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[null,null,null,null,null,null,"A tool to implement the most suitable scenario for your organisation: which skills are needed for which positions?"]
[null,null,null,null,null,null,"Tool n°4"]
[]
["HR Pack – Program data management for Humanitarian Aid and International Development CSOs"]
[]
["A tool to implement the most suitable scenario for your organisation: which skills are needed for which positions?"]
[null,null,null,null,null,null,"March 2021"]
[]
["1.   A tool which combines roles & skills: what for?"]
["This tool has been designed to meet the needs of Civil Society Organisations (CSOs) in addressing the challenges of structuring program data management skills within a mission or an organisation. It aims to provide an accessible synthesis of the different skills related to a role (in program data management) for a given scenario. It is thus relevant to use such a tool after having first looked up the document entitled Structuring Program Data Management responsibilities within your organisation: 5 “typical case” scenarios.\n\nTo each role (also each associated with a scenario) are assigned skills and know-how that are preferable to have in order to ensure the proper conduct of program data management activities. \n\nThis tool makes it possible, among other things, to:\n• Make an inventory of the essential skills and know-how for each position in a given scenario\n• Easily identify the recruitment needs and/or the needs for building capacity among existing teams or for certain individuals"]
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["2.   Who can use this tool? When to use it?"]
["This tool can be used by both headquarters and field teams, whether by a person involved in program data management or by an HR department who wants to understand what program data management skills and know-how are required for team members in a given scenario.\n\nAmong other things, the skills sheets by role can be particularly useful when:\n• Drafting a job description, for assessing needs and describing activities and competencies. \n• Recruiting (designing a test, determining the questions to ask during an interview, facilitating communication with the HR department, etc.). \n• Assessing the need to build capacity in program data management of some staff members among a given team.  \n\nThese sheets are found to be most helpful when used in conjunction with other documents of the HR pack, in particular:\n• The professional frame of reference (which summarises the skill sets and their associated activities). \n• The proposal of organisational scenarios. In particular, you can refer to page 4 of this document entitled Structuring Program Data Management responsibilities within your organisation: 5 “typical case” scenarios for an overview of the various existing scenarios or else use this brief summary below:"]
[]
["Scenario","Projects","Organisation","HR","Analysis","Specific technical needs","Data characteristics"]
["A","Poorly articulated (in terms of data management)","Each project has its own non-centralised data management logic, serving its own purposes (no organisational needs)","No dedicated staff for data management","Simple analysis (e.g. limited to operational decision-making and reporting)","No complex analysis (such as case management)\nAd hoc and circumstantial choices","Small volume of data\nNo sensitive data"]
["B","Highly specialised in a particular subject area, not necessarily articulated in data management","Data management is a pillar of the intervention (e.g. patient monitoring) specific to the project","Existing staff is/can be trained in using the technological solution","The technological solution is central to the intervention (patient monitoring software)","Existence of technological solutions specific to the sector of intervention for specific analyses","Large volume of data"]
["C","Coordinated management of program data needed (national/multi-country strategy)","Although data needs are significant, they are mainly used for M&E and reporting","M&E team in place or planned","Simple analysis (e.g. operational decision making or reporting)","No complex analysis (such as case management)\nMobile data collection solution + spreadsheet + GPS are sufficient","Small volume of data\nHigh interoperability stakes"]
["D","Coordinated management of program data needed (national/multi-country strategy)","Significant amount of data from different sources are needed for a variety of purposes (M&E, communication, decision making, etc.)","Program data management team and/or existing/planned program data management team with multiple capabilities","Frequent and complex needs for data analysis, potentially longitudinal (followed over time)","Varied analyses of moderate complexity\nNoticeable coordination needs (e.g. partner training)","High interoperability stakes\nLarge volume of data"]
["E","Coordinated management of program data needed (national/multi-country strategy)","Data management is a strong component of a programme, which may involve sector-specific data management solution(s)","Program data management team and/or existing/planned program data management team with multiple capabilities","Frequent and complex needs for analysis of potentially longitudinal Need for visualisations with frequent updates","Wide variety of technical solutions used for complex analysis\nInvolvement of numerous external actors in data management (ex: consortium)","Large volume of data\nSensitive data"]
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["3.   How to use and understand this tool? "]
["With just a few clicks, you can display all the skills of a given role, allowing you to create or complement a job description for future recruitments, for example, or to identify potential areas of focus and/or training needs for your current staff."]
[]
["To do this, we recommend that you follow these 3 steps:"]
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["1 - Choice of scenario (defining the positions available)"]
["In the Role_Sheet tab, please click on the box C2 and select the scenario (see page 4 of the tool Structuring Program Data Management responsibilities within your organisation: 5 “typical case” scenarios) corresponding to your organisation. "]
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["2 - Choice of the position (displaying the different blocks of skills and know-how)"]
["In the Role_sheet tab, please click on the D2 box and select the position/role for which you want to display the list of skills, all those related to the said position will then automatically get displayed below."]
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["3 - Viewing the other existing positions in the same scenario"]
["Still in the Role_sheet tab, please click on the D2 box and select another position/role, the skill blocks will update automatically."]
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["Acknowledgment"]
["This publication is supported by the French Development Agency (AFD). Nevertheless, the ideas and opinions presented in this document do not necessarily represent those of the AFD. "]
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["Licence"]
["This study is made available under the terms of the Creative Commons Attribution – ShareAlike 4.0 International Licence (CC BY-SA 4.0):"]
["https://creativecommons.org/licenses/by-sa/4.0/"]

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["Please select the scenario and the desired role →",null,"Scenario:","Role: "]
[null,null,"ScenarioA","Project Manager"]
["Skills",null,"Level","Technical know-how","Methodological know-how"]
["Assess the data management needs of a project or organisation and identify methodologies and technical solutions to address them","S1.1",{"$f":"IFERROR(INDEX(synthese2,MATCH(B4,combi_competence2,0),MATCH(selection_poste&selection_scenario,INDEX(combi_poste2&combi_scenario2,0),0)),0)","v":"B"},{"$f":"IF(VLOOKUP($B4&$C4,'SF - Blocks'!$C$1:$E$43,2,FALSE)=0,\"\",VLOOKUP($B4&$C4,'SF - Blocks'!$C$1:$E$43,2,FALSE))","v":"[B]\nBreak down the different data collection and processing needs during the project cycle (e.g., needs assessment, case management, M&E, CRM, etc.)\n• Identify metrics that may cause data management complications (e.g., multiple data sources, case management etc.) so that they may be taken into account.\n\nTranslate the program’s [and M&E] data management needs into technical data management principles.  Examples:\n• Understanding that medical patient follow-up involves a particular practice and data model adapted to case management.\n• Avoiding double-counting involves assigning a unique number/code to each beneficiary\n• Combining data from different programs involves ensuring data interoperability.\n\nUse data flow models to coordinate data management activities (e.g., database update, data transfer, etc.).\n"},{"$f":"IF(VLOOKUP($B4&$C4,'SF - Blocks'!$C$1:$E$43,3,FALSE)=0,\"\",VLOOKUP($B4&$C4,'SF - Blocks'!$C$1:$E$43,3,FALSE))","v":"[B]\nMap the data management cycle and adapt it to the needs of the program [and M&E].\n\nIdentify the comparative advantages of various technical solutions and methods for all stages of data management (ex: MDC, DBMS, Analysis).\n\nConfront needs with a comparative analysis, making it possible to choose technical and methodological solutions adapted to projects.\n\nJustify technical scenarios for one or several projects.\n\nPlan and implement the deployment of a tool (collection, management and analysis) or of a working method covering technical, HR and financial aspects."}]
["Define and implement technical, methodological standards and associated procedures in accordance with the organisation’s and the sector’s best practices and standards","S1.2",{"$f":"IFERROR(INDEX(synthese2,MATCH(B5,combi_competence2,0),MATCH(selection_poste&selection_scenario,INDEX(combi_poste2&combi_scenario2,0),0)),0)","v":0},{"$f":"IF(VLOOKUP($B5&$C5,'SF - Blocks'!$C$1:$E$43,2,FALSE)=0,\"\",VLOOKUP($B5&$C5,'SF - Blocks'!$C$1:$E$43,2,FALSE))","v":{"$error":"#N/A"}},{"$f":"IF(VLOOKUP($B5&$C5,'SF - Blocks'!$C$1:$E$43,3,FALSE)=0,\"\",VLOOKUP($B5&$C5,'SF - Blocks'!$C$1:$E$43,3,FALSE))","v":{"$error":"#N/A"}}]
["Develop and influence internal and external data management practices and strategies","S1.3",0,{"$f":"IF(VLOOKUP($B6&$C6,'SF - Blocks'!$C$1:$E$43,2,FALSE)=0,\"\",VLOOKUP($B6&$C6,'SF - Blocks'!$C$1:$E$43,2,FALSE))","v":{"$error":"#N/A"}},{"$f":"IF(VLOOKUP($B6&$C6,'SF - Blocks'!$C$1:$E$43,3,FALSE)=0,\"\",VLOOKUP($B6&$C6,'SF - Blocks'!$C$1:$E$43,3,FALSE))","v":{"$error":"#N/A"}}]
["Design, organise and administer databases according to industry best technical practices (via one or several IT tools)","S2.1","A",{"$f":"IF(VLOOKUP($B7&$C7,'SF - Blocks'!$C$1:$E$43,2,FALSE)=0,\"\",VLOOKUP($B7&$C7,'SF - Blocks'!$C$1:$E$43,2,FALSE))","v":"[A]\nBe familiar with the various data formats (e.g., digital, text, single or multiple choice, date).\n\nEnter data and perform operations on an existing database (e.g., calculation, cleansing, filters, sorting, organisation and formatting, checking for double entries).\n\nDesign databases:\n• in Excel\n• with “1 to 1” relationships between tables or data sources.\n\nDesign and harmonise simple data models, using practices such as nomenclature, categorisation, setting standards. Examples:\n• PCODE (attributed of a unique code to a geographical area),\n• age group,\n• calculation of indicators in which a plurality of data is grouped,\n• having knowledge of the import-export formats of the technical solutions used, such as: .xlsx, .csv, .dta, etc.\n\nImport data into an existing database."},{"$f":"IF(VLOOKUP($B7&$C7,'SF - Blocks'!$C$1:$E$43,3,FALSE)=0,\"\",VLOOKUP($B7&$C7,'SF - Blocks'!$C$1:$E$43,3,FALSE))","v":""}]
["Support data collection processes by contributing to their coordination and the development of their protocols whilst ensuring the establishment of suitable data collection forms (via one or several IT tools)","S2.2","A",{"$f":"IF(VLOOKUP($B8&$C8,'SF - Blocks'!$C$1:$E$43,2,FALSE)=0,\"\",VLOOKUP($B8&$C8,'SF - Blocks'!$C$1:$E$43,2,FALSE))","v":"[A]\nDesign input masks or create forms via a form-builder.\n\nMaster one or several MDC tools (e.g., ODK, KoBoToolbox): configure tools for data collection.\nSupport data collection teams with troubleshooting bugs.\n\nIntegrate secondary data, import data into an existing database."},{"$f":"IF(VLOOKUP($B8&$C8,'SF - Blocks'!$C$1:$E$43,3,FALSE)=0,\"\",VLOOKUP($B8&$C8,'SF - Blocks'!$C$1:$E$43,3,FALSE))","v":"[A]\nBe familiar with the broad principles of MDC and know how to identify situations in which these tools are appropriate.\n\nHave knowledge of the steps required prior to any mobile data collection (such as the need to test the questionnaire: test protocol and validation)\n\nTrain enumerators and data-monitoring personnel and adapt to the various levels encountered."}]
["Ensure the production of graphical visualisations and preliminary analyses (via various IT tools) of quantitative data adapted to the needs of the teams according to industry standards","S3.1","A",{"$f":"IF(VLOOKUP($B9&$C9,'SF - Blocks'!$C$1:$E$43,2,FALSE)=0,\"\",VLOOKUP($B9&$C9,'SF - Blocks'!$C$1:$E$43,2,FALSE))","v":"[A]\nPerform simple calculations on Excel (averages, sums…).\n\nMake simple representations and graphs on Excel."},{"$f":"IF(VLOOKUP($B9&$C9,'SF - Blocks'!$C$1:$E$43,3,FALSE)=0,\"\",VLOOKUP($B9&$C9,'SF - Blocks'!$C$1:$E$43,3,FALSE))","v":"[A]\nBe familiar with statistical analysis and graphical representation issues (e.g., data types, aggregation of data, choice of graphical representation according to available data).\n\nApply an analysis plan."}]
["Ensure the production of preliminary analyses and visualisations of qualitative data adapted to the needs of the teams according to industry standards","S3.2","B",{"$f":"IF(VLOOKUP($B10&$C10,'SF - Blocks'!$C$1:$E$43,2,FALSE)=0,\"\",VLOOKUP($B10&$C10,'SF - Blocks'!$C$1:$E$43,2,FALSE))","v":"[B]\nApply the different stages of qualitative data analysis (such as transcription, coding, comparison of key topics, synthesis and extraction of relevant verbatim reports).\n\nTranscribe, summarise, and categorise elements from qualitative data collections.\n\nKnow how to code manually and produce a synthesis with the onset of a “profiling” analysis."},{"$f":"IF(VLOOKUP($B10&$C10,'SF - Blocks'!$C$1:$E$43,3,FALSE)=0,\"\",VLOOKUP($B10&$C10,'SF - Blocks'!$C$1:$E$43,3,FALSE))","v":"[B]\nBe familiar with issues related to qualitative data analysis (such as objectives, limitations)."}]
