If you find yourself with a never-ending queue of backorders causing lost sales and/or failure to meet customer demand on time, then you may find this list of actions helpful.
Simply buying more stock is not the correct response.
Without understanding why you don’t have the right stock available at the right time to meet customer demand, you run the risk of sitting on excess inventory and tying up cash unnecessarily.
If dealing with perishable goods, you don’t want to end up having to throw food away.
But having excess inventory can also lead to a requirement for larger warehousing facilities, or shop fronts.
These all coming with a price.
Having a numerically driven understanding of the causes of lost sales is a vital first step.
Understand the Variability of Demand
Analysing for and classifying each line by its variability of demand will help you better understand your situation.
Are you running out of stock with both high and low levels of variability, or just high?
You would be unlikely to return to a coffee shop that one day told you they had run out of coffee. With a consistent custom, you expect them to always have enough stock available.
However, you might let them off if one day they were out of your favourite (lower overall demand) blueberry muffin.
“Is it the core lines that never seem to be in stock when you need? The less-frequently moving items? Or both?”
Identifying the items where you’re losing the most sales will help focus your attention on where to improve reordering levels to best satisfy customer requirement.
Check Your Forecasting Accuracy
All companies aspire to have as high level of forecast accuracy as possible. And the one thing that companies can be equally confident about is that forecasts will not be accurate. However, that is no reason to be defensive about forecast error or striving to improve.
It’s important to understand if the forecast is inaccurate across all lines in general or for a specific set of items.
Looking at the difference between your forecast sales quantity and actual sales for each line, you should identify any correlating factors.
You may find that high churn, high demand variability, and/or high seasonality impacted lines are found to be the most inaccurately forecast. This could require looking into customer demand at more detailed time-intervals.
Responsiveness of Suppliers
It’s critical to know how quick each of your suppliers is likely to respond.
If you have no stock of a requested item, and the customer request is urgent, would your suppliers help you rush through an order, and at what cost?
Is there any leeway on your supplier lead times, or do you already have the best they can do?
Lead times are important for managing your stock holding and should be a focus to getting stock levels accurate.
Short lead time = lower risk to stock out
Long lead time = high risk to stock out and therefore to lost sales
Sharing Planning with Suppliers
Informing suppliers of planned updates or predicted adjustments to your demand requirements allows for them to plan accordingly.
Any change you make within your supply chain will have knock-on effects to your suppliers and how they provision their inventory.
Suppliers may need to adjust their supply chains to align with your requirements better.
Providing as much timely information about the changes as you can will help them optimise their delivery strategies too.
This improved communication can help you appropriately source orders for as and when required.
It can also open opportunities to reduce lead times, improve delivery time, or hold consignment stock.
Planning with supplier’s involvement further reduces risk to stock outages.
If you’re experiencing high backorder queues and lost sales, it is important to understand:
- Variability of demand of your lines
- Accuracy of your forecasting
- Responsiveness of your suppliers
- Level of collaborative planning you are sharing with suppliers
As with any major industries, customer requirements are constantly changing. Therefore, analysis should be carried out often to ensure stock is available to meet their demands.
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About the author
Ashleigh’s work focuses on the performance of data analysis and production of statistical models to derive insights.
Ash has worked with start-ups, defence contractors, retailers and the NHS to derive value from data and solve big problems.