 Hello, everyone. Good afternoon, good evening, or good morning, depending on where you're joining us from. Welcome to Engineering for Change, or E-4C for short. Today, we're pleased to bring you this month's installment of E-4C's webinar series, focusing on how a data-driven management operating system can help eradicate global poverty. My name is Mariela Machado, and I'm program manager here at Engineering for Change. I'll be the moderator for today's webinar. In the webinar you're participating in today will be archived on our webinar stage and our YouTube channel. Both of those URLs are listed on the slide. Information on upcoming webinars is available on our webinar stage. E-4C members will receive invitations to upcoming webinars directly. If you have any questions, comments, and recommendations for future topics and speakers, please contact the E-4C webinar series team at webinars at engineeringforchange.org, as seen on the slide. If you're following us on Twitter today, please join the conversation with our hashtag E-4C webinars. Before we move on to our presenters, I would like to tell you a bit about Engineering for Change. E-4C is a knowledge organization, digital platform, and global community of more than one million engineers, designers, development practitioners, and social scientists who are leveraging technology to solve quality of life challenges faced by underserved communities. Some of those challenges include access to clean water and sanitation, sustainable energy, improved agriculture, ICTs, and more. We invite you to become a member of E-4C membership of E-4C. It's free and provides access to news and thought leaders, insights of hundreds of essential technologies on our solutions libraries, professional development resources, and current opportunities such as jobs, funding calls, scholarships, and more. E-4C members also enjoy a unique experience based on their side behavior and engagement. Essentially, the more you interact with the E-4C side, the better we'll be able to serve your resources aligned to your interests. We invite you to visit our website at engineeringforchange.org to learn more and sign up. If you're interested in learning more about tools and enable data collection related to water systems, we invite you to explore the E-4C Solutions Library after the webinar. An example of the type of tech that you'll find is the MWater Explorer mobile app, which allows users to map water resources and sanitation facilities and report functionality, water quality, or sanitary instruction reports using standard forms. The app allows the user to test and water source, take a picture of the results, and upload them to an online database for other users to see and use. The full report in the Solutions Library provides more information about technical performance, compliance with standards, academic research, and user provision models of the system. All of the information is sourced by E-4C's research fellows and reviewed by our community of experts. And it's available to E-4C members free of charge, so be sure to take advantage of this resource. So a few housekeeping items before we get started. Let's practice using the Webex platform by telling us where you are in the world. So let's do that right now. Let's hear where you're all coming from. In the chat window, which is located at the bottom right of your screen, please type your location. If the chat is not open on your screen, try clicking the chat icon at the bottom of the screen in the middle of the slides. You can use this window to share remarks during the webinar as well. So let's start by hearing where you all are joining us from. So just type where you're joining us from. There, I will start as well. London, UK. We're joining from New York. Seattle, Washington. Vienna. Welcome, everyone. And if you have any technical questions, just send a private chat to Engineer for Change admin. During the webinar, please use the Q&A window located below the chat to type in your questions for the presenters. Again, if you don't see it, click the Q&A icon at the bottom of the screen in the middle of the slides. If you're listening to the audio broadcast and you encounter any trouble, try hitting stop and then start. You might also want to try opening WebEx, opening a different browser. If you see webinars, qualify engineers for one professional development hour to request your PDH, please sign in and go to your member dashboard to access the PDH form. Great. So let's get down to business. I would like first to take a moment now to tell you a bit about our presenters today. First, we have Annie, I hope I said it right. Annie Fury, who is a behavioral health scientist specializing in management systems, behavior change, and global health. She's the co-founder and CEO of Mwater, a tech startup that leveraged real-time cloud-based management tools to catalyze the work of health professionals and governments around the globe. Dr. Fury is the mother of three children and lives in New York. To our next presenter, we have Petri Audio. Petri Audio is a product manager for Mwater, responsible for the ongoing development of the mobile data management platform. Previously, he was a system advisor for planning, monitoring, evaluation, and reporting at Water Aid UK, involved in rolling out a global MIS, as well as mobile data collection processes. So without further to say, I will pass here the mic to our presenter, Annie. Great. Thanks so much. Thank you all for your time. We're very grateful to have the chance to talk to you today. We're going to be speaking about a general overview and introduction to the Mwater platform with a little background about why we took some of the decisions that we did in creating it. The first thing that we'd like you to understand is our core values and our motto that drives everything is what gets measured gets done. And so our approach as a nonprofit organization working in the world's global poverty eradication effort is to measure better to help all of the stakeholders from governments to NGOs, to multilaterals, and academic researchers approach this by more efficient and more collaborative measuring. The center of the platform and what we're going to spend most of our time talking about today is surveys. And so I want to explain that for an NGO, surveys are M&E. For an academic researcher, a survey is your instrument. And for governments, surveys are the engine of all of governance. They're actually how the management gets done. So you