["Ensure the production of spatial representations and analyses through the establishment and use of a geographic information system","S3.3","A",{"$f":"IF(VLOOKUP($B11&$C11,'SF - Blocks'!$C$1:$E$43,2,FALSE)=0,\"\",VLOOKUP($B11&$C11,'SF - Blocks'!$C$1:$E$43,2,FALSE))","v":"[A]\nManipulate a mobile device to collect geographical data (GPS / smartphone…) and exploit data collected by these means.\n\nUse basic graphical representation modes (point, polygon, line, etc.).\n\nProduce simple maps on tools such as Google Earth or uMAP."},{"$f":"IF(VLOOKUP($B11&$C11,'SF - Blocks'!$C$1:$E$43,3,FALSE)=0,\"\",VLOOKUP($B11&$C11,'SF - Blocks'!$C$1:$E$43,3,FALSE))","v":"[A]\nUnderstand basic geographical concepts such as GPS format, latitude/longitude, administrative data or geographically transposable addresses."}]
["Provide support to other departments in their data analysis, usage and dissemination processes","S3.4",0,{"$f":"IF(VLOOKUP($B12&$C12,'SF - Blocks'!$C$1:$E$43,2,FALSE)=0,\"\",VLOOKUP($B12&$C12,'SF - Blocks'!$C$1:$E$43,2,FALSE))","v":{"$error":"#N/A"}},{"$f":"IF(VLOOKUP($B12&$C12,'SF - Blocks'!$C$1:$E$43,3,FALSE)=0,\"\",VLOOKUP($B12&$C12,'SF - Blocks'!$C$1:$E$43,3,FALSE))","v":{"$error":"#N/A"}}]
["Implement measures that ensure the availability, reliability, traceability and quality of data, to contribute to the quality of programs","S4.1","A",{"$f":"IF(VLOOKUP($B13&$C13,'SF - Blocks'!$C$1:$E$43,2,FALSE)=0,\"\",VLOOKUP($B13&$C13,'SF - Blocks'!$C$1:$E$43,2,FALSE))","v":"[A]\nMaster the data management cycle and apply it to data preparation and cleaning practices.\n\nPrepare for data collection: consistent naming (e.g., PCODE), attention to data types and attributes.\n\nClean up duplicate and inconsistent data.\n\nCheck the collected data: spot check, calculation, meaning."},{"$f":"IF(VLOOKUP($B13&$C13,'SF - Blocks'!$C$1:$E$43,3,FALSE)=0,\"\",VLOOKUP($B13&$C13,'SF - Blocks'!$C$1:$E$43,3,FALSE))","v":"[A]\nBe aware of the issues involved in collecting certain program-specific information."}]
["Implement change management that is focused on a data culture tailored to the needs of the organisation/project","S4.2",0,{"$f":"IF(VLOOKUP($B14&$C14,'SF - Blocks'!$C$1:$E$43,2,FALSE)=0,\"\",VLOOKUP($B14&$C14,'SF - Blocks'!$C$1:$E$43,2,FALSE))","v":{"$error":"#N/A"}},{"$f":"IF(VLOOKUP($B14&$C14,'SF - Blocks'!$C$1:$E$43,3,FALSE)=0,\"\",VLOOKUP($B14&$C14,'SF - Blocks'!$C$1:$E$43,3,FALSE))","v":{"$error":"#N/A"}}]
["Be familiar with and implement data protection procedures and practices that ensure compliance with national and international law","S5.1","A",{"$f":"IF(VLOOKUP($B15&$C15,'SF - Blocks'!$C$1:$E$43,2,FALSE)=0,\"\",VLOOKUP($B15&$C15,'SF - Blocks'!$C$1:$E$43,2,FALSE))","v":"[A]\nDistinguish personal from sensitive data.\n\nExecute clear instructions for data protection (configuration of tools, obtaining consent, execution of archive protocols, or de-identification, anonymisation, pseudonymisation, aggregation, etc.)."},{"$f":"IF(VLOOKUP($B15&$C15,'SF - Blocks'!$C$1:$E$43,3,FALSE)=0,\"\",VLOOKUP($B15&$C15,'SF - Blocks'!$C$1:$E$43,3,FALSE))","v":""}]
["Be familiar with and apply the ethical principles of responsible data management taking into account industry best practices and contextual specificities","S5.2","B",{"$f":"IF(VLOOKUP($B16&$C16,'SF - Blocks'!$C$1:$E$43,2,FALSE)=0,\"\",VLOOKUP($B16&$C16,'SF - Blocks'!$C$1:$E$43,2,FALSE))","v":"[B]\nAdopt the data protection standards applied to humanitarian aid and international development (Signal type Code of Ethics, Principles for Digital Development, etc.) and context (non-state armed groups, medical data, etc.).\n\nImplement donor guidelines for data protection."},{"$f":"IF(VLOOKUP($B16&$C16,'SF - Blocks'!$C$1:$E$43,3,FALSE)=0,\"\",VLOOKUP($B16&$C16,'SF - Blocks'!$C$1:$E$43,3,FALSE))","v":"[B]\nIdentify the key ethical issues of a data processing or project and alert if there is any doubt or identification of a risk (for instance, block a data transfer in the absence of a risk analysis).\n\nEnsure ownership by program teams of ethical issues (awareness raising techniques and training)."}]
["Define and implement data security best practices","S5.3","A",{"$f":"IF(VLOOKUP($B17&$C17,'SF - Blocks'!$C$1:$E$43,2,FALSE)=0,\"\",VLOOKUP($B17&$C17,'SF - Blocks'!$C$1:$E$43,2,FALSE))","v":"[A]\nPre-identify the types of data that need to be protected (sensitive, personal, community data).\n\nHave simple reflexes for securing paper based and digital data: locked cupboard, choice of a secured password, encrypting a file, sharing data internally and externally etc.\n\nBe familiar with the best practices for securing the various tools used."},{"$f":"IF(VLOOKUP($B17&$C17,'SF - Blocks'!$C$1:$E$43,3,FALSE)=0,\"\",VLOOKUP($B17&$C17,'SF - Blocks'!$C$1:$E$43,3,FALSE))","v":""}]

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["For each role: fill in the expected level of expertise per skill"]
[]
[]
[null,null,"Roles of scenario A",null,"Roles of scenario B",null,null,"Roles of scenario C",null,null,"Roles of scenario D",null,"Roles of scenario E"]
["Skills",null,"Project Manager","Technical and Methodological Support","Project Manager","Technical and Methodological Support","Technical Program Data Management","General Coordination","Technical and Methodological Support","M&E-Program Data Management Manager (field)","Program Data Management Coordination","Program Data Management Manager","Program Data Management Coordination","Technical Program Data Management at national level","Program Data Management Manager (field)","Method and Training Support"]
[null,null,"ScenarioA","ScenarioA","ScenarioB","ScenarioB","ScenarioB","ScenarioC","ScenarioC","ScenarioC","ScenarioD","ScenarioD","ScenarioE","ScenarioE","ScenarioE","ScenarioE"]
["Block 1 ","S1.1","B","B","B","C",0,"B","C",0,"C",0,"C",0,"B","C"]
[null,"S1.2",0,"B","B","C",0,"B","C",0,"C",0,"C",0,"B","C"]
[null,"S1.3",0,"C","C","C",0,0,"C",0,"C",0,"C",0,0,"C"]
["Block 2","S2.1","A","B","B","C","D","B","C","A","C","B","C","D","B","D"]
[null,"S2.2","A","B","A","C","D","B","C","A","C","B","C","C","B","C"]
["Block 3","S3.1","A","B","A","D","D","B","D","A","C","B","C","D","B","C"]
[null,"S3.2","B","C","B","D","D","B","D","B","C","B","C","D","B","C"]
[null,"S3.3","A","B","A","D","D","B","D","A","C","B","C","D","B","C"]
[null,"S3.4",0,0,"B",0,"B","B",0,0,"C","B","C","D","B","C"]
["Block 4","S4.1","A","B","C","C","B","B","C","A","C","B","C","B","B","C"]
[null,"S4.2",0,"B","C","C","B","B","C",0,"C","B","C","B","B","C"]
["Block 5","S5.1","A","B","B","C","B","B","C","A","C","B","C","A","B","D"]
[null,"S5.2","B","B","B","C","B","B","C",0,"C","B","C","B","B","C"]
[null,"S5.3","A","B","B","C","B","B","C","A","C","B","C","A","B","D"]

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[null,null,null,"Technical","Methodological"]
["S1.1","B",{"$f":"CONCATENATE(A2,B2)","v":"S1.1B"},"[B]\nBreak down the different data collection and processing needs during the project cycle (e.g., needs assessment, case management, M&E, CRM, etc.)\n• Identify metrics that may cause data management complications (e.g., multiple data sources, case management etc.) so that they may be taken into account.\n\nTranslate the program’s [and M&E] data management needs into technical data management principles.  Examples:\n• Understanding that medical patient follow-up involves a particular practice and data model adapted to case management.\n• Avoiding double-counting involves assigning a unique number/code to each beneficiary\n• Combining data from different programs involves ensuring data interoperability.\n\nUse data flow models to coordinate data management activities (e.g., database update, data transfer, etc.).\n","[B]\nMap the data management cycle and adapt it to the needs of the program [and M&E].\n\nIdentify the comparative advantages of various technical solutions and methods for all stages of data management (ex: MDC, DBMS, Analysis).\n\nConfront needs with a comparative analysis, making it possible to choose technical and methodological solutions adapted to projects.\n\nJustify technical scenarios for one or several projects.\n\nPlan and implement the deployment of a tool (collection, management and analysis) or of a working method covering technical, HR and financial aspects."]
["S1.1","C",{"$f":"CONCATENATE(A3,B3)","v":"S1.1C"},"[C]\nChoose and represent graphical data models and flows adapted to the needs of the structure, allowing joins (relationships) and analysis queries.\n• Knowledge of typical and standard industry models (e.g., flakes, HXL),\n• Identify and locate data (tangible vs. IT),\n• Graphically display data.\n\nDesign data management processes based on the data models chosen. \n\n","[C]\nPerform a data management diagnosis on a mission that includes needs, opportunities and constraints, practice analysis (context-specific or non-context-sensitive), comparison of different tools, proposal for recommendations, cost estimate. \nDevelop the data management strategy for a mission or organisation, involving identification of the following:\n• standard technical solutions,\n• interoperability needs,\n• workflow and segregation of duties,\n• human resources (recruitment, training),\n• budget."]
["S1.2","B",{"$f":"CONCATENATE(A4,B4)","v":"S1.2B"},"[B]\nHave knowledge about and be capable of using the technical tools chosen by the organisation.\n\nBe familiar with and enforce data management best practices and standards at each stage of the project cycle, for instance:\n• unique identifiers,\n• metadata usage,\n• single-entry database usage.\n\nDevelop and organise harmonised data management models across multiple zones. \n• interoperable forms and collection tools,\n• similar database models.","[B]\nAdapt and implement procedures for collecting, transferring, managing, analysing and storing data (data management cycle). Example: Standard Operating Procedures (SOPs) well suited to an area, or project.\n\nAdapt methods and tools to the opportunities and challenges encountered (context).\n\nEnsure proper dissemination of information on practices and tools used or projected to be used.\nEnsure consistency of data management tools and methods at the different levels and programs of an organisation/mission (e.g., coordination between branches).\n\nCarry out activities fostering the exchange of best practices between the various projects.\n\nProvide feedback on methods and tools."]
["S1.2","C","S1.2C",null,"[C]\nBe familiar with the data management ecosystem within the organisation and among external stakeholders, so as to adapt to it (depending on the sector or area of intervention, e.g., knowledge of the health data management ecosystem).\n\nEnsure integration and application of the organisation's general policies in data management procedures (technical and methodological)\n\nDevelop consistent general standards and procedures for all stages of the data management cycle:  collection, transfer, management, analysis, storage.\n\nLink data management policies and procedures with related policies and procedures: IT infrastructure, legal, MEAL, HR, risks."]
["S1.3","C","S1.3C","\n","[C]\nHost a community of practice (e.g., create or become part of an IM cluster).\n\nHave a cross-sectoral vision of data management tools and best practices in the industry.\n\nAssess the data management ecosystem within Humanitarian Aid and International Development CSOs, its sector or its area of intervention.\n\nIdentify the strengths and weaknesses of other data management actors.\n\nInfluence CSOs and donors' practices on data management issues via production of sector-structuring documents.\n\nArgue and adapt the discourse on data management to different audiences (internal, external, technical, non-technical).\n\nCoordinate and exchange on data management practices related to specific areas or themes with other stakeholders in the sector."]

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[null,null,null,"Technical","Methodological"]
["S2.1","A",{"$f":"CONCATENATE(A2,B2)","v":"S2.1A"},"[A]\nBe familiar with the various data formats (e.g., digital, text, single or multiple choice, date).\n\nEnter data and perform operations on an existing database (e.g., calculation, cleansing, filters, sorting, organisation and formatting, checking for double entries).\n\nDesign databases:\n• in Excel\n• with “1 to 1” relationships between tables or data sources.\n\nDesign and harmonise simple data models, using practices such as nomenclature, categorisation, setting standards. Examples:\n• PCODE (attributed of a unique code to a geographical area),\n• age group,\n• calculation of indicators in which a plurality of data is grouped,\n• having knowledge of the import-export formats of the technical solutions used, such as: .xlsx, .csv, .dta, etc.\n\nImport data into an existing database."]
["S2.1","B",{"$f":"CONCATENATE(A3,B3)","v":"S2.1B"},"[B]\nDesign and harmonise complex data models (e.g., Database coordination, relationship management).\n\nConfigure data collection fields (age, gender).\n\nTranslate a data model in a database management software.\n\nEnsure data interoperability between different data sources (e.g., asynchronous, non-automatic, manual import).\n\nMaster platform / interface of mobile data collection applications management including:\n• access rights management,\n• role management.","[B]\nTranslate the program’s [and M&E] analysis needs into effective databases:\n• understand program constraints and expectations,\n• understand the rules and opportunities that the IT department can bring and adapt the collection tools accordingly (ask the IT department the right questions)."]
["S2.1","C","S2.1C",null,"[C]\nDecide the data management strategy:\n• choice and combination of tools,\n• data management best practices,\n• workflow,\n• choice and representation of data models.\n\nCoordinate data management modalities and related services (M&E, IT, Programs)."]
["S2.1","D","S2.1D","[D]\nDesign databases:\n• on a variety of tools (including SQL-based),\n• with “1 to many” relationships,\n• enabling case management.\n\nSet up data management tools (AidImpact, ActivityInfo): configure indicators, databases.\n\nBe familiar with the features provided by the various IM and IT solutions (e.g., cloud, authentication system).\n\nDesign automatic interfaces between databases and various collection, management or analysis tools (e.g., cloud).\n\nEnsure real-time data interoperability with APIs (e.g., API query)."]
["S2.2","A","S2.2A","[A]\nDesign input masks or create forms via a form-builder.\n\nMaster one or several MDC tools (e.g., ODK, KoBoToolbox): configure tools for data collection.\nSupport data collection teams with troubleshooting bugs.\n\nIntegrate secondary data, import data into an existing database.","[A]\nBe familiar with the broad principles of MDC and know how to identify situations in which these tools are appropriate.\n\nHave knowledge of the steps required prior to any mobile data collection (such as the need to test the questionnaire: test protocol and validation)\n\nTrain enumerators and data-monitoring personnel and adapt to the various levels encountered."]
