Founded in 1987, Kathmandu is a transnational retailer of travel and adventure outdoor equipment, apparel and clothing. The parent company “Kathmandu Holdings” also recently purchased iconic clothing and surf wear brand Rip Curl.
The challenge for most businesses in the outdoor adventure space is the restriction on travel due to Covid and Kathmandu would be no different. The brand sells a vast array of camping, skiing, clothing and accessories with a large network of retail stores throughout Australia & New Zealand.
We have experience working with adventure wear brands in the past, however Kathmandu has been particularly interesting because of the diversity of the business model, multi store formats, and market position. Businesses that have a large range of products can put a lot of pressure on supply chain management, this is especially true when operating in shopping centre environments where rent costs can heavily impact profitability and with often limited space it can be critical to get the product merchandising right.
In addition to these factors the climate can play a large part in the profitability of a business that primarily sells products designed to use outdoor. So even if Covid has meant international travel is off the list, when movement is restricted within the country due to Covid, this can also impact the business. You can only pivot so much of the business online which can be quite limiting.
The challenge for us was to help the business identify the factors driving sales performance across the different store formats (Shopping centre, Suburban retail strips and Regional) which ultimately leads to a better understanding of the contribution various factors make to sales performance. In other words what is the relationship between demographics and population catchment size or site positioning vs competition. Is my brand more destinational or impulse driven?
Off the back of the analysis, the resultant pie chart might look something like this – it’s one thing to understand that demographics play a part in store performance if opened in an area that had a significant number of the identified key target market, however its quite another to know how much of an impact a less than ideal demographic area would have on sales performance compared with the other factors as noted below.
Adding complexity into the mix was to analyse how the online and in store Once the key sales drivers are identified further analysis and modelling is required to build sales & cannibalisation models. There is no point opening a new store in an area that is going to take significant sales off the closest surrounding stores. The sales forecasting models can then be applied to all of the existing stores to determine which stores may be underperforming based on the model prediction. Given many brands have more cautious growth plans, much of what we now do is use the modelling and analysis to help to provide insight into how a network can optimise what they currently operate.
An extension of this analysis is to help provide clarity around what drives product sales at store level. This would involve dividing products into major and sub categories to look at the drivers of product sales and the factors related to the characteristics of the stores and why specific product sales are higher/lower at different locations. This type of statistical analysis can be extremely useful when setting up and merchandising new stores, as well as aid in the ongoing supply chain management making sure the right stock is placed into the right locations, channels interacted and where opportunities would be in relation to making sure the channels complimented each other.
Geotech offers an end to end solution for clients, undertaking detailed analysis for existing networks, providing clarity around store performance and what makes the better performing stores perform as they do, building sales & impact forecasting models, store and product optimisation and forward strategic network planning.