Are we ready? Yes, we are. So we want to invite you guys to come a bit closer. It's a very big room for people that are online. They don't see it. That's good. It's a big room. Please come closer. This is a fashion that has created a lot of attention and awareness in the history. Goods, because after the pandemic, you really saw the importance and strength of sharing data across sectors. And I also think government had a kind of an awareness of how to use VHS to for more than health, because during the pandemic we were of course having integration with immigration authorities, civil registries, ICB tracking tourism, etc. And then after the pandemic, we have seen a demand and an interest in also to look into, to all of the sectors, how we can benefit all the sharing data across for analytics and for strengthening national, but also local government. So we are actually talking about the estuaries and remember this morning we were talking about kind of health. The estuaries are covering 17 different sectors and many of which are environmental oriented. And the aim of the estuaries is to address poverty, to address a better planet. And we are halfway to 2030. So there is kind of a time and a time for action and a time for being able to utilize the opportunity that are in the countries to get more awareness about monitoring these across sectors and also utilizing in different ways. So we will today, this last session of the day before the technical sessions afterwards, we will go through four different examples, we will hear from Uganda, we will hear from Rwanda, we will hear from Ethiopia, and then we will have virtual presentation towards the end. So Prosper will you introduce our first speaker that will be virtual, but we will prosper this program as well. So we will be able also to join the discussion if that's possible. Necessary. Okay. Thank you very much, Christine. Welcome to this session, very exciting session after discussing the digital public goods. And these are really examples and some of the use cases that we are already starting to see as we go beyond health. Yeah, so we're excited to be sharing today, one of the big use cases that we have in Uganda, a use case that is really not good bringing one sector to the DHS to but multiple sectors, and we are very excited to have a presentation from the government. From Mr. Rwanda, who is the principal information systems specialist at the office of the Prime Minister in Uganda, who has been very keen in trying to design this implementation and roll it out. So just taking it to him, he's presenting live visa issues again, he will be presenting live from Kampala, and it's almost after work in Uganda, so we again want to produce for taking your, you know, after work. So, let's get to you there. But if we have any connection problem, we can be flexible that we always are, we can start with Rwanda if we're not able to solve it in a couple of days. We'll just do the next one. Is it? So he's not on the second, so. Okay. He's disappeared, so I don't know where he is. So I can't do it. No sharing. Okay, so let's take Rwanda and we shall probably come to, to here. So let me just start with Rwanda, no problem. Okay, you're in the spot. Okay. Thank you, thank you. Thank you. So for the Rwanda cross sector monitor, are we together? Hello. Very good, very good, very good. So for the Rwanda cross sector monitoring tool, actually, this is another tool that we've been developing actually to track the cross sector indicators. This one is different from the health sector one, because the health sector is only health, but this one is collecting almost all sectors indicators. So maybe giving the background, these are the pictures I wanted you to show you how these cross sector indicators are really published currently. Most of these. Okay. Yeah, okay. The cross sector indicators, they are published manually. You know what happens we just print, we print them and put them on the dashboard we call it citizen public data portal, but it's a manual one. They just print and post it somewhere in the public place where people come and check the performance of the local entity. So what we're doing is just to automate the whole process. So you can see different dashboards standings out in the district. It's in the king around I will bear with me. Then sees another example of, sorry, I have to click. Another example of what we call the station room. The station room actually currently how it works. It's a, it's a room where they track all the performance of these indicators that come from different sectors, which is health, education, social protection, gender and others. But the way we really update the situation room is that the right to manual is a box, there's like a paper there you go on the right 1030 manually. So we thought that automating the whole process will help us also to come up with an automated dashboard that will help these people to take decisions and other actions. So why should we care about the monitoring tool that is capable to really automate the whole process as I said, you know, this KPI, which is key performance indicator. It's not led by the means of local government, it's not Mr of health because means of local government is the one that is in charge of the whole local administrative entities. Then I don't want to consider is that as you go down at the grass root. They don't, they don't care about health only they care about the citizens and other services which is either health education and others. So we, we are expecting that the system will be able to help them when it comes to data translation I mean translating that across the sectors. In the in the simple way, then it will help us to have these dashboards and we have seen they write the dashboard using their pens and hands. Then again, of course, we'll be able to monitor the performance of these indicators across the sectors and levels, different levels. So, as I said, you know the weakness of this project is that it will be really implemented at the grass root level, which is the cell. The cell actually for us we have this fixed sectors and cells. So this data will be collected at the cell level. But again, we have also the situation report that is collected at the village level because they will be using mobile phones. Then we will try to come up. We will have tried to come up with a thematic data entry forms, but again also thematic dashboards. So, actually, the difference between the traditional reporting that we are having currently and the automated that we are really implementing currently. Is that at least having the, the, the, the, the one butter bank will help us to have some other things that are able to detect earlier where we're not performing well. Then again, it will simplify the process of reporting. It will improve the quality of data. The dashboards of course will be both automated. So these are the outcomes that we're expecting to gain from this tool. One is that we have a greater visibility of what is happening at the ground level, which is currently done through either WhatsApp or through email and manual papers. It is not easy to aggregate and be able to see what is happening down. Again, it will enhance the decision making capabilities at all levels. It will increase accountability. Of course, if you are having the visibility, you are able to ask why things are not going based on the investment that you are putting on. Then of course, the main, the main reason we're implementing the tool is not accountability only is also continuous improvement. We are saying that we have committed to reach at this number after three months, but in one month we're seeing that we're not will not be meeting our target. Then again, aligning with the goals when we say goals, we have many goals. We have different goals as SDGs, there's national commitments and others. All these indicators are confined on the national commitments, SDGs and others. So, as I said, we are happy that the HS2 currently supports different devices. At the village level, we are planning to use the number phones, which is the government have offered the hundred phone to the head of the village. So we are planning to use them, but at the other levels we'll be using laptops and tablets. So we'll not read the rest of those others. So, these are the