November 16, 2022

Introducing Time Disaggregation in Demand Planner for More Accurate Forecasting

In this blog, we explore how the new functionality of time disaggregation in DELMIA Demand Planner can provide quicker, more accurate forecasting for manufacturers to efficiently plan production and manufacturing operations.
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Adrian Wood

Every year, manufacturers of products with peak and low seasons must determine a forecasted number of items to produce in order to minimize waste and maximize profit. As the purchase and consumption of their products are highly dependent on ever-changing factors such as buying trends and the weather, forecasting demand can be a difficult task with a massive amount of pressure to get it right.

DELMIA demand planner used in the high tech industry

When the COVID-19 outbreak turned into a full-blown pandemic, demand planning seemed to be an impossible task for manufacturers. Businesses in the supply chain as well as buyers in the demand chain had their operations grounded to a halt, and unfortunately some never made the recovery for business to pick up again.

Even now, with talks of a recession, a prediction of decline in economic growth in the next few years and geopolitical conflicts causing global inflation­—all these have impacted the ability to accurately forecast demand.

With these circumstances in mind, the question remains for manufacturers who have endured periods of major disruption then and face an unknown future now: how can forecasting methods be enhanced to better plan for contingencies like these?

In this blog, we explore how the new functionality of time disaggregation in DELMIA Demand Planner can provide quicker, more accurate forecasting for manufacturers to efficiently plan production and manufacturing operations.

Demand Planning for Global Disruption

During the pandemic, as well as the current economic crises, sales data from previous years would essentially be of no help to manufacturers who needed to anticipate the demand and popularity of their products. However, demand scenarios still had to be generated regardless of the unusual circumstances faced, as it would not be feasible for production to only start when orders came in or for manufacturers to wait for normalcy to return.

The key challenges of forecasting in this situation were to not only avoid over-producing and stocking up on excessive inventory, but to also prepare for demand by securing on-shelf availability and fulfillment.

What manufacturers needed was a solution that can create multiple types of “what-if?” scenarios, provide the ability to change plans rapidly, and show how these changes affect the supply chain so that operations can react accordingly.

Why is Time Disaggregation Needed for Forecasts?

While forecasts are usually calculated for aggregate periods, managers and operators may require more granular forecasts in nearer time frames depending on the industry or enterprise they work for. Adding to that, different departments within an enterprise may also need its own forecasting time horizons, and demand planners need to synchronize forecasts so that they are consistent at every time configuration.

For example, a business may benefit from having an attractive number of product choices for consumers, but with thousands of SKUs, varieties and packaging, the challenge of forecasting for each item increases in complexity.

Businesses like these usually work with extremely detailed granular time forecasting. But with the large number of forecasts required, the data processing ability of the software used also requires substantial power and computation time. Furthermore, if the business needs to generate such a high number of forecasts on a daily or weekly basis, it compounds the (already large) amount of data to process.

In these cases, it is necessary for the software used to provide disaggregate forecasts that will accurately reflect the dynamics of the calendar. This complex problem requires an advanced solution, one that can produce faster results with improved forecasts.

DELMIA Demand Planner offers time disaggregation as an alternative to granular forecasting, providing detailed results from high-level forecasts and an efficient and robust way to compute with quicker results. With this innovative feature, planners can spend their time focusing on high-value items, while using aggregated forecasting for tasks with less priority.

Higher vs. Lower Time Aggregated Forecasts

So, how can switching between higher and lower time aggregations help manufacturers with demand planning? Historical demand data is usually recorded at more granular time levels, but it can be beneficial to an enterprise to generate statistical forecast at monthly time periods as well.

A higher level of time aggregation will reduce the noise of the data, decrease the computational load of data to be processed and provide forecasts with higher accuracy.

However, some forecasts still require estimates on lower time levels, such as on a weekly or daily basis. This is when certain challenges arise for planners, as they are tasked with disaggregating a monthly forecast.

The time period in question may have inconsistent days in a month or include weeks spanning more than a month. Being able to switch between fiscal and monthly calendar views would be an extremely helpful feature for planners in this case. Filters on workdays versus full weeks should also be considered, as well as holidays and facility closings.

Some patterns on a weekly forecast may not appear correctly if only monthly data is used, and a weekly forecast will also be able to drive weekly supply requirements more accurately for departments that rely on those time frames.

How Time Disaggregation in Demand Planner Helps with Forecasting

DELMIA Demand Planner (DP) is a comprehensive solution that can generate accurate forecasts at multiple levels of granularity over different time intervals. This new feature has been tried-and-tested by the robustness of the solution’s time aggregated models.

With Demand Planner, manufacturers can use the disaggregation function for several strategies. Not only will they be able to disaggregate based on various time interval configurations (calendar and fiscal 4-4-5), but also consider calendar events and history. Time disaggregation can also be based on concurrent weights, measured proportionally to existing values, and by copying when using average aggregation.

When it comes to the accuracy of demand forecasting, there are two key factors manufacturers need to note: 1) the thoroughness of the available data and 2) how well that data is used.

DELMIA Demand Planner enables better data integration, seamless workflow management and detailed demand analysis, so that manufacturers and supply chains can maximize the data they have to optimize their operations and meet common industry challenges.

Main Features of DELMIA Demand Planner

Time disaggregation is just one of many useful functions that Demand Planner offers. If you want to anticipate demand through improved statistical forecasting, collaborate more effectively with internal sales teams and external customers, and explore demand scenarios to increase sales, you need a robust solution such as DELMIA Demand Planner.

Not only will the solution help you analyze historical demand and market intelligence to accurately predict demand, but it will also enable you to revise forecasts immediately according to market conditions and determine how your business can profit from it.

For more information, read our data sheet on how you can “Improve Forecasting Accuracy with Comprehensive Time Disaggregation”.


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