“One of the biggest challenges that companies face is predicting demand for new products over time. Overestimate it, and risk warehouses full of excess inventory. Underestimate it, and your customers could leave empty handed—or you might be left with a hefty bill for expedited delivery.” – Kellogg School of Management, Northwestern University
Innovate or die trying.
The phrase is almost as overused as “retail apocalypse,” yet a concise depiction of what retailers face constantly when we think about the video-gone-viral level of speed behind the changing retail landscape and unpredictable nature of demand.
As if determining the optimal assortment wasn’t already difficult enough, introducing new products to your strategy when some fashion trends barely last is a risk merchants must take.
When it comes to new products, retailers are getting burned (more often than not) when a quick pivot or adjustment to changing demand is unmet. Today, these losses hurt big time, especially considering retailers are clenching onto their purse strings more tightly than ever.
Why is it so difficult to accurately predict consumer demand for a new product? And, more importantly, how can we overcome these difficulties?
The main difficulty is, by far, uncertainty.
How can anyone predict the future? As I mentioned before, it’s difficult enough to plan your inventory assortment accurately even when you have historical data on existing products.
How can we even begin to accurately plan for new product lifecycles, given that there is no product history?
Due to this uncertainty, merchants make really big bets on new products based on experience or gut-feeling. Which, don’t get me wrong, is really important. However, you need need need to combine this expertise with data–even if this data comes from similar styles or class levels.
The risk is too high, and margins are most vulnerable.
Business 101: Be wary of new product cannibalizing existing product.
The threat of cannibalization of an existing product by a new product is one retailers are all too familiar with. You produce a new version or style of an existing product that ends up selling at the expense of other products.
This is exactly what we want to avoid.
As fashion cycles shrink and a see-now-want-now mentality dominates the consumer’s mentality, the desire to try new things and introduce new products grows more everyday. Which is super challenging if the fear of cannibalization—the fear of uncertainty—prevents retailers from capitalizing on new opportunities.
It’s a lose-lose scenario where uncertainty leads to cannibalization, and inaction leads to missed opportunities.
The last challenge, and reoccurring theme we touch on frequently on this blog, is speed.
Last week, we touched on this topic pretty extensively during a webcast with AlixPartners. Retailers are under immense pressure to move faster across all areas of the merchandise, planning, and allocation process - with speed ultimately driving success.
However, the lack of data-driven, actionable insights and the rush to get a product to market is a recipe for disaster.
Especially in fashion, where trends are short-lived and consumer preferences change quickly, how can merchants get a clear sense of when to cut off the product pipeline? When to introduce a new program, or discontinue a SKU?
How can we make quicker, more effective (and ACCURATE) retail decisions?
A Secret Weapon to Accurately Predict Demand
“Imagine you have a crystal ball and you know exactly how demand for your product will go up or down, month by month. That would make it very easy to prepare to meet demand, because if you know your lead times, you just use your crystal ball to source the right number of units from the cheapest source on time, and you can satisfy 100% of demand with no waste. That is the Holy Grail." - Kellogg School of Management, Northwestern University
While we won’t find a crystal ball that can do this sort of thing, however, the innovative technology out there can get pretty darn close.
With advanced analytics, merchandising planners can shed some “Holy Grail” level predictions and recommendations about location-specific demand for a product to uncover hidden opportunities to carry new classes, styles, and brands across stores.
Recommendations based on what your customers actually want.
Learn more about accurately predicting demand for existing and new products through advanced analytics here.