Sisay Sinamo (MD, MPH, PhD)Senior Program Manager, Seqota Declaration,Federal Program Delivery UnitMinistry of Health, Addis Ababa, EthiopiaTel: +251 911 510 988 Email: seniorprogrammanagerfpdu@gmail.com

5 900Woredas will be suppliedwith computers and a database (UNISE) capturing key indicators -pilot begins October 2019

Health posts will be connected to tablets and satellite internet (Yazmi) with 5 starting by December 2019

Woredas implementingresource tracking and partnership management 33

THE PROBLEM

THE SOLUTION

KEY FEATURES OF THE DATA REVOLUTION

The goal of the Data Revolution innovation is to develop and implement a culture of data-driven decision-making by establishing a robust, multisectoral data management system to collect high quality data that will inform decision-making and intervention targeting, ultimately leading to a reduction in childhood stunting. The scope of the Data Revolution activities continues to change rapidly as new systems such as the Unified Nutrition Information System for Ethiopia (UNISE) platform, Yazmi’s satellite data transmission systems, resource tracking and partnership management tools are introduced and piloted. The underlying aim of this innovative approach is to harness new technologies and methodologies to support data availability and use.

The primary activities under this innovation are:

· Build robust electronic data systems to capture routine administrative data from key Seqota Declaration implementing sectors.

· Develop lean supplementary reporting systems in select geographies to collect performance management indicators to track program implementation and to guide decisions around scaling.

· Design evaluation studies where needed to capture outcomes that otherwise would not be possible to track or require more robust levels of evidence to guide decision-making.

· Analyze monitoring and evaluation data to produce meaningful information that can be used for decision-making.

· Advocate for and build capacity of sectoral focal persons across levels to use data when designing and refining programs and interventions.

· Map Seqota Declaration implementing stakeholders to improve coordination and responsible, rational resource allocation.

· Track government and development partners’ financial allocation and expenditure and use the data for informed decision-making and rational resource allocation.

In an era of increasingly tight fiscal resources and budgets, policymakers need objective and impartial means of reviewing programs for efficiency and effectiveness to inform decisions about modifying, scaling-up, or stopping publicly-funded programs.

The Seqota Declaration implementing sectors’ data systems are of variable stages of maturity and strength. Consequently, the multisectoral data relevant for tracking nutrition outcomes are of limited availability and often are not used to inform decision making.

Policymakers are not always involved in the development of these data systems nor are these data systems sufficiently flexible to reflect the evolving needs, resulting in a failure to capture the data needed. In other cases, the timeliness and other quality issues mean that policymakers cannot rely on data to inform their decision-making processes.

Data RevolutionA N I N N OVAT I O N O F T H E S E Q OTA D E C L A R AT I O N ,

E T H I O P I A ' S CO M M I T M E N T TO E N D ST U N T I N G

Sisay Sinamo (MD, MPH, PhD)Senior Program Manager, Seqota Declaration,Federal Program Delivery UnitMinistry of Health, Addis Ababa, EthiopiaTel: +251 911 510 988 Email: seniorprogrammanagerfpdu@gmail.com

5 900Woredas will be suppliedwith computers and a database (UNISE) capturing key indicators -pilot begins October 2019

Health posts will be connected to tablets and satellite internet (Yazmi) with 5 starting by December 2019

Woredas implementingresource tracking and partnership management 33

THE PROBLEM

THE SOLUTION

KEY FEATURES OF THE DATA REVOLUTION

The goal of the Data Revolution innovation is to develop and implement a culture of data-driven decision-making by establishing a robust, multisectoral data management system to collect high quality data that will inform decision-making and intervention targeting, ultimately leading to a reduction in childhood stunting. The scope of the Data Revolution activities continues to change rapidly as new systems such as the Unified Nutrition Information System for Ethiopia (UNISE) platform, Yazmi’s satellite data transmission systems, resource tracking and partnership management tools are introduced and piloted. The underlying aim of this innovative approach is to harness new technologies and methodologies to support data availability and use.

The primary activities under this innovation are:

· Build robust electronic data systems to capture routine administrative data from key Seqota Declaration implementing sectors.

· Develop lean supplementary reporting systems in select geographies to collect performance management indicators to track program implementation and to guide decisions around scaling.

· Design evaluation studies where needed to capture outcomes that otherwise would not be possible to track or require more robust levels of evidence to guide decision-making.

· Analyze monitoring and evaluation data to produce meaningful information that can be used for decision-making.

· Advocate for and build capacity of sectoral focal persons across levels to use data when designing and refining programs and interventions.

· Map Seqota Declaration implementing stakeholders to improve coordination and responsible, rational resource allocation.

· Track government and development partners’ financial allocation and expenditure and use the data for informed decision-making and rational resource allocation.

In an era of increasingly tight fiscal resources and budgets, policymakers need objective and impartial means of reviewing programs for efficiency and effectiveness to inform decisions about modifying, scaling-up, or stopping publicly-funded programs.

The Seqota Declaration implementing sectors’ data systems are of variable stages of maturity and strength. Consequently, the multisectoral data relevant for tracking nutrition outcomes are of limited availability and often are not used to inform decision making.

Policymakers are not always involved in the development of these data systems nor are these data systems sufficiently flexible to reflect the evolving needs, resulting in a failure to capture the data needed. In other cases, the timeliness and other quality issues mean that policymakers cannot rely on data to inform their decision-making processes.

