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More expensive than real estate, merchandising, or even labor -- inventory is the largest investment your company makes. But getting the biggest return on that investment, especially in today’s tough retail environment, requires a more nuanced, data-driven approach to inventory management than most retailers are used to.  Below, we’ll describe 7 guaranteed inventory reduction ideas in some detail. But first, let’s take a look at what reducing inventory really means, and why it matters. What does reducing inventory levels really mean? When the top floor sends word that you need to reduce inventory levels, you don’t just cut your inventory indiscriminately. There’s more to it.  You need to consider retail key performance indicators (KPIs) that are based on average inventory costs -- such as turnover and gross margin return on investment. Reducing your inventory costs will improve KPIs.  So what happens when you slash inventory across-the-board? You end up with less inventory of your top-performing products -- which will hurt other KPIs like in-stock percentage and profit per transaction. The real problem is not having too much inventory. It is that having too much of the wrong products in the wrong places, and not enough of the right products where they sell the best.  The definition of inventory reduction is...

Why should retailers care about data analytics? It's really quite simple. Today’s retailers are facing a bevy of new challenges, including declining sales, fierce competition from online-only stores, and changing consumer preferences. In the digital age, there are a million things retailers have to stay on top of, and simply not enough time in the day. Yet, despite these challenges, some traditional retailers are managing to grow year-over-year, shredding previous sales records time and time again. The winners are doing something differently -- something that not only helps them survive, but also thrive in this quickly unfolding retail apocalypse. According to McKinsey & Company, the reason some retailers are winning (while others struggle) is advanced analytics. New research says that retailers using advanced analytics outperform the competition by 68% in earnings -- and the disparity is growing exponentially. But what exactly is “advanced analytics,” and how does it differ from regular old Excel analysis? To explain what makes advanced analytics so special, we need to start at the beginning.  What is Retail Data Analytics? Retail data analytics is the process of collecting and studying retail data (sales, inventory, pricing, etc.) to discover trends, predict outcomes, and make better decisions. Done well, data analytics allows retailers to get more...

Top-performing retailers cannot rely on inaccurate, decades-old approaches to forecasting demand.  In order to optimize their inventory investments and maximize GMROII, today’s retailers need accurate demand forecasts for every SKU in every store. But achieving this level of granularity requires a big data analytics approach to demand forecasting -- designed for the digital era of retailing.  In order to understand how to take full advantage of this new technology, we will first explain what demand forecasting actually is, the most common methods of demand forecasting in retail, key constraints that need to be accounted for, and modern examples of accurate demand forecasting. What is Demand Forecasting? To understand demand forecasting, you must first understand demand and forecasting as separate concepts.  Demand is an economics concept that describes the willingness of consumers to purchase a specific product at a specific price. Forecasting is a statistical process that uses existing data to predict future performance. Therefore, demand forecasting is a statistical prediction of the willingness of consumers to purchase specific products, at a specific price, in a specific time frame. Put plainly, if retailers could predict this accurately, they can easily minimize costs and maximize profits by: Setting accurate financial and merchandise targetsChoosing optimal prices for every SKUStocking enough inventory...

For the past few years, retailers have been faced with an exponentially growing gap between industry leaders and laggards. A Mckinsey & Company report shows clearly that those who leverage analytics are outperforming their competition by 68%, and the gap continues to widen exponentially. Source: Mckinsey & Company report Digital transformation in the industry has created additional challenges for retailers to tackle. The traditional approach (which used to be good enough) has now become obsolete. Relying on the ‘good enough’ makes it impossible for a business to survive in the digital age. In today’s landscape, when a new fashion retail trend latches on, companies need to have the ability to make the right decisions quickly. Retailers have found that machine learning and predictive analytics is a game changer which is leaving slow to adapt competitors far behind. So, why is advanced analytics so successful and what is the difference between the traditional approach and this new advanced approach to fashion analytics? Fashion Retail’s Unique Challenges In order to truly understand the benefits of advanced analytics, we must consider the challenges retailers face. The digital transformation has affected every retailer, but fashion retailers are amongst the hardest hit verticals facing specific challenges which complicate the use of...

As a retailer, inventory is one of your biggest investments.  Afterall, retailers invest in merchandise hoping to sell it at a profit. That’s the crux of the entire retail business model. As such, the GMROI formula is used to evaluate how successful retailers are in getting a return on their inventory.  In fact, GMROI is one of the top key performance indicators (KPIs) used in retail.  Calculating GMROI is like taking your business’s temperature. It can let you know how financially healthy your business truly is, or even how profitable a category or a single product is. A low GMROI is often the cause of poor business performance for retailers.  The good news is once you know what your GMROI is, you can take clear steps to improve it. What is GMROI? You may already be familiar with the term Return on Investment or ROI. Traditionally, return on investment measures how much profit you get when you invest a dollar.  GMROI stands for Gross Margin Return on Investment, and is usually used in the retail industry for calculating profitability of inventory purchases.  In other words, the GMROI formula lets you know how much profit you get from each dollar you invest into inventory. It is a measurement of the...