["S2.2","B","S2.2B","[B]\nCreate forms using XLS Forms encoding.\n\nMaster multiple MDC tools (ex: KoBo, ODK, ONA, Survey CTO, Survey 123).\n\nCarry out an analysis plan:\n• define the variables to measure the desired metrics and indicators,\n• plan descriptive analysis, general trends of the entire population, variable-crossing, statistical calculations.\n\nOrganise activity tracking collections (case management), requiring a particular protocol.\n\nMaster platforms / interfaces of mobile data collection applications management including:\n• access rights management,\n• role management,\n• survey form update following a change,\n• implementation of preliminary interest analysis.","[B]\nBe familiar with the data ecosystem in its environment (sector, area), to retrieve secondary data.\n\nSupport program [and M&E] teams in producing an analysis plan prior to quantitative data collection.\n\nDraft protocols for specific data collections (e.g., survey protocol).\n\nConfront needs with a comparative analysis, making it possible to choose suitable technical and methodological solutions.\n\nPerform comparisons of technical solutions, technical scenarios, and tool deployment experience. Based on limited information.\n\nCoordinate the human and financial resources required for collection."]
["S2.2","C","S2.2C","\n","[C]\nCoordinate standardised data collections in separate areas.\n\nEnsure consistency of collected data, via:\n• implementation of standard protocols,\n• quality and compliance monitoring of the collected data.\n\nDefine resource mobilisation strategies for data collection."]
["S2.2","D","S2.2D","[D]\nMaster advanced questionnaire functions related to case management.\n\nMaster the use of comprehensive and/or industry data management platforms (from collection to analysis). Examples: Akvo Flow, AidImpact, Dharma."]

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[null,null,null,"Technical","Methodological"]
["S3.1","A",{"$f":"CONCATENATE(A2,B2)","v":"S3.1A"},"[A]\nPerform simple calculations on Excel (averages, sums…).\n\nMake simple representations and graphs on Excel.","[A]\nBe familiar with statistical analysis and graphical representation issues (e.g., data types, aggregation of data, choice of graphical representation according to available data).\n\nApply an analysis plan."]
["S3.1","B",{"$f":"CONCATENATE(A3,B3)","v":"S3.1B"},"[B]\nPerform complex calculations from formulas on Excel (ex: SUM.SI.ENS).\n\nPerform “advanced” analysis and graphical representations on Excel (using dedicated features such as pivot tables, dynamic graphs, segments).\n\nAggregate data from multiple formats (xls, csv, json, etc.) and sources (using tools such as Access, Excel).\n\nApply the following statistical concepts: workforce, average, median, frequency, standard deviation.","[B]\nSupport the program [and M&E] in producing an analysis plan if this has not carried out prior to quantitative data collection.\n\nInterpret the needs of the program [and M&E] in terms of statistical analysis and data representation."]
["S3.1","C","S3.1C",null,"[C]\nBe familiar with the comparative advantages of several data visualisation tools (in terms of technical possibility, durability and organisational compatibility, prerequisite skills, etc.), in order to make a choice.\n\nQuestion the most relevant modes of analysis, visualisation and representation, based on the needs and means of an organisation."]
["S3.1","D","S3.1D","[D]\nDevelop static and dynamic dashboards using visualisation tools (such as Power BI, Table, Qlik sense, Zoho Analytics), and in particular, create visuals from multiple linked tables (relational tables).\n\nMaster statistical tools (e.g., Stata, R)."]
["S3.2","B","S3.2B","[B]\nApply the different stages of qualitative data analysis (such as transcription, coding, comparison of key topics, synthesis and extraction of relevant verbatim reports).\n\nTranscribe, summarise, and categorise elements from qualitative data collections.\n\nKnow how to code manually and produce a synthesis with the onset of a “profiling” analysis.","[B]\nBe familiar with issues related to qualitative data analysis (such as objectives, limitations)."]
["S3.2","C","S3.2C",null,"[C]\nSupport program [and M&E] teams in producing an analysis plan prior to quality data collection.\n\nInterpret the needs of the program [and M&E] teams in terms of qualitative data analysis and representation.\n\nKnow how to analyse the coding outcome by highlighting complex trends and typical profiles."]
["S3.2","D","S3.2D","[D]\nUse qualitative data analysis software (such as coding or lexicometrics software).\n\nUse transcription software."]
["S3.3","A","S3.3A","[A]\nManipulate a mobile device to collect geographical data (GPS / smartphone…) and exploit data collected by these means.\n\nUse basic graphical representation modes (point, polygon, line, etc.).\n\nProduce simple maps on tools such as Google Earth or uMAP.","[A]\nUnderstand basic geographical concepts such as GPS format, latitude/longitude, administrative data or geographically transposable addresses."]
["S3.3","B","S3.3B","[B]\nStructure associated geographic and attribute data with the aim of producing maps.\n\nImport data into QGIS or ArcGIS (e.g., vector and raster layers, transform GPS data…), with data cleaning capability, and occasionally some simple spatial processing (e.g., Cross-referencing data, buffer zones…).\n\nProduce simple maps using tools such as QGIS or ArcGIS.\n\nImplement and technically support a simple GIS project using tools such as QGIS or ArcGIS.","[B]\nBe familiar with and know how to apply the rules of graphical semiology (visual variables types and appropriate modes of representation) and geographical concepts (geodesy, projection, metadata…).\n\nBe familiar with all of the components of a map (e.g., title, legend, source, North arrow, scale, disclaimers...) as well as all of the types of maps (e.g., basemap, thematic…).\n\nBe familiar with best practices for structuring geographic data sets to ensure consistency."]
["S3.3","C","S3.3C",null,"[C]\nCoordinate the implementation of a comprehensive mission-wide geographic information system."]
["S3.3","D","S3.3D","[D]\nProduce advanced maps (e.g., significant number of layers, complex representation modes).\n\nConnect the GIS to external databases and transform data.\n\nFrequently perform advanced GIS processing (e.g., satellite image processing, raster data, etc.) and mass processing on the data.\n\nImplement and maintain a complex GIS (multi-layered, geographic and project) offline.\n\nImplement and maintain a dynamic online mapping platform."]
["S3.4","B","S3.4B","[B]\nProduce communication materials.\n\nCreate simple computer graphics from the data.","[B]\nEnsure and guide the use of data and analysis (e.g., ability to stand back vis-à-vis data use, coordination with program teams, put collection and analysis needs / macro vision into perspective).\n\nProvide a framework (statistical limits, biases identified) for the interpretations made following data analysis."]
["S3.4","C","S3.4C",null,"[C]\nGuide best communication practices (identify target audience, simplify data).\n\nDecide which external communication media to produce.\n\nProduce coherent and harmonised data analysis and usage systems, meeting the needs of the program [and M&E]."]
["S3.4","D","S3.4D","[D]\nProduce illustrations gathered from data analysis using dedicated software such as Scribus or Illustrator."]

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[null,null,null,"Technical","Methodological"]
["S4.1","A",{"$f":"CONCATENATE(A2,B2)","v":"S4.1A"},"[A]\nMaster the data management cycle and apply it to data preparation and cleaning practices.\n\nPrepare for data collection: consistent naming (e.g., PCODE), attention to data types and attributes.\n\nClean up duplicate and inconsistent data.\n\nCheck the collected data: spot check, calculation, meaning.","[A]\nBe aware of the issues involved in collecting certain program-specific information."]
["S4.1","B",{"$f":"CONCATENATE(A3,B3)","v":"S4.1B"},"[B]\nImplement workflows in a team ensuring traceability, reliability, consistency and quality:\n• use of metadata and monitoring of the data collection,\n• Data validation \n• Triangulation of data with other sources,\n• editing and deletion rules,\n• refreshing data and backups of previous copies.\n\nEnsure data availability: storage of single-entry table data (allowing for efficient analysis queries such as pivot tables).","[B]\nGet involved in setting the goals for an M&E plan and challenge the program teams.\n\nInterpret M&E needs, in collection, management and analysis methods.\n\nCoordinate quality control methods on a mission-wide basis.\n\nEnsure a consistent level of data and analysis quality.\n\nSupport program teams in defining standards for the calculation of their indicators (e.g., counting beneficiaries or results)."]
["S4.1","C","S4.1C",null,"[C]\nEvaluate data collection, management, and analysis methods against data quality objectives.\n\nAssess data quality, reliability, traceability and availability and identify gaps (e.g., data quality method audit, of the USAID DQA type for instance).\n\nContribute to the data management aspects of the M&E strategy, the strategy for collecting, managing and analysing data across multiple projects.\n\nRecommend best practices in terms of data management.\n\nIntegrate data management principles into an M&E strategy\n\nAssess M&E feasibility from a data management, tool management interoperability, aggregation, data integrity perspective."]
["S4.2","B","S4.2B","[B]\nSynthesise qualitative and quantitative data for the program teams.\nBuild and understanding of data and develop skills their analysis, with a view to decision-making:\n• understand what is included in a data set,\n• to which questions data may help provide an answer,\n• understand the data (types, attributes, data vs. information),\n• know how to analyse the data (causation vs.  correlation),\n• understand data aggregation.\n\nTrain in best practices at all stages of the data cycle: collection, cleaning, analysis, for instance:\n• sampling, data aggregation,\n• Data cleaning\n• use of suitable visuals (map, type of chart, representation for qualitative analysis).\n\nInitiate reflection around data quality, management, and analysis objectives:\n• understanding of the origin and reliability of the data,\n• collection methods,\n• data protection.","[B]\nAdapt training to one’s public and spark interest within the organisation (pedagogy and popularisation).\n\nGuide program teams in their understanding of the quantitative, qualitative and cartographic analysis produced.\n\nAssess the teams’ levels and needs.\n\nGuide data management teams in their data collection, management and analysis practices.\n\nEnforce data management best practices across departments."]
["S4.2","C","S4.2C",null,"[C]\nAssess data quality and identify gaps.\n\nGuide the teams in charge of the data management strategy in their data collection, management and analysis practices.\n\nDevelop and steer an action plan for improving data management within an organisation.\n\nDefine data management best practices across departments.\n\nFoster change management within an organisation."]

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[null,null,null,"Technical","Methodological"]
["S5.1","A",{"$f":"CONCATENATE(A2,B2)","v":"S5.1A"},"[A]\nDistinguish personal from sensitive data.\n\nExecute clear instructions for data protection (configuration of tools, obtaining consent, execution of archive protocols, or de-identification, anonymisation, pseudonymisation, aggregation, etc.)."]
["S5.1","B",{"$f":"CONCATENATE(A3,B3)","v":"S5.1B"},"[B]\nBe familiar with and enforce the key elements of international data protection regulations (GDPR etc.).\n\nBe familiar with and enforce the key elements of the data protection regulation of the country or countries of intervention, such as the principles of processing limitation, limited conservation, proportionality, the rights of the data subject, etc.\n\nImplement data protection measures, from the time of default data design and protection, for instance via the choice and configuration of data management tools, the design of collection forms, etc.","[B]\nBriefly analyse legislation.\n\nDesign and implement awareness-raising and training actions.\n\nIdentify action points to improve program data protection.\n\nAdapt the recommended measures to the intervention contexts.\n\nEstablish practices, procedures and methodologies allowing the implementation of key data protection principles, for example:\n• choice of a legal basis, \n• obtainment of informed consent,\n• choice of a retention period, \n• implementation of archiving protocols, de-identification, anonymisation, pseudonymisation, aggregation, etc."]
["S5.1","C","S5.1C","[C]\nHave specific knowledge of the international and national data protection legislation.\n\nEstablish practices, procedures and methodologies ensuring data protection of all components, for instance:\n• draft of data-sharing agreements,\n• evaluation of a sub-contractor,\n\nDrafting or reviewing DTA/DSA type agreements or contracts.\n\nConduct and draft a Data Protection Impact Assessment (DPIA) on a data processing or simple project, involving few players or few technical solutions.\n\nEnsure contractual monitoring of partners and donors on the data protection-related dimension.","[C]\nMake a diagnosis and implement an action plan to ensure compliance with national and international legislation.\n\nAnalyse whether a processing is compliant and highlight non-conformities.\n\nDevelop a data protection strategy for a mission or organisation.\n\nDesign and disseminate practices, procedures and methodologies allowing the implementation of key data protection principles."]
["S5.1","D","S5.1D","[D]\nConduct and draft a Data Protection Impact Assessment (DPIA) on a complex data processing at mission or organisational level, involving a great deal of solutions and players."]
["S5.2","B","S5.2B","[B]\nAdopt the data protection standards applied to humanitarian aid and international development (Signal type Code of Ethics, Principles for Digital Development, etc.) and context (non-state armed groups, medical data, etc.).\n\nImplement donor guidelines for data protection.","[B]\nIdentify the key ethical issues of a data processing or project and alert if there is any doubt or identification of a risk (for instance, block a data transfer in the absence of a risk analysis).\n\nEnsure ownership by program teams of ethical issues (awareness raising techniques and training)."]
["S5.2","C","S5.2C",null,"[C]\nIdentify the issues at stake in the debate related to the application of data protection concepts and laws in the field of humanitarian aid and international development:\n• concept of responsible management vs. protection,\n• application of informed consent, inadequacy of the GDPR for the intervention context.\n\nConduct an in-depth assessment of the ethical issues of a data processing or project (be able to argue independently to refuse data transfer to a partner, assess the level of risk of data collection, etc.).\n\nMake a diagnosis and implement an action plan to comply with national and international legislation."]
["S5.3","A","S5.3A","[A]\nPre-identify the types of data that need to be protected (sensitive, personal, community data).\n\nHave simple reflexes for securing paper based and digital data: locked cupboard, choice of a secured password, encrypting a file, sharing data internally and externally etc.\n\nBe familiar with the best practices for securing the various tools used."]
["S5.3","B","S5.3B","[B]\nImplement project-wide securing of paper based and digital data (shared cloud encryption, password sharing modality, choice of authentication method, user access management, traceability measures, password strength assessment, back-up modality, anonymisation and pseudonymisation method etc.)\n\nBe familiar with the entire range of data security components (including methods for securing the various tools used).","[B]\nAdapt the organisation’s guidelines to specific contexts and develop standard practice guides. \n\nDisseminate and know how to ensure implementation of procedures."]
["S5.3","C","S5.3C","[C]\nPerform “basic” data security audits.\n\nGain a thorough understanding of the various components of technical and organisational data security and the degrees associated with each:\n• difference between encryption during transfer vs. during storage,\n• server certification, PGP key concept or AES standard etc.","[C]\nDesign and align data security practices across the organisation.\n\nAssess the level of data security implemented in a project or organisation or with a partner (assess practices, assess relevance and appropriateness of the chosen measures).\n\nBe able to communicate easily with IT teams with regards to cybersecurity."]
["S5.3","D","S5.3D","[D]\nBe thoroughly familiar with the organisation’s IT environment and the appropriate cybersecurity measures associated with it.\n\nApply advanced data security measures in a complex environment (players, tools, and multiple location).\n\nPerform complete data security audits."]