sectors, the indicators are really aligned to these sectors, different sectors. We have agriculture, we have education, we have energy. We have environmental natural resources, gender and family promotion, governance and decentralization, health, ICT justice. So actually, when we say health on this side, it means a lot. It means all these sectors because you know, for you to prevent yourself from infectious disease, you need to have knowledge for you to attend the health care, you need to be aware that it's really important for your baby. So all of these sectors when we are planning to be there, that's when we call it health by the way. Okay, so these are the districts we have in Rwanda, we have five provinces, districts there are 30, sectors 416. Then say the 2100, that's where you are laughing, small, no, no, it's not small villages. Of course, yeah, actually these are the administrative hierarchy on top we have provinces, it's like region, some countries they have region, others they have states. So for us we have province, we have five province. Under the province we have districts. Then under the district we have sectors, then under sectors we have cells. Those are the structure. So for the, for this initiative will be the reporting will be at the level of the cells. Then also at the level of the village. Yeah. So those are the numbers of village and cells. So, of course, implementing this initiative was not easy because you know, looking at reality from the ground, you find that each district will always have their different interventions. Like the KPI, we have what we call Emigo, normally in Rwanda, all of us we have KPI, like me I have KPI, district we have KPI's, the ministry have the KPI's. So those KPI's we sign them with your supervisor. Like if it's the minister, they sign it with the president, even the district they sign with the president. So those are the KPI's that the means of finance will invest in. So when they're investing in, it means if you go down and you start linking them with interventions. Those different interventions are the ones that we end up coming up with different indicators. So which means one district may have 10 indicators that are different from another district based on the intervention that they think we really push them to meet the commitment that they signed. So one district may have a period of building roads, another one the period will not be building roads. Maybe previous year they built roads, this year they're not going to have building roads at their purity. That's why we started with the assessment to ensure that we are able to know what is available, what are interventions that they have, what are the key indicators, then we redefine them. Our assessment, what we have seen in assessment we found that most of them they have different indicators. Then we started the customization, the customization to the system. We did the testing, but again the testing was different from different regions. So as I will say we started with the Eastern Provis, this is the Eastern Provis where we were piloting. That was our plan to start and pilot here but previously it changed. The government said no, we don't want you to pilot in one, just go to all provinces. So currently we are doing the same exercise to all provinces to come up with one harmonizing reporting, which have different indicators but maybe in the future they will be harmonized. So that is what we are doing. Very soon we will be launching Contraite. So these are different categories that we devote to what we call situation report is a KPI performance indicators. There's also immediate reporting, which is reported in different, there is one in business with another quarterly and monthly. So this is an example of what we customized. You can see, these are different forms that has agricultural environment, these are section forms that have different reporting forms. This is a KPI that is reported by the district and sector. This is what we call in the ego, the one that we sign that the district and the ministry sign with the government with the president. So these are also the ego, this is the situation report actually in the beginning when we were customizing the system. The situation report was not part of overall projects, but when we were customizing the governor and the ministers were saying no, no, no, we need to know what is happening in real time. So use the system to really notify us what is happening. So we created all of them. You're from this program. To ensure that at least we are able to respond to the needs because you know it's not all about reporting the quarterly, but also the real time data. So the next steps actually after changing the plan because the plan is piloting in the Eastern province. Currently, what we're doing is customizing the ensuring that the system is able to generate the standard reports. Then they were requesting us to have like a approval process. We are lucky that the HST actually the HST actually have to appreciate the developers. We are lucky that these features are already there, but they think we are developing it. They now think that we are developing it so when we go back and just implement and I think we have developed it. So we'll come back to the training for all of them to ensure that they have skills on using all these futures. Then of course we have to, we've been reviewing the metadata because most of them they are different. Actually, it have some conflicts on implementing such a system that doesn't have the harmonize indicators. Of course, we'll be supporting users on daily basis. So these are the challenges but they are not big challenges as such. The most challenge is indicators because indicators are different in all the sectors. So you find they have different interventions. So at the end of the day they will have different indicators. So harmonization is not easy. Then we are requested to make the system talking to other system will have to map them. Then the data entry of course because the data entry was not designed for KPI. So we are thinking to add some of the, because you know for them they want to see the baseline, the actual status, then the, the, the, the, the target. These are the solutions but you can read them. I think we are showing challenges but also the solution. Thank you. This is the end of my presentation. So I think we save the question for later so we make sure that we're now getting the ministry in from, from Kampala. So you can put in a presentation but just to recognize again, Robert Roasa, who is the principal systems administrator in the office of the prime minister Uganda and is actually also joined by colleagues from the same office. And that is a loan and I don't know is also the monitoring and evaluation officer. And these two have been very clean in this implementation. So you're going to switch over to Kampala and they get this live presentation from the, the tool. Thank you very much. You can go ahead Robert. Okay, thank you very much and greetings to everyone. As already introduced by pros for my name is Robert Roasa. I'm the principal systems administrator and I double as the head of it at the office of the prime minister for the Republic of Uganda. I'm here to share about the system that we're implementing specifically for monitoring the development plan for the country five year, and it is being developed on on DHS, DHS tool. And this system was actually based on the third development plan, which is a framework for the government of Uganda, and it is hinged on the public sector monitoring and evaluation system, which came into force in 2013. The development of this particular tool started in 2020 with support from the European Union. And it has been supported by a consortium, of course, first by the office of the prime minister, where I'm domiciled together with the national planning authority, but also support from Kaui in Belgium. And then we have the first Ethiopia where we had a built, and then his pew ganda where we have the support of a prosper Eric and his colleagues. So the system was actually developed by the right honorable prime minister for this Republic in July 2021 so it we are going to be making two years since we launched this particular system. The system, there is a framework of how the man he is being done in the government of Uganda