The Art and Science of Inventory Management


Inventory management. The term has become so familiar, and the practice such a part of the warp and woof of retail, that many don’t give it a second thought. But there’s always a need and opportunity to gain efficiency in inventory management, as it touches on and impacts every area of operations. This includes the warehouse or fulfillment center, omnichannel management, logistics and transportation, shipping and receiving, and the overall supply chain.

And oh yes, inventory management does overlap all of these functional areas in some fashion. Data on inventory levels needs to be conveyed to transportation managers so they can schedule shipments against plan. E-commerce and retail managers need access to real-time stock levels, with inventory often combined in a single pool, allocated by software.    

Consider all the downsides of inefficient handling of inventory. Stock levels run too low, or too high. Records don’t match between the website, the stores, and the warehouse. Forecasts are inaccurate, leading to missed opportunities (promotions, peak season, etc.) or higher carrying costs.

We’re going to take a deep dive into the practice of inventory management in retail, the challenges and opportunities – the art and science, if you will. Along the way, we’ll explore ways to adapt improvements through the troika of people, process, and technology.

The Dynamic Landscape of Inventory Management

Because business success is so dependent on inventory management accuracy, and access to data on stock levels and positions, there is little room for error in a highly competitive environment. In retail especially, having poor inventory management processes creates adverse effects in a number of ways.

There is a periodic shift back and forth from a prevailing inventory management strategy of “just in time” versus “just in case.” In the past couple of years, the consensus has swung from just in case – when pandemic-fueled supply chain uncertainty led to over-ordering and overstocks – to just in time, as stock levels have normalized and demand is low.

The current market picture rewards organizations that take an agile, responsive approach to inventory management, avoiding overstocking or stockouts. This is necessary in order to more accurately align SKU levels with fluctuating consumer and business buying patterns.

Whether the market is up, down, or sideways, having a poor handle on stock levels relative to demand and forecast is an expensive proposition. Consider this: Inventory carrying costs – what you pay for having it on the books – can range from 20% to 30% of total inventory costs. For this reason, the focus should be on lean stock levels and keeping inventory turn rates as high as possible to maintain margin.

Another downside of poor inventory management is missed orders due to stockouts, which happen when online availability doesn’t match actual SKU counts. Someone who clicks “buy” only to find that their cherished item isn’t available will likely buy from a competitor, perhaps never to return due to the poor experience.

Technology is playing a key role in enhancing inventory accuracy through the use of radio-frequency identification (RFID) tags, barcode scanners, and the Internet of Things (IoT). These systems, often in tandem, enable real-time tracking, inventory management, and inventory counts. When integrated with inventory management software and a warehouse management system (WMS), teams can automate data collection and reduce human error from manual counts. This leads to greater forecast precision, optimized stock levels, and an overall streamlined supply chain.

The Science of Inventory Management

By science, we don’t mean men in lab coats holding beakers, but it can involve data science! It encompasses all the technology and processes retailers and brands use to keep stock levels in the “Goldilocks zone” of not too much or not too little.

The goal is minimizing costs while meeting demand while avoiding overstocks or stockouts. A key metric in determining inventory efficiency is economic order quantity (EOQ). It uses a formula to determine the optimal number of goods required to meet demand while avoiding unnecessary costs.

ABC analysis is used to rank the business value of inventory into three main buckets based on demand, risk, and cost. This drives the decision-making process for inventory managers, helping them prioritize ordering, investment, and overall business focus.

Technology plays a key role as well. An inventory management system automates tracking and provides real-time data to drive smarter replenishment decisions at the SKU level and across channels. The aim is to increase efficiency, optimize stock levels, and improve customer satisfaction.

Inventory Forecasting

This process involves inputting data from a number of variables into a formula and analyzing the results to determine how much inventory is to be ordered for an upcoming sales period. One primary method is qualitative forecasting, based on data from previous sales periods; the longer the history, the better the forecast accuracy.

Qualitative forecasting leans more on analysis of external factors such as economic conditions and competitive research. Trend forecasting looks at data on SKU performance over time to surface things like shifts in consumer behavior, what’s hot on TikTok, or where VCs are placing their bets.

For brands supplying retail partners, tight coordination is required on demand forecasting. This involves regular communication, sharing real-time sales and inventory data, market trend analysis, and collaborative planning. The tighter the coordination, the better the forecast accuracy, alignment with demand, and SKU-level optimization.

As this is such a data-driven area, demand forecasting modules are often embedded in software platforms such as enterprise resource planning (ERP), customer relationship management (CRM), business intelligence (BI), and supply chain management (SCM).

Demand Planning

Demand planning goes a step further than forecasting. Inventory planners use forecasts to make strategic decisions on stock levels, production plans, and sales strategies. Inputs include forecast demand, along with other factors such as marketing campaigns, new product launches, and economic indicators.

Using analytical tools built into systems such as BI, ERP, and WMS, inventory teams determine stock levels and SKU assortments needed to meet projected demand without running into stockouts or overstocking. In short, the goal is aligning inventory levels with sales targets and marketing initiatives.