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["Compétence","Niveau","concat","Technical","Methodological"]
["S1.1","B",{"$f":"CONCATENATE('SF - Blocks'!$A2,'SF - Blocks'!$B2)","v":"S1.1B"},{"$f":"VLOOKUP($C2,'KH - Block1'!$C$2:$E$6,2,FALSE)","v":"[B]\nBreak down the different data collection and processing needs during the project cycle (e.g., needs assessment, case management, M&E, CRM, etc.)\n• Identify metrics that may cause data management complications (e.g., multiple data sources, case management etc.) so that they may be taken into account.\n\nTranslate the program’s [and M&E] data management needs into technical data management principles.  Examples:\n• Understanding that medical patient follow-up involves a particular practice and data model adapted to case management.\n• Avoiding double-counting involves assigning a unique number/code to each beneficiary\n• Combining data from different programs involves ensuring data interoperability.\n\nUse data flow models to coordinate data management activities (e.g., database update, data transfer, etc.).\n"},{"$f":"VLOOKUP($C2,'KH - Block1'!$C$2:$E$6,3,FALSE)","v":"[B]\nMap the data management cycle and adapt it to the needs of the program [and M&E].\n\nIdentify the comparative advantages of various technical solutions and methods for all stages of data management (ex: MDC, DBMS, Analysis).\n\nConfront needs with a comparative analysis, making it possible to choose technical and methodological solutions adapted to projects.\n\nJustify technical scenarios for one or several projects.\n\nPlan and implement the deployment of a tool (collection, management and analysis) or of a working method covering technical, HR and financial aspects."}]
["S1.1","C",{"$f":"CONCATENATE('SF - Blocks'!$A3,'SF - Blocks'!$B3)","v":"S1.1C"},{"$f":"CONCATENATE(VLOOKUP($C2,'KH - Block1'!$C$2:$E$6,2,FALSE),\"\n\",VLOOKUP($C3,'KH - Block1'!$C$2:$E$6,2,FALSE))","v":"[B]\nBreak down the different data collection and processing needs during the project cycle (e.g., needs assessment, case management, M&E, CRM, etc.)\n• Identify metrics that may cause data management complications (e.g., multiple data sources, case management etc.) so that they may be taken into account.\n\nTranslate the program’s [and M&E] data management needs into technical data management principles.  Examples:\n• Understanding that medical patient follow-up involves a particular practice and data model adapted to case management.\n• Avoiding double-counting involves assigning a unique number/code to each beneficiary\n• Combining data from different programs involves ensuring data interoperability.\n\nUse data flow models to coordinate data management activities (e.g., database update, data transfer, etc.).\n\n[C]\nChoose and represent graphical data models and flows adapted to the needs of the structure, allowing joins (relationships) and analysis queries.\n• Knowledge of typical and standard industry models (e.g., flakes, HXL),\n• Identify and locate data (tangible vs. IT),\n• Graphically display data.\n\nDesign data management processes based on the data models chosen. \n\n"},{"$f":"CONCATENATE(VLOOKUP($C2,'KH - Block1'!$C$2:$E$6,3,FALSE),\"\n\",VLOOKUP($C3,'KH - Block1'!$C$2:$E$6,3,FALSE))","v":"[B]\nMap the data management cycle and adapt it to the needs of the program [and M&E].\n\nIdentify the comparative advantages of various technical solutions and methods for all stages of data management (ex: MDC, DBMS, Analysis).\n\nConfront needs with a comparative analysis, making it possible to choose technical and methodological solutions adapted to projects.\n\nJustify technical scenarios for one or several projects.\n\nPlan and implement the deployment of a tool (collection, management and analysis) or of a working method covering technical, HR and financial aspects.\n[C]\nPerform a data management diagnosis on a mission that includes needs, opportunities and constraints, practice analysis (context-specific or non-context-sensitive), comparison of different tools, proposal for recommendations, cost estimate. \nDevelop the data management strategy for a mission or organisation, involving identification of the following:\n• standard technical solutions,\n• interoperability needs,\n• workflow and segregation of duties,\n• human resources (recruitment, training),\n• budget."}]
["S1.2","B",{"$f":"CONCATENATE('SF - Blocks'!$A4,'SF - Blocks'!$B4)","v":"S1.2B"},{"$f":"VLOOKUP($C4,'KH - Block1'!$C$2:$E$6,2,FALSE)","v":"[B]\nHave knowledge about and be capable of using the technical tools chosen by the organisation.\n\nBe familiar with and enforce data management best practices and standards at each stage of the project cycle, for instance:\n• unique identifiers,\n• metadata usage,\n• single-entry database usage.\n\nDevelop and organise harmonised data management models across multiple zones. \n• interoperable forms and collection tools,\n• similar database models."},{"$f":"VLOOKUP($C4,'KH - Block1'!$C$2:$E$6,3,FALSE)","v":"[B]\nAdapt and implement procedures for collecting, transferring, managing, analysing and storing data (data management cycle). Example: Standard Operating Procedures (SOPs) well suited to an area, or project.\n\nAdapt methods and tools to the opportunities and challenges encountered (context).\n\nEnsure proper dissemination of information on practices and tools used or projected to be used.\nEnsure consistency of data management tools and methods at the different levels and programs of an organisation/mission (e.g., coordination between branches).\n\nCarry out activities fostering the exchange of best practices between the various projects.\n\nProvide feedback on methods and tools."}]
["S1.2","C",{"$f":"CONCATENATE('SF - Blocks'!$A5,'SF - Blocks'!$B5)","v":"S1.2C"},{"$f":"CONCATENATE(VLOOKUP($C4,'KH - Block1'!$C$2:$E$6,2,FALSE),VLOOKUP($C5,'KH - Block1'!$C$2:$E$6,2,FALSE))","v":"[B]\nHave knowledge about and be capable of using the technical tools chosen by the organisation.\n\nBe familiar with and enforce data management best practices and standards at each stage of the project cycle, for instance:\n• unique identifiers,\n• metadata usage,\n• single-entry database usage.\n\nDevelop and organise harmonised data management models across multiple zones. \n• interoperable forms and collection tools,\n• similar database models."},{"$f":"CONCATENATE(VLOOKUP($C4,'KH - Block1'!$C$2:$E$6,3,FALSE),VLOOKUP($C5,'KH - Block1'!$C$2:$E$6,3,FALSE))","v":"[B]\nAdapt and implement procedures for collecting, transferring, managing, analysing and storing data (data management cycle). Example: Standard Operating Procedures (SOPs) well suited to an area, or project.\n\nAdapt methods and tools to the opportunities and challenges encountered (context).\n\nEnsure proper dissemination of information on practices and tools used or projected to be used.\nEnsure consistency of data management tools and methods at the different levels and programs of an organisation/mission (e.g., coordination between branches).\n\nCarry out activities fostering the exchange of best practices between the various projects.\n\nProvide feedback on methods and tools.[C]\nBe familiar with the data management ecosystem within the organisation and among external stakeholders, so as to adapt to it (depending on the sector or area of intervention, e.g., knowledge of the health data management ecosystem).\n\nEnsure integration and application of the organisation's general policies in data management procedures (technical and methodological)\n\nDevelop consistent general standards and procedures for all stages of the data management cycle:  collection, transfer, management, analysis, storage.\n\nLink data management policies and procedures with related policies and procedures: IT infrastructure, legal, MEAL, HR, risks."}]
["S1.3","C",{"$f":"CONCATENATE('SF - Blocks'!$A6,'SF - Blocks'!$B6)","v":"S1.3C"},{"$f":"VLOOKUP($C6,'KH - Block1'!$C$2:$E$6,2,FALSE)","v":"\n"},{"$f":"VLOOKUP($C6,'KH - Block1'!$C$2:$E$6,3,FALSE)","v":"[C]\nHost a community of practice (e.g., create or become part of an IM cluster).\n\nHave a cross-sectoral vision of data management tools and best practices in the industry.\n\nAssess the data management ecosystem within Humanitarian Aid and International Development CSOs, its sector or its area of intervention.\n\nIdentify the strengths and weaknesses of other data management actors.\n\nInfluence CSOs and donors' practices on data management issues via production of sector-structuring documents.\n\nArgue and adapt the discourse on data management to different audiences (internal, external, technical, non-technical).\n\nCoordinate and exchange on data management practices related to specific areas or themes with other stakeholders in the sector."}]
["S2.1","A",{"$f":"CONCATENATE('SF - Blocks'!$A7,'SF - Blocks'!$B7)","v":"S2.1A"},{"$f":"VLOOKUP($C7,'KH - Block2'!$C$2:$E$9,2,FALSE)","v":"[A]\nBe familiar with the various data formats (e.g., digital, text, single or multiple choice, date).\n\nEnter data and perform operations on an existing database (e.g., calculation, cleansing, filters, sorting, organisation and formatting, checking for double entries).\n\nDesign databases:\n• in Excel\n• with “1 to 1” relationships between tables or data sources.\n\nDesign and harmonise simple data models, using practices such as nomenclature, categorisation, setting standards. Examples:\n• PCODE (attributed of a unique code to a geographical area),\n• age group,\n• calculation of indicators in which a plurality of data is grouped,\n• having knowledge of the import-export formats of the technical solutions used, such as: .xlsx, .csv, .dta, etc.\n\nImport data into an existing database."},{"$f":"VLOOKUP($C7,'KH - Block2'!$C$2:$E$9,3,FALSE)","v":0}]
["S2.1","B",{"$f":"CONCATENATE('SF - Blocks'!$A8,'SF - Blocks'!$B8)","v":"S2.1B"},{"$f":"CONCATENATE(VLOOKUP($C7,'KH - Block2'!$C$2:$E$9,2,FALSE),VLOOKUP($C8,'KH - Block2'!$C$2:$E$9,2,FALSE))","v":"[A]\nBe familiar with the various data formats (e.g., digital, text, single or multiple choice, date).\n\nEnter data and perform operations on an existing database (e.g., calculation, cleansing, filters, sorting, organisation and formatting, checking for double entries).\n\nDesign databases:\n• in Excel\n• with “1 to 1” relationships between tables or data sources.\n\nDesign and harmonise simple data models, using practices such as nomenclature, categorisation, setting standards. Examples:\n• PCODE (attributed of a unique code to a geographical area),\n• age group,\n• calculation of indicators in which a plurality of data is grouped,\n• having knowledge of the import-export formats of the technical solutions used, such as: .xlsx, .csv, .dta, etc.\n\nImport data into an existing database.[B]\nDesign and harmonise complex data models (e.g., Database coordination, relationship management).\n\nConfigure data collection fields (age, gender).\n\nTranslate a data model in a database management software.\n\nEnsure data interoperability between different data sources (e.g., asynchronous, non-automatic, manual import).\n\nMaster platform / interface of mobile data collection applications management including:\n• access rights management,\n• role management."},{"$f":"CONCATENATE(VLOOKUP($C7,'KH - Block2'!$C$2:$E$9,3,FALSE),VLOOKUP($C8,'KH - Block2'!$C$2:$E$9,3,FALSE))","v":"[B]\nTranslate the program’s [and M&E] analysis needs into effective databases:\n• understand program constraints and expectations,\n• understand the rules and opportunities that the IT department can bring and adapt the collection tools accordingly (ask the IT department the right questions)."}]
["S2.1","C",{"$f":"CONCATENATE('SF - Blocks'!$A9,'SF - Blocks'!$B9)","v":"S2.1C"},{"$f":"CONCATENATE(VLOOKUP($C7,'KH - Block2'!$C$2:$E$9,2,FALSE),VLOOKUP($C8,'KH - Block2'!$C$2:$E$9,2,FALSE),VLOOKUP($C9,'KH - Block2'!$C$2:$E$9,2,FALSE))","v":"[A]\nBe familiar with the various data formats (e.g., digital, text, single or multiple choice, date).\n\nEnter data and perform operations on an existing database (e.g., calculation, cleansing, filters, sorting, organisation and formatting, checking for double entries).\n\nDesign databases:\n• in Excel\n• with “1 to 1” relationships between tables or data sources.\n\nDesign and harmonise simple data models, using practices such as nomenclature, categorisation, setting standards. Examples:\n• PCODE (attributed of a unique code to a geographical area),\n• age group,\n• calculation of indicators in which a plurality of data is grouped,\n• having knowledge of the import-export formats of the technical solutions used, such as: .xlsx, .csv, .dta, etc.\n\nImport data into an existing database.[B]\nDesign and harmonise complex data models (e.g., Database coordination, relationship management).\n\nConfigure data collection fields (age, gender).\n\nTranslate a data model in a database management software.\n\nEnsure data interoperability between different data sources (e.g., asynchronous, non-automatic, manual import).\n\nMaster platform / interface of mobile data collection applications management including:\n• access rights management,\n• role management."},{"$f":"CONCATENATE(VLOOKUP($C7,'KH - Block2'!$C$2:$E$9,3,FALSE),VLOOKUP($C8,'KH - Block2'!$C$2:$E$9,3,FALSE),VLOOKUP($C9,'KH - Block2'!$C$2:$E$9,3,FALSE))","v":"[B]\nTranslate the program’s [and M&E] analysis needs into effective databases:\n• understand program constraints and expectations,\n• understand the rules and opportunities that the IT department can bring and adapt the collection tools accordingly (ask the IT department the right questions).[C]\nDecide the data management strategy:\n• choice and combination of tools,\n• data management best practices,\n• workflow,\n• choice and representation of data models.\n\nCoordinate data management modalities and related services (M&E, IT, Programs)."}]
