If you’re in retail, you have an inventory planning process of some sort—even if you’re just entering numbers into an Excel sheet or jotting down notes on a piece of paper. But now isn’t the time for data-starved, gut decisions in this tough economy.
Good news, though: There’s a better approach. With a modern data tool, you bring real-time inventory data into a centralized, accessible platform that guides decision-making for the whole team.
Here’s a practical guide to building an inventory planning process that boosts operational efficiency and profits.
Table of contents:
Inventory planning is the process of determining the ideal amount of stock you need on hand at any given time to meet customer demand. The goal is to predict customer demand and then accurately plan lead times to have the right amount of stock available.
Inventory planning is a vital part of the broader process of inventory management.
The inventory management flow typically goes like this:
Purchase: Purchase inventory according to your inventory plan
Store: Keep your stock in a secure area
Use: Either sell that stock (if you’re in retail), use it to make something (if you’re in manufacturing), or use it for repairs, maintenance, or employee well-being (think office supplies)
Track: Monitor what’s in stock so you know when to buy additional supplies
Reorder: Restock based on demand
Forecast: Lean on past data and predictions about market demand to identify your inventory needs
Inventory planning is used throughout the inventory flow to ensure you purchase the right amount of stock, minimize the amount sitting on shelves, reorder at the optimal time, and correctly forecast future inventory needs.
There’s inventory planning, and then there’s inventory “planning.” Too many businesses still stock shelves based on high-level, generalized data and “what happened last year.” In other words—they guess.
If you’re doing this, no judgment. You might be limited by your company’s legacy tools, processes, and systems that unintentionally silo data. Getting unified, insightful data out of these tools usually requires expert help.
You might have to wait weeks for an ad-hoc report on the more granular details of customer behavior. When you have the data to make an accurate forecast, the ship has (sometimes literally) sailed. ⛵
It's no wonder that gut feelings and past trends often make inventory decisions. But with the right data analytics tools and data-rich inventory planning, you’ll see benefits like:
1. More profitability
Inventory planning lets you forecast customer behavior with far greater accuracy and spot unexpected trends—leading to more revenue for your business.
For instance, imagine you run a chain of department stores that carries swimwear in the summer. With granular data insights, you might notice that customers in affluent areas take more winter vacations to hot countries. Knowing this, you could order more swimsuits for specific locations to meet the off-season customer demand—resulting in increased revenue.
2. Happier customers
By accurately predicting demand and maintaining sufficient inventory, you avoid stockout costs (when you run out of products) and backorders (when you must delay fulfilling an order while you wait for new stock). And when your customers know they can rely on you, they’re more likely to make future purchases.
3. Reduced holding costs
Holding or carrying costs are the expenses associated with storing your inventory. They can be significant, adding up to 20–30% of your overall business cost. But with more accurate forecasting, you reduce overstock and decrease spending.
4. Additional cost savings across the inventory flow
In fact, with better inventory planning, you cut costs throughout the entire inventory cycle:
Improve how you monitor product shelf life and expiration dates to avoid spoilage.
Identify opportunities to shift stock via discounting and rotating.
Eliminate redundancies and duplications—for example, you know product X is almost identical to product Y, even though they have different SKUs.
5. Improved supply chain
Last but not least, better inventory planning creates a positive ripple effect down the whole supply chain. You can:
Track your lead times more effectively so you don’t need to rely on supplier estimates.
Avoid stockouts even during supply-chain issues such as power outages or transportation delays.
Strengthen your supplier relationships. When you share demand forecasts with vendors, you create a win-win partnership leading to more favorable pricing terms and faster order fulfillment.
Learn more about supply chain data analytics.
Canadian Tire: Coming out swinging after the pandemic
In 2020, Canadian retail giant Canadian Tire learned the importance of using data to drive inventory decisions. Due to COVID-19, Canadian Tire had to close around 40% of its retail outlets. But after turning to ThoughtSpot for help, Canadian Tire saw their sales increase by 20% in Q2 of 2020.
Eddie Weekse, Canadian Tire’s Manager of Merchandise Planning, says their data existed in siloes before introducing ThoughtSpot. The problem, he says, is “people don’t know what they don’t know.” Now, with ThoughtSpot, his team accesses multiple data sources at once and uses that data to build trust with their merchants—and drive business growth.
Watch how Canadian Tire overhauled its inventory planning process in 2020 right here.
When done well, inventory planning creates clear wins for everyone involved—you, your suppliers, and your customers. Follow these six steps to level up your inventory planning processes:
1. Assess demand and sales patterns
You must analyze company and market data for the most accurate demand estimates. You probably already monitor market trends and seasonality—but looking at your historical sales data is a bit trickier.
