Public Policy: The Big Data Revolution

The Chamber of Representatives adopted, on Monday July 6, two bills approved by the Government Council four days earlier, on July 2. The two texts, bills 046.26 and 047.26, consist of roughly fifty articles each.

The first bill sets up a statistical regulatory system with the creation of the National Council for Statistical Information (CNIS), while the second repositions the High Commission for Planning (HCP) as an independent body administratively and financially, with missions including, among others, the production and dissemination of statistical information and support for the strategic coordination of development policies.

When presenting the two texts to deputies, the Minister of the Interior, Abdelouafi Laftit, stressed that these two bills “constitute a comprehensive reform based on two fundamental pillars, the first concerning the reorganization of the HCP and the strengthening of its position as an independent constitutional institution, while the second concerns the establishment of a modern national statistical system.”

First of all, at the institutional level, this is a revolution in itself. The government has just activated a constitutional prerogative, art. 159, with the aim of enriching the range of good-governance institutions, by transforming the status of the HCP.

With that parenthesis closed, the adoption of the two new texts is not limited to the reconfiguration of the national statistics system governed by a 1968 decree; it is, strictly speaking, the trigger of a revolution in the field.

The State is in the process of equipping itself with a real “strategic watch” tool at the national scale, whose scope ranges from macro to granular (and even hypergranular) levels, both territorially and socially. This big-data–based revolution will have a direct implication and a major impact on public policies. A concrete example to gauge the scale of this change: the calculation of the unemployment rate, which was formerly the source of many controversies.

If, according to the current method, a periodic survey fixes this rate at a figure x%, in the new configuration, by crossing the national survey data with administrative statistical data provided by several institutions and public establishments, one can calculate exactly the unemployment rate among young women under 25 in the Guelmim-Oued Noun region and, consequently, design an employment program adapted by activating the appropriate economic integration tool (Forsa, Idmaj, Taahil, …) while also being able to measure its impact.

Here we see the consecration of the results-based approach advocated by the government in implementing the social State, focused on the impact of projects rather than the means mobilized.

Statistical authorities

In the new arrangement, the HCP, promoted as a good-governance body, will not collect everything itself. It sits at the heart of an ecosystem that also ingests, in addition to the collection and processing of information, training, since the two public institutions, INSEA and ESI, come under its supervision.

It also ensures that large-scale data from the public and private sectors can be shared securely, in the form of aggregated statistics.

The HCP becomes the integrator of traditional data (collected by surveys) and new data (big data) to produce statistical information that is richer, faster, more reliable and more relevant.

Generally speaking, analysts say the two bills establish a new, comprehensive and modern legal framework. That is to say, a formal law, no longer a decree, that covers the entire data cycle, from collection to dissemination, including processing, governance, quality and confidentiality.

An institutionalized and centralized coordination is also put in place. In that sense, the HCP becomes a national statistical authority with powers of coordination, labelling and standardization over the whole system.

In other words, the new national statistical system is no longer limited to the HCP alone. It encompasses all “statistical authorities”: state administrations, public establishments and organizations, public enterprises and entities entrusted with public service missions that produce or disseminate official statistics.

The precise list will, logically, be set by decree, on the proposal of the future National Council. In this configuration, the CNIS itself defines the general orientations. An independent regulatory body with legal personality and financial autonomy, the Council oversees respect for principles, the proper functioning of the system and the continuous improvement of data quality.

Moreover, in the new framework for national statistics, professional independence is now enshrined in law and “absolute” statistical secrecy is established. The new legal framework also paves the way for the aggregation of all public statistical information and administrative data.

The law obliges, at this level, public and private bodies entrusted with a public service mission to transmit their data to the statistical system. This opens up, moreover, a colossal reservoir of information. Mandatory and structured access to administration data (health, education, taxes, energy, etc.) is a major technical and cultural change.

This reduces the response burden on citizens and makes it possible to obtain much more granular and frequent information than the HCP’s periodic surveys alone.

Code of good practices

In practice, the bill also requires both natural and legal persons to answer surveys accurately. This obligation is supported by financial penalties in case of refusal or inaccurate response, thereby guaranteeing the representativeness and quality of the data collected.

At the same time, and this is of paramount importance, the individual information collected “cannot, under any circumstances, be used for control, economic, fiscal or criminal sanction purposes.”

This provision is crucial to establish a relationship of trust between citizens/companies and statistical bodies, a sine qua non condition to obtain truthful data.

The bill also imposes a “Code of good practices” and uniform quality standards, which allows data to be compared reliably, unlike cases where each organization might use its own methods. And of course, this reform of national statistics is geared toward promoting statistical open data.

The law enshrines the principle of broad and free dissemination of anonymized data, in open data, to encourage innovation, research and public debate. Most importantly, this approach also improves the forecasting and evaluation of policies.

In short, according to experts, this orientation reflects Morocco’s shift from “descriptive statistics” to “decision-making statistics.” The new system thus better aligns data production with user needs, fostering greater responsiveness to social, economic or environmental changes.

It follows that, in terms of economic policy, the new information engineering will reduce the cost of decisions not based on precise data. Employment policies, social support, regional investment, tax reform and agricultural programs, as we know, require reliable data.

We also know that lack of precision or insufficiency in statistics can lead to a waste of resources, while data quality steers public spending toward the most priority areas.

This leads the expert to say that the creation of the National Council for Statistical Information represents a transition toward a “central bank of reliable statistics,” while the High Commission for Planning becomes “the analytical brain of the State.”