After you have determined what you want to measure, it is time to decide on the measuring instruments. From experience, we know that many people give up at this step because they don’t know the right measurement tool, and don’t know where to find it. Don’t give up though, this is a step you need to get past. You can do some literature research, ask around in your sector or contact knowledge institutions. We recommend to start as soon as possible with a measuring instrument that has NOT to be perfect from the start! As far as possible, make sure there is:
sufficient (scientific) substantiation
a ‘feasible’ instrument in using
Under this topic you find some rules of thumb on measuring, the figure gives an overview of measuring instruments.
Rules of Thumb
The question drives the method!
Existing (validated) measuring instruments or tailor-made? The advantage of working with an existing The advantage of working with an existing validated measuring instrument is the elimination of the development costs. Setting up a validated measurement instrument yourself itself requires expertise and resources that are usually are too high to be borne by one organization. Opting for a non-validated measurement instrument is cheaper, but carries the risk of not being taken serious.
Qualitative or quantitative data? Choosing measuring instruments that collect qualitative or quantitative collect depends on the research question and personal preferences of the organization and stakeholder(s) for whom the data are collected. s) for whom the data are being collected. Some value only hard data. Others find that Others feel that impact can only be fully represented can only be fully represented by means of narrative data. A balance between the two is the most optimal.
Baseline measurement? A baseline measurement has the great advantage that the difference between the starting point and later measurements can be read off. Although a zero measurement is recommended, it is not always possible. Even without a zero measurement you can start measuring.
Keep it simple and integrate as much as possible into existing processes. Measuring is not only time consuming. Take this extra load into account in advance and keep the measurement design simple by integrating as much as possible into existing processes as much as possible, will promote the sustainability and quality of the data.