might think of the health worker as being the furthest reach out from the central government to the communities. And the health worker does his or her job by conducting basically a survey. They go house to house and check on how many children are there. Is there a new baby? Is mum able to breastfeed? Is there a hand washing station? And they then send that survey to their supervisor. And their supervisor creates an assemblage of surveys as well. That is the result of the surveys to report up to the central government once or twice a year. For the first 74 years of the aid industry, this was a process that happened on paper. And this is the main reporting is what I'm showing a wall at a healthcare facility in Tigray, Ethiopia. This is the reporting on vaccination rates. And so what we did was we took this very efficient effort and tried to make it efficient and actually sharing the data further. In the more developed countries, surveys are also how work gets done. You might be familiar with the checklist manifesto. It's a book about the effectiveness of checklists, which are in effect surveys for everything from flying airplanes to nurses being more efficient at treating their patients. So what we did was take the paper-based survey interface that was so well understood in the international aid community and turn it into a digital interface that could, the surveys can be done on a mobile phone or a tablet. It's a next billion rigorous technology so it can handle working offline or online. And as soon as the person's back-end service, the survey syncs with the cloud. And everyone that has permission to see that data from the managers to the stakeholders to the central government or if there are various NGOs within their own NGO, they will be able to instantly see the results of this survey. So it turned what was a once or twice a year understanding your data process into an instant interactive process. This is a very quick way to say how over the past six years we grew this platform to include over 45,000 NGOs, governments, academic researchers and local community organizations who can all work together because they share this relational database. They can collaborate as much as they want or they can keep their data as private as they want in their data collection work. So basically we've tried to create what is an operating system for managing your work in low resource regions. What this looks like in practice is a mobile app called Surveyor. You can use it as a web app at surveyor.inwater.co or it's a free download in the iOS and Android source that works on and offline to communicate with a data management portal and you can see the portal at portal.inwater.co. What we encourage people to understand is the platform is there to help the longitudinal management of stable sites. These sites might be water sources, water systems, healthcare facilities, schools. We can then map those to where they can then be surveyed against over time creating the opportunity for longitudinal management. We can also map them to each other. So a survey about a healthcare facility and a survey about a water point near the healthcare facility can be used together to understand how much access to safe water is functionally there for healthcare facilities. The surveys themselves can be attached to a site but they don't have to be. We encourage the process of management monitoring to include physical locations. They can also be attached to a site privately or a geographic point privately without making a site by just using the GPS question type. As you update the status of your point over time, if you're managing, say, a water system, a utility with its various water points, multiple surveys over time are used to create a day-to-day management system instead of the old-fashioned project model of now and then sending someone out to check how things work. The sum total of this is a workflow that we see works well for management. So as well as for NGOs that are doing very many and reporting to donors. You can see how if you're working in the government's frame of mind, you can use the same system with some slight changes. And if you're working from an NGO perspective or an academic perspective, you can also use the exact same system. Over time, we've grown very fast, grown very exponentially to collect about 150,000 surveys a month to map about 60,000 new sites a month, but more importantly to update over 100,000 sites per month. So we're very happy that the growth of the platform is taking off in this exponential way. We also hope that you all will jump in and try it out and share this platform with your colleagues because it is a free platform that becomes more valuable over time with more users. So now I'm going to introduce you to my colleague Petri who's going to talk more about the nuts and bolts of how this actually works. All right, thanks, Ani, for the good overview and hello everybody. Yes indeed, I'm the product manager and that was exactly what I was going to begin with. I wanted to jump in from that overview to the nuts and bolts and get you excited about the platform and show you how quick and easy it can be for any user just signing up and logging in for free to get the visualization going using the public information available. I'll reveal a brand new feature we just got out yesterday and then for the second part I'll talk about one of our larger and more exciting collaborations where we've scaled up to whole countries data collection efforts and management efforts. So quite a bit of this I'll be doing straight in the platform so I'll be sharing my screen here available. So this is me having just logged in to the platform. It's the same view as you would get. I'll just refresh because we've already got an update going and there's a number of features we won't have time to touch on today but as soon as you've logged in you'll be able to start building visualizations on the basis of information that's already there in the system and that has been shared with the world and what I wanted to just build is a bit of a dashboard looking at Guinea-Bissau. So I've gone to a dashboard so what we intend with that is sort of a punchy one page one view visualization that gives you something valuable to look at. If you want to combine many dashboards into one bigger story use consoles within dashboards you can have maps and tables and all the things you see here on the left side on a palette. So imagine this as a blank canvas that you can create to be what you