• Vjeko Skarica

Bottom-up vs Top-down Forecasting in Demand Planning

Updated: 5 days ago

Why is everyone talking about bottom-up and top-down planning? What are they? Are they crucial in the context of demand planning?

Roughly speaking, in the top-down approach, the management sets the goals and passes them down the line, and in the bottom-up, employees from the lower parts of the organization send the information upwards.


In this post, I will try and answer:

  • What does top-down and bottom-up demand forecasting look like in practice?

  • Are they universal?

  • What are the benefits and downsides of each method?

  • Are there better demand planning approaches out there?



Top-down Forecasting in Demand Planning


Top-down forecasting is the simpler of the two. The steps vary from company to company. Here’s one example of how the process might look on a monthly level.

  • The management uses market research data and benchmarks with sales and marketing data to predict the trends and set general revenue targets.

  • The central planning team (demand planners and/or finance) and Sales then challenge these figures

  • After that, demand planners forecast the figures on the product group level.

  • To further forecast SKUs in the product family, they use historical sales data to break the quantities to distribution centers, channels and months, taking into account seasonality and expected promotions.


Top Down Planning illustration with a hierarchy - folder on top and 3 levels of documents underneath it


Bottom-up Forecasting in Demand Planning


Bottom-up forecasting starts with the baseline SKU level forecast, generated by the central demand planning team using statistical models and the latest real-world data sent by the local demand planners.

  • Central and local demand planners then go back and forth, discussing the latest forecast changes, trying to pinpoint the exact causes of forecast errors. And make no mistake, these always happen.

  • After this, the sales team comes in with their market knowledge and changes the forecast accordingly.

  • Demand planners then create separate forecasts for all new products. These don’t have any historical data to be used as a baseline, so demand planners work with Marketing to make the best assumptions for the new product(s).

  • When all this is done, central demand planners translate the forecasts from SKU volumes to $ values.

  • The $ value forecasts are presented to the management. Usually, the management won’t sign off on forecast numbers right away but will challenge them instead (sometimes even several times). Which means that the entire process starts again.

  • After some back and forth between the Management and Demand planners, the Management signs off the forecast. Operations then use it to create the production plan.

Bottom Up Planning illustration with a hierarchy - folder on top and 3 levels of documents underneath it


Which one is better?


In terms of forecast accuracy and the granularity of your forecasts, bottom-up is the way to go. The process offers more realistic and accurate forecasts on the SKU level, more employees are included, they have more autonomy working using this approach, and more information is circulating through the organization.

But not every company can forecast this way. Most of them do not have the necessary resources, because the process is complex and time-consuming.



Top Down and Bottom Up Planning Comparison, List of Pros and Cons for both

So they stick with the top-down approach. It doesn’t require as much data and employee engagement, it offers results quickly and gets the job done. But it is far from perfect.



Hybrid approach in demand planning


All seasoned demand planners know that, no matter how straightforward the plan is, whatever CAN go wrong, probably WILL at some point. In theory, both of these approaches are pretty simple. In practice, they often transform into something like this:

A chaotic plan structure in a hierarchy, folder on top with 3 levels of documents underneath it

There are many reasons for this, but it always comes down to these 3:


  • Inefficient communication across the organization - too many emails, Zooms, Slack pings, and endless meetings make demand forecasting harder for everyone.

  • Siloed data - as the operation grows, data is piling up, and it gets harder for departments to share and make sense of it.

  • Outdated tools - Extracting data from a 30-year-old ERP system and storing and sharing it via spreadsheets creates endless problems in the long run.


It is painstakingly obvious that demand planners need new strategies to improve their forecast accuracy. A hybrid approach in demand planning is not a new idea by any means. Planners have been talking about combining the best features of bottom-up and top-down for a long time now. But how does this look in practice? The implementation varies from company to company, but it always follows these basic principles:


  • Effective collaboration - The demand planning process should go in both directions and simultaneously empower both the upper management and everyone in S&OP.

  • Single source of information - Creating a virtual, validated, and frequently updated environment for your data that everyone can refer to will improve data quality and make the demand planning process faster and much more accurate.

  • Automation - reports, models, data entry, systems integration, status notifications - automate whatever you can to save valuable time for collaboration and problem-solving.


Conclusion


So, let us recap what we’ve learned here today quickly.

  • Top-down and bottom-up forecasting methods are simple to explain but can get pretty complicated in practice.

  • Bottom-up demand forecasts are more accurate, but most companies do not have the resources to do them.

  • Hybrid forecasting, a mix of bottom-up and top-down, is the best solution for most companies.