13 Sep Improve Key KPIs & Meet Yearly Goals with Predictive Analytics
With the New Year comes new goals and resolutions. For retailers, this means taking stock of their company’s strengths and weaknesses, and identifying key performance indicators as they set their objectives for 2015.
Each retailer has its own unique set of KPIs that are used to evaluate the growth and success of the organization. Retailers need to pick the right KPIs based on the outcome they want to achieve or their strategic goals. For example, one retailer might want to manage their inventory better, so they would use KPIs like inventory to sales ratios or inventory integrity. On the other hand, another retailer might want to enhance the customer experience, so they would choose KPIs like customer satisfaction and retention.
As we all know, the challenge isn’t in setting goals, it’s achieving them. In today’s omnichannel retail world, the best way to improve KPIs and meet yearly objectives is by adopting a predictive analytics solution that can forecast true demand, accurately allocate inventory, optimize promotions, and balance inventory and assortment between stores while being in tune with individual business goals.
Some common examples of retail objectives are to reduce costs and eliminate the expense of out-of-stocks and overstocks. Below are a few examples of KPIs that retailers might choose in order to meet those objectives and an explanation of how a predictive analytics solution can help effectively and efficiently achieve those goals.
The key to reducing the expense of out-of-stocks and overstocks is having the correct balance of inventory across stores. But demand fluctuates, and retailers that don’t have a comprehensive inventory and assortment balancing system across stores are seriously diluting their gross margin.
Retailers that integrate an inter-store inventory and assortment balancing solution into their business can anticipate the necessary transport of an item proactively, before the transfer becomes tedious or overwhelmingly expensive.
All costs associated with the transfer — from logistics and store capacity to demographic diversity and the sizes and colors most likely to sell at the specific location — are incorporated automatically. This dramatically increases revenue from transfers, lowers inventory costs and increases sales while helping you avoid unnecessary markdowns and subsequent allocations.
Every retailer aims to minimize the amount of out-of-stocks in their stores, so a particularly useful KPI is in-stock percent. Bottom line and customer experience suffer when consumers are forced to wait for shelves to be restocked or hunt for sold-out stock at a different location. But for most retailers, the restocking process doesn’t begin until inventory starts to run low at a specific store.
This strategy is retrospective and simply incapable of improving in-stock percent. Predictive analytics helps retailers more accurately calculate demand forecasts, order quantities and optimal safety stock levels while they wait for the order to arrive so their most profitable products are in stock 98.5% of the time, which is a common industry standard.
For retailers that would like to measure the effect of promotions, marketing initiatives, customer experience, markdowns, media types or price changes, the KPI they should prioritize is promotion lift.
A predictive analytics solution can calculate the real effect of retailers’ promotions, the types of promotions that work best for different types of products, geographies and so on. What’s more, a solution that can measure the effect of product cannibalization can tell retailers if a promotion for one product is driving down the sales of other products, a scenario that can unknowingly affect total revenue.
Moreover, having a fully integrated end-to-end predictive analytics solution means that promotions will always take the supply chain part of your business into account. No more surprising promotions that the supply chain team cannot fulfill.
Not all retailers adopt the same KPIs to meet their organizational goals, so they should use a predictive analytics solution that caters to their specific needs. Every business is unique, with specific goals, strategies, potential and issues. But with a predictive analytics solution, retailers can be well-equipped to improve their KPIs and achieve their goals for 2015.