learning-workshop_3_OMWaysForward

= **imGoats project: Learning and reflection workshop** = == Udaipur, India, 2-6 July 2012 ==

What is the way forward with Outcome Mapping in IMGoats?
In February 2011, I wrote some progress markers for myself.

I //expected// to see: the imGoats team apply knowledge on OM to the development of a people and outcome-focused M&E appropriate to the project information needs. This has been achieved.

I felt I would //like// to see: the imGoats team adapt OM to the different contexts of imGoats. This has largely been achieved.

I felt I would //love// to see: team members apply the principles, approaches, and tools of OM. It's too early to tell, but, you have my email address and I look forward to hearing how you get on in the final 6 months of the project.

**Addressing OM challenges**
[//"Clinic": team splits into two to discuss both 'data analysis' (India team) and 'scoring & global analysis' (Mozambique team) with an expert on the subject//]

**Data Analysis (India team)**
//What's the problem?// Large amount of data.

//Why is that a problem?//
 * It is difficult to analyze the data.
 * We have two clusters with 1000 families, and we collect this data regularly. It is difficult to enter this much information and to then analyze it, without the right people.
 * After the baseline survey, we can collect data accordingly. We took 10% of the 1000 families and made a baseline

The question is//: if data is being collected, you expect that data to be used. If you don't enter it into the system, why collect it in the first place? What do you want to do with the data? Why collect it?//
 * We want to find out more about these families.
 * Production, marketing, diseases, servicing, breeding
 * We collect it to, to feedback to field guides and to make policy recommendations
 * In the longterm it may be used in the research world
 * Data may show changes in society, to measure change
 * Data can show us changes in behaviour and we can keep track of practices and adoption
 * It helps us track progress of the project


 * Summary: Data is collected to measure change, to give feedback to the field guides, to make policy recommendations and in the longterm to contribute to the wider research community**

//How important is it for you to capture data from __all__ of the individual households? In which case// //it's worth appointing someone to deal with the data (fulltime)... Or are you happy to measure trends from a sample of households?//

Is the amount of data really a problem or not? Could you employ someone to enter that data, and what are the costs? You need to think about how you are going to use this data. Don't throw away data at an early stage if you are not sure what you're going to find useful and what is not. It might be that you want to keep a record of everything, or you may reach the conclusion that sampling is best and there is no need for so much information to be collected and stored.


 * Here in Udaipur there is experience in entering data, every month
 * Bit more difficult to find someone to work on data in Jharkhand
 * Data entry is not an issue, but someone is needed for data analysis
 * If data base is set up, it shouldn't matter how much data you have (all households or sample) for the analysis stage


 * Summary: For the rest of the project, get the right people to manage the data (i.e. someone to input data, and someone to analyze the data). Keep your data, try to enter it, give it some time, take a step back at the end of the year to review the process and see whether it was the best way to do this.**

//You mentioned coding?//
 * Somebody does coding, and then another person will enter the information afterwards
 * After seeing the initial narrative, coding has been simplified
 * It could even be simplified further and the field guide may reach a stage where he doesn't even need the form anymore
 * There is a supervisor for every 5 field guides, who supports the guides and monitors what they are doing
 * Field guides are part-time staff. They are getting an incentive of 1000 Rs. Is it enough?
 * There was a problem with consistency of data
 * When it comes to sampling, there is a question over doing the same households each time, or using random samples. It is not straightforward. For that reason, there is an argument for looking at the same individual households. E.g. you can see the changes affecting one farmer and his goats (easier info. to standardize)
 * There's a need for careful input of data on each household, so as it doesn't get mixed up
 * Quality of data is OK


 * Summary:** **Data entry is not the problem (although in Jharkhand someone is needed to do this). Data analysis is the problem. N****eed to reflect on what you really want to do with the data.**

Holding monthly progress meetings is too often, so every 3 months or so is best.

Scoring and global analysis (Mozambique team)

 * How to proceed with OM during the next 6 months (up to December 2012)**
 * Participants: Amosse, Ann, Birgit, Roberto and Saskia**

__**Frequency of meetings**__ Pros and cons of having monthly meetings were discussed. Having monthly meeting implies that:
 * **Negative** || **Positive** ||
 * Not much change may have happened to report on. || Extension officer will remember better what changes have happened in the last reporting period. ||
 * Extension officers are missing one day of field work since they have to be in Vilanculos. || Allows for adapting activities if something needs to be corrected. ||

Given the short remaining project period and because we expect a lot of changes to happen in the next months, we thought that it might be better to keep the monthly meeting, sometimes perhaps going up to 6 weeks.

We also agreed that the facilitator needs to probe more in case one of the progress markers is assessed as “no change”. Often something has happened in relation to a progress marker it’s just that the what is described in the progress markers has not happened yet.

__**Scoring**__ For scoring of progress following the progress markers for the different boundary partners:

Since the scale of the project is limited, there is no real need to have an elaborate scoring system (e.g. 1 to 7) and a 3 level scoring could do:


 * Low: no or limited progress
 * Medium: progress happening but still room for improvement.
 * High: almost meeting the highest level of achievement identified in July 2011

In addition: the table can have a column for ”comments” in which you explain based on what information you based your scoring.

The scoring should be based on information from the field (e.g. number of producers that are treating their animals, number of community grazing areas established). The scoring can be done twice before the end of the project, the first time in early October. Before the meeting the team, led by Birgit should collect the information for the different progress markers up to 30th September 2012 that can be used in the scoring exercise.

As of how the scoring can happen: doing it in a group (as done in Udaipur) was thought to be appropriate. It could be done on Friday afternoon, after having the outcome mapping meeting in the morning.