As in many other applications, retailers are using generative AI technology to assist in optimizing demand planning. High-tech personal styling service Stitchfix, for instance, uses GenAI to reimagine overall inventory management, demand planning, and forecasting through a deep analysis of customer preferences.

Inventory Replenishment and Safety Stock

Replenishment kicks in based on demand planning information. In a warehouse, one aspect of replenishment involves transferring inventory from reserve locations to forward picking so it’s available for order fulfillment. Again, a WMS or inventory management system keeps tabs each day on stock levels in each channel, as well as SKU velocity (how quickly each item is selling), in order to determine replenishment cycles.

Stockouts of course are very costly as dissatisfied customers are more than likely to go elsewhere if you don’t have what they want. But did you know that between 70% and 90% of stockouts are caused by poor stock replenishment methods? That means the overwhelming majority of them are within your control.

Inventory replenishment can become very complex, especially as SKUs can have a wide range of velocity levels, so reordering is happening at different times and different rates. Systems that automate stock management can track inventory levels and alert teams that it’s time to replenish based on preset guidelines.

Factors that drive replenishment schedules include demand, anticipated lead times from suppliers, and where you want to set your safety stock levels. When a SKU count hits a predetermined level, an inventory manager contacts the supplier to reorder.

Safety stock is inventory kept on hand in excess of forecast as a hedge against the risk of stockouts due to shifts in supply and demand. It acts as a buffer against variables like late delivery from suppliers, unexpected demand spikes, or supply chain disruptions, ensuring goods are available and customers are kept happy.

But as ballooning carrying costs are a profit killer, the difficulty lies in setting safety stock levels in the “Goldilocks zone” of just enough. This involves analysis of historical sales data, having a realistic handle on supplier lead times, and being aware of demand variability. Statistical modeling and inventory applications in systems such as OMS and ERP can help tremendously in driving inventory optimization. Safety stock levels should be regularly reviewed and adjusted based on market conditions and sales data in order to minimize costs and ensure customer satisfaction.

Inventory Allocation and Distribution

A major piece of inventory management is not only making sure you have optimal levels of each SKU based on current sales and forecast, but also that it’s placed strategically based on where demand is coming from.

The traditional retail distribution model followed a hub-and-spoke configuration, relying primarily on two, three, or more major warehouses to replenish regional stores. But with the rise of e-commerce, orders are going to consumers everywhere. This led many omnichannel companies to adopt a more diffused network model, with a number of smaller fulfillment nodes placed as close to high-demand centers as possible.

In many cases, retailers employed the now popular ship-from-store tactic, with each location acting as a mini fulfillment center. This approach really came into its own during the pandemic, when store closures forced retailers to adopt it as a survival tactic. Brands and manufacturers have been partnering with logistics providers such as 3PLs with broad network coverage, bringing inventory closer to demand to increase efficiency and saving on delivery costs.

Analytical tools have also played a major role in optimizing inventory allocation in an omnichannel world, based on demand patterns, customer history and preferences, and other signals. More recently, this has included leveraging AI and machine learning to quickly analyze various data sources and make allocation recommendations. This not only covers where to place inventory geographically, but by channel (retail, DTC, marketplaces, drop shipping, etc.).

When inventory allocation is done right, retailers and brands can maximize profitability by increasing the ratio of full-price sales to markdowns. By localizing assortment planning, for example, inventories can be tailored to meet specific preferences. Understanding regional trends and demands helps ensure the right products are available in the right places, leading to more full-price sales. This is especially critical in low-margin categories such as apparel, consumer electronics, and books.

Dynamic pricing tools can automatically adjust prices based on real-time demand, competition, and localized inventory levels. This helps drive up the ratio of full-price sales, improving profitability.

Performance Monitoring and Analysis

Once you have established an improved inventory management strategy, it’s important to maintain regular performance monitoring and analysis to ensure maintenance of operational efficiency. For starters, determine the key performance indicators (KPIs) or metrics that you want to track.

Here are some basic inventory management KPIs, along with a brief explanation of each:

  • Initial order fill rate: the percentage of orders completed within 24 hours, a key marker of fulfillment efficiency.
  • Inventory turn rate: the number of times the entire inventory is sold or “turned over” within a period (quarterly or annual), indicating the level of efficiency in managing stock and sales.
  • Final order fill rate: the percentage of orders completed at the end of a period, such as a promotional campaign or peak season, indicating efficiency.
  • Order cancellation rate: the percentage of orders canceled; this can be tracked based on reason code, such as “item out of stock” or cart abandonment.
  • Cost per back-ordered unit: This takes the total costs (customer service, fulfillment, shipping) divided by the number of back orders.
  • Return rate: percentage of returned orders.

A variety of software tools have modules that can track and manage inventory KPIs, including WMS, ERP, CRM, SCM, BI, and inventory management. The main goal is continuous improvement through data analysis, as well as processes like Six Sigma, kaizen, total quality management (TQM), and lean.

Communication and Collaboration

As noted, many functional areas intersect with inventory management, including operations and fulfillment, supply chain, transportation, marketing, and sales. Therefore, it’s critical to have regular communication and data sharing, ideally through a cross-functional team.