want it to be configure it and then share it with as wide an audience as you like. So I'm going to drag a chart. I want to show some water point information about Guinea-Bissau. I want to show it by type. I'm going to get a suggestion to save my dashboard so that it's saved so I'll do that and now we've got our blank chart in front of us. So the next step is to click into it and it gives me the options that are available for different chart types. I'll start with something basic. I'll just add a bar chart and then I get taken to the next view which gives me all the options available to me of a data source. Okay so the system understands that I want to build a chart. I want to build a bar chart. What data do I want to feed it with? Well this is all publicly available information already. It can get quite complicated surveys as Annie was talking about the real heart of what's going on and then sites these persistent infrastructure locations. I'm going to choose the first one for simplicity water points and then it will ask me okay you want to map a water point what do you want to map about that? I know we've got different preset types and so I'll start setting the horizontal axis. Now here we get a fairly complicated view of all the possible things about a water point you might want to visualize. I think the key takeaway for all of you would be anything you see here is something that you can bring into your visualization and anything that you track you create a survey for in MWater you can bring into your visualizations and your analyses. So the complexity is there but you can navigate that. I'm just going to choose the type because I want to map and visualize water points by type. Okay so I get again completely openly something that I didn't need to ask permission for I just signed up logged in and created a view of all the water points by type that have been made publicly visible as sites in Guinea-Bissau. I'll do a bit of tweaking. I'll make it horizontal let's say maybe I want to color it nicely so I'll ask to set individual colors and set a little color scheme maybe add a little title fairly straightforward things that you'll get to grips with once you start playing with it. Let's say by type and name the series as well for completeness and then I can X out of this view and get a chart. Well that's pretty nice but if we want to take this to the next level of course we want to have different types of things to juxtapose and what's brilliant is like with many other business intelligence solutions these days if you have the same relational database all the data in the same place you can then bring in multiple visualizations multiple charts maps and so on and interact with them such that if you filter one then the others respond to that. So that's what I'm going to do next by taking a map let's juxtapose this chart with a map. So I've dragged from the left the palette a map onto the canvas on the right exactly what you can do as well and I'm going to start configuring it from the cogwheel on the right and again we're focusing on water points the key thing is if you want the widgets to interact with each other you want to make sure it's pointing at the same kind of data source so the system understands it's the same thing so we're looking at water points here let's maybe filter down to Guinea-Bissau that's what we want I'm typing here finding the country country name so if I've picked by the country name I'm able to filter because the system understands if a point is in a geographical location in the world then it must be in this district and must be in this region it must be in this country I'm going to take a tiny second here to load the list of countries there we go Guinea-Bissau so now we don't need to render all of the points in all of Africa and all of the world we can just filter down to the ones in Guinea-Bissau that's already really nice it's a good example from the point of view of having tons and tons of water points mapped maybe we'd want to make it more consistent with the type so if I color by data and select the color scheme to match what I just chose then I'll have the nice consistency between the bar chart and the map and that gives us our first layer well this is already neat so now if I only wanted to look at protected springs I can click it here for example and see all the protected springs on the map so that's nifty and click out of it or have multiple filters so this is just to give you a flavor of these are just two widgets two data points two kinds of things to look at but of course it's going to get more powerful if you're able to juxtapose it with other relevant information maybe household information maybe communities schools health facilities and we'll look at that in the example but here I wanted to share something I'm really excited about which is a brand new feature from yesterday which is population density layers for for African countries so I've gone back to the map I'm adding a new layer here and I've got this option since yesterday evening of population density now if I choose Guinea Bissau it's going to add a layer straight to the map a layer that is visible because of the sheer amount of stuff that needs to be rendered at the city and district level so we'll start seeing these points here in colored view I think when we're juxtaposing with water points that are themselves colored I'd rather have it in gray scale so I have the option to do so and here we have household information that we've plucked from the public domain from the humanitarian data exchange just reordering them to render the households first that's been derived from satellite information and census data and a big infrastructure enterprise using machine learning like Columbia University scientists and Facebook AI researchers that's now available to the public and what we're bringing even closer to public consumption and consumption of the people who who might be built in the business of building these management operating systems so here we've just taken two layers and are juxtaposing them and we can see okay this community seems to be there must be a community here based on this analysis of households and we can see that there are two different types of borehole and protected dug well by the looks of things so this is now available for almost all the countries in Africa and that's just dependent on the source data set we have and we have a nice post outlining the details of what this is and what you might want to do with this and