, potential problems also exist in that resellers may misinterpret data without giving statisticians a chance to set the record straight.

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