["S2.1","D",{"$f":"CONCATENATE('SF - Blocks'!$A10,'SF - Blocks'!$B10)","v":"S2.1D"},{"$f":"CONCATENATE(VLOOKUP($C7,'KH - Block2'!$C$2:$E$9,2,FALSE),VLOOKUP($C8,'KH - Block2'!$C$2:$E$9,2,FALSE),VLOOKUP($C9,'KH - Block2'!$C$2:$E$9,2,FALSE),VLOOKUP($C10,'KH - Block2'!$C$2:$E$9,2,FALSE))","v":"[A]\nBe familiar with the various data formats (e.g., digital, text, single or multiple choice, date).\n\nEnter data and perform operations on an existing database (e.g., calculation, cleansing, filters, sorting, organisation and formatting, checking for double entries).\n\nDesign databases:\n• in Excel\n• with “1 to 1” relationships between tables or data sources.\n\nDesign and harmonise simple data models, using practices such as nomenclature, categorisation, setting standards. Examples:\n• PCODE (attributed of a unique code to a geographical area),\n• age group,\n• calculation of indicators in which a plurality of data is grouped,\n• having knowledge of the import-export formats of the technical solutions used, such as: .xlsx, .csv, .dta, etc.\n\nImport data into an existing database.[B]\nDesign and harmonise complex data models (e.g., Database coordination, relationship management).\n\nConfigure data collection fields (age, gender).\n\nTranslate a data model in a database management software.\n\nEnsure data interoperability between different data sources (e.g., asynchronous, non-automatic, manual import).\n\nMaster platform / interface of mobile data collection applications management including:\n• access rights management,\n• role management.[D]\nDesign databases:\n• on a variety of tools (including SQL-based),\n• with “1 to many” relationships,\n• enabling case management.\n\nSet up data management tools (AidImpact, ActivityInfo): configure indicators, databases.\n\nBe familiar with the features provided by the various IM and IT solutions (e.g., cloud, authentication system).\n\nDesign automatic interfaces between databases and various collection, management or analysis tools (e.g., cloud).\n\nEnsure real-time data interoperability with APIs (e.g., API query)."},{"$f":"CONCATENATE(VLOOKUP($C7,'KH - Block2'!$C$2:$E$9,3,FALSE),VLOOKUP($C8,'KH - Block2'!$C$2:$E$9,3,FALSE),VLOOKUP($C9,'KH - Block2'!$C$2:$E$9,3,FALSE),VLOOKUP($C10,'KH - Block2'!$C$2:$E$9,3,FALSE))","v":"[B]\nTranslate the program’s [and M&E] analysis needs into effective databases:\n• understand program constraints and expectations,\n• understand the rules and opportunities that the IT department can bring and adapt the collection tools accordingly (ask the IT department the right questions).[C]\nDecide the data management strategy:\n• choice and combination of tools,\n• data management best practices,\n• workflow,\n• choice and representation of data models.\n\nCoordinate data management modalities and related services (M&E, IT, Programs)."}]
["S2.2","A",{"$f":"CONCATENATE('SF - Blocks'!$A11,'SF - Blocks'!$B11)","v":"S2.2A"},{"$f":"VLOOKUP($C11,'KH - Block2'!$C$2:$E$9,2,FALSE)","v":"[A]\nDesign input masks or create forms via a form-builder.\n\nMaster one or several MDC tools (e.g., ODK, KoBoToolbox): configure tools for data collection.\nSupport data collection teams with troubleshooting bugs.\n\nIntegrate secondary data, import data into an existing database."},{"$f":"VLOOKUP($C11,'KH - Block2'!$C$2:$E$9,3,FALSE)","v":"[A]\nBe familiar with the broad principles of MDC and know how to identify situations in which these tools are appropriate.\n\nHave knowledge of the steps required prior to any mobile data collection (such as the need to test the questionnaire: test protocol and validation)\n\nTrain enumerators and data-monitoring personnel and adapt to the various levels encountered."}]
["S2.2","B",{"$f":"CONCATENATE('SF - Blocks'!$A12,'SF - Blocks'!$B12)","v":"S2.2B"},{"$f":"CONCATENATE(VLOOKUP($C11,'KH - Block2'!$C$2:$E$9,2,FALSE),\"\n\",VLOOKUP($C12,'KH - Block2'!$C$2:$E$9,2,FALSE))","v":"[A]\nDesign input masks or create forms via a form-builder.\n\nMaster one or several MDC tools (e.g., ODK, KoBoToolbox): configure tools for data collection.\nSupport data collection teams with troubleshooting bugs.\n\nIntegrate secondary data, import data into an existing database.\n[B]\nCreate forms using XLS Forms encoding.\n\nMaster multiple MDC tools (ex: KoBo, ODK, ONA, Survey CTO, Survey 123).\n\nCarry out an analysis plan:\n• define the variables to measure the desired metrics and indicators,\n• plan descriptive analysis, general trends of the entire population, variable-crossing, statistical calculations.\n\nOrganise activity tracking collections (case management), requiring a particular protocol.\n\nMaster platforms / interfaces of mobile data collection applications management including:\n• access rights management,\n• role management,\n• survey form update following a change,\n• implementation of preliminary interest analysis."},{"$f":"CONCATENATE(VLOOKUP($C11,'KH - Block2'!$C$2:$E$9,3,FALSE),\"\n\",VLOOKUP($C12,'KH - Block2'!$C$2:$E$9,3,FALSE))","v":"[A]\nBe familiar with the broad principles of MDC and know how to identify situations in which these tools are appropriate.\n\nHave knowledge of the steps required prior to any mobile data collection (such as the need to test the questionnaire: test protocol and validation)\n\nTrain enumerators and data-monitoring personnel and adapt to the various levels encountered.\n[B]\nBe familiar with the data ecosystem in its environment (sector, area), to retrieve secondary data.\n\nSupport program [and M&E] teams in producing an analysis plan prior to quantitative data collection.\n\nDraft protocols for specific data collections (e.g., survey protocol).\n\nConfront needs with a comparative analysis, making it possible to choose suitable technical and methodological solutions.\n\nPerform comparisons of technical solutions, technical scenarios, and tool deployment experience. Based on limited information.\n\nCoordinate the human and financial resources required for collection."}]
["S2.2","C",{"$f":"CONCATENATE('SF - Blocks'!$A13,'SF - Blocks'!$B13)","v":"S2.2C"},{"$f":"CONCATENATE(VLOOKUP($C11,'KH - Block2'!$C$2:$E$9,2,FALSE),\"\n\",VLOOKUP($C12,'KH - Block2'!$C$2:$E$9,2,FALSE),\"\n\",VLOOKUP($C13,'KH - Block2'!$C$2:$E$9,2,FALSE))","v":"[A]\nDesign input masks or create forms via a form-builder.\n\nMaster one or several MDC tools (e.g., ODK, KoBoToolbox): configure tools for data collection.\nSupport data collection teams with troubleshooting bugs.\n\nIntegrate secondary data, import data into an existing database.\n[B]\nCreate forms using XLS Forms encoding.\n\nMaster multiple MDC tools (ex: KoBo, ODK, ONA, Survey CTO, Survey 123).\n\nCarry out an analysis plan:\n• define the variables to measure the desired metrics and indicators,\n• plan descriptive analysis, general trends of the entire population, variable-crossing, statistical calculations.\n\nOrganise activity tracking collections (case management), requiring a particular protocol.\n\nMaster platforms / interfaces of mobile data collection applications management including:\n• access rights management,\n• role management,\n• survey form update following a change,\n• implementation of preliminary interest analysis.\n\n"},{"$f":"CONCATENATE(VLOOKUP($C11,'KH - Block2'!$C$2:$E$9,3,FALSE),\"\n\",VLOOKUP($C12,'KH - Block2'!$C$2:$E$9,3,FALSE),\"\n\",VLOOKUP($C13,'KH - Block2'!$C$2:$E$9,3,FALSE))","v":"[A]\nBe familiar with the broad principles of MDC and know how to identify situations in which these tools are appropriate.\n\nHave knowledge of the steps required prior to any mobile data collection (such as the need to test the questionnaire: test protocol and validation)\n\nTrain enumerators and data-monitoring personnel and adapt to the various levels encountered.\n[B]\nBe familiar with the data ecosystem in its environment (sector, area), to retrieve secondary data.\n\nSupport program [and M&E] teams in producing an analysis plan prior to quantitative data collection.\n\nDraft protocols for specific data collections (e.g., survey protocol).\n\nConfront needs with a comparative analysis, making it possible to choose suitable technical and methodological solutions.\n\nPerform comparisons of technical solutions, technical scenarios, and tool deployment experience. Based on limited information.\n\nCoordinate the human and financial resources required for collection.\n[C]\nCoordinate standardised data collections in separate areas.\n\nEnsure consistency of collected data, via:\n• implementation of standard protocols,\n• quality and compliance monitoring of the collected data.\n\nDefine resource mobilisation strategies for data collection."}]
["S2.2","D",{"$f":"CONCATENATE('SF - Blocks'!$A14,'SF - Blocks'!$B14)","v":"S2.2D"},{"$f":"CONCATENATE(VLOOKUP($C11,'KH - Block2'!$C$2:$E$9,2,FALSE),\"\n\",VLOOKUP($C12,'KH - Block2'!$C$2:$E$9,2,FALSE),\"\n\",VLOOKUP($C13,'KH - Block2'!$C$2:$E$9,2,FALSE),\"\n\",VLOOKUP($C14,'KH - Block2'!$C$2:$E$9,2,FALSE))","v":"[A]\nDesign input masks or create forms via a form-builder.\n\nMaster one or several MDC tools (e.g., ODK, KoBoToolbox): configure tools for data collection.\nSupport data collection teams with troubleshooting bugs.\n\nIntegrate secondary data, import data into an existing database.\n[B]\nCreate forms using XLS Forms encoding.\n\nMaster multiple MDC tools (ex: KoBo, ODK, ONA, Survey CTO, Survey 123).\n\nCarry out an analysis plan:\n• define the variables to measure the desired metrics and indicators,\n• plan descriptive analysis, general trends of the entire population, variable-crossing, statistical calculations.\n\nOrganise activity tracking collections (case management), requiring a particular protocol.\n\nMaster platforms / interfaces of mobile data collection applications management including:\n• access rights management,\n• role management,\n• survey form update following a change,\n• implementation of preliminary interest analysis.\n\n\n[D]\nMaster advanced questionnaire functions related to case management.\n\nMaster the use of comprehensive and/or industry data management platforms (from collection to analysis). Examples: Akvo Flow, AidImpact, Dharma."},{"$f":"CONCATENATE(VLOOKUP($C11,'KH - Block2'!$C$2:$E$9,3,FALSE),\"\n\",VLOOKUP($C12,'KH - Block2'!$C$2:$E$9,3,FALSE),\"\n\",VLOOKUP($C13,'KH - Block2'!$C$2:$E$9,3,FALSE),\"\n\",VLOOKUP($C14,'KH - Block2'!$C$2:$E$9,3,FALSE))","v":"[A]\nBe familiar with the broad principles of MDC and know how to identify situations in which these tools are appropriate.\n\nHave knowledge of the steps required prior to any mobile data collection (such as the need to test the questionnaire: test protocol and validation)\n\nTrain enumerators and data-monitoring personnel and adapt to the various levels encountered.\n[B]\nBe familiar with the data ecosystem in its environment (sector, area), to retrieve secondary data.\n\nSupport program [and M&E] teams in producing an analysis plan prior to quantitative data collection.\n\nDraft protocols for specific data collections (e.g., survey protocol).\n\nConfront needs with a comparative analysis, making it possible to choose suitable technical and methodological solutions.\n\nPerform comparisons of technical solutions, technical scenarios, and tool deployment experience. Based on limited information.\n\nCoordinate the human and financial resources required for collection.\n[C]\nCoordinate standardised data collections in separate areas.\n\nEnsure consistency of collected data, via:\n• implementation of standard protocols,\n• quality and compliance monitoring of the collected data.\n\nDefine resource mobilisation strategies for data collection.\n"}]
["S3.1","A",{"$f":"CONCATENATE('SF - Blocks'!$A15,'SF - Blocks'!$B15)","v":"S3.1A"},{"$f":"VLOOKUP($C15,'KH - Block3'!$C$2:$E$15,2,FALSE)","v":"[A]\nPerform simple calculations on Excel (averages, sums…).\n\nMake simple representations and graphs on Excel."},{"$f":"VLOOKUP($C15,'KH - Block3'!$C$2:$E$15,3,FALSE)","v":"[A]\nBe familiar with statistical analysis and graphical representation issues (e.g., data types, aggregation of data, choice of graphical representation according to available data).\n\nApply an analysis plan."}]
["S3.1","B",{"$f":"CONCATENATE('SF - Blocks'!$A16,'SF - Blocks'!$B16)","v":"S3.1B"},{"$f":"CONCATENATE(VLOOKUP($C15,'KH - Block3'!$C$2:$E$15,2,FALSE),\"\n\",VLOOKUP($C16,'KH - Block3'!$C$2:$E$15,2,FALSE))","v":"[A]\nPerform simple calculations on Excel (averages, sums…).\n\nMake simple representations and graphs on Excel.\n[B]\nPerform complex calculations from formulas on Excel (ex: SUM.SI.ENS).\n\nPerform “advanced” analysis and graphical representations on Excel (using dedicated features such as pivot tables, dynamic graphs, segments).\n\nAggregate data from multiple formats (xls, csv, json, etc.) and sources (using tools such as Access, Excel).\n\nApply the following statistical concepts: workforce, average, median, frequency, standard deviation."},{"$f":"CONCATENATE(VLOOKUP($C15,'KH - Block3'!$C$2:$E$15,3,FALSE),\"\n\",VLOOKUP($C16,'KH - Block3'!$C$2:$E$15,3,FALSE))","v":"[A]\nBe familiar with statistical analysis and graphical representation issues (e.g., data types, aggregation of data, choice of graphical representation according to available data).\n\nApply an analysis plan.\n[B]\nSupport the program [and M&E] in producing an analysis plan if this has not carried out prior to quantitative data collection.\n\nInterpret the needs of the program [and M&E] in terms of statistical analysis and data representation."}]
