Better approximately right than precisely wrong
“Better approximately right than precisely wrong”, a well-known phrase that we all know and understand. It means that perfect precision does not exist (planning paralysis), but sound approximations are good enough to do the planning job for you.
In planning & budgeting, we have a tendency to add more details to the plan, which allows use to have a more detailed overview. But it also means much more work (more data points) to create and update the plan. It gives a false feeling of control: more detail = more data = better decisions. But that is not the case, it adds to the workload and in most cases, it decreases the forecast accuracy.
And why is that? The more granular the level in your planning, the higher the chance of disruptions to your plan. Let me give a simplified example: you always planned on product level per country. A new planner arrives and wants to start to plan on product level per store per country. This adds more detail, so you have a better understanding what is needed on store level. But due to local conditions, actions, competitors, the actual figures per store can deviate largely from your plan (precisely wrong). Looking at actuals from an aggregate (country) level, it suddenly is approximately right. This is because deviations on store level (higher or lower) level out on aggregate (country) level.
With planning on country level, you still can stock the stores based on the actual sales figures. This data will come in regularly and your distribution centre (DC) can schedule frequent delivers to the stores, this is an operational exercise. The question remains to what level of detail you need to plan. The good news is that If you plan on a very detailed level, you have all the data at your disposal to do the math. Based on different levels of aggregation, you can look backwards at your plans and compare that to the actuals. On the lowest levels of details, your forecast accuracy is probably not that great. Look for the aggregate levels where your forecast accuracy starts to increase and becomes consistent, so over a longer period of time. This is the level of detail (or aggregation) to be used in your recurring planning exercise.
And yes, that will feel awkward. You have to let go of that false sense of control, of the detailed plans. But it saves you a ton of time per planning iteration, and you have an increased forecast accuracy (approximately right). A plan is per definition wrong, but is used as ‘the dot on the horizon’, the goal your organisation wants to achieve. But the path towards that goal can be adjusted based on changing market conditions, unforeseen events. And even an initial plan can be adjusted based on major disruptions. Many companies adjusted their year planning during 2020, when COVID-19 made the majority of plans redundant. In that case, it is easier to adjust the plan to the levels of detail with the highest forecast accuracy to be able to quickly respond to changing events. More detail = more data points = longer time needed to adjust.
Forget about adding more detail to your plans, find the right (aggregate) levels and make your planning cycle quicker, more accurate and easier to adjust. It is much better to be approximately right than precisely wrong.