Global marketplaces have been rocked over recent years, with customer demand and inventory supply more erratic and complex than ever before. The effects of Covid-19, international conflicts, natural disasters, and extreme weather conditions have put supply chain management (SCM) teams well and truly in the spotlight, as they play a crucial role in ensuring business continuity.
Many businesses have turned to technology to support their operations and embrace digitalisation to help overcome supply chain challenges. This blog reviews demand forecasting challenges and how SCM teams can use inventory optimisation to overcome them.
As global supply and demand have been affected, some businesses saw dramatic rises in demand; others saw their sales disappear overnight, meaning SCM teams had to move fast to ensure business continuity.
Demand forecasting will remain very difficult, with what feels like never-ending disasters hitting the news. Therefore, demand planners must ensure they have the best tools and forecasting processes.
If you haven’t already, investing in a statistical demand forecasting tool that can continually analyse and adapt to the latest market conditions is an excellent place to start. Such software will help you understand the volatility of your demand and adjust your replenishment parameters as needed. It can also quickly identify trends in customer behaviour and help you respond accordingly.
With markets in flux, customer behaviour will likely remain erratic. This means that if you’re using a basic 30-day moving average to calculate demand, it’s almost impossible to generate an accurate forecast. This is because a 30-day rolling average forecast is only suitable for inventory items with stable demand, where the previous 30 days’ demand is a good indicator of the future forecast period.
As very few items have stable demand, you need to use appropriate historical data and look for sales periods with similar trends and market dynamics as the present day. Forecasting models need to account for a range of demand patterns and treat items differently, depending on the type of demand they’re experiencing.
Stockouts make forecasts inaccurate and decrease your sales numbers. If you have periods of stockouts, removing these from your forecasts will make them more accurate. If you can predict the lost sales and add these figures to your forecasts, you’ll be onto a winner.
Inventory optimisation software like EazyStock does this by analysing the demand patterns of all your stock items and assigning each to one of seven different demand types based on its position in its product lifecycle. In today’s climate, many items will move around this lifecycle; for example, some items in the automotive industry may move overnight from growth and maturity to decline but return to the growth phase as sales pick back up.
With demand types assigned, the software then uses the most appropriate statistical algorithm to calculate demand so every item can be treated differently. For example, items with stable demand will be assigned one algorithm, whilst those with lumpier or slow-moving demand will use a more suitable formula.
Having the ability to monitor demand trends will be key to ensuring stock levels match your customers’ requirements.
Demand trends can move fast, and inventory managers using manual forecasting will be left behind. In contrast, a demand forecasting tool will review projections regularly to ensure they reflect the marketplace. With up-to-date forecasts, inventory management teams can react quickly, maximising sales opportunities and preventing excess stock build-up.
When demand is unstable, using qualitative forecast data or human insights to augment quantitative inventory forecasts can provide a well-rounded approach to demand forecasting and achieve the most realistic demand projections possible.
For example, you could use statistical moving averages from a good forecasting tool like EazyStock to set a base demand forecast, then add qualitative information, such as feedback from your sales teams, market intelligence and customer insights.
Good communication between departments will help improve the quality of data you receive from the teams to provide better sales and trend pattern tracking.
Unfortunately, producing forecasts with 100% accuracy will be extremely challenging with so many unpredictable events. Demand planners need to find ways to spot inaccurate forecasts and put safety nets in place to help prevent consequential stockouts or increases in surplus inventory. Here are some ways inventory optimisation software can help:
EazyStock’s demand-to-date alerts track your actual demand throughout the forecast period and alert you when it’s deviating significantly from its projection. You can then investigate the cause, keep an eye on the items and adjust reordering if needed. EazyStock can also automatically adjust replenishment parameters such as reorder points, reorder quantities and safety stock to increase your ability to meet service levels and fulfilment targets.
Instead of manually sorting through data, EazyStock uses advanced pattern analysis to automatically identify and integrate seasonal demand profiles into your demand forecasting process. This will ensure stock levels reflect demand, i.e., you have enough stock to capitalise on demand peaks while being confident that as sales start to dip, your stock levels will also reduce.
EazyStock compares actual demand against its forecast at the end of a forecast period and highlights extreme variances, e.g., demand outliers. You can then investigate the reasons behind the data and decide whether to include the outlier in your next forecast, which, in turn, will update replenishment parameters.
EazyStock generates a daily risk of run-out report that compares the forecasts of all stock items to current stock levels (including stock in transit) and supplier lead times, alerting you to potential stockouts. You then have the information to manage by exception, delving into each item’s details and confirming whether to place an order.
It’s also important to identify the most critical items to your supply chain, e.g., those you rely on to keep production flowing or that your customers can’t be without. In EazyStock, you can upload and flag this list to scrutinise items more closely and assign different replenishment parameters to help ensure availability, e.g., increased safety stock levels and more sensitive stockout alerts.
Safety stock is a great way to help alleviate issues with demand and supply. An inventory optimisation tool, such as EazyStock, can dynamically set safety stock levels based on a wide range of factors, such as an item’s demand type, forecast, supplier lead times and your target service levels (stock availability). During times of unstable demand, it’s usual to increase safety stock levels to help mitigate unexpected rises in demand or delays to supply.
The challenge of working with multiple suppliers globally is made much easier by using EazyStock. Thanks to dynamic lead times, order scheduling, order calendars, and order fill-up functionality, you can get the best supplier to fulfil your orders. EazyStock will automatically select the best supplier based on their lead times, unit prices and minimum order quantities (MOQs) to ensure you can cost-effectively meet your service levels and avoid stockouts.
Demand forecasting will be challenging even with inventory optimisation software as we continue to navigate a world of changing economic and financial conditions. However, inventory management teams using automation to support their efforts will undoubtedly be best prepared for the task ahead.
Using EazyStock, your business will have a powerful demand forecasting engine to do all forecasting calculations in the background so your team can focus on your customers and suppliers. In addition, you’ll have an arsenal of functionality to help prevent stockouts and excess inventory building up to help protect your cash flow.
If you’d like to know more about how EazyStock can support your inventory management processes, please get in touch with the team – we’d be happy to discuss your needs.
First published in March 2022, updated October 2023