the updating plans so it's it's pretty thrilling to imagine how this might have an impact on operational management decisions if you have rapidly changing environments urbanizing environments changing demographics and you have up-to-date population density data being updated every three months currently and possibly more more frequently in the future and and again this was just something that you could go right after this call and this webinar and do yourself and and look at a look at a juxtaposition of data that's effectively never been looked at before this was just released yesterday and nobody had the time to look at guiney-bissau population density data and this water point data here so and that's how easy it is granted I ran through it fairly quickly but we do have documentation here up top in the help area and yeah the sky's the limit with what you'd want to do if you then wanted to share this with your colleagues with anybody else we've got a share link that allows you to create a shareable link so that people don't even need to log in to see it they would just take the link and paste it and people can follow it and see this so there we go this is the first part I wanted to talk about which is how to get started and let's look at something that's gone way beyond this when it comes to to stuff of actually using it I'll present from here because we've got the gift so this is a collaboration ongoing in Malawi with the Climate Justice Fund Water Futures program technically supported by the University of Strathclyde in Glasgow and it's really thrilling because the ultimate aim is to establish a national level wash data management process so not just an NGO's internal work something like that but something that really goes and covers the whole country and here on the gift on the right side you see when when mWater became the tool of choice for collecting data in 2017 you start seeing the big expansion in data collection and how the platform scales up to support all these points as you saw in Guinea-Bissau there's quite a few so just a few points about what this is it's a long-standing government level collaboration between Scotland effectively and Malawi the Climate Justice Fund has been working in Malawi since 2011 I think the history goes all the way back to Dr. David Livingston a few hundred years ago and we've come on board in 2017 where the CJF began assessing every rural water point across Malawi as well as potential risks to water quality such as sanitation and waste sites and a new development that I'll talk about is that in late 2018 in a collaboration with the government of Malawi the CJF and its partners began developing a decision support tool for rural water supply investment using using mWater as the digital interface layer and here we see a few of the partners involved and it's exciting and very valuable from my point of view that this is a government level collaboration it's absolutely key to get government on board whether what technology you have so again jump soon to an interactive portion of this but here I wanted to demonstrate even further the idea of what becomes possible and how you're able to ask better and better questions and make hope to make better operational decisions when you've got this one shared database of different kinds of data juxtaposed with each other okay so hopefully everybody's aware of the SDGs SDG 6.1 on water and and that's what part of a smaller part of CJF has been to do household level surveys to establish the SDG 6.1 service level and let's look at this layer here where all you see is households households mapped by their service level and of course you're going to start building a picture well okay if I had ten thousand dollars to spend on an intervention where might I go well you see the the surface water level service levels here on the bottom left that might be the key area of intervention maybe bottom right when you've got dense population maybe you'd want to consider roads and where it's easy to access so there's some yellow limited service ones just by the roadside here on the top and that's what kind of questions you'll be able to see if you're just looking at a set of household surveys well that's good but what would happen if you start juxtaposing things so here we've added just the locations of water points that exist and we'll start getting a more granular picture so again all in and water so we discovered this area on the on the left side where there's low coverage there's a seemingly a long way to go to get to a water point and same at the top there in the yellow area maybe the reason they have a limited access so limited service level is because there's just no water point nearby so that refines our image our thinking our decision-making process from from just having that one layer beyond that since we were just looking at the locations of the water point shouldn't we also in an ideal case have an up-to-date information about how are those water points working are they given you know it's one thing having the infrastructure there it's another thing actually being able to get reliable supplies of water from it so here we've got that layer refined with blues showing functional yellow partially functional red not functional so we're discovering these we're discovering these condensed places of dense population here where there seems to be a non-functional water point and knowing that rehabilitation is often cheaper than building and drilling new water points maybe this is now the right place to decide to intervene or right here but it's far from the road so maybe this is another option so again these discussions and these decision-making processes get more refined no water point here a non-functional here but there is another one decided that works so you're able to make this more nuanced analysis and then you can keep going with this and this is what the decision-making tool in Malawi is doing has tools okay that might make an impact and the level of the school primary secondary is something else this school maybe it's not so important if you've got nearby alternatives for example here but but this one has a school only one water point and a community next to it so maybe we're honing in on this or this school so so this is just to demonstrate all these things you could keep going and going depending on how you your process is set up and what data you're collecting but but this is getting really exciting with the decision support tool and not just to the point of making