with his excellence in the president at the top, and he's the chair of the cabinet, but the office of the prime minister is the one that is mandated to do monitoring and evaluation in all the processes. And beside it, we have the apex which is a platform which also does some of the monitoring under the presidency, but also the national planning authority, which is actually the one that is behind the, the development plan itself. You can see that we have development partners with whom we work, and then we have programs under the different ministries departments and agencies all feeding into opium. Since 2001, we moved away from having sectors doing planning via sectors with a view of trying to avoid operating in Syros. So entities that are contributing to particular programs are all grouped together to do the programmatic budgeting. We have the local governments which are under the ministry of local government, and then we have ministry of finance planning and economic development. These are the ones that are managed, our accounts, the ones that manage our projects that is where we have the integrated bank of projects domiciled there. Then of course we have Uganda Bureau of Statistics, which is mandated to collect statistics across. So, the requirements for the public sector, E-Police included having quarterly reviews by the respective institutions and then by annual internal reviews by the program working groups, and then the annual, which is conducted again by all the program working groups, but we also do performance assessments half-year and also for the whole year. Then there is also fair proportion of public investment projects that are subjected to rigorous evaluations. I have already mentioned that we have the integrated bank of projects under the ministry of finance, and there is the evaluation that goes on from time to time to assess the performance of these respective projects. Then of course opium provides standards and guidance on conducting these evaluations and managing the M and E systems across governments. So, regarding the design and workflows, the system itself was based on the third national development plan. For the first and second development plans, we did not have this tool. So to improve, so we came up with this tool to be able to help and it's based on the third national development plan which spans from 2020-21 and goes on up to 2024-25. It is also based on program implementation action plans, as well as our bigger vision, that is Uganda vision 20. It covers all government ministries, departments and agencies, as well as the local governments up to the grassroots. So using DHIS-2, a total of five custom applications that make the system have been done. So one, we have the NDP results dashboard. We also have the targets data entry. We have the performance that is the actual data entry. And then we are also able to track actions and policies. Many at times there are some policy resolutions, policy actions that are agreed on, and these needs to be tracked. So we also have the NDP document library using the same tool. The scope of this case is we have three media reporting frameworks. That is the national development plan. Then we also have the local governments with the indicators that are also defined in the NDP. And then we have our flagship, which is the parish development model. Because we implement interventions up to the smallest level, up to the granular level down at the parish. Then we have cross sector monitoring at both central and local government levels where we have say ministries, which are a total of around 30 entities. Then we have 122 departments and government agencies. Those are different from the ministries. And then we have local government votes. So these are either ministries or municipalities or cities. Then we also have 20 public sector programs. Remember, I mentioned earlier that initially we're operating sectors. Now we are operating programs. So we have 20 programs under which we have 68 sub programs. And on the system already we have over 5000 indicators that have been defined, and all these are aligned to the different programs in the system. Then they have already alluded to the issue of shifting from sector best to program best. So we already we are implementing or we have rolled out the system in say the human capital development program that is where we have ministries like a Ministry of Health, Ministry of Education, Ministry of Public Service. Then we have the Development Plan Implementation Program where we have the Office of the Prime Minister itself. We have the National Development, the National Planning Authority. We have the Ministry of Finance and others. And of course, Governance and Security, where also Office of the Prime Minister contributes to because some of the interventions that we implement fall under the Governance and Security Program. So our data and level of reporting, we have those three categories. I already mentioned the central government where we have the NDP3 goal. We have the objectives, outcomes, the intermediate outcomes and output results as defined in the plan itself. So we also have the actions, the budgets and releases also defined there. Of course, there is an integration between say the system and the integrated financial management system to avoid data entry fatigue. So there is an interoperability. Also with the integrated bank of projects. We also have project tracking like I've already alluded to government implements different programs and these monitoring and evaluation for purposes of tracking the progress and also the policy action tracking, like I said earlier. Then under the local government district level. There we also have outputs defined for each local government. And also at the lowest level. That is where we go up to the parish level. Of course we have received them. We have received requests to drill down up to the village level. So this is something that would probably require more resources to be able to have the capacity, even collect the data up to that lowest level. So here we have NDP results reporting and visualization. Of course, we develop dashboards. Like here we have we are able to have summaries over key result areas defined in the NDP3. We are able to provide the performance figures against budgets. In this lower section, you can see that we have different, we have different say objectives of the NDP, then the key result area, then the different indicators that have been defined. So we set targets. And then for the, for the respective financial years, we are able to input what have we been able to achieve for the respective indicators. The different color codes depends on the performance. If you have been able to say to achieve the targets up to say maybe 95%, then we have a green color code. And then for where we are, we've been able to perform moderately would have to the color code would be yellow. And then where we've underperformed say under 50%, that is where I would have the red color code to be able to show the progress. And then, of course, I've already alluded to the different indicators where you have different votes, the different ministries, the different entities, which belong to particular or contribute to particular programs, where you are able to have specific indicators, where you report on them. And also, we are able to compare, depending on the baseline that there is for the respective indicators. I've already mentioned that we have dashboards defined here, depending on what we want to see. The Prime Minister, by virtue of being the leader of government business, may have maybe interested in viewing specific indicators. There could be maybe income per capita. It could be something to do with the poverty levels. It could be something to do with say infrastructure. So we are able to filter out depending on the program, depending on the sub programs, or even the respective entities that would want to visualize. But also, there is an element of filtering, depending on the scope of the period that you want to reference. Of course, there are analytics. Now like, say, we have, say, MDP results where you have the bigger vision, that is vision 2040 targets, and then under that we have the goal that is as per the MDP 3, the objective, and the outcome levels, as is shown on the left-hand side. So