I spent years as a supply chain planner, and I know a lot of planners across the industry. Every one of us has a story about our planning tools. The one I hear most often goes something like this: my company spent a small fortune and more than a year implementing a state-of-the-art planning system, and it never worked the way I needed it to. So I use it, technically, but the real planning still happens in Excel on my computer.
That story is the most common one I hear, and it is also one of the most avoidable mistakes a supply chain organization can make. The right tool is not always the fanciest tool. It is the one planners can use easily, trust the results of, and rely on without keeping a backup tool running on the side.
It is worth walking through the real options, because the honest pros and cons rarely come from the people selling them.
Excel
Excel is always there. Everyone has it, everyone knows it, and it is endlessly flexible. For a lean team or an early program, you can build a workable plan in a spreadsheet and be running the same day, with no procurement cycle and no implementation project.
The problem is that Excel is rudimentary and error-prone. A plan can be quietly wrong because of one broken formula, a bad copy-paste, or a reference that did not update, and nobody notices until the wrong number has already driven a decision. It also does not scale well. The spreadsheet that worked beautifully for one product becomes a fragile, sprawling thing once you are managing several, and the person who built it becomes a single point of failure. Excel holds up longer than people like to admit, and it becomes dangerous right around the time they stop admitting it.
The enterprise systems
At the other end are the big, ERP-integrated planning solutions. SAP IBP and Oracle's planning tools sit here, built to be the single source of truth, tightly connected to the rest of your enterprise data. There are also dedicated planning platforms like Kinaxis that sit outside the ERP but integrate with it.
These are powerful, and in theory they solve Excel's problems. In practice they come with their own. They are expensive. They take serious funding, time, and effort to stand up, and they usually need heavy customization to fit how you actually plan. And here is the part that gets undersold: after all of that, planners often end up not using them. The system is too rigid, or too slow, or too far from how the work actually happens, so people quietly go back to Excel and the expensive platform becomes the most costly shelfware in the building. When these tools are matched to the right size and maturity of company, they can be excellent. Deployed too early, or without the resources to maintain them, they are a large investment that does not get used.
The off-the-shelf middle
In between is a category of purpose-built planning tools that are more robust than Excel but far lighter to adopt than an enterprise system. ABC Plan is a good example. These are designed specifically for planning, so you get real structure and far fewer of Excel's silent-error problems, without the funding, the long implementation, and the heavy customization that the enterprise tier demands.
For a lot of companies, especially lean ones that have outgrown spreadsheets but are not ready to build their planning around a full ERP module, this middle ground is the pragmatic sweet spot. It is often the tool that actually gets used, which, as above, is the thing that matters most.
AI
And then there is AI, which is the genuinely new entrant and the one nobody has fully placed yet. Here is where I think it has real promise.
AI has the potential to be immensely powerful for scenario planning, especially for the non-typical scenarios. In Excel, a new or unusual scenario often means meaningful rework, adjusting formulas, rebuilding logic, and the result is limited by the planner's own capabilities with the tool. AI can let you include more unique factors in a scenario without that overhead, where today you often end up making simplifying assumptions or estimates simply because the tool or the planner's time will not stretch to the real complexity. That is a real unlock, and it can save planners a significant amount of time.
The concern, and it is a real one, is how you know it is right. We all know AI is prone to errors, and the responsibility for finding and correcting them sits with the user, particularly before the work is presented as finished. There is a useful distinction here. When AI generates something transparent, like an Excel file of scenarios, the output is inspectable and mistakes are relatively easy to catch and fix. When it is doing the work inside a tool or a less visible process, checking it gets harder, because you are evaluating an answer without fully seeing how it got there. (I am not an AI expert, so take that as a planner's caution rather than a technical verdict.)
Even with that caveat, I think the opportunity is large. AI is going to become a significant support tool for planners, and I expect it to get integrated into the more established systems over time. Some of the more nimble planning tools are already there. ABC Plan, for instance, has built AI into its software in a solution-oriented way, ahead of where a lot of the larger systems currently are.
The real decision
The through-line across all of these is that the best planning tool is the one your team will actually use and trust. A sophisticated system that sits unused is worse than a clean spreadsheet that someone maintains carefully. Match the tool to the size, maturity, and resources you genuinely have, not to the one that looks most impressive in a demo. The goal is a plan people rely on, and that comes down to adoption far more than it comes down to capability.