Fortunately, there are many great tools available to facilitate this kind of effort. On the communication side, Slack is a popular, intuitive platform for cross-functional collaboration, enabling one-on-one, channel-based, and general communication and file sharing. For virtual meetings, options range from Google Meet to Microsoft Teams, Zoom, and others.

Data management platforms like Google Cloud, Amazon Web Services, and Microsoft Azure offer data storage, database, and analytics capabilities so teams can securely share and analyze data across systems. Data visualization and BI tools such as Tableau and Power BI from Microsoft allow the creation of interactive, shareable dashboards that connect to virtually any database or file, surfacing insights for data-driven decision-making. File-sharing platforms like Dropbox and Google Workspace have a range of storage and collaborative capabilities. Other free tools include WeTransfer and Wimi.

Beyond the tools, it’s important to set up feedback loops so team members can surface and address potential issues and take advantage of new growth opportunities. For instance, demand forecasting models can be continuously refined by comparing projections against actual sales data. Feedback loops can also help identify optimal stock levels, reducing carrying costs and minimizing the risk of liquidation.

The Art of Inventory Management

Now onto the “art” side of the inventory management equation. This speaks to the importance of taking an approach that goes beyond the data, leaning on the value of industry knowledge to support a disciplined process.

This happens best through years of experience managing inventory across large and small organizations with a variety of product types, demand levels, and network structures. It requires an approach borne of working in B2B and DTC scenarios, from “eaches” for e-commerce to pallet/case for retail, to managing inventory with lot code expirations. From this comes an understanding of common inventory management issues so processes can be built to quickly identify and address potential issues.  

The “art” of inventory management involves nuanced, intuitive decisions that balance numerical analysis with human insight. It requires a deep understanding of the subtle dynamics of consumer behavior, the ebb and flow of market trends, and a grasp of intangibles like brand perception.

It also calls for a creative approach to problem-solving, the ability to forecast trends not yet reflected in the data. A skilled hand is needed to guide the complex dance of supply and demand, steering by gut instincts to help navigate the unpredictable. The “science” of inventory management seeks precision and predictability; the art combines agility and vision to craft a strategy informed by a deep understanding of customer wants and needs.

The Productiv Way: Wedding the Art and Science

Productiv, a leading 3PL specializing in retail and omnichannel fulfillment and distribution, represents the perfect marriage of technology and digital tools with industry savvy borne of deep experience. This has enabled Productiv to combine responsiveness with adaptability, meeting high-level brand SLAs while lowering the total cost of ownership (TCO). In a nutshell, Productiv helps brands increase supply chain velocity and get products to market faster.

On inventory management, Productiv develops custom SOPs for each client engagement, improving efficiency and operational performance. Inventory accuracy is optimized by use of automated cycle counts. Robots equipped with computer vision read ID tags and compare totals against WMS data, significantly reducing error rates and false positives.

Product density of reserve stock is maximized by determining the optimal storage medium for each SKU (pallet, bin, case, racking, pallet, shelving) based on demand and outbound requirements. This increases efficiency by making the best use of every square foot of active space, eliminating waste and paying for “air.”  

Using “the Productiv way,” which employs lean principles and precision-engineered processes, omnichannel inventory is allocated in a highly efficient manner. This minimizes the need for brands to break cases and pallets in order to fulfill online “each” orders. In other words, you won’t be “robbing Peter to pay Paul” by shorting B2B stock. Productiv’s WMS allocates inventory into channel “buckets” by unit of measure, minimizing excess or duplicate stock and saving on carrying costs. Inventory transfers from reserve to forward picking locations are limited to once per month, saving both time and labor costs.

Through feedback mechanisms and root cause analysis, Productiv takes a deep dive into shortfalls against plan or errors in production to prevent future occurrences. For instance, a shipment may incur a retailer penalty for missing its strict “on time/in full” (OTIF) requirement. Productiv takes a granular, SKU-level look at inventory in each channel to ferret out the problem. Why did retail cases run out if e-commerce had adequate stock levels to meet demand? Is allocation being handled properly? Where did it break down? Every scenario is addressed and every question is answered to course-correct the process.

When it comes to kitting and assembly – increasingly vital in e-commerce, especially with customization, subscription services, and bundling – Productiv’s processes help limit out-of-stock situations on component parts to keep production humming. Suppliers are proactively notified when a potential shortfall is on the horizon.

Inventory Management: A Lot of Moving Parts Ensure Parts Move Where and When They’re Needed

Yes, managing and optimizing stock levels both geographically and by channel is a highly complex process. When it breaks down, the results become quickly apparent: missed orders, late deliveries, a mad scramble to restock, or a CFO looking askance at the bottom-line hit from overage. But when done right, inventory management is indeed a mix of art and science, a symphonic blend of technology with battle-tested industry experience.  

With a strong industry track record in retail and e-commerce logistics and fulfillment, Productiv works closely with brand inventory managers to optimize order fulfillment, logistics, and transportation. We have an in-depth knowledge of routing guides and requirements at more than 60 major retailers, ensuring strict compliance and providing peace of mind that all your commitments are being kept. To learn more, talk to an expert today.


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