here you see we have the goals, and then the key result areas, under which we have the respective indicators. Like you can see we have the income per capita, we have the real GDP growth rates, and then for each of the financial years, we are able to report on the actual vis-a-vis the targets. So this was only realized that for the financial year 2023 and 2024, there is no actual, because this one is ending at the end of this month, June, then we'll open up and be able to capture what the performance will have been for the respective indicators, programs, and MDS. So this continues, say, this is for the policy actions. Remember, I said that we have a policy tracker, so a particular vote may have a specific policy that they're supposed to be implementing. So we are able to track, so when is the start date, when is the end date, and what is the progress status. And again, the color coding is used to visualize the progress of implementation of the different policy actions. So this is the implementation status of the system, the NDP, M and E management information system. So we've been having system improvements and customizations that have been going on, because users keep on requesting for different things, and then customizing it to make it very visible. So all targets, as we speak, have been uploaded onto the system as per the third national development plan. And since a mid-term review was actually done for the third NDP-3, so the results have also been input to the system. And performance results for the last two financial years have also been uploaded onto the system. That's why we are able to see for the two financial years 20, 21, and 21, 22, they are already in the system. We've been able to put available for the users comprehensive documentation. And at the same time, we have also put in place an instance or a platform to enable users to go in and, yes, please. Yeah, could you go through quickly the next slides. We're running out of time. Thank you. Okay. Okay. So we've been able to upload manuals to help users be able to have a reference point for support. So we've carried out a series of trainings for purposes of enabling users to be able to navigate the system themselves and be able to report. We've already rolled out, of course, beginning with ourselves here at the ministry and also the planners in the NPA. And we've also carried out engagements. We've carried out engagements with different players. We have, we've been able to do so for the M and E working group and then the DPI program. So we have initiated because the support that we receive from his, the contract is ending soon, but we've initiated an MOU to ensure that we have their support as we roll out this, this system and it is pending clearance from the Solista general. And the success factors is the one of course buy in by government and ownership, and of course high level participation we have our top leadership that is participating in this. We've recorded success by entities like Ministry of Health. We're already implementing other than this, there is another system they're implementing on the same platform DHS to then flexibility of the system to generate user friendly visualizations to be able to come up with different dashboards. And then they are, they are a number of government entities that are fully capacity to access and provide timely reports, as well as analysis integration of data collection has also been able to it is a success factor that we've been able to leverage on and then the linkage between NDP three and other government complementary systems like I've already alluded to for interoperability and of course not to downplay the support from the DHS experts from his Uganda. We've had challenges of course resource constraints for purposes of roll out, because this needs us to go and move from entity to entity, we need to move to different districts as we roll this one out and we need resources, then the quality of data. The data that we have already input for the two financiers has pointed that there are some data gaps. So that one is also a challenge, and then the difficulty in managing dynamic changes of the indicators as we transition from sector to programmatic budgeting. That one has also been a very big challenge that we have suffered. So I want to thank you for listening. Thank you so much. Thank you so much. This work in Uganda has actually created a lot of attention for other countries. I've been looking into the same solution. This is the advert, you know, the same advert, so that he was thanking for this. So you should think that this will be comparatively, but it's small. We're going into the same solution as this national development plan. And that is putting up a slice. And we saw the random examples, the same, however, much more focusing on the development, so the local government. Thank you so much. What's happening with the transformation plan. Thank you Kristina. Sure, that you've done an experience with your best planning permission and looking to look into it. So yes, it has a lot of interest. And it kind of continues.  I don't know what's going on. is not just enough especially for the local administrative units. Yeah I mean we need to have something similar for other sectors as well and that's what this whole multi-sectoral engagement of Ethiopia is telling us. It's kind of an aspiration to see a transform in Ethiopia. It's a big initiative by the government of Ethiopia strategy to increase number of high performing local administrative units and of course it's a vehicle to transform Ethiopia from low to middle income country. In fact it's a multi-sectoral engagement of ministries, agencies, development partners and other stakeholders who have a number of ministries, ministry of health, education, agricultural transport and so on the list kind of continues. That means it's a local, it's just a district, it's a local administrative unit and in fact it's a lost and pragmatic governance unit where a lot of planning a typical classic government activities kind of takes place. I think our colleague from Ethiopia talked about this one plan, one budget, one report. This word that transformation is kind of a manifestation of that because everything has to go through that mechanism. Yes I mentioned it's a multi-sectoral engagement but unfortunately currently it's only ministry of health which kind of leading the pack in implementing this because ministry of health has already a system in place. They have been implementing the HRS since 2017. They have already experienced and because of that we were able to kind of implement the word that transformation pretty quickly. What's happening in that is the ministry of health have identified five key measurable components or more like pillars of engagement or more like a component. One of the components is quality of service. These are more like the earlier in the Uganda we have the 18 or 20 programs. Earlier we were about 18 now currently they are implementing 20 programs but here we have five pillars and each of them have kind of a number of or a set of indicators. Quality of service, the major quality of service, leadership and governance again they have a set of indicators to manage this and also this motivated compassionate and caring workforce. They also have set of indicators to measure this healthcare financing and information revolution. All these kind of in good deep down into each of these components they have a set of indicators and these are going to be measured against a very specific set of where it does and a total of 65 indicators as I said each of them have composite indicators and in fact that's where a specific or a special app was developed to inside DHRs to to kind of manage this composite indicator. It's more like indicators inside indicators and that's just to show you the the app we have inside DHRs to. This is part of the word that transformation system. It's an app that was developed by his Ethiopia and the advantage with this is they are using DHRs to even to manage this because what's interesting is DHRs to is it doesn't dictate you what sort of indicators to collect a report and process in DHRs to. You have the user are free to define and those come from the five pillars or components and the advantage is there is already capacity in the country the system is