Data should be devolved to grassroots

In my public speaking engagements over the past three weeks, the emerging issue of Big Data featured in eight of the ten speeches I gave.

There is consensus that we need evidence-based policy making and nowhere is that more important than at sub-national level.

Even counties need to devolve data to sub-country level and not just deal with inequalities but also advance the most appropriate discourse.

Let me highlight a few examples to show why it is necessary that we focus our data collection and use efforts at sub-national level.

In a 2015 International Monetary Fund World Economic Outlook report, Luxembourg was featured as the richest country in world on exchange rate basis.

The GDP (nominal) per capita of Luxembourg was estimated at $111,716 in 2014. The world average per capita income stood at $10,880, thus making Luxembourg’s per capita income 10.27 times greater.

GDP (Nominal) per capita of Luxembourg increased by $1,410 in 2014 and that is $200 more than the per capita income of Kenya.

READ: There’s a data revolution at grassroots

Such comparisons help to highlight global income disparities. Without breaking down these data by country, it could be assumed that there is no poverty yet there are more than 600 million people living below $2 per day.

Similarly, developing countries, when they rely on national per capita income, fail to see disparities at sub-national level.

There is reason to foster greater inclusivity if there is visibility at sub-national data within the country, otherwise we may never understand the significance of data to correct existing inequalities.

Let me now turn to another case that directly impacts Kenya’s devolved system and was highlighted in the recent Kenya Institute for Public Policy Research and Analysis (Kippra) report.

Kippra and the World Health Organisation (WHO) 2015 report estimate life expectancy in Kenya at 63 years. Kenyans in Bomet County on average enjoy three more years than the average Kenya.

The county has the highest life expectancy in Kenya at 66 years. There is disparity also between men (61 years) and women (66 years).

What is startling is the disparity between Bomet and its neighbouring counties. Kenyans within the Lake Victoria region counties of Kisumu, Homa Bay, and Siaya have fewer people living below the poverty line when compared to other counties.

Yet their life expectancy of 40 years is significantly below neighbouring Bomet. Even though we know that these counties have different risk factors, it is my considered view that such significant disparities should be part of national political, social and economic discourse.

Instead, the matter is buried in data. The point I am trying to make is that data is telling us that national averages are deceptive and if we want greater impact at county and sub-county levels, data must be devolved and used for evidence based policy making. This is not happening currently.

Analyses of different data sets, from fiscal management to hiring practices, reveal the serious lack of capacity to respond to the glaring problems at county level.

Even though the Constitution created institutions like the Commission on Revenue Allocation (recommends equitable distribution of national resources) and Office of Controller of Budget (oversees implementation of the budgets of the National and County Governments by authorising withdrawal from public funds) their mandate as has been demonstrated over the last four years does not impact the management of counties in any meaningful way.

In my opinion, we need a more interventionist national government acting the way the Bretton Woods institutions do to developing countries. There is urgent need to develop various capacities but, more important, that of data analytics, and use the same to inform policy at sub-national level.

At the moment, we are virtually using voodoo to run the counties. The rising interest in the Member of County Assembly seats tells volumes of stories. With more than 40,000 aspirants for 1,450 seats, the allure of power and money is evident. Yet these are the offices meant to provide checks and balances.