["S3.1","C",{"$f":"CONCATENATE('SF - Blocks'!$A17,'SF - Blocks'!$B17)","v":"S3.1C"},{"$f":"CONCATENATE(VLOOKUP($C15,'KH - Block3'!$C$2:$E$15,2,FALSE),\"\n\",VLOOKUP($C16,'KH - Block3'!$C$2:$E$15,2,FALSE),\"\n\",VLOOKUP($C17,'KH - Block3'!$C$2:$E$15,2,FALSE))","v":"[A]\nPerform simple calculations on Excel (averages, sums…).\n\nMake simple representations and graphs on Excel.\n[B]\nPerform complex calculations from formulas on Excel (ex: SUM.SI.ENS).\n\nPerform “advanced” analysis and graphical representations on Excel (using dedicated features such as pivot tables, dynamic graphs, segments).\n\nAggregate data from multiple formats (xls, csv, json, etc.) and sources (using tools such as Access, Excel).\n\nApply the following statistical concepts: workforce, average, median, frequency, standard deviation.\n"},{"$f":"CONCATENATE(VLOOKUP($C15,'KH - Block3'!$C$2:$E$15,3,FALSE),\"\n\",VLOOKUP($C16,'KH - Block3'!$C$2:$E$15,3,FALSE),\"\n\",VLOOKUP($C17,'KH - Block3'!$C$2:$E$15,3,FALSE))","v":"[A]\nBe familiar with statistical analysis and graphical representation issues (e.g., data types, aggregation of data, choice of graphical representation according to available data).\n\nApply an analysis plan.\n[B]\nSupport the program [and M&E] in producing an analysis plan if this has not carried out prior to quantitative data collection.\n\nInterpret the needs of the program [and M&E] in terms of statistical analysis and data representation.\n[C]\nBe familiar with the comparative advantages of several data visualisation tools (in terms of technical possibility, durability and organisational compatibility, prerequisite skills, etc.), in order to make a choice.\n\nQuestion the most relevant modes of analysis, visualisation and representation, based on the needs and means of an organisation."}]
["S3.1","D",{"$f":"CONCATENATE('SF - Blocks'!$A18,'SF - Blocks'!$B18)","v":"S3.1D"},{"$f":"CONCATENATE(VLOOKUP($C15,'KH - Block3'!$C$2:$E$15,2,FALSE),\"\n\",VLOOKUP($C16,'KH - Block3'!$C$2:$E$15,2,FALSE),\"\n\",VLOOKUP($C17,'KH - Block3'!$C$2:$E$15,2,FALSE),\"\n\",VLOOKUP($C18,'KH - Block3'!$C$2:$E$15,2,FALSE))","v":"[A]\nPerform simple calculations on Excel (averages, sums…).\n\nMake simple representations and graphs on Excel.\n[B]\nPerform complex calculations from formulas on Excel (ex: SUM.SI.ENS).\n\nPerform “advanced” analysis and graphical representations on Excel (using dedicated features such as pivot tables, dynamic graphs, segments).\n\nAggregate data from multiple formats (xls, csv, json, etc.) and sources (using tools such as Access, Excel).\n\nApply the following statistical concepts: workforce, average, median, frequency, standard deviation.\n\n[D]\nDevelop static and dynamic dashboards using visualisation tools (such as Power BI, Table, Qlik sense, Zoho Analytics), and in particular, create visuals from multiple linked tables (relational tables).\n\nMaster statistical tools (e.g., Stata, R)."},{"$f":"CONCATENATE(VLOOKUP($C15,'KH - Block3'!$C$2:$E$15,3,FALSE),\"\n\",VLOOKUP($C16,'KH - Block3'!$C$2:$E$15,3,FALSE),\"\n\",VLOOKUP($C17,'KH - Block3'!$C$2:$E$15,3,FALSE),\"\n\",VLOOKUP($C18,'KH - Block3'!$C$2:$E$15,3,FALSE))","v":"[A]\nBe familiar with statistical analysis and graphical representation issues (e.g., data types, aggregation of data, choice of graphical representation according to available data).\n\nApply an analysis plan.\n[B]\nSupport the program [and M&E] in producing an analysis plan if this has not carried out prior to quantitative data collection.\n\nInterpret the needs of the program [and M&E] in terms of statistical analysis and data representation.\n[C]\nBe familiar with the comparative advantages of several data visualisation tools (in terms of technical possibility, durability and organisational compatibility, prerequisite skills, etc.), in order to make a choice.\n\nQuestion the most relevant modes of analysis, visualisation and representation, based on the needs and means of an organisation.\n"}]
["S3.2","B",{"$f":"CONCATENATE('SF - Blocks'!$A19,'SF - Blocks'!$B19)","v":"S3.2B"},{"$f":"VLOOKUP($C19,'KH - Block3'!$C$2:$E$15,2,FALSE)","v":"[B]\nApply the different stages of qualitative data analysis (such as transcription, coding, comparison of key topics, synthesis and extraction of relevant verbatim reports).\n\nTranscribe, summarise, and categorise elements from qualitative data collections.\n\nKnow how to code manually and produce a synthesis with the onset of a “profiling” analysis."},{"$f":"VLOOKUP($C19,'KH - Block3'!$C$2:$E$15,3,FALSE)","v":"[B]\nBe familiar with issues related to qualitative data analysis (such as objectives, limitations)."}]
["S3.2","C",{"$f":"CONCATENATE('SF - Blocks'!$A20,'SF - Blocks'!$B20)","v":"S3.2C"},{"$f":"CONCATENATE(VLOOKUP($C19,'KH - Block3'!$C$2:$E$15,2,FALSE),\"\n\",VLOOKUP($C20,'KH - Block3'!$C$2:$E$15,2,FALSE))","v":"[B]\nApply the different stages of qualitative data analysis (such as transcription, coding, comparison of key topics, synthesis and extraction of relevant verbatim reports).\n\nTranscribe, summarise, and categorise elements from qualitative data collections.\n\nKnow how to code manually and produce a synthesis with the onset of a “profiling” analysis.\n"},{"$f":"CONCATENATE(VLOOKUP($C19,'KH - Block3'!$C$2:$E$15,3,FALSE),\"\n\",VLOOKUP($C20,'KH - Block3'!$C$2:$E$15,3,FALSE))","v":"[B]\nBe familiar with issues related to qualitative data analysis (such as objectives, limitations).\n[C]\nSupport program [and M&E] teams in producing an analysis plan prior to quality data collection.\n\nInterpret the needs of the program [and M&E] teams in terms of qualitative data analysis and representation.\n\nKnow how to analyse the coding outcome by highlighting complex trends and typical profiles."}]
["S3.2","D",{"$f":"CONCATENATE('SF - Blocks'!$A21,'SF - Blocks'!$B21)","v":"S3.2D"},{"$f":"CONCATENATE(VLOOKUP($C19,'KH - Block3'!$C$2:$E$15,2,FALSE),\"\n\",VLOOKUP($C20,'KH - Block3'!$C$2:$E$15,2,FALSE),\"\n\",VLOOKUP($C21,'KH - Block3'!$C$2:$E$15,2,FALSE))","v":"[B]\nApply the different stages of qualitative data analysis (such as transcription, coding, comparison of key topics, synthesis and extraction of relevant verbatim reports).\n\nTranscribe, summarise, and categorise elements from qualitative data collections.\n\nKnow how to code manually and produce a synthesis with the onset of a “profiling” analysis.\n\n[D]\nUse qualitative data analysis software (such as coding or lexicometrics software).\n\nUse transcription software."},{"$f":"CONCATENATE(VLOOKUP($C19,'KH - Block3'!$C$2:$E$15,3,FALSE),\"\n\",VLOOKUP($C20,'KH - Block3'!$C$2:$E$15,3,FALSE),\"\n\",VLOOKUP($C21,'KH - Block3'!$C$2:$E$15,3,FALSE))","v":"[B]\nBe familiar with issues related to qualitative data analysis (such as objectives, limitations).\n[C]\nSupport program [and M&E] teams in producing an analysis plan prior to quality data collection.\n\nInterpret the needs of the program [and M&E] teams in terms of qualitative data analysis and representation.\n\nKnow how to analyse the coding outcome by highlighting complex trends and typical profiles.\n"}]
["S3.3","A",{"$f":"CONCATENATE('SF - Blocks'!$A22,'SF - Blocks'!$B22)","v":"S3.3A"},{"$f":"VLOOKUP($C22,'KH - Block3'!$C$2:$E$15,2,FALSE)","v":"[A]\nManipulate a mobile device to collect geographical data (GPS / smartphone…) and exploit data collected by these means.\n\nUse basic graphical representation modes (point, polygon, line, etc.).\n\nProduce simple maps on tools such as Google Earth or uMAP."},{"$f":"VLOOKUP($C22,'KH - Block3'!$C$2:$E$15,3,FALSE)","v":"[A]\nUnderstand basic geographical concepts such as GPS format, latitude/longitude, administrative data or geographically transposable addresses."}]
["S3.3","B",{"$f":"CONCATENATE('SF - Blocks'!$A23,'SF - Blocks'!$B23)","v":"S3.3B"},{"$f":"CONCATENATE(VLOOKUP($C22,'KH - Block3'!$C$2:$E$15,2,FALSE),\"\n\",VLOOKUP($C23,'KH - Block3'!$C$2:$E$15,2,FALSE))","v":"[A]\nManipulate a mobile device to collect geographical data (GPS / smartphone…) and exploit data collected by these means.\n\nUse basic graphical representation modes (point, polygon, line, etc.).\n\nProduce simple maps on tools such as Google Earth or uMAP.\n[B]\nStructure associated geographic and attribute data with the aim of producing maps.\n\nImport data into QGIS or ArcGIS (e.g., vector and raster layers, transform GPS data…), with data cleaning capability, and occasionally some simple spatial processing (e.g., Cross-referencing data, buffer zones…).\n\nProduce simple maps using tools such as QGIS or ArcGIS.\n\nImplement and technically support a simple GIS project using tools such as QGIS or ArcGIS."},{"$f":"CONCATENATE(VLOOKUP($C22,'KH - Block3'!$C$2:$E$15,3,FALSE),\"\n\",VLOOKUP($C23,'KH - Block3'!$C$2:$E$15,3,FALSE))","v":"[A]\nUnderstand basic geographical concepts such as GPS format, latitude/longitude, administrative data or geographically transposable addresses.\n[B]\nBe familiar with and know how to apply the rules of graphical semiology (visual variables types and appropriate modes of representation) and geographical concepts (geodesy, projection, metadata…).\n\nBe familiar with all of the components of a map (e.g., title, legend, source, North arrow, scale, disclaimers...) as well as all of the types of maps (e.g., basemap, thematic…).\n\nBe familiar with best practices for structuring geographic data sets to ensure consistency."}]
["S3.3","C",{"$f":"CONCATENATE('SF - Blocks'!$A24,'SF - Blocks'!$B24)","v":"S3.3C"},{"$f":"CONCATENATE(VLOOKUP($C22,'KH - Block3'!$C$2:$E$15,2,FALSE),\"\n\",VLOOKUP($C23,'KH - Block3'!$C$2:$E$15,2,FALSE),\"\n\",VLOOKUP($C24,'KH - Block3'!$C$2:$E$15,2,FALSE))","v":"[A]\nManipulate a mobile device to collect geographical data (GPS / smartphone…) and exploit data collected by these means.\n\nUse basic graphical representation modes (point, polygon, line, etc.).\n\nProduce simple maps on tools such as Google Earth or uMAP.\n[B]\nStructure associated geographic and attribute data with the aim of producing maps.\n\nImport data into QGIS or ArcGIS (e.g., vector and raster layers, transform GPS data…), with data cleaning capability, and occasionally some simple spatial processing (e.g., Cross-referencing data, buffer zones…).\n\nProduce simple maps using tools such as QGIS or ArcGIS.\n\nImplement and technically support a simple GIS project using tools such as QGIS or ArcGIS.\n"},{"$f":"CONCATENATE(VLOOKUP($C22,'KH - Block3'!$C$2:$E$15,3,FALSE),\"\n\",VLOOKUP($C23,'KH - Block3'!$C$2:$E$15,3,FALSE),\"\n\",VLOOKUP($C24,'KH - Block3'!$C$2:$E$15,3,FALSE))","v":"[A]\nUnderstand basic geographical concepts such as GPS format, latitude/longitude, administrative data or geographically transposable addresses.\n[B]\nBe familiar with and know how to apply the rules of graphical semiology (visual variables types and appropriate modes of representation) and geographical concepts (geodesy, projection, metadata…).\n\nBe familiar with all of the components of a map (e.g., title, legend, source, North arrow, scale, disclaimers...) as well as all of the types of maps (e.g., basemap, thematic…).\n\nBe familiar with best practices for structuring geographic data sets to ensure consistency.\n[C]\nCoordinate the implementation of a comprehensive mission-wide geographic information system."}]
["s3.3","D",{"$f":"CONCATENATE('SF - Blocks'!$A25,'SF - Blocks'!$B25)","v":"s3.3D"},{"$f":"CONCATENATE(VLOOKUP($C22,'KH - Block3'!$C$2:$E$15,2,FALSE),\"\n\",VLOOKUP($C23,'KH - Block3'!$C$2:$E$15,2,FALSE),\"\n\",VLOOKUP($C24,'KH - Block3'!$C$2:$E$15,2,FALSE),\"\n\",VLOOKUP($C25,'KH - Block3'!$C$2:$E$15,2,FALSE))","v":"[A]\nManipulate a mobile device to collect geographical data (GPS / smartphone…) and exploit data collected by these means.\n\nUse basic graphical representation modes (point, polygon, line, etc.).\n\nProduce simple maps on tools such as Google Earth or uMAP.\n[B]\nStructure associated geographic and attribute data with the aim of producing maps.\n\nImport data into QGIS or ArcGIS (e.g., vector and raster layers, transform GPS data…), with data cleaning capability, and occasionally some simple spatial processing (e.g., Cross-referencing data, buffer zones…).\n\nProduce simple maps using tools such as QGIS or ArcGIS.\n\nImplement and technically support a simple GIS project using tools such as QGIS or ArcGIS.\n\n[D]\nProduce advanced maps (e.g., significant number of layers, complex representation modes).\n\nConnect the GIS to external databases and transform data.\n\nFrequently perform advanced GIS processing (e.g., satellite image processing, raster data, etc.) and mass processing on the data.\n\nImplement and maintain a complex GIS (multi-layered, geographic and project) offline.\n\nImplement and maintain a dynamic online mapping platform."},{"$f":"CONCATENATE(VLOOKUP($C22,'KH - Block3'!$C$2:$E$15,3,FALSE),\"\n\",VLOOKUP($C23,'KH - Block3'!$C$2:$E$15,3,FALSE),\"\n\",VLOOKUP($C24,'KH - Block3'!$C$2:$E$15,3,FALSE),\"\n\",VLOOKUP($C25,'KH - Block3'!$C$2:$E$15,3,FALSE))","v":"[A]\nUnderstand basic geographical concepts such as GPS format, latitude/longitude, administrative data or geographically transposable addresses.\n[B]\nBe familiar with and know how to apply the rules of graphical semiology (visual variables types and appropriate modes of representation) and geographical concepts (geodesy, projection, metadata…).\n\nBe familiar with all of the components of a map (e.g., title, legend, source, North arrow, scale, disclaimers...) as well as all of the types of maps (e.g., basemap, thematic…).\n\nBe familiar with best practices for structuring geographic data sets to ensure consistency.\n[C]\nCoordinate the implementation of a comprehensive mission-wide geographic information system.\n"}]
["S3.4","B",{"$f":"CONCATENATE('SF - Blocks'!$A26,'SF - Blocks'!$B26)","v":"S3.4B"},{"$f":"VLOOKUP($C26,'KH - Block3'!$C$2:$E$15,2,FALSE)","v":"[B]\nProduce communication materials.\n\nCreate simple computer graphics from the data."},{"$f":"VLOOKUP($C26,'KH - Block3'!$C$2:$E$15,3,FALSE)","v":"[B]\nEnsure and guide the use of data and analysis (e.g., ability to stand back vis-à-vis data use, coordination with program teams, put collection and analysis needs / macro vision into perspective).\n\nProvide a framework (statistical limits, biases identified) for the interpretations made following data analysis."}]