already operating and functional so they have already halfway ahead of the pack that's why the Ministry of Health is already one step ahead of the different ministries and in fact they are ready to share that experience. It's just to show you what's going on inside this word that transformation app. There are three levels of indicator calculations. It's just a normal indicator at the level one and these indicators will be calculated against some weight and then they constitute another set of indicators that's level two and then they're going to a third level. Again, there is also a different weight because if you take a very specific catchment area for example a warada how did this one component of it. There is also education there are also other sectors. Each of these have their own rates. Again we dig down into the highs we have the five pillars and each of these have their own rates and that's where we have these inside indicators inside indicators or in general what we call composite indicators. Let's just again to show you how extensive the set of indicators are. It's quite long and basically you have that element and then indicator and then indicator the hierarchy is really complex. So that's just where that transformation but interestingly as I said because we are trying to have put no limit on what sort of indicators or data you want to collect and we are already collecting data for example related to Ministry of Agriculture. For example some quintiles of vegetables produced quintiles of biophotified root crops produced basically food production in a very specific catchment area. This one is about Kavele's monthly report Kavele is really clearly one level below a district. Similarly we also have something about again another data in terms of agriculture specific to nutrition household food production something related to again food agriculture nutrition all this again part of within the Ministry's HMI system why because there is already the infrastructure they installed was already in place. Again something similar to just to give you an idea again related to nutrition and in fact the advantage of this is you can kind of cross analyze together with the malnutrition data you have in the HMI against the food production you have in the country and you can see where you have the high food production and you can see whether you have low malnutrition and then kind of say whether you are doing good or bad. Then probably some final words again when you look into this multi-sexual engagement having a Ministry of Health alone cannot solve the challenge I mean it's a multi-sexual engagement others need to come on board. Again because there is already an existing install date there is already the chance to in place and the chance to unless you to collect data of your need you are quite flexible to do that we need to kind of build into that. One good example we have here with the case of Ethiopia is Ministry of Health is kind of leading by example they are sharing their experience they are sharing their resource for example within the HMI they are also collecting food and production food and agriculture related data and they are also guiding other ministries to kind of follow their footsteps because often the challenge is for the other ministries Ministry of Health is already doing it why not you are not doing it I mean that's something that they can't really say no because the tools are already there for example with the HISP Uganda case HISP Uganda the local team is already there to support the kind of jumping and then support the office of the prime minister and the national planning authorities. Again probably this is this final slide is for us developers but I have two heart from the HISP center at the global as a DHS developer and also part of the HISP Ethiopia team. This multi-sector multi-stakeholder engagement is a new norm for DHS too and then what particularly we are kind of dealing with layers of items for example the case of Ethiopia we have composite indicators indicators inside indicators that means the URN case of indicator indicator group indicator group set is not really enough we need to step up beyond that and kind of solve into that and the case where Andrew presented like we will standard data entry app we only have one column we don't have this baseline target and actual for that we have already an app that we can share with HISP Uganda but again we have to kind of make it into the global core where it becomes pretty generic. Again when we look into these this typical national development programs national planning and they're usually a multi-year engagement and when it comes to DHS too the maximum pay to have is one year it's just a year for example for Uganda we have a five year it could be a three year so that means again we need to do something for the parrot but again also for the indicators we have 20 programs and then we're in the programs we have sub-program we have objectives outputs outcomes goals the list kind of the depths kind of goes down again indicator indicator group indicator group set the same as data element data element group and data element group set is not enough again this is something for us to take as a homework and then come up with a solution and in fact my final say is because this multi-sector multi-stakeholder engagement is the new norm uh there will an existing install but in the country uh we are the developer as a developer has to kind of step up and you also have uh some responsibility I mean to solve this as a network and I would say that's our responsibility to respond to this new emerging challenges to DHS too thank you that's pretty fast with so many questions now but we have one more presentation before we open up for questions so please hold on and I'm gonna call up Allison and read it from Evidence and Research Coordinator at FOS Feminista and then we have questions okay okay hi yes thank you um hi everyone um it's great to be here as Kristen mentioned my name is Allison Andrade and I work as the Evidence and Research Coordinator at FOS Feminista and today I'm going to be sharing a tool we created in DHIS2 called the Advocacy Tracking Tool and we've developed this tool in order to facilitate the meaningful use of advocacy data to support decision making and to promote sexual and reproductive health rights and justice so to begin I'll provide some information on who we are um FOS Feminista is a new international feminist alliance formed in 2021 and we work with over 220 organizations um local autonomous partners across 40 countries from around the world and together we um work to carry out our mission to ensure universal access to sexual and reproductive health care um advance comprehensive sexuality education and to advocate for sexual and reproductive health rights and justice we are formed from the merger of three different organizations international Planned Parenthood Federation of the Western Hemisphere region um International Women's Health Coalition or IWHC and Change and together we have over 70 years of experience working to promote the health and rights of women girls and gender diverse people and we also have over 10 years of experience using DHIS2 to help inform our decision making to carry out this mission so um advocacy data really spans across sectors um it starts off in the philanthropic sector goes across the non-governmental and governmental sectors and the end users of advocacy data for our alliance are the advocacy teams of our local autonomous partners in the global south as well as the global advocacy unit at FOS Feminista and these advocacy teams um advocate with governments in order to pass reform that promotes the sexual and reproductive health and rights um of women girls and gender diverse people and here you can see a timeline this is an example of what advocacy data could look like so prior to developing the tool that I'm going to be showing today um we would use the captor application and DHIS2 to track our advocacy data we refer to this data as advocacy wins which we defined as the successful approval or defense of a law policy or protocol um that can promoted sexually productive health and rights and to which our partners contributed and this data was collected on an annual basis uh and as for analytics we would create tables like this in event