that decision but also following up on it so with mwater it's possible of course to keep doing those longitudinal surveys and map by different time areas time zones time dates and here we can see what the situation was at the household level on the left in terms of drinking water service levels being quite biased towards limited and unimproved and then after intervention here having this water point built visiting maybe slightly different households because the household heads weren't present and so on and seeing a much different picture so that gives us some empirical or gives the CJF program some empirical evidence to say look this intervention really did make a difference and we can we can say that from many many households having a more improved sdg service level so so i think this is a really exciting example was possible and what's also nice in the few minutes i've got remaining is that there's an interactive console that's open to all of you to play with as well that we'll share um with a number of tabs so remembering consoles are a place in mwater where you can bring together as many tabs dashboards tables and so on and maps to build one coherent story and and this is kind of looking at what we just did maybe starting from water points and juxtaposing some drinking water service levels so this has been filtered down to be west of uh of zumba and it's rendering the rendering the drinking water service levels so we can do and you can do the same kind of exercise and and think okay well what uh what does this tell us in terms of where might we want to invest and you can imagine the government really being able to do a lot if this data when this data is properly adopted into decision making processes and beyond that we can we can layer some schools as well might be in my laptop uh internet here acting up a little bit um okay that we're coming so just overlaying all of the other tabs as well show whatever is most useful so it's one thing knowing um that the water points there you might want to understand seasonal variation so of course being an academic institution University of Strathclyde can be diving quite deep into technical reasons of failure and and contextual elements which can be very exciting so here we see a a school smack in the middle of a cluster of population but all the water points seem to be working so that situation is good except north of this road so if I just look at this part of Malawi for the first time with the data available I'd start thinking okay well why this seems really good um and but as soon as you get further away from the school further away from the main road or further north here and the situation isn't so good maybe there's a case then to use um use this data to lobby lobby government local government to make an intervention here and so on for all of Malawi effectively depending on where these drinking water service level surveys are done idea certainly isn't to do to do everything right now in terms of that but um as I said this link is part of the slides and you'll be able to to view all of it and explore and this was presented a couple of months ago already and and the process of course is going on with solid commitment for for many more years and a handover to government in the pipeline so much exciting potential here um but I think that's all I wanted to share uh explore right now so I'll hand this back over to Yuanyi there we go all right thank you so much I think an important thing to point out already one of the questions I that I um that I talked him through is it just is the lot this is a fire hose and so one of the important things to point out is that we have featured dashboards available for you to look at and duplicate and begin playing with changing the data sources yourself so there's two ways for you to jump in and one is to go in design a survey deploy it to yourself to your organization's users we see a lot of organizations begin just with HR surveys did you get to work at eight o'clock you know spill out a survey when you got in and when you left just start making surveys start learning to drive every part of your management workflow with data and then they it grows very fast and we also have this advanced help library you'll see the help button at the top of the portal that has a number of tutorials videos and dashboards uh walkthroughs that can help you with most of the aspects of the platform the survey interface itself is designed in what's called a what you see is what you get interface that means uh you shouldn't need to know advanced coding to use it it's about the level of fluency that is needed for google docs to be able to use this platform one thing I also wanted to correct on myself that that I wasn't clear to say that the portal does require you to have an internet connection to work it can handle shoddy internet but it does require you to to be online uh we recommend if you're in an area with low quality internet that you do your your data management in the portal in the morning um so just getting back to slides let's see there we go um let me just bump through these slides real fast sorry we wanted to make sure that we uh we talked about one more example the the motivation of the platform design that we have is to try to increase efficiencies and let everybody work together to work faster and to catalyze people's progress the idea is especially in water if everybody spends as much money as they have very well right now there's still not enough to meet the sdg by 2030 so we've got to be finding more efficiencies and making investments turn over more times and one of the ways you do that is to begin sharing your data collection environment and let me show you what that looks like functionally so this is a data console a console is multiple dashboards maps data grids or pivot tables that you put together as one m is as one data management workflow of all of the data that you've collected through your mapping of the sites and you're conducting of the surveys this console is run by the government of Haiti who's also one of the countries that has taken up the platform for national level monitoring this is to communicate to the NGOs working within Haiti what the government's priorities are they're trying to bring everybody into the same page as to what what we're working on and let me show you a map that they're sharing with each other you can see these data layers that we talked about that this is a population layer the water points are then mapped by size of 