["S3.4","C",{"$f":"CONCATENATE('SF - Blocks'!$A27,'SF - Blocks'!$B27)","v":"S3.4C"},{"$f":"CONCATENATE(VLOOKUP($C26,'KH - Block3'!$C$2:$E$15,2,FALSE),\"\n\",VLOOKUP($C27,'KH - Block3'!$C$2:$E$15,2,FALSE))","v":"[B]\nProduce communication materials.\n\nCreate simple computer graphics from the data.\n"},{"$f":"CONCATENATE(VLOOKUP($C26,'KH - Block3'!$C$2:$E$15,3,FALSE),\"\n\",VLOOKUP($C27,'KH - Block3'!$C$2:$E$15,3,FALSE))","v":"[B]\nEnsure and guide the use of data and analysis (e.g., ability to stand back vis-à-vis data use, coordination with program teams, put collection and analysis needs / macro vision into perspective).\n\nProvide a framework (statistical limits, biases identified) for the interpretations made following data analysis.\n[C]\nGuide best communication practices (identify target audience, simplify data).\n\nDecide which external communication media to produce.\n\nProduce coherent and harmonised data analysis and usage systems, meeting the needs of the program [and M&E]."}]
["S3.4","D",{"$f":"CONCATENATE('SF - Blocks'!$A28,'SF - Blocks'!$B28)","v":"S3.4D"},{"$f":"CONCATENATE(VLOOKUP($C26,'KH - Block3'!$C$2:$E$15,2,FALSE),\"\n\",VLOOKUP($C27,'KH - Block3'!$C$2:$E$15,2,FALSE),\"\n\",VLOOKUP($C28,'KH - Block3'!$C$2:$E$15,2,FALSE))","v":"[B]\nProduce communication materials.\n\nCreate simple computer graphics from the data.\n\n[D]\nProduce illustrations gathered from data analysis using dedicated software such as Scribus or Illustrator."},{"$f":"CONCATENATE(VLOOKUP($C26,'KH - Block3'!$C$2:$E$15,3,FALSE),\"\n\",VLOOKUP($C27,'KH - Block3'!$C$2:$E$15,3,FALSE),\"\n\",VLOOKUP($C28,'KH - Block3'!$C$2:$E$15,3,FALSE))","v":"[B]\nEnsure and guide the use of data and analysis (e.g., ability to stand back vis-à-vis data use, coordination with program teams, put collection and analysis needs / macro vision into perspective).\n\nProvide a framework (statistical limits, biases identified) for the interpretations made following data analysis.\n[C]\nGuide best communication practices (identify target audience, simplify data).\n\nDecide which external communication media to produce.\n\nProduce coherent and harmonised data analysis and usage systems, meeting the needs of the program [and M&E].\n"}]
["S4.1","A",{"$f":"CONCATENATE('SF - Blocks'!$A29,'SF - Blocks'!$B29)","v":"S4.1A"},{"$f":"VLOOKUP($C29,'KH - Block4'!$C$2:$E$6,2,FALSE)","v":"[A]\nMaster the data management cycle and apply it to data preparation and cleaning practices.\n\nPrepare for data collection: consistent naming (e.g., PCODE), attention to data types and attributes.\n\nClean up duplicate and inconsistent data.\n\nCheck the collected data: spot check, calculation, meaning."},{"$f":"VLOOKUP($C29,'KH - Block4'!$C$2:$E$6,3,FALSE)","v":"[A]\nBe aware of the issues involved in collecting certain program-specific information."}]
["S4.1","B",{"$f":"CONCATENATE('SF - Blocks'!$A30,'SF - Blocks'!$B30)","v":"S4.1B"},{"$f":"CONCATENATE(VLOOKUP($C29,'KH - Block4'!$C$2:$E$6,2,FALSE),\"\n\",VLOOKUP($C30,'KH - Block4'!$C$2:$E$6,2,FALSE))","v":"[A]\nMaster the data management cycle and apply it to data preparation and cleaning practices.\n\nPrepare for data collection: consistent naming (e.g., PCODE), attention to data types and attributes.\n\nClean up duplicate and inconsistent data.\n\nCheck the collected data: spot check, calculation, meaning.\n[B]\nImplement workflows in a team ensuring traceability, reliability, consistency and quality:\n• use of metadata and monitoring of the data collection,\n• Data validation \n• Triangulation of data with other sources,\n• editing and deletion rules,\n• refreshing data and backups of previous copies.\n\nEnsure data availability: storage of single-entry table data (allowing for efficient analysis queries such as pivot tables)."},{"$f":"CONCATENATE(VLOOKUP($C29,'KH - Block4'!$C$2:$E$6,3,FALSE),\"\n\",VLOOKUP($C30,'KH - Block4'!$C$2:$E$6,3,FALSE))","v":"[A]\nBe aware of the issues involved in collecting certain program-specific information.\n[B]\nGet involved in setting the goals for an M&E plan and challenge the program teams.\n\nInterpret M&E needs, in collection, management and analysis methods.\n\nCoordinate quality control methods on a mission-wide basis.\n\nEnsure a consistent level of data and analysis quality.\n\nSupport program teams in defining standards for the calculation of their indicators (e.g., counting beneficiaries or results)."}]
["S4.1","C",{"$f":"CONCATENATE('SF - Blocks'!$A31,'SF - Blocks'!$B31)","v":"S4.1C"},{"$f":"CONCATENATE(VLOOKUP($C29,'KH - Block4'!$C$2:$E$6,2,FALSE),\"\n\",VLOOKUP($C30,'KH - Block4'!$C$2:$E$6,2,FALSE),\"\n\",VLOOKUP($C31,'KH - Block4'!$C$2:$E$6,2,FALSE))","v":"[A]\nMaster the data management cycle and apply it to data preparation and cleaning practices.\n\nPrepare for data collection: consistent naming (e.g., PCODE), attention to data types and attributes.\n\nClean up duplicate and inconsistent data.\n\nCheck the collected data: spot check, calculation, meaning.\n[B]\nImplement workflows in a team ensuring traceability, reliability, consistency and quality:\n• use of metadata and monitoring of the data collection,\n• Data validation \n• Triangulation of data with other sources,\n• editing and deletion rules,\n• refreshing data and backups of previous copies.\n\nEnsure data availability: storage of single-entry table data (allowing for efficient analysis queries such as pivot tables).\n"},{"$f":"CONCATENATE(VLOOKUP($C29,'KH - Block4'!$C$2:$E$6,3,FALSE),\"\n\",VLOOKUP($C30,'KH - Block4'!$C$2:$E$6,3,FALSE),\"\n\",VLOOKUP($C31,'KH - Block4'!$C$2:$E$6,3,FALSE))","v":"[A]\nBe aware of the issues involved in collecting certain program-specific information.\n[B]\nGet involved in setting the goals for an M&E plan and challenge the program teams.\n\nInterpret M&E needs, in collection, management and analysis methods.\n\nCoordinate quality control methods on a mission-wide basis.\n\nEnsure a consistent level of data and analysis quality.\n\nSupport program teams in defining standards for the calculation of their indicators (e.g., counting beneficiaries or results).\n[C]\nEvaluate data collection, management, and analysis methods against data quality objectives.\n\nAssess data quality, reliability, traceability and availability and identify gaps (e.g., data quality method audit, of the USAID DQA type for instance).\n\nContribute to the data management aspects of the M&E strategy, the strategy for collecting, managing and analysing data across multiple projects.\n\nRecommend best practices in terms of data management.\n\nIntegrate data management principles into an M&E strategy\n\nAssess M&E feasibility from a data management, tool management interoperability, aggregation, data integrity perspective."}]
["S4.2","B",{"$f":"CONCATENATE('SF - Blocks'!$A32,'SF - Blocks'!$B32)","v":"S4.2B"},{"$f":"VLOOKUP($C32,'KH - Block4'!$C$2:$E$6,2,FALSE)","v":"[B]\nSynthesise qualitative and quantitative data for the program teams.\nBuild and understanding of data and develop skills their analysis, with a view to decision-making:\n• understand what is included in a data set,\n• to which questions data may help provide an answer,\n• understand the data (types, attributes, data vs. information),\n• know how to analyse the data (causation vs.  correlation),\n• understand data aggregation.\n\nTrain in best practices at all stages of the data cycle: collection, cleaning, analysis, for instance:\n• sampling, data aggregation,\n• Data cleaning\n• use of suitable visuals (map, type of chart, representation for qualitative analysis).\n\nInitiate reflection around data quality, management, and analysis objectives:\n• understanding of the origin and reliability of the data,\n• collection methods,\n• data protection."},{"$f":"VLOOKUP($C32,'KH - Block4'!$C$2:$E$6,3,FALSE)","v":"[B]\nAdapt training to one’s public and spark interest within the organisation (pedagogy and popularisation).\n\nGuide program teams in their understanding of the quantitative, qualitative and cartographic analysis produced.\n\nAssess the teams’ levels and needs.\n\nGuide data management teams in their data collection, management and analysis practices.\n\nEnforce data management best practices across departments."}]
["S4.2","C",{"$f":"CONCATENATE('SF - Blocks'!$A33,'SF - Blocks'!$B33)","v":"S4.2C"},{"$f":"CONCATENATE(VLOOKUP($C32,'KH - Block4'!$C$2:$E$6,2,FALSE),\"\n\",VLOOKUP($C33,'KH - Block4'!$C$2:$E$6,2,FALSE))","v":"[B]\nSynthesise qualitative and quantitative data for the program teams.\nBuild and understanding of data and develop skills their analysis, with a view to decision-making:\n• understand what is included in a data set,\n• to which questions data may help provide an answer,\n• understand the data (types, attributes, data vs. information),\n• know how to analyse the data (causation vs.  correlation),\n• understand data aggregation.\n\nTrain in best practices at all stages of the data cycle: collection, cleaning, analysis, for instance:\n• sampling, data aggregation,\n• Data cleaning\n• use of suitable visuals (map, type of chart, representation for qualitative analysis).\n\nInitiate reflection around data quality, management, and analysis objectives:\n• understanding of the origin and reliability of the data,\n• collection methods,\n• data protection.\n"},{"$f":"CONCATENATE(VLOOKUP($C32,'KH - Block4'!$C$2:$E$6,3,FALSE),\"\n\",VLOOKUP($C33,'KH - Block4'!$C$2:$E$6,3,FALSE))","v":"[B]\nAdapt training to one’s public and spark interest within the organisation (pedagogy and popularisation).\n\nGuide program teams in their understanding of the quantitative, qualitative and cartographic analysis produced.\n\nAssess the teams’ levels and needs.\n\nGuide data management teams in their data collection, management and analysis practices.\n\nEnforce data management best practices across departments.\n[C]\nAssess data quality and identify gaps.\n\nGuide the teams in charge of the data management strategy in their data collection, management and analysis practices.\n\nDevelop and steer an action plan for improving data management within an organisation.\n\nDefine data management best practices across departments.\n\nFoster change management within an organisation."}]
["S5.1","A",{"$f":"CONCATENATE('SF - Blocks'!$A34,'SF - Blocks'!$B34)","v":"S5.1A"},{"$f":"VLOOKUP($C34,'KH - Block5'!$C$2:$E$11,2,FALSE)","v":"[A]\nDistinguish personal from sensitive data.\n\nExecute clear instructions for data protection (configuration of tools, obtaining consent, execution of archive protocols, or de-identification, anonymisation, pseudonymisation, aggregation, etc.)."},{"$f":"VLOOKUP($C34,'KH - Block5'!$C$2:$E$11,3,FALSE)","v":0}]
["S5.1","B",{"$f":"CONCATENATE('SF - Blocks'!$A35,'SF - Blocks'!$B35)","v":"S5.1B"},{"$f":"CONCATENATE(VLOOKUP($C34,'KH - Block5'!$C$2:$E$11,2,FALSE),\"\n\",VLOOKUP($C35,'KH - Block5'!$C$2:$E$11,2,FALSE))","v":"[A]\nDistinguish personal from sensitive data.\n\nExecute clear instructions for data protection (configuration of tools, obtaining consent, execution of archive protocols, or de-identification, anonymisation, pseudonymisation, aggregation, etc.).\n[B]\nBe familiar with and enforce the key elements of international data protection regulations (GDPR etc.).\n\nBe familiar with and enforce the key elements of the data protection regulation of the country or countries of intervention, such as the principles of processing limitation, limited conservation, proportionality, the rights of the data subject, etc.\n\nImplement data protection measures, from the time of default data design and protection, for instance via the choice and configuration of data management tools, the design of collection forms, etc."},{"$f":"CONCATENATE(VLOOKUP($C34,'KH - Block5'!$C$2:$E$11,3,FALSE),\"\n\",VLOOKUP($C35,'KH - Block5'!$C$2:$E$11,3,FALSE))","v":"\n[B]\nBriefly analyse legislation.\n\nDesign and implement awareness-raising and training actions.\n\nIdentify action points to improve program data protection.\n\nAdapt the recommended measures to the intervention contexts.\n\nEstablish practices, procedures and methodologies allowing the implementation of key data protection principles, for example:\n• choice of a legal basis, \n• obtainment of informed consent,\n• choice of a retention period, \n• implementation of archiving protocols, de-identification, anonymisation, pseudonymisation, aggregation, etc."}]
["S5.1","C",{"$f":"CONCATENATE('SF - Blocks'!$A36,'SF - Blocks'!$B36)","v":"S5.1C"},{"$f":"CONCATENATE(VLOOKUP($C34,'KH - Block5'!$C$2:$E$11,2,FALSE),\"\n\",VLOOKUP($C35,'KH - Block5'!$C$2:$E$11,2,FALSE),\"\n\",VLOOKUP($C36,'KH - Block5'!$C$2:$E$11,2,FALSE))","v":"[A]\nDistinguish personal from sensitive data.\n\nExecute clear instructions for data protection (configuration of tools, obtaining consent, execution of archive protocols, or de-identification, anonymisation, pseudonymisation, aggregation, etc.).\n[B]\nBe familiar with and enforce the key elements of international data protection regulations (GDPR etc.).\n\nBe familiar with and enforce the key elements of the data protection regulation of the country or countries of intervention, such as the principles of processing limitation, limited conservation, proportionality, the rights of the data subject, etc.\n\nImplement data protection measures, from the time of default data design and protection, for instance via the choice and configuration of data management tools, the design of collection forms, etc.\n[C]\nHave specific knowledge of the international and national data protection legislation.\n\nEstablish practices, procedures and methodologies ensuring data protection of all components, for instance:\n• draft of data-sharing agreements,\n• evaluation of a sub-contractor,\n\nDrafting or reviewing DTA/DSA type agreements or contracts.\n\nConduct and draft a Data Protection Impact Assessment (DPIA) on a data processing or simple project, involving few players or few technical solutions.\n\nEnsure contractual monitoring of partners and donors on the data protection-related dimension."},{"$f":"CONCATENATE(VLOOKUP($C34,'KH - Block5'!$C$2:$E$11,3,FALSE),\"\n\",VLOOKUP($C35,'KH - Block5'!$C$2:$E$11,3,FALSE),\"\n\",VLOOKUP($C36,'KH - Block5'!$C$2:$E$11,3,FALSE))","v":"\n[B]\nBriefly analyse legislation.\n\nDesign and implement awareness-raising and training actions.\n\nIdentify action points to improve program data protection.\n\nAdapt the recommended measures to the intervention contexts.\n\nEstablish practices, procedures and methodologies allowing the implementation of key data protection principles, for example:\n• choice of a legal basis, \n• obtainment of informed consent,\n• choice of a retention period, \n• implementation of archiving protocols, de-identification, anonymisation, pseudonymisation, aggregation, etc.\n[C]\nMake a diagnosis and implement an action plan to ensure compliance with national and international legislation.\n\nAnalyse whether a processing is compliant and highlight non-conformities.\n\nDevelop a data protection strategy for a mission or organisation.\n\nDesign and disseminate practices, procedures and methodologies allowing the implementation of key data protection principles."}]
