New energy technologies like photovoltaics, electric vehicles, and heat pumps increasingly find their way to distribution networks. At the time the existing distribution networks were designed, only conventional loads were considered. The capacity of the (existing) distribution networks is therefore insufficient to handle the additional (bidirectional) peak load caused by these new technologies. The distribution system operator (DSO) is facing network congestion. Flexibility to shift and/or change power and energy in time and/or amount is considered as an option to mitigate network congestion with various implicit and explicit mechanisms. This leaves DSOs with the question on how to deploy such mechanisms seamlessly and effectively in daily business with uncertain congestion scenarios and complex integration processes. To tackle these operational challenges, this paper introduces a generic four-step approach to operationalize the flexibility need of a DSO, for any chosen implementation of an implicit or explicit flexibility mechanism (e.g. price-based schemes, flexibility markets, direct control). To this end, this paper addresses the steps: 1. Data acquisition, 2. Forecasting, 3. Decision-making, and 4. Flexibility mechanism interfacing. Furthermore, a particular implementation is described in relation to the Dutch’ H2020 InterFlex demonstrator, showing the field application of the proposed steps. In this demonstrator, a large amount of flexibility (26 electric vehicle charge points of 22kW, a 250kW/315kWh battery energy storage system, and a 260kWp photovoltaic installation) is connected to two 630kVA transformers in a residential area with approximately 350 apartments. The results of the implementation show that the proposed steps enable the DSO to predict congestion, put a monetary value on flexibility, and use this value to evaluate flexibility offered through – in this case study – a flexibility market.