500 meters access because that is the government's functional definition of access and then whether they are potable by having met the the standard standard for safe drinking water with the in water test or other water quality test and whether whether they are functional is also denoted by color so if you look at the map in this way the government and the NGOs can work together to make that really critical decision of a more efficient work in aid which is where to spend the next dollar you can see where there's the most population but the least safe access or where there's the most distance access but the least functional access might change your strategies of how you're actually working to to manage this water system and then one other this way one other layer that we can even add to this is groundwater the groundwater potential to even help you make your decision based on if this is a really important place that we need to meet it has very little access but it's the hardest to reach by by boreholes we definitely want to look at a pipe system there right one of the things that's next for in water is pipe systems we're working with the government of Haiti to to to release now you can map water systems and you can map the water points within their components and we'll also be adding a piped management features they they can help people make decisions based on size of pipes location of pipes the the angle of pipes to better manage utilities and small water systems as opposed to what might have been our previous focus which was very heavily focused on wells and singular water points now if you look at this environment that i've shown you this is the government's view of the data set but here is one of the larger NGOs working in Haiti called Haiti outreach and they've represented the same data set in this very donor friendly way they want to communicate to their donors how effective they're doing it at spending the donors money so you can see how collaborating with the same relational database helps everybody meet their needs and yet they don't have to be working desperately to to meet those to meet those needs the most important part of the data collection cycle for an NGO might be to communicate the the effective and safe and transparent use of the donor's money so they're able to do that while the most effective part of the data collection cycle for the government is actually decision making and organizing of of the stakeholders including those NGOs they're just returning to the slides one more time we want to make sure that you know one of the our biggest advance in our next step that we're moving toward is called solstice many of our users came to us and said we're working in water and that's great we found you in water but we're also doing schools and healthcare facilities and when i take this to my managers they're not very happy with the outcome that i'm recommending to use something called water so merely for the point of having a brand agnostic title we've created the sister brand called solstice we're doing it's in soft beta launch now we're doing a hard launch June 21st on the solstice our motivation is that the solstice was the first data points that humans monitored to understand their world and so this is a data centric management platform that's made for all sorts of aid industry and government focused management approaches we have a lot of emerging interest in solstice for emergencies for we've been very involved in the Cox bizarre refugee camp for example where checking on wash in healthcare facilities is as important as checking on stock outs in healthcare facilities you can use the same platform for both we have a lot of interest in schools in agriculture so solstice the app is coming soon the platform is already available for you to play with at solstice global we're we're looking forward to growing out what we have is the global indicator library which is one of the ways it's a wikipedia inspired library of data sets and their associated indicators to help people learn even what to measure when you jump into the platform so we want to give lots of time for your questions so we're going to go ahead and finish our presentation now formally but we continue to be able to answer your questions with some demonstrations if you if you want to jump in with more questions that you might have excellent thank you Annie and Patrick that was super insightful and we have a few questions here so start with the first um the tools you presented seem to be very powerful but also a little overwhelming is technical support available for NGOs who would like help in setting up reports and dashboards the the quick answer is yes absolutely it's a little bit more complicated if you want free support we try to provide as much free support as we can in the in the help button on the platform but we do also charge for training and I can provide one day or a week full of training we we make the money that supports the platform off of customization and training so we we certainly like for people to write us into their funding if you're doing a funded program to try to include and in water training we think we're able to make your data collection process much more effective if you can include us at that level because we also help you bring in legacy data so that there's not a hard stop and end to when you began using the platform and we can also help you align your data with national and international indicators which helps everyone continue to work together more effectively great um the next question is how is currently or recently updated data differentiated from older data in the tool and database so Petri maybe you can talk more about filtering sure uh yeah absolutely so every everything you collect every survey that you submit has dates down perhaps to it and everything that you collect in and water becomes something that you can filter by so we've seen that bit in action but I could share my screen a bit if you like but basically either you use the time of submission of the survey this is when we received or you received the data from the field or you can add a date question to the field so to the survey itself and then whatever you have there you can bring into a filter you can use it as an axis in a chart so like show by by quarter show by month the progress for example functionality or we have some interesting stuff with sensors which bring in daily data and you can see the daily data over time how much volume how many hours of use was