["S5.1","D",{"$f":"CONCATENATE('SF - Blocks'!$A37,'SF - Blocks'!$B37)","v":"S5.1D"},{"$f":"CONCATENATE(VLOOKUP($C34,'KH - Block5'!$C$2:$E$11,2,FALSE),\"\n\",VLOOKUP($C35,'KH - Block5'!$C$2:$E$11,2,FALSE),\"\n\",VLOOKUP($C36,'KH - Block5'!$C$2:$E$11,2,FALSE),\"\n\",VLOOKUP($C37,'KH - Block5'!$C$2:$E$11,2,FALSE))","v":"[A]\nDistinguish personal from sensitive data.\n\nExecute clear instructions for data protection (configuration of tools, obtaining consent, execution of archive protocols, or de-identification, anonymisation, pseudonymisation, aggregation, etc.).\n[B]\nBe familiar with and enforce the key elements of international data protection regulations (GDPR etc.).\n\nBe familiar with and enforce the key elements of the data protection regulation of the country or countries of intervention, such as the principles of processing limitation, limited conservation, proportionality, the rights of the data subject, etc.\n\nImplement data protection measures, from the time of default data design and protection, for instance via the choice and configuration of data management tools, the design of collection forms, etc.\n[C]\nHave specific knowledge of the international and national data protection legislation.\n\nEstablish practices, procedures and methodologies ensuring data protection of all components, for instance:\n• draft of data-sharing agreements,\n• evaluation of a sub-contractor,\n\nDrafting or reviewing DTA/DSA type agreements or contracts.\n\nConduct and draft a Data Protection Impact Assessment (DPIA) on a data processing or simple project, involving few players or few technical solutions.\n\nEnsure contractual monitoring of partners and donors on the data protection-related dimension.\n[D]\nConduct and draft a Data Protection Impact Assessment (DPIA) on a complex data processing at mission or organisational level, involving a great deal of solutions and players."},{"$f":"CONCATENATE(VLOOKUP($C34,'KH - Block5'!$C$2:$E$11,3,FALSE),\"\n\",VLOOKUP($C35,'KH - Block5'!$C$2:$E$11,3,FALSE),\"\n\",VLOOKUP($C36,'KH - Block5'!$C$2:$E$11,3,FALSE),\"\n\",VLOOKUP($C37,'KH - Block5'!$C$2:$E$11,3,FALSE))","v":"\n[B]\nBriefly analyse legislation.\n\nDesign and implement awareness-raising and training actions.\n\nIdentify action points to improve program data protection.\n\nAdapt the recommended measures to the intervention contexts.\n\nEstablish practices, procedures and methodologies allowing the implementation of key data protection principles, for example:\n• choice of a legal basis, \n• obtainment of informed consent,\n• choice of a retention period, \n• implementation of archiving protocols, de-identification, anonymisation, pseudonymisation, aggregation, etc.\n[C]\nMake a diagnosis and implement an action plan to ensure compliance with national and international legislation.\n\nAnalyse whether a processing is compliant and highlight non-conformities.\n\nDevelop a data protection strategy for a mission or organisation.\n\nDesign and disseminate practices, procedures and methodologies allowing the implementation of key data protection principles.\n"}]
["S5.2","B",{"$f":"CONCATENATE('SF - Blocks'!$A38,'SF - Blocks'!$B38)","v":"S5.2B"},{"$f":"VLOOKUP($C38,'KH - Block5'!$C$2:$E$11,2,FALSE)","v":"[B]\nAdopt the data protection standards applied to humanitarian aid and international development (Signal type Code of Ethics, Principles for Digital Development, etc.) and context (non-state armed groups, medical data, etc.).\n\nImplement donor guidelines for data protection."},{"$f":"VLOOKUP($C38,'KH - Block5'!$C$2:$E$11,3,FALSE)","v":"[B]\nIdentify the key ethical issues of a data processing or project and alert if there is any doubt or identification of a risk (for instance, block a data transfer in the absence of a risk analysis).\n\nEnsure ownership by program teams of ethical issues (awareness raising techniques and training)."}]
["S5.2","C",{"$f":"CONCATENATE('SF - Blocks'!$A39,'SF - Blocks'!$B39)","v":"S5.2C"},{"$f":"CONCATENATE(VLOOKUP($C38,'KH - Block5'!$C$2:$E$11,2,FALSE),\"\n\",VLOOKUP($C39,'KH - Block5'!$C$2:$E$11,2,FALSE))","v":"[B]\nAdopt the data protection standards applied to humanitarian aid and international development (Signal type Code of Ethics, Principles for Digital Development, etc.) and context (non-state armed groups, medical data, etc.).\n\nImplement donor guidelines for data protection.\n"},{"$f":"CONCATENATE(VLOOKUP($C38,'KH - Block5'!$C$2:$E$11,3,FALSE),\"\n\",VLOOKUP($C39,'KH - Block5'!$C$2:$E$11,3,FALSE))","v":"[B]\nIdentify the key ethical issues of a data processing or project and alert if there is any doubt or identification of a risk (for instance, block a data transfer in the absence of a risk analysis).\n\nEnsure ownership by program teams of ethical issues (awareness raising techniques and training).\n[C]\nIdentify the issues at stake in the debate related to the application of data protection concepts and laws in the field of humanitarian aid and international development:\n• concept of responsible management vs. protection,\n• application of informed consent, inadequacy of the GDPR for the intervention context.\n\nConduct an in-depth assessment of the ethical issues of a data processing or project (be able to argue independently to refuse data transfer to a partner, assess the level of risk of data collection, etc.).\n\nMake a diagnosis and implement an action plan to comply with national and international legislation."}]
["S5.3","A",{"$f":"CONCATENATE('SF - Blocks'!$A40,'SF - Blocks'!$B40)","v":"S5.3A"},{"$f":"VLOOKUP($C40,'KH - Block5'!$C$2:$E$11,2,FALSE)","v":"[A]\nPre-identify the types of data that need to be protected (sensitive, personal, community data).\n\nHave simple reflexes for securing paper based and digital data: locked cupboard, choice of a secured password, encrypting a file, sharing data internally and externally etc.\n\nBe familiar with the best practices for securing the various tools used."},{"$f":"VLOOKUP($C40,'KH - Block5'!$C$2:$E$11,3,FALSE)","v":0}]
["S5.3","B",{"$f":"CONCATENATE('SF - Blocks'!$A41,'SF - Blocks'!$B41)","v":"S5.3B"},{"$f":"CONCATENATE(VLOOKUP($C40,'KH - Block5'!$C$2:$E$11,2,FALSE),\"\n\",VLOOKUP($C41,'KH - Block5'!$C$2:$E$11,2,FALSE))","v":"[A]\nPre-identify the types of data that need to be protected (sensitive, personal, community data).\n\nHave simple reflexes for securing paper based and digital data: locked cupboard, choice of a secured password, encrypting a file, sharing data internally and externally etc.\n\nBe familiar with the best practices for securing the various tools used.\n[B]\nImplement project-wide securing of paper based and digital data (shared cloud encryption, password sharing modality, choice of authentication method, user access management, traceability measures, password strength assessment, back-up modality, anonymisation and pseudonymisation method etc.)\n\nBe familiar with the entire range of data security components (including methods for securing the various tools used)."},{"$f":"CONCATENATE(VLOOKUP($C40,'KH - Block5'!$C$2:$E$11,3,FALSE),\"\n\",VLOOKUP($C41,'KH - Block5'!$C$2:$E$11,3,FALSE))","v":"\n[B]\nAdapt the organisation’s guidelines to specific contexts and develop standard practice guides. \n\nDisseminate and know how to ensure implementation of procedures."}]
["S5.3","C",{"$f":"CONCATENATE('SF - Blocks'!$A42,'SF - Blocks'!$B42)","v":"S5.3C"},{"$f":"CONCATENATE(VLOOKUP($C40,'KH - Block5'!$C$2:$E$11,2,FALSE),\"\n\",VLOOKUP($C41,'KH - Block5'!$C$2:$E$11,2,FALSE),\"\n\",VLOOKUP($C42,'KH - Block5'!$C$2:$E$11,2,FALSE))","v":"[A]\nPre-identify the types of data that need to be protected (sensitive, personal, community data).\n\nHave simple reflexes for securing paper based and digital data: locked cupboard, choice of a secured password, encrypting a file, sharing data internally and externally etc.\n\nBe familiar with the best practices for securing the various tools used.\n[B]\nImplement project-wide securing of paper based and digital data (shared cloud encryption, password sharing modality, choice of authentication method, user access management, traceability measures, password strength assessment, back-up modality, anonymisation and pseudonymisation method etc.)\n\nBe familiar with the entire range of data security components (including methods for securing the various tools used).\n[C]\nPerform “basic” data security audits.\n\nGain a thorough understanding of the various components of technical and organisational data security and the degrees associated with each:\n• difference between encryption during transfer vs. during storage,\n• server certification, PGP key concept or AES standard etc."},{"$f":"CONCATENATE(VLOOKUP($C40,'KH - Block5'!$C$2:$E$11,3,FALSE),\"\n\",VLOOKUP($C41,'KH - Block5'!$C$2:$E$11,3,FALSE),\"\n\",VLOOKUP($C42,'KH - Block5'!$C$2:$E$11,3,FALSE))","v":"\n[B]\nAdapt the organisation’s guidelines to specific contexts and develop standard practice guides. \n\nDisseminate and know how to ensure implementation of procedures.\n[C]\nDesign and align data security practices across the organisation.\n\nAssess the level of data security implemented in a project or organisation or with a partner (assess practices, assess relevance and appropriateness of the chosen measures).\n\nBe able to communicate easily with IT teams with regards to cybersecurity."}]
["S5.3","D",{"$f":"CONCATENATE('SF - Blocks'!$A43,'SF - Blocks'!$B43)","v":"S5.3D"},{"$f":"CONCATENATE(VLOOKUP($C40,'KH - Block5'!$C$2:$E$11,2,FALSE),\"\n\",VLOOKUP($C41,'KH - Block5'!$C$2:$E$11,2,FALSE),\"\n\",VLOOKUP($C42,'KH - Block5'!$C$2:$E$11,2,FALSE),\"\n\",VLOOKUP($C43,'KH - Block5'!$C$2:$E$11,2,FALSE))","v":"[A]\nPre-identify the types of data that need to be protected (sensitive, personal, community data).\n\nHave simple reflexes for securing paper based and digital data: locked cupboard, choice of a secured password, encrypting a file, sharing data internally and externally etc.\n\nBe familiar with the best practices for securing the various tools used.\n[B]\nImplement project-wide securing of paper based and digital data (shared cloud encryption, password sharing modality, choice of authentication method, user access management, traceability measures, password strength assessment, back-up modality, anonymisation and pseudonymisation method etc.)\n\nBe familiar with the entire range of data security components (including methods for securing the various tools used).\n[C]\nPerform “basic” data security audits.\n\nGain a thorough understanding of the various components of technical and organisational data security and the degrees associated with each:\n• difference between encryption during transfer vs. during storage,\n• server certification, PGP key concept or AES standard etc.\n[D]\nBe thoroughly familiar with the organisation’s IT environment and the appropriate cybersecurity measures associated with it.\n\nApply advanced data security measures in a complex environment (players, tools, and multiple location).\n\nPerform complete data security audits."},{"$f":"CONCATENATE(VLOOKUP($C40,'KH - Block5'!$C$2:$E$11,3,FALSE),\"\n\",VLOOKUP($C41,'KH - Block5'!$C$2:$E$11,3,FALSE),\"\n\",VLOOKUP($C42,'KH - Block5'!$C$2:$E$11,3,FALSE),\"\n\",VLOOKUP($C43,'KH - Block5'!$C$2:$E$11,3,FALSE))","v":"\n[B]\nAdapt the organisation’s guidelines to specific contexts and develop standard practice guides. \n\nDisseminate and know how to ensure implementation of procedures.\n[C]\nDesign and align data security practices across the organisation.\n\nAssess the level of data security implemented in a project or organisation or with a partner (assess practices, assess relevance and appropriateness of the chosen measures).\n\nBe able to communicate easily with IT teams with regards to cybersecurity.\n"}]

{"sheet":"listes","index":9,"n_rows":26,"n_cols":6,"rows_kept":26,"cut":false,"hidden":true,"merged":[]}
["Skill","Level",null,"Scenario","scenario","poste"]
["S 1.1","B",null,"ScenarioA","ScenarioA","Project Manager"]
["S 1.1","C",null,"ScenarioB","ScenarioA","Technical and Methodological Support"]
["S 1.2","B",null,"ScenarioC","ScenarioB","Project Manager"]
["S 1.2","C",null,"ScenarioD","ScenarioB","Technical and Methodological Support"]
["S 1.3","C",null,"ScenarioE","ScenarioB","Technical Program Data Management"]
["S 2.1","A",null,null,"ScenarioC","General Coordination"]
["S 2.1","B",null,null,"ScenarioC","Technical and Methodological Support"]
["S 2.1","C",null,null,"ScenarioC","M&E-Program Data Management Manager (field)"]
["S 2.1","D",null,null,"ScenarioD","Program Data Management Coordination"]
["S 2.2","A",null,null,"ScenarioD","Program Data Management Manager"]
["S 2.2","B",null,null,"ScenarioE","Program Data Management Coordination"]
["S 2.2","C",null,null,"ScenarioE","Technical Program Data Management at national level"]
["S 2.2","D",null,null,"ScenarioE","Program Data Management Manager (field)"]
["S 3.1","A",null,null,"ScenarioE","Method and Training Support"]
["S 3.1","B"]
["S 3.1","C"]
["S 3.2","B"]
["S 3.2","C"]
["S 3.2","D"]
["S 3.3","A"]
["S 3.3","B"]
["S 3.3","C"]
["S 3.4","C"]
["S 5.3","B"]
["S 5.3","C"]