If the holiday season of 2022 has left a slightly sour taste in your mouth, is it ever too early to start thinking and preparing for the next peak period?
It could be time to commit to a different way of tackling your yearly peak demand and avoid the (what almost feels inevitable) scramble for additional processing capacity, safety stock, and inventory space.
Peak season is home to enough variables to blindside any business, especially across retail sectors. This, without mentioning the uncertainty of supply and availability of seasonal workers amplified by Covid and Brexit. (Bored of that yet?)
There’s also the question of ‘when does peak start and end?’. For some, Black Friday and Cyber Monday herald the onslaught of the peak, for others, holiday promotions can begin as early as late-September or early-October. Other retailers might lament the start of the summer season or the run up to Easter.
No matter what your business, there are ways to utilise your data to best predict and prepare for peak demand.
So, what does 2023 have in store?
Pressure from network disruptions will likely continue in 2023 and need to be considered as part of an overall peak plan. This leaves supply chain leaders in an unenviable position when determining the best way to manage their year.
In the worst case, inaccurate forecasts will magnify issues like cost management, maintaining service levels, and carries a high risk of diminished consumer confidence driven by network failures. Something we’d all like to avoid.
Data modelling for peak planning
We advocate taking a proactive and analytical approach to managing peak seasons, by modelling various scenarios to help supply chain leaders best prepare for high-volume events.
Plans based on detailed analysis can also reveal hidden opportunities. Peak periods typically require extra staff to churn through the higher volume months, but with better understanding of processes and capacities with data, it can be possible to identify opportunities to better ‘balance the line’ and depend less on temporary resources.
How then can supply chain managers better understand and plan for what is needed and effectively ‘flatten’ peak to minimise disruptions and keep costs under control?
Collaborations with external supply chain consultancy services like Trym remove the guesswork from planning for peak.
Through scenario modelling, the impacts of service level and costs can be more fully understood. By simulating for uncertainties in projected peak volumes, supply performances, and/or activity capacities, supply chains can be stress-tested. The outputs of which can form the basis of a supply chain strategy that the whole business can get behind.
A clear understanding of the resources required to deliver in peak periods ahead of time can enable business-wide projects and decisions to relieve pressured areas that can be key cost-to-serve drivers.
Supply chain leaders armed with data-backed information are able to lay out the best plans and adapt to changing business priorities.
Contact the team at Trym today for help with advanced peak planning and cost-saving initiatives.
About the author
Jon’s client work extends across Manufacturers and Retailers with a scope that covers high-level supply chain strategy through to detailed operational reviews and performance improvement.