Forecasting products you’ve never sold before is always a challenge. Without historical data to draw upon, how do you predict the best way to allocate them to stores, pricing, promotional demand, and balance online versus in-store sales? Guess wrong and you will run out of inventory, have too much inventory, or have the right inventory in the wrong place. - all costly mistakes.  The traditional approaches to estimating demand only hint at how a particular product will perform. Your store footprints, existing product mix, customer demographics, and many other variables are too difficult for analysts to fully consider. Retail Artificial Intelligence (AI) and advanced analytics significantly improve retail performance by incorporating hundreds of data inputs to produce reliable demand forecasts for new products. Without Past Performance, Product Forecasts Create Risk Introducing replacement SKUs or line extensions fits naturally into your existing demand forecast process. But the existing process cannot handle products without clear sales histories. As a result, new product forecasting introduces more uncertainty and risk into your business. You make significant commitments to your vendors when you launch a new product. Their forecast windows lock your initial orders and early replenishment orders. Co-marketing funds you receive require investments in store merchandising and promotional...

Most Important KPIs for the Retail Industry in 2020 Navigating changing consumer tastes and the evolving technology landscape has always made retail a challenging industry. Today, it is more important than ever for retailers to have a tight grip on the state of their business. Only with the right retail industry performance metrics can they answer questions like:  Do they have the right product mix? How effective are their promotional campaigns? Is the right product getting to the right place at the right time? Choosing the right Key Performance Indicators (KPIs) to measure and benchmark retail performance is essential to answering those questions. But of the myriad options, what are the KPIs in retail that will truly drive profitability and make the best use of a retailer’s substantial inventory investment? In reality there are many different retail verticals with their own unique considerations. Choosing the most important KPIs for a specific retail business will depend on your industry, merchandise, supply chain structure, selling channels and many other factors. Here are 12 common retail industry KPIs, why they’re used and how to improve them. Jump Ahead1. In-Stock Percentage2. Inventory Turnover Ratio3.  GMROI4. Revenue Growth5. Sales Per Square Foot6. Sales Per Employee7. Promotions Uplift8. Foot Traffic9. Conversion Rate10. Average...

Despite the fact that forecasting is a backbone of most retail organizations, there is still much confusion about the definition of a sales vs. demand forecast (as well as their respective benefits and drawbacks). All retailers use some form of forecast to anticipate the future, and the reason is simple. Without having an idea of how many items you will sell tomorrow, building a successful and lasting retail business is impossible. You'll end up buying too much of the wrong inventory and not enough of the right inventory, making your customers angry and losing massive sales. This is why retailers are becoming more and more data-obsessed, especially in regards to forecasting. A good forecast stands between being profitable and going bankrupt. And yet, Forrester Research found that while 74% of retailers want to be data-driven, only 29% are able to connect analytics to action. In other words, most retailers are still guessing with their data. They don't know how to use data to build accurate forecasts, nor how to leverage forecasting to build solid strategies. A major reason for this difficulty, as will be explained below, is that most retailers have still not grasped the difference between sales forecasting and demand forecasting....

Price planning is one of the most difficult (and often misunderstood) elements of retailing strategies. A relatively small change in price can have an enormous impact on product demand, and ultimately, your bottom line. “Pricing right is the fastest and most effective way for managers to increase profits.” (McKinsey & Company). That’s why the most successful retailers set pricing optimization as a critical priority. But emulating successful retailers in price planning isn’t enough. Standard price planning strategies (competition pricing, cost-plus, high-low, EDLP, etc.) may cover generic approaches to managing and optimizing price for any given product, but they don’t account for the most critical variables that determine your pricing success. These missing variables (like demand throughout product life cycles, pricing’s impact on demand, internal and external pricing constraints, etc.) ultimately determine how profitable your business is. Retailers who don’t account for these considerations often struggle with profitability. More sophisticated (and successful) retailers have built these variables into their price planning process to maximize their profits. So, what are these considerations, and exactly how do they impact pricing strategy? And moreover, how do you apply this knowledge to increase your profits? Table of Contents:1. Define Your Positioning2. Forecast Your Product Demand, Not Product SalesWhat’s the difference, and why does it matter?What does this mean for price planning?3. Get Granular With Unique...