Reviewers are not a uniform group of people. Those who can apply your new idea in their own work certainly appreciate explaining it in a way that is as simple and as direct as possible. They are more likely to give you a negative review if you present your idea in a way that is unnecessarily difficult to understand. So here, there is no conflict between the aims of getting your paper accepted and providing the most value to the reader.
Who you may be concerned about are the reviewers who are from adjacent domains, who may rely on their gut feeling to tell if the paper should be accepted or not, without making it explicit to the editor. They are more likely to recommend rejection when it looks like there is no deep insight in your contribution, and they may use the complexity of it as proxy for the amount of insight. Whether such reviewers are actually common depends on the field. For instance, in computer science with conferences and strict review deadlines, they are probably more common than in journals that take their time to find the optimal reviewers.
So what to do in such a case? Making the contribution hard to understand is a disservice to the posterior world, and you certainly don't want to become known for it. Luckily, there are a couple of alternative strategies:
- Adding an adjacent result to give the paper more technical depth. So you found a method to solve A. Perhaps you can also show how to solve a related problem A' with it after some modifications? If the latter is technically challenging, and solving A is arguably very useful, then you may make all reviewers happy, and the core contribution is still there. And who knows, perhaps somebody actually needs a solution to A', and then finds your paper.
- Formalize the key insight behind your new approach, and add this as theoretical analysis. If you keep the paper in a way that the paper is still readable without the theoretical analysis, it's still a helpful paper even for those who want to skip the theory.
- Build a nice running example that shows why exactly your new approach circumvents problems of previous approaches and discuss in detail where exactly the previous approaches fail on it and what makes your new approach succeed on it. This highlights the insight that went into your rather simple approach.
The last one surely has its advantages over the others. But it may be unrealistic in your particular case.