reports and our partners would be able to analyze their data um sort these tables by date by other fields however um we receive some feedback from our partners that this is not necessarily the most usable format for them because it it didn't really allow them to track their progress over time and we know that it can take a long time for advocacy efforts to achieve change um and also it doesn't allow them to assess the impact of advocacy on the lives of people because we know that advocacy doesn't stop when a law is passed it has to be able to make a difference for people on the ground and so here are a couple of other challenges that we identified with reporting on advocacy in general um first monitoring and evaluation in advocacy often focuses on data for donors and for international accountability and it isn't really designed for local advocacy teams in their contexts um historically data capture models have reflected simplistic narrow logic where one action directly leads to one outcome but we know that that's not realistic because advocacy occurs in a complex system and there are many mediating factors like actions by anti-rights groups or socioeconomic conditions that can influence whether or not reform is successful. Tools also to not reflect the prolonged process it takes for advocacy to have an effect and the assessment of impact is often limited to the approval of new policies and laws when we know that there's so much more that needs to happen after a law is approved and so this logic model here represents our prior model. We have on the left green representing the inputs of the philanthropic sector and the post-feminista alliance these include things like human resources donor funding in the middle in pink we have the activities and outputs of the post-feminista alliance so activities include capacity bridging knowledge sharing with outputs including events marches demonstrations and campaigns and finally the long-term outcomes for advocacy refer to government reforms. So what makes our a new tool really unique is that our model it takes into account external factors that can influence advocacy like political social economic conditions and actions taken by anti-rights movements in groups it also considers short-term outcomes which are things like the introduction of reform the advancement of reform and most importantly it considers impact the implementation of reforms and how these measures are impacting the lives of people. And so with this model in mind we enlisted the help of KTT which is a consulting firm that helps NGOs to leverage DHIs to to improve health outcomes and so at the help of KTT we developed our advocacy tracking tool and this slide shows how some technical information about how this tool was built it uses a simple structure built in DHIs to under event program it's a simple structure of just 12 data elements without registration users can view multiple entities simultaneously data entry is done using a custom form that has dynamic field labels and finally it's a custom DHIs to web app that uses HTML and CSS to display a timeline format to help facilitate analysis so now walk through some of the most important features of the tool first as I mentioned the data is rendered on a timeline which is something that partners had requested because it allows them to track their advocacy actions over time it also allows for robust tracking of contributions and impact with contributions being shown in gray on top of the timeline and impact being shown on the bottom and unlike impact which often refers to those short and long-term outcomes contributions refer more to activities and outputs so things like campaigns marches demonstrations and it's important to include contributions when monitoring our advocacy work because it tells us what works and what is needed for advocacy to be successful this is the most important feature of the advocacy tracking tool is that it allows partners to track their progress according to the incremental stages of reform by policy makers so as you can see here we have all the stages color coded users can check or uncheck the boxes to filter along the timeline we also include regression introduce and loss because it's important to learn from our failures not just our successes and to account for oppositional forces within the ecosystem of advocacy we also have defended which refers to when a partner successfully contributes to the blocking or a repeal of a regressive measure and then we have reform introduce advanced approved and implemented with implemented being how was this law policy translated into practice so that it is it becomes a reality for people on the ground our tool also has a flexible data entry form for learning so partners select an advocacy stage from the drop-down menu and then the questions that appear are tailored to the stage they select and prompts are included to encourage learning and analysis data is entered according to need so could be a support for people living with HIV access to contraception and then people users can also filter the timeline by need which helps to ensure that decision-making based on advocacy data is done with people's needs in mind and is person-centered it also features a multi-year display which is helpful because advocacy takes place over long periods of time all of the entries on the timeline are also editable so users can edit the text the stage they can upload images or supporting documentation and this allows for the app to serve as a dynamic repository of information there's also an export to PDF option which is helpful if you want to print out the timeline or if you have limited access to internet and now I'll present a brief use case on the advocacy tracking tool to make it more concrete this is an example of how our partners in Argentina could use the advocacy tracking tool to help evaluate their advocacy work as a part of the green wave movement which is the movement for safe and legal abortion in Latin America and so to provide some background information on our partner's advocacy work in Argentina back in 2005 is when they first started taking advocacy actions advocating for access to safe and legal abortion and so starting in 2005 they would submit a bill to the chamber of deputies which is the lower of two houses in Argentina's national congress and they would resummit this bill every two years for the next 13 years and it continued to fail but finally after 13 years in 2018 it passed and while it did not pass through the senate the other house of their congress that year the fact that it was up for congressional debate and that it did pass through the chamber of deputies was a monumental achievement and so we could track that here on the timeline as advanced it's an advancement under June 2018 and then over the next several years our partners engaged in different advocacy activities which we have listed here as contributions so things like marches demonstrations that really strengthen the green wave movement and then finally in December of 2021 the bill for voluntary abortion was introduced for discussion by the chamber of deputies and then in January 2021 it passed through the senate as well and the national law authorizing access to voluntary interruption of pregnancy was enacted however as I mentioned before we know that advocacy doesn't stop when a law was passed and so we have created options in the timeline that enable partners to track how they're implementing this law and making it a reality for people and so one example of this is that one of our partners made a formal request to the ministry of health in their province to have a training on safe abortion care for public health providers and so the ministry of health in that province accepted the request and they were able to hold the training which enabled people in that province to have the option to access safe and legal abortion and it made it a reality for them and finally just to conclude we have some user feedback on the tool that we've received thus far from some validation sessions we've done partners have expressed that it seems like a much needed method of assessing incremental progress and advocacy they appreciate the flexible rendering in the timeline they also expressed their appreciation of the fact that it recognizes that advocacy continues beyond