The first step in embarking on an IDAP journey is to establish the volume, content and spread of the current situation, understanding where the challenges lie can be the key to unlocking potential. It can also be worthwhile to understand, what is making positive impact - for instance does monitoring and evaluation data provide enough insight to advantage future programs? Often is the case where there much effort going in different directions, usually producing high standard of insight, but without the coordination can seem like a confusing mess. To streamline this, you could interview organisation functional experts, and document their data scope, assets, and initiatives. Laying out the landscape, classifying what works, and what to initiatives develop is a major milestone completed.

The goal of an IDAP is to intelligently predict where NGOs and IDOs should play its next move. So, there is little point in such initiatives if we cannot see the direct impacts it will bring. Thus, setting out business requirements and establishing where data can have meaningful value is imperative. It may be that NGOs and IDOs wish to achieve certain sustainability development goals, or specific programmatic key performance indicators. By setting this requirement, you can tailor the rest of the journey. The idea of determining critical data will ensure that only the data with meaningful relationships to the established requirements will be prioritised. For instance, considering sustainability goals we could define fieldwork data in a specific region or population age group as critical.

Increasing the quality of data can have significant impacts on the insights it brings. Implementing a data governance framework can create a harmonised landscape, increase data quality and efficiency to accessing data. NGOs and IDOs are leveraging the use of a data warehouses, data quality solutions and other tools which enable management of data. If we look at fieldwork data, it is likely to be unstructured and fragmented as it is generated from a variety of sources and tools. There are certain ways in which consistency can be provided to this, choosing a data lake instead of a warehouse, and carrying out a mass data cleansing exercise, will both assist in analysis of this unstructured data. Other methods such as establishing data standards through methods such as data cataloguing and data dictionaries will enable quality reporting, in turn constantly determining a high calibre data landscape.

So far, we have highlighted where our efforts work and where they don’t, understood the need for high data quality and discovered which parts of the business we are going to use this asset for. Setting up a data organisation with assigned responsibilities, data ownership and maintenance is going to turn theory into reality. Typically, NGOs and IDOs with a Chief Data Officer or equivalent are much further along the journey of becoming insight driven than those who do not. Implementing a central data team providing best practices and guidance to the programs or functions will help break down silos and harmonise data processes across NGOs and IDOs.

Improving effectiveness and decision making, whilst serving stakeholders, by developing an integrated solution, can generate value and reduce complexity. This means building the solution hand in hand with users, making them part of the team just as much as the developers, embracing iterations to allow for testing along the way. For instance, if the requirement is to maximize programmatic impact, we work with a country team manager to improve current processes and needs. The best IDAP approaches are designed and implemented with the users not for them.

Applying these five steps and implementing an IDAP approach will increase the digital experience through allowing for a greater diversity on content accessible from fewer channels, at a greater granularity.