Data RevolutionA N I N N OVAT I O N O F T H E S E Q OTA D E C L A R AT I O N ,

E T H I O P I A ' S CO M M I T M E N T TO E N D ST U N T I N G

Data RevolutionA N I N N OVAT I O N O F T H E S E Q OTA D E C L A R AT I O N ,

E T H I O P I A’ S CO M M I T M E N T TO E N D ST U N T I N G

Innovations to improve data availability

UNISE e n fied on n o a on e o op a a on o n ool o l e o al n on oo d na on de ned

o a l e o al n on da a o lo e e ele a a and o eda o e onal e onal na onal le el and o o

pe o an e p o e n a da oa d o e de on a e and ple en e ool a de eloped ppo and

np o e op an o e n en and e a e olde

ONLINE NUTRITION RESOURCE TRACKING AND PARTNERSHIP MANAGEMENTo ppo n o ed de on a n on finan al e o e e e o a nd n ppo o on n e na onal a ond ed finan al allo a on and e pend e a n o e pa

o ea n o eda

SUPPORT DATA USEe ll en o e oon o e e ed o eda oo d na o

o ppo e anal and e o da a a e o eda and lo e le el le e la l ee n ede al n e and a n o e a d na a e epo an la n e da a n o lea a ona le

e o enda on

OUTCOMES MONITORING o a e p o e o e o e n en and de elop en pa ne n e en o o e on o n ll e ond ed o a e e

p o e o ele ed p o nd a o o e a el ne d ll e a o na on o ann al o ann al e o pple en

e la e e o o on o n da a ep e en n a depa e o e ad onal and e pen e la e ale o e old endl ne

e

YAZMI TECHNOLOGY SOLUTION o p o e da a a e l n a ea e e e e no a e o

ele and poo n e ne onne e o e n en o op a ll la n ola po e ed a ell e a ed a e nolo ol on

ll ena le a ell e a ed da a an e n eal po a a and apa ld n pla o o de elop en a en

PROCESS LEARNINGS

partner was engaged with funding support from Big Win Philanthropy to assess the data needs of the Seqota PDUs and develop a MEL strategy. The MEL technical partner, IDinsight, adopted a two-pronged approach of being

PDU.

sectors and the PDU have jointly developed key performance indicators

performance. Costed Woreda plans have also been developed, an

sectors need to strengthen data systems to facilitate data analysis and

geographies they cover, which makes MEL needs more complex than an average large-scale program. To this end, a comprehensive and cohesive

Online resource tracking and partnership management system launched

-

resource tracking, partnership management, stakeholder mapping,

were developed, training-of-trainers (TOT) was provided along with woreda

guidelines translated into local languages. An online partnership manage-ment system has been developed and field tested. The TA team also

second in-depth assessment was carried out in 13 woredas to assess staff and woreda capacity needs to implement a resource tracking and partnership management system.

management and (iv) stakeholder mapping.

RESOURCE MOBILIZATION

and the provision of computers in these woredas to address challenges faced in the original pilot.

Demandfor Data

Data-Driven Decision-Making Cycle

Vision:

High-quality data coupled with intuitive data analysis and presentation enables data use for decision-making. Data use for decision-making improves

outcomes and helps create new demand for data, which in turn generates new or improves the quality of existing data collection activities, setting up a

virtuous cycle of data collection, analysis, sharing, and use. This is a cycle that continues to reinforce itself as steps are implemented and refined. This allows

for responsible, rational resource allocation for improved performance.

Cross Cutting Inputs

Decision needs

Program changes demonstrate value

of data-driven process

Accountabilityaround inputs

used for decision-making

Appropriatemethods

Addresses specific

program decision needs

Available to relevant

decision-makers

Data is available at the right time

Data valued and seen

as credible

Guided by a clearresponse

framework

Documentation and

communication of decision rationale

Follow up to ensure decisions

lead to actions

t

Guided by analysis

plan and toolsdeveloped

ex-an e

User-friendlyinterface/output

System for sharing at

all relevant levels

Appropriatefrequency

management

Responsive and flexible system

Clear roles and responsibilites at each stage Appropriate capacity and skill sets

Aligned incentives arounddata-driven decision making

Adequate resources

Focused and simple indictors

High Quality Data Collection

Intuitive Data Analysis &

Presentation

Data Use for Decision

Making

Data RevolutionA N I N N OVAT I O N O F T H E S E Q OTA D E C L A R AT I O N ,

E T H I O P I A ' S CO M M I T M E N T TO E N D ST U N T I N G

Data RevolutionA N I N N OVAT I O N O F T H E S E Q OTA D E C L A R AT I O N ,

E T H I O P I A’ S CO M M I T M E N T TO E N D ST U N T I N G

Program changes demonstrate value

of data-driven process

Accountabilityaround inputs

used for decision-making

Decision needs Appropriatemethods

Appropriatefrequency

Focused and simple indictors

management

Responsive and flexible system

Addresses specific

program decision needs

Available to relevant

decision-makers

t

Guided by analysis

plan and toolsdeveloped

ex-an e

Documentation and

communication of decision rationale

Follow up to ensure decisions

lead to actions

Data valued and seen

as credible

Guided by a clearresponse

frameworkSystem for sharing at

all relevant levels

User-friendlyinterface/output/output/

Data is available at the right time