Grocery retail has irrevocably changed. The last two years in particular have exposed many gaps in business. Predictive replenishment emerged as one of the major fault lines in the changed grocery retail environment with many retailers unprepared to address challenges such as frequent out-of-stocks, increasing inventory costs, wastage that comes with fresher and newer products, omnichannel nature of business, and shift in customer behavior.
Here are nine best practices for grocery replenishment that are fast catching on and can help you build a robust replenishment framework:
- A Good Demand Forecast Is Essential, However It Is Not the Only Critical Input
A good replenishment planning solutions system must also factor in existing inventory balance, expiration dates, open orders, average lead time, minimum order quantity, standard ordering frequency, and other data points that are key to effective planning. - Simulations Will Help to Hone Your Replenishment Strategy
Both demand and supply-side fluctuations characterize your supply chain. Monte Carlo simulations can create thousands of different ‘what-if’ decisions to develop supply chain scenarios. These scenarios can help you optimize your resources (cost), improve customer service, and strengthen your competitive approach with a robust replenishment strategy. - Leverage Optimization Algorithms to Get the Right Outcome Every Time
Artificial Intelligence in ai replenishment planning has proven effective in dealing with large-scale multifactorial optimization. AI can do the heavy lifting of identifying predictors and best-fit models for demand forecasts, and optimizing