With respect to baseline data verification, the county officials had been tasked to
verify the baseline data before the monitoring visit. However but this was not
possible as Isiolo is an expansive county and the verification exercise through
community visits had not been budgeted for by the county. As a result this exercise
had to be done retrospectively and was conducted together with the first monitoring
visit which occurred just after the commencement of interventions.
15.2.5 Output and Outcome Data
Output data, was collected after a period of 9 months, against the indicators in the
ward ToCs and the county government score card (Table 15.3). Early outcome data
was collected with an outcome assessment tool, after one and a half years to
determine whether there were any changes being experienced from adaptation
actions being implemented. This tool allowed the ward adaptation planning committees to assess the extent to which outcomes as depicted in their respective ToCs
had been achieved through a scoring system. The results of this scoring are depicted
in Table 15.2.
15.3 Challenges with Implementing the Methodology
13
A few challenges were experienced when implementing the described methodology
as detailed below:
• Developing adaptation Indicators: As stakeholders were used to developing
output indicators as opposed to outcome indicators in development projects,
the process of developing adaptation indicators to adequately measure resilience
in the longer term proved to be a challenge.
• Use of climate variability information in the development and adjustment of
adaptation actions: An adaptation M&E framework assumes that the design of
adaptation actions has incorporated climate risk information. It also assumes that
climate trends will be continuously monitored throughout project implementation in order to attribute any outcomes to enhanced adaptive capacity as a result
of the interventions. However it was found that climate variability data had not
been used when designing the adaptation interventions due to its unavailability
during the design phase of the actions. In addition technical capacity to downscale climate trends in order to determine baseline scenarios in the county were
also limited.
13 Adapted from Karani, I., Kariuki, N., & Osman, F. (2014). Tracking adaptation and measuring
development. Kenya research report. London, UK: International Institute for Environmental
Development (IIED). Retrieved from http://pubs.iied.org/10101IIED.html
278
I. Karani and N. Kariuki
verify the baseline data before the monitoring visit. However but this was not
possible as Isiolo is an expansive county and the verification exercise through
community visits had not been budgeted for by the county. As a result this exercise
had to be done retrospectively and was conducted together with the first monitoring
visit which occurred just after the commencement of interventions.
15.2.5 Output and Outcome Data
Output data, was collected after a period of 9 months, against the indicators in the
ward ToCs and the county government score card (Table 15.3). Early outcome data
was collected with an outcome assessment tool, after one and a half years to
determine whether there were any changes being experienced from adaptation
actions being implemented. This tool allowed the ward adaptation planning committees to assess the extent to which outcomes as depicted in their respective ToCs
had been achieved through a scoring system. The results of this scoring are depicted
in Table 15.2.
15.3 Challenges with Implementing the Methodology
13
A few challenges were experienced when implementing the described methodology
as detailed below:
• Developing adaptation Indicators: As stakeholders were used to developing
output indicators as opposed to outcome indicators in development projects,
the process of developing adaptation indicators to adequately measure resilience
in the longer term proved to be a challenge.
• Use of climate variability information in the development and adjustment of
adaptation actions: An adaptation M&E framework assumes that the design of
adaptation actions has incorporated climate risk information. It also assumes that
climate trends will be continuously monitored throughout project implementation in order to attribute any outcomes to enhanced adaptive capacity as a result
of the interventions. However it was found that climate variability data had not
been used when designing the adaptation interventions due to its unavailability
during the design phase of the actions. In addition technical capacity to downscale climate trends in order to determine baseline scenarios in the county were
also limited.
13 Adapted from Karani, I., Kariuki, N., & Osman, F. (2014). Tracking adaptation and measuring
development. Kenya research report. London, UK: International Institute for Environmental
Development (IIED). Retrieved from http://pubs.iied.org/10101IIED.html
278
I. Karani and N. Kariuki