the passage of laws and that positive impact is achieved only when governments create conditions for people to exercise their rights they also appreciate that it considers the impact of external factors on advocacy work including adversarial actions taken by anti-rights actors they liked the ability to include images they thought that was powerful and then most importantly they found that it was a cost effective and scalable tool for supporting learning and data informed actions because DHIS2 is a system they already use and are familiar with and so it would be relatively easy to scale up so that's all that I have if you would like to know more about the tool here is our email address and we'd be happy to answer any questions thank you thank you so much this is a very interesting presentation and I've told the different use case from the other side on it but stay on I think we're now make a bit of a panel come guys and you are Robert I mean can also be Robert if Robert still is online yeah yeah yeah yeah but please so we can send a bit of a panel because we need to to to to be more energetic um here is so so any question from the audience on this kind of new demands for cross-sector monitoring uh you know yep we already have one super need to have more more mics yes thank you so much extremely useful um very high potential and I'm very impressed actually to see the the brave attempt of going cross-sector the cross-sectoral analysis two questions I have on the frequency of data updates the data systems for Rwanda Uganda and Ethiopia the fact that you are measuring data at a very granular level the sub-national level even what is called the cell level um for instance my education comes from the SDGs the SDGs are 230 say indicators I'm just speaking about the global policy instrument level 80 plus of these indicators come from household surveys and you know the issues there that we don't have the frequency we want so just if you can enlighten us about the frequency of of data updates at that level and then the example from a feminist at the first one means it's incredible you're actually doing uh policy tracing analysis uh this is the Tanahashi model you have managed to put it in a you call it a timeline but you're actually doing a policy analysis along the way so I think you should document that because countries will eventually want you are doing it as a global analysis which is different but at the country level we want to see the effectiveness of policies so you have a very high potential to actually demonstrate that by some comparative analysis even between two three countries pivoted in say um abortion care whatever it is that takes your fancy in this but fantastic work thank you so much for the chance to hear it who's taking the challenge first I can't thank since I have the mic no I mean that's a good question and it kind of depends on the under different use cases for example yeah uh the kids with Uganda even with Ethiopia those the targets they are collected more like on a yearly basis but then the some of the the actual performances they are on a quarterly basis but for example when it comes to Ethiopia we also have a monthly data so we have quite a range and uh in fact one of the questions we have for example from Uganda was we don't want to put the targets on a yearly basis so we we want to complete once for five years but again uh technically we don't have a problem but it's more like uh how often really we are going to collect that data so yeah it kind of depends from context to context but technically we have the solution from because we are using the out of the box DHR solution it goes from a daily all the way to a yearly and in fact as I put on my final slide we need to go beyond that and come up with a multi-year kind of uh frequency yeah and yeah I think the same applies to Rwanda we we have monthly we have quarterly and as I said these are the uh these indicators come from the interventions so it means they are lower level interventions that are turned into indicators that are collected on monthly and quarterly but again there is one report I was showing regarding the situation report that is daily yeah thank you daily here yes yes yes I just want to confirm that whereas the demonstration shows that it is annual but we are able to report quarterly considering that resources are veiled on a quarterly basis and some interventions are implemented only when resources are veiled and that is when you can probably report for them on them but we can be able to do quarterly we can be able to do half year and then annually thank you any any other questions from the audience yes there is there's Hamul was from promising to run thanks so much um yeah maybe a question for all of you actually um how were you able to uh to decide who are the users of the people that are responsible for gathering this this information um is it the is it the the people that work for different interventions that are responsible for for collecting this data or is it or do you use protocols that already exist for example you know through community health visits through an moh how was the process you know looking like for you to decide what kind of workforce and what kind of users you're gonna deploy to be able to collect all this information across sectors maybe Robert want to start will you Robert yeah well I can start thank you yes uh each of the entities in the government of Uganda has got um has got a personnel that are responsible for monitoring and evaluation there are units in every entity that do monitoring and evaluation so each entity contributes to a particular program and they are in their responsible to report on specific indicators depending on the mandate of the respective entities so that is how we determine which entity which users report on which specific indicators so it depends on the entity and which program it belongs to and then the sector yeah I mean uh that's very true but just to add on to that especially when it comes to this multi-sector the challenge often is who is going to see our data that's because there are multiple stakeholders and uh and we are relying very strongly on DHIS data sharing setting and the confidence we kind of tell to the users is that no you are free to decide on that because the HIS will let you control who can do what in the system so uh yeah I think we have considered that as well. Just we've been talking about you know that way we have used the core DHIS too so when you look into the system design like the data sets they are quite multiple it's not that it's one data set for everybody so as he was talking about you know it's not one data set that I go and report where I'm reporting so we have this mechanism that you design a data set for each of the different sectors and then they are putting on that and then you can be able to control the access as as required by the different sectors because some of the data is very sensitive and so it has to be really shared very well which DHIS took already providing terms of access. Any comments from Rwanda? Yeah actually uh the first pilot uh from Rwanda on one of the province eastern province we wanted them to see the data sets uh opening the data set for everyone then you pick your data set your sector then this second revised one they told us no you just assign our data set we don't want others to see our data set the new revised reporting system now we are assigning these modules based on the thematic area it means if you're from agriculture you only see agriculture related indicators you will not see health so that is how we are doing it at the district level where we have a bigger number of stuff but at the sale level we have a certain number of few stuff it's only one stuff that will be reporting to everything yeah thank you. Okay thank you very much um Aluka from Nigeria um you're taking the question out of my mouth but I didn't know the approximate was going to present something like this today because yesterday we started the discussion and he said wait if you want to know more you come to the um presentation we have a new government in place and one of the key things that we wanted to do before my comment was to set up an agenda for we started like a pilot we call it agenda setting for one of the governors to be able to see how we monitor some