there so it's no problem at all okay excellent so the hardest part of the mobile data collection tools is to gather quality data how do you ensure quality information and do you verify it oh that's a really great question so it's important to know that we're just the platform provider we don't do the actual implementation data collection but the technology as we've designed it has many features that make it easy for you to collect higher and higher quality data and the very low bar of that is to avoid text fields we have lots of question types and we have a big health item in our health library about just how many question types we have and so for example if you ask someone to put in the date we want you to use a date question type so that all of your data is standardized this is the low bar of making sure that you have a high quality of data the second is we we offer a secret time and date stamp and location stamp to be in the metadata under any question I like to recommend people design their surveys to have this under the first question and the last question because one of the ways you can analyze your user's activity later to see how high quality or low quality their survey data might be is how long they spent on the instrument and if you've tested out this survey to be about 30 minutes and somebody's been in five you might want to go in and do a much the more thorough job cleaning and checking on their data and then cleaning itself is a very elaborate process we allow approval stages and we have a cleaning dashboard that we build for you automatically that you don't have to build yourself to see your data's visual is visualized results in real time as they come in and this helps you to clean a survey you can reject a survey back to the user and tell them you know obviously you got the location wrong go back and fix this we offer we offer tickets or issues these are like you can when someone has a problem they can issue a ticket we like to use this for broken water points for example they can set off a series of rules so all of this is moving your management into a structure where you can tell by visualizing the data when it is an expected result and you can identify outliers straight away one of the one of the rules that you sort of follow in a data collection is the more similar reports are the more likely they are to be accurate and an outlier is visually identified in a visualization very fast and should be investigated most so I think oh and then just finally I want to say as far as the quality of the data our data belongs to the users we do not own your data you do and so if you're working as an organization I you you can decide just how many people see your data within your organization or your entire organization and you can also make sure that when you're reporting your data you can report as your organization separately from you can report as the whole world so if you have much higher data quality standards than you think others do you can only report on your data very easily got it but um expanding on that question this is like out of curiosity Petri mentioned that you also had layers of for example you know the the population you know density is this something that you guys mix them together like do you offer that on the dashboard like do you have this already embedded into the platform aside from you know the mobile data collection that that client you know might might do on their own yes yes these are these are standardized map layers that you can use to enhance the ability of your decision-making process so when we use a standardized map layers such as admin is admin boundaries is a good example of one that you can say like this is the shape of this district and I want data within this district we use that from official sources only we don't publish just anyone's admin boundaries so this would be the government's official admin boundary and then when it comes to population this is the result of a very complex and large academic effort between uh season at Columbia and Facebook to so it's also a rigorously validated uh data layer so anything that's there that you didn't collect as a data source yourself that is a map layer is from an official source got it very interesting great our next question is regarding intervention so are there any potential applications that could help facilitate facilitate more sustainable management of water points for example as a tool for local level external support structures like district governments circuit writer programs area mechanics definitely so uh first of all this is an area we're interested in growing in and the whole platform has been created uh feature by feature when a partner usually a stakeholder such as a multilateral institution or an NGO comes to us and says we love your whole platform but we just wish it did a specific interface for circuit writers and that's something that we would partner with you to build and we would write that contract that what we build for you we'll make free to the world so first of all just having said we do want improved circuit writer interface one of the things we're building right now is improved call center interface which would work very well with that I one of the recent uses that show just how these uh pieces work together that I'm very proud of is recently Cyclone and I hit uh the eastern uh southeastern African countries especially Mozambique and Malawi and as you remember from Petrie's presentation Malawi is one of the countries that has already adopted in water-based management at the national level and so due to the the you know the 845 square mile inland sea that was created by this storm biggest natural disaster to hit the southern hemisphere this year um due to the size of this storm uh many of the water points in rural Malawi were suddenly flooded and contaminated and so the government was able to use the exact same monitoring system that was in place for mapping and monitoring in good condition they sent out a survey that was to evaluate whether water point was contaminated by by flood water and if the water was contaminated by the flood water it led to a survey that was a recipe for remediating that that water point you've got something that is a very dynamic and responsive management interface that was possible because all the NGOs and all of the local communities were communicating already in this infrastructure with the central government super interesting excellent any thanks okay so our next question what technologies