First, you need to bring sales data together from disparate sources to create a single source of truth. This may require you to move away from siloed legacy systems and toward a cloud data warehouse that can handle complex data sets. Here’s an in-action example of what we’re talking about:
If you implement a modern data stack and create an interactive retail dashboard like the one above, you can analyze your historical sales data more granularly. Instead of tracking overall trends, you get SKU-level insights on units, price, promotions, per-store behavior, and anything else your team can imagine.
Want more? Watch this webinar to see how retailers use ThoughtSpot for SKU-level sales analysis.
2. Set inventory goals and objectives
With your new insights into sales patterns and market trends, you can set more precise service levels—targets for how often you fulfill orders without running out of stock. Establishing service levels is a trade-off between keeping customers happy and low costs. For instance, you need to determine how to stock enough inventory to meet customer demand—but not so much that you overstock and overspend.
Supply chain consultant Nicolas Vandeput cautions against setting arbitrary service-level targets. For instance, saying you want to reach a 95% service level—meaning there’s just a 5% chance you’ll run out of stock—just opens up more questions:
How do you know if 95% is optimal? Why not 98% or 92%?
Should every single product reach a 95% service level? Or is it just an average?
Instead, try targeting more nuanced, detailed inventory metrics.
Key inventory planning metrics
Inventory turnover: How quickly you sell and replenish inventory
Turn rate per product: How long it takes to sell out of a specific product
Stockout rate: Percentage of time a product is out of stock
Fill rate: Percentage of customer orders fulfilled from available inventory without backorders
Backorder rate: Percentage of customer orders placed on backorder
Lead time: Time from order placement to order fulfillment
Overstock rate: Percentage of stock that sits on warehouse shelves unsold
Here’s a complete list of KPIs and metrics for retail decision makers if you’re curious.
3. Forecast demand
At this point, you’ve gathered your data and decided which metrics to track. Now it’s time to analyze your customer data and use statistical forecasting methods to estimate your inventory requirements.
Read more about advanced sales forecasting methods on our blog.
With ThoughtSpot, this process becomes dramatically easier. ThoughtSpot offers AI-Powered Analytics to search and analyze billions of rows of data from any source—from online sales to social media conversations, inventory sales, and even in-store sensors—in seconds.
4. Determine reorder points and safety stock
Calculating when to replenish your stock is as important as planning your initial order. To determine your reorder points, base lead times on actual data rather than supplier estimates. Then, decide on appropriate safety stock levels for any unexpected variability.
ThoughtSpot Monitor simplifies this process. It tracks your stock levels and automatically notifies store owners when their inventory gets low. Automation like this allows you to easily manage company-wide re-ordering thresholds and standardize service levels across stores.
5. Collaborate with suppliers to manage lead time
You need solid relationships with your suppliers to optimize your inventory management—and that takes data. With hard facts about lead times, like actual sales data and accurate forecasting, you set yourself up as a retailer of choice. This makes it far easier to negotiate favorable lead times, take priority in your suppliers’ decision-making, and build a mutually beneficial relationship with suppliers.
6. Implement inventory control measures
You’re ready to set up stock monitoring systems to ensure your data stays up-to-date. As always, the “garbage in, garbage out” principle applies. Conduct regular audits on your data to ensure accuracy and improve inventory control.
What works for one business won’t work for another. Here are some strategies to optimize your inventory levels and meet customer demand.
1. Just-in-time (JIT) inventory management
If you have strong relationships with your suppliers and a reliable supply chain, consider JIT. With this strategy, you carry only the minimum inventory levels by stocking just before production or customer orders.
2. Economic Order Quantity (EOQ)
The EOQ formula models the optimal order quantity to minimize inventory carrying and ordering costs. It’s based on factors like customer demand, ordering costs, holding costs, and lead time.
3. ABC analysis
The ABC approach categorizes inventory into three groups (A, B, and C) based on the items’ value, demand, and profitability. You then focus on meeting service level targets for products in Category A first, B second, and so on.
4. Safety-stock planning
Safety stock is the additional inventory you hold as a buffer if operating in a space with lots of demand or lead time variability. With accurate demand forecasting and historical data analysis, you calculate the appropriate safety stock level to prevent stockouts and meet ever-fluctuating demand.
Find additional inventory optimization techniques here.
ThoughtSpot lets organizations optimize inventory with AI-Powered Analytics. With our intuitive business intelligence (BI) experience, your team members can view stock levels, sales trends, and customer demand in real time from any device.
The result? You stay on top of all the details you need to maintain optimal inventory. Plus, you get self-service reporting capabilities from a central platform, leading to improved operations processes, reduced costs, and greater profitability. Sign up now for a free trial with ThoughtSpot and see how our inventory optimization solution saves your retail business time and money.
