A strategic mine plan is a fundamental part of any mining operation. It must provide a realistic and operative extraction and processing schedule, and yield the highest value for the business. For open pit mines, the problem can be modelled as a set of blocks representing the deposit, for each of which we need to decide if it is going to be mined, if so, when and where it will be sent (process, stock or dump).This problem can be proven to be of NP-Hard complexity. The traditional approach used by mining engineers to tackle this complexity is to separate the problem into more tractable components, solving each separately. The first step is to use the Lerchs-Grossman (LG) algorithm to obtain the final pit limit, as well as a set of optimised pit shells (nested pits), using different input prices. Then, using this input, operational phases are designed. Third, the set of phases can be used as an input for a phase-bench style optimisation, usually using a mathematical programming-based algorithm.There are, however, several problems with this approach. First, dividing the problem into simpler parts has the consequence that any compromises made at early stages limit the potential value left for the following steps. Second, LG is a static algorithm, with no concept of the time-value of money, capacity limits, opportunity costs, etc. Phase design is essentially a manual step, for which nested pits provide insufficient information in practice, and therefore the quality of the result in terms of potential net present value (NPV) depends strongly on the experience and expertise of the designer. This means that key input data such as commodity prices, different processes capacities and mine movement limits, are considered only at scheduling, when there is little room for optimisation. This sequential approach limits the potential value in each step, where a simplified problem is addressed, instead of addressing the real, and more complex problem, which is dynamic and should be solved as a whole.We present in this paper an algorithm, and its commercial software implementation, that addresses the dynamic problem as a whole, simultaneously and automatically creating a high-value strategic mine plan that adheres to basic operational constraints, determining dynamic cut-off grades and delivering a set of phases which can serve as a much stronger guide than nested pits for the final design. We discuss some of the key elements of the algorithm and propose a new methodology for strategic mine planning, where phase design dynamically responds to mining strategy definition. Results using different mining and operational parameters on a fictitious copper deposit are used as a demonstrative example.CITATION:Juarez, G, Dodds, R, Echeverria, A, Guzman, J I, Recabarren, M, Ronda, J and Vila-Echague, E, 2014. Open pit strategic mine planning with automatic phase generation, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 147-154 (The Australasian Institute of Mining and Metallurgy: Melbourne).