do you use to collect the initial data from remote areas and transport back to the rdvms servers then collection of follow-up data from monitoring and reporting to them yes there's two questions there petri maybe you can talk a little bit about so absolutely the basis of it are the apps that annie mentioned in the beginning so the the android app and the same that can run on a web browser now there is extensive offline capability there so we have the numerators who can go out into the field who have poor connectivity for their entire visit and they can preload data onto their apps such as map cache layers and where sites are and and then only once they get back to an area with connectivity does the automatic link to the cloud happen again and then there are a few additional exceptions well really the that's how it happens there's no sort of local otherwise there's no sms apart from the sensors i briefly mentioned that is a bit of a different flow and that's something we've built so that it can be expanded and expanded as a demand expands so there there is a satellite connected in the case of Ethiopia by now a satellite connected sensors that then submit the data to the third party that handles it and we get the daily summary which we then do an import of so we have a different mechanism going for that but that's one branch of it really the the bulk of it is you have the app you go to the field don't worry about being in an area of connectivity low connectivity as long as at some point you can expect to have a bit of internet got it excellent and and the part so for the do you it's the same mechanism for the follow-up data right for monitoring and reporting so you have the same offline functionality and you usually gather that in the same way correct that's right okay excellent next question we're using m water in Ethiopia and seems going well even in managing district data but government has concerns of storing the data in the cloud then having a server in country what is your experience in other countries like Ethiopia i would say this is um something that we try to be extraordinarily sensitive to uh there is a little bit well there's two nuances to this to this answer i there's sometimes people think that it's possible to conduct a data collection platform with the mobile app and just keep it in the country that's not possible your cell phone does touch other countries in its signal no matter what even if you do see your servers locally so what we offer in the case of if you have a concern in a local server that can mirror all of the data there this ensures that if there were ever a dispute with another country the Ethiopia has their own data in their country i we don't see this as a concern as much as we used to it's it's a it's growing and one reason is there were some rather rudimentary technologies i would say 10 years ago that made it very difficult for technology platforms to uh to the cloud-based meeting was just very in its infancy now cloud-based computing is very common most people are getting more comfortable with it uh it's still the safest response that we tell them if we can set up a local server uh phis2 this is in the country that mirrors all the data so that you always have to make happy yourself and no one could ever lock you out of your data got it that's uh it's a very valid concern can you guys hear me yes okay yeah it's a valid volume concern and it's moving more to the cloud so we're following up on that question where do you usually store the data in in regular projects we use amazon web servers it's all cloud-based they're based around the world and it's the same industry level highest safety technology that we can get because we're really writing on the backs of very large technology providers that have much more money and in capital to invest in security we want to make sure we have the highest level of the encrypted and safe and uh firewalls uh features that can be uh it can make sure that everybody's data remains extraordinarily safe and we have many documents on our in our help library that have to set up safe data collection and how to make sure that you're making the most of the data safety procedures we use so i would say the reason that we follow industry standards as strictly as we do is because uh industries that have more money than the aid industry are even more invested in security than we are sorry um thank you so much annie for that the last question is how many agencies or governments have adopted your platform so far so i at this point six governments have adopted this at the national level that i include at least one sector of their government moving towards national level and that's where they encourage all the NGOs in their government all the stakeholders to help them create one uh management ecosystem uh we have 160 countries represented in our user base we just uh we had 158 up until two weeks ago we just added mildives and uh in brunei so we're at to 160 when we count our users for our actual user accounts it gets a little messy because some are one office and some are individuals we have 45 000 NGOs government offices uh local community organizations and researchers represented in accounts but we look at their use and their metrics and their activity as much more of a a reflection of what they're doing and they're growing quite fast at this time last year we were collecting about 60 000 surveys a month and now we're collecting 150 000 surveys a month we know our users are growing in their management and and their activity exponentially are you there i can't hear you now maryl i'm sorry do you hear me now yes great thank you annie yeah i heard everything and thank you so much for sharing that um we're a fan of your tool so we're very excited that more and more you know countries and people are adopting with we're a fan of of data driven initiatives and you guys are driving that so congrats um great so i think we're almost at time so we'll leave it at at now thank you so much for attending um please you know be sure if you want to obtain your pda certificate using the link that i have on the slide right now on the screen if you have any questions please uh contact us and don't forget to become members thank you so much annie and thank you so much battery for your time thank you thank you we look forward to your questions please do reach out to us we're on twitter and facebook and you can always email info at inwater.co great thank you so much you guys have a great day bye bye bye