of those things so I think this is a very useful product and we'll be getting back to you especially the assessment that was done in Rwanda and how you are able to conduct indicators upon indicators and be able to come over with something I think this is a very good because my question was going to be on the security of it because you know the ministries they wouldn't want anybody to see their own data set or whatever so you've already clarified that so I think it's a good product so I will ask the question again I want to go to comment the initiative that you have done and please feel free to let us have an insight into what you are doing so that we can also develop that thank you. So this is just an example also I see you so somebody have to run up there any volunteers running grant is running so while the grant is running and this is just an example also how innovation are shared you heard Abhiyat was involved in the Uganda Andrew is whispering in my ear I will actually borrow that data you know capturing true need to be done in the same way so this kind of sharing or innovations across is actually very is the strength of the network it's not necessarily a steaming from the same place but sharing as long as we hear that this is done then it's shared so even though Abhiyat was involved in many of them but not in the random one but of course sharing solutions yep yeah my name is Precious Piri from Malawi this is very interesting um you know we have this one-health approach one-health approach where we don't look when we look into epidemics it's not only one sector like health you would find also corrigan from agriculture you know we have these other zoonotic diseases so um you would like also to see or to compare to say if our colleague in this sector they are highly performing there's likelihood of any positive impact to our sector in a reduction I would give example of lebes you would find if we control in agriculture about animals on lebes it will impact on health when it comes to treatment or maybe to give vaccine and also now we are looking at other diseases related to food maybe food poisoning you know there's also that kind of impact from other sectors so as you said that when you are presenting you would allow only maybe one sector to be reflected other than other sectors but at the local level earlier level you would like to support each other to say look this is what is happening but we could also see from our side that as these are increasing all our indicators are not doing very well but there's also an attribution from your sector so now how do we balance this so that we can have like a joint approach to some of these epidemic control given that he's watching one your sector looking at those indicators thank you it was I mean it was I think almost a comment but yeah but I think it's more of a question in terms of you know how you bring I mean we've talking about the data sharing and what and I think you are trying to say to say that there is I mean we don't need to limit the data sharing because this the analysis really needs to to appear to the lower level I think it will depend on each country you know data sharing policies and guidelines this will find that you know in some countries the data sharing across sectors is quite limited and however much the system can support it the policies and the and the workflows don't don't apply but it's it's been very interesting when it comes to you know the cross sector especially when it's a government led as a as Mr. West was sharing here is there is a level where they want to see data across all these sectors and they have been doing it only that they have not been having a platform that is easily accessible by the different sectors but here DHIS2 is allowing them to be able to go online and probably look at the sectors and that's something that we need to deal with in terms of you know access because accessing it in a book in a printed material is different from the online so that's that's where we are going but it's very exciting that you know governments really want to share the data cross apart maybe from the finance where you know it may be a little bit tricky but when it comes to the one health when it comes to related sectors I think this is what is being promoted and that's what DHIS2 is clearly bringing up out thank you Yes I have a quick question to Allison so the thing is now I think Amani from WHO Sierra also highlighted while we are doing especially this cross sector things and monitoring and now the next requirement is for us to visualize and timeline visualization mind you like has been a really good tool especially when especially like when we wanted to do even research publications during COVID pandemic we always wanted to show how things were progressing right so with all that like and also like in the previous presentation previous session we were discussing about DHIS2 as a core and the extensions you don't have to answer it just now but like have you considered making this app that you have created maybe open source so kind of making it more generic so that others can really utilize this timeline visualizations? Yeah thank you for the question so I think that is ultimately the hope however it's still in its very early stages and so we still have to iron out the bugs and make sure that it's ready to share we have to pilot it and everything but definitely feel free to email us for more information and our hope is that one day once it's ready we'll be able to share it with everyone. Thank you time is up if there's no more questions from the audience or from the panel the distinguished panel any last comment from you guys I mean this is actually something that I think we think will be you know an increasing demand in the future because you can hear that how the world is spread through countries when it's when you see it's possible to do this cross-section monitoring of progress, STGs, KPIs. Prosper you have a last comment? Yeah the last comment I have is as we implement I think this is the sector where the investors have not been coming on the table so it's quite challenging for us to be able to attract more funding to support this. We need investors in this. Mr. Wasashi had you know like you know the governments also need support to be to roll out these systems and implement but one one important thing that we have learned I think what we're seeing in Uganda is that once this cross-sector implementation comes across it also attracts other sectors take on their own systems so like we're talking about the health now the education so other sectors are going to be coming and they want their internal systems to be on DHS too so that they can be able to push data directly into the DHS too today we've been talking about with the commissioner of health who is responsible for putting into the this OPM system and they're saying now why should we be now double entering we just need to connect our DHS to go health to automatically push data into the into the the M&E the NDP monitoring system so we see a lot of potentials for you know these kinds of collaborations and you know other sectors also taking up their own systems thank you. And another you mentioned it agriculture I think another open coming sector that is utilizing DHS too then for open beta 7S is agriculture and we have examples from Malawi as you mentioned and we have heard it was this presented last year in a no-conference and we will present this year as well I think okay thank you so much for voting on which so thank you everyone for attending this uh to be continued discussion we will have mainly with very continued this discussion on Thursday morning so transfer um okay we are finished yeah this is finished now. That's the end of the parallel sessions for today um I think there are now just expert lounge sessions out in the community and we're going to try and capture some interviews with people as well so if you would like to tell us what DHS 2 means to you we'll be outside in the courtyard in five minutes thank you very much and if everyone online that's the end of the session and the end of the day so we'll see you all tomorrow right and early thank you very much. Hello hello. No, I was just doing a little tour and tomorrow we're going to split again a little bit around. Yeah so what you need to do is