What is the quality of the numbers?

A lot has been said about the promised 2,2 million jobs. There is data to this expectation, which makes it easier to evaluate from a quantitative standpoint. However, of those quantitative jobs, what metrics are we using to evaluate their quality? The quantitative benchmark does not say whether or notthe 2,2 million jobs will be productive, occupationally safe, technologically relevant, or even competitive to current and future trade corridors.

This hints at Zimbabwe’s and most of our African peers’ data assessment challenge.

Data is often presented in a quantitative context that lacks effective qualitative explanation; yet, especially for developing nations such as us, quality is a matter that should be of extreme urgency, and it should be measurable.

It is often emphasised how developing nations often lack credible quantitative data and strong institutions that collect and compile such information.

We fall under this grouping both in terms of the data we produce and the strength of the institutions that collect and compile it.

Fortunately, our Staff Monitored Programme with the IMF notes the importance of capacity-building in our data centres.

Notwithstanding, attending to this quantitative challenge must be superseded by an emphasis on the qualitative relevance and context of the data that capacity building will help us collect and compile.

For instance, the Zimbabwe National Statistics Agency can be empowered to achieve better GDP compilation.

But as a country, what does GDP mean in terms of Zimbabwean citizens’ economic conditions?

For instance, a reader may rush to say that GDP indicates the size of our economy.

Well, Zimbabwe has the highest GDP today than it has had since independence; can that same reader find satisfaction in the GDP figures’ explanation to our current economic circumstance?

Perhaps one will graciously concede on this importance of quality.

A lot of quantitative data that is upheld as essential to giving stature to Africa’s economic outlook retains specious relevance and context to its citizens’ economic conditions.

Unfortunately, we rush to abide by this data because it is the global standard; regardless that it has lost relevance and context to even the citizens of many developed nations themselves.

Consider Africa’s infrastructure deficit which is estimated at US$90 billion a year for the entire continent.

Each country must further analyse its portion to this deficit and consider the impact of the quantitative figure to the quality of its citizens’ economic conditions.

In Zimbabwe, for instance, our 2016 National Budget pointed out a required expenditure of almost a billion dollars on transport and communication infrastructure.

However, Government could only allocate US$100, 814, 249 to this sector.

This left an 89,8 percent or nearly US$900 million deficit in the sector.

Similarly, required expenditure on water and sanitation infrastructure was US$188,706,096 with Government only committing US$77, 271, 200.

This left a 59,1 percent deficit in water and sanitation infrastructure for 2016.

What does these deficits mean to the qualitative economic condition of infrastructure dependants?

Perhaps then, Zimbabwe should vocalise transport and communication deficits in context of how people struggle to be connected to markets, in effect losing out on opportunities to enter value chains, or losing out on information that could enhance their economic competence as human capital.

Moreover, water and sanitation deficits could mean that farmers often perceived as occupants of productive land actually lack water access that makes our productivity expectations exaggerated — a shortfall in our imagined quality of asset.

Sanitation deficit can also be interpreted as citizens exposed to dire health risks due to lack of access to fresh and clean water and proximity to waste and sewer systems.

Indeed, the idea is not to discount the value of quantitative data.

It would be unintelligent to proffer a zero-sum perspective.

The nuance in granting esteem to qualitative evaluation is that it creates a societal and personal narrative that raises our consciousness to the imperatives of achieving effective quantitative metrics.

There is much to consider in how we can create effective qualitative assessment of our economic conditions.

It has become an undesirable trait in our policy-making and economic analysis to discount the qualitative implications of our decision making, often due to pressure to achieve specious numbers.

The best policy makers are those who are guided by an appreciation of qualitative outcomes, merely using the numbers as a guiding stick to effect potent qualitative improvement in citizens’ economic conditions.

As we continue capacity building of our data centres, we must remain cognisant of the relevance and context of the quality we hope to achieve.