Overrule the Pareto Principle: How to improve portfolio profitability with Inventory Optimization
The Pareto principle, or 80/20 rule, is a simple rule that when applied to business acknowledges that 20% of your customers represent 80% of your sales, or that 20% of your time generates 80% of your results. In retail, it is often the case that 20% of SKUs represent 80% of sales.[i]
When just 20% of SKUs drive the vast majority of a retailer’s sales, it means there is a lot of room for improvement, as the vast majority of SKU’s are doing very little to contribute to topline results. Inventory is the largest investment for many retailers and CPG companies, yet inventory management is a perennial challenge. Retailers are spending a lot upfront to purchase inventory that is ultimately driving little revenue. To make matters worse, 70% of retailers say that their inventory practices are below market average.[ii] To address the disparity between upfront cost and revenue, retailers and CPGs could benefit from a more robust, data-driven approach to SKU decisions.
If retailers can reallocate or distribute their currently underperforming SKUs, they can dramatically increase their revenue to capture what was once a lost market share.
Unfortunately, forecasting and SKU selection is a multi-faceted problem, and the challenges that make it difficult exist at many levels. Sales data that is not granular enough, combined with inflexible analytics systems, often leads to poor forecasting that fails to ensure correct products are on the shelves at all times.
Let’s consider some of the pain points that teams face when managing inventory:
Sales data is too high-level and too outdated
Currently, many companies are conducting quarterly or even annual SKU analysis at a regional level. Whether they believe that this is sufficient to understand SKU trends, or simply lack the resources to take a more granular approach, retailers and CPG companies are operating with an incomplete understanding of their SKU performance.
Imprecise data affects everyone. Sales data is often outdated by the time it reaches sales directors. In-store field sellers are recommending products based on macro sales data and have no ability to see SKU-by-SKU or store-by-store 
performance. Without this, sellers cannot optimize portfolios and make sure the right products are on the shelves and racks. Worse still, retailers have shelf and rack space devoted to products that aren’t earning their keep, while products that fit better are stuck in a warehouse.
Data is difficult to turn into insights
Even if companies have mountains of granular sales and SKU data at their disposal, they often lack the tools to interpret that data and turn it into action: 44% of CPG firms don’t have adequate resources to interpret analytics outputs.[iii] If data is difficult to access or cannot be explained correctly, merchandising directors will not be successful in predicting sales, managing products, or directing marketing and sales efforts.
Why is the interpretation of data so difficult? Existing reporting systems have limited ability to visually represent the complex connection between sales data and external variables. Without dashboards to help make sense of what’s going on, teams are stuck digging through mountains of data for important insights.
Forecasting is unreliable
Lack of insights results in forecasting models that cannot not accurately track changing customer preferences. It’s critical to have access to near real-time data during forecasting to make decisions using the most recent information available. In one survey of apparel retailers, 55% were able to capture a demand trend in under five weeks, while 44% responded to a demand trend at a painstakingly slow rate of six weeks or more, causing seasonal issues wi
th stocking[iv]. Overstocked products are wasteful and expensive, while understocked products frustrate customers and result in lost sales opportunities. Retailers and CPG companies need to know what to expect so they can make the right decisions about where to allocate their resources and budget. And the best way to do that is to implement an inventory optimization solution that takes advantage of the power and scalability of the cloud and advanced analytics.
But retailers can solve for these constraints
The increased efficiency of a single, end-to-end solution helps key roles such as analytics directors and COOs drive revenue and optimize inventory across the organization. Flexible inventory management solutions can scale and integrate with all aspects of a business, enabling tracking an
d dissemination of granular data at frequent intervals. Specialized dashboards help merchandising directors understand the relationship between multiple business processes and sellers identify and address high-priority improvement opportunities. Equipping sellers with mobile views enables them to recommend specific products for customers based on trends and data from similar stores.
With barriers to SKU optimization resolved, all team members will be able to help drive increases in revenue and sales, optimizing portfolios every step of the way and choosing the right SKUs for every store or outlet. Capturing and inputting this sales data into reliable forecasts gives teams more confidence they are making effective stocking choices. Finally, using the advanced analytics provided by a single, end-to-end inventory management solution ensures that new insights can occur with every sales cycle.
A new way to maximize your profit from every SKU
Neal Analytics, a leading Microsoft partner, has developed an inventory optimization solution on the Microsoft Cloud. It helps increase sales and profitability by determining the best performing SKUs in each market, optimizing product placement, and capturing product demand. The solution reduces production and supply chain complexity for retailers and consumer goods companies and can identify (among those 80% of marginally beneficial SKUs) which are underperforming products to cut out and which can be top performers in need of more attention.
Try the Inventory Optimization solution on Microsoft’s AppSource. Neal Analytics’ Inventory Optimization is a part of Microsoft’s cloud solution portfolio for the retail and CPG industries, including AFS Retail Execution, AFS POP Retail Execution, Plexure Retail Personalization, and Dynamics 365.
[i] http://www.nealanalytics.com/10-signs-you-have-too-many-skus/
[ii] http://apparel.edgl.com/reports/Inventory-Optimization–Retail-Strategies-for-Eliminating-Stock-Outs-and-Over-Stocks64377
[iii] EKN 2016
[iv] http://apparel.edgl.com/reports/Inventory-Optimization–Retail-Strategies-for-Eliminating-Stock-Outs-and-Over-Stocks64377
