Many companies are all too willing to create new products at a client’s request. Over time, these additional SKUs lead to more business complexity through smaller production runs, more setups in the manufacturing process, and supplementary administration. This added complexity increases costs and lowers overall profitability. If this sounds familiar, it may be time to look at SKU rationalization in your business.
At its most basic meaning, SKU rationalization is the process of deciding which products to keep (or improve) and which ones to discontinue — all with the goal of improving your organization’s bottom line. The key drivers are typically space prioritization, innovation time, and price optimization with an overall business goal to improve cash flow, increase return on invested capital, and boost gross margins.
So, where do you start? The key to successful SKU rationalization is to begin with accurate product cost information. All too often, SKU rationalization is suboptimal or ultimately fails because critical decisions are based on poor product costing data — the “garbage-in, garbage-out” effect. To be successful, you need detailed margin data for each product that’s based on correct and accurate item master data and integrated within multichannel analytics.
All too often, SKU rationalization is suboptimal or ultimately fails because critical decisions are based on poor product costing data — the “garbage-in, garbage-out” effect.
Here are five key costing data items to consider when planning your SKU rationalization initiative.
1. Confirm bill of material accuracy.
Raw materials and packaging are usually the largest components of a product — often making up 50-75 percent of its cost — so accurate raw material costs, measurements, and production yield are critical. Have you checked how your material costs are set up in the system? Are you seeing significant purchase price material usage variances? Is yield-loss accurately reflected? Is there a lot of variability in the market due to seasonality or other supply and demand factors like tariffs? It’s wise to be aware of these factors and understand their impact on the cost of materials.
2. Determine labor cost.
Labor cost is another big piece of the product cost puzzle. It’s usually the largest variable component of cost, and due to the wide range of methods used to calculate it, there’s a lot that can go wrong when factoring it into overall product cost. Is your labor cost a blended cost for the plant? If so, what if a particular operation requires a specialized skill with a higher wage? Are your labor fringe costs accounted for as labor or included in overhead? Is crewing for setup and production time accurately calculated for each SKU? How productive is the labor force, and is productivity being driven by product mix or other factors? Is overtime driven by demand or customer order patterns? These are all key questions that can significantly swing your labor cost for a SKU.
3. Assign overhead costs.
How you assign overhead costs to products is critical. Most overhead expenses can be assigned by causality or correlation, and ideally direct assigned to a product or process. Is everything driven by labor hours? Are machine-driven costs applied separately from labor-driven expenses? Assigning these costs based on appropriate drivers, results in far more accurate product costs.
4. Measure variable contribution and total gross margins.
It’s important to understand your variable costs versus fixed costs. For example, if you eliminate a product or channel without changing your fixed costs, it could appear that you’re saving more cost than you actually are. Look at a product from a variable-contribution-margin basis, and then look at the fixed support, and equipment and facility costs and determine what can be eliminated when eliminating product. In some cases, you may free up capacity, while the cost doesn’t go away; however, those resources can be redirected to other products/projects. A product with a negative gross margin but positive contribution margin may be a keeper in the short term, but only until it can be replaced by a more profitable product.
5. Analyze cost to serve.
Many costs aren’t driven by the SKU at all but rather by the cost of supporting specific channels or customers. For example, in the food and beverage industry, you not only have the cost of each SKU to consider but also the cost of serving each channel. So, whether you’re selling to grocery stores, convenience stores, restaurants, or directly to consumers, each has different layers of cost to support. The same holds true for individual customers — each is unique and will impact costs differently based on ordering windows, turnaround time, and delivery costs. Are your costs to serve simply averaged into an overall selling, general and administrative (SG&A) percentage of sales? Or, do you separate out SG&A costs that are driven by the relevant channel or customer and apply them accordingly?
When done right, SKU rationalization has the potential to increase profit margin significantly. Once you’ve gotten good data, you can leverage your data analytics tools to reap the benefits of the cost information.
SKU profitability data needs to be analyzed not solely on cost, but also on what’s best for the market.
Data analytics will help you measure SKU, channel, and customer margin quickly in the context of market-based scenarios and help you identify where to reprice, eliminate products, or invest further in product, channel, or customer development. But to reap the full benefits of your rationalization, SKU profitability data needs to be analyzed not solely on cost, but also on what’s best for the market. So, for example, it may make sense to keep a money-losing product for strategic reasons such as filling out a portfolio of products, securing shelf space, or testing product potential. In these situations, data produced in the rationalization process is still useful for monitoring product performance and measuring the ongoing impact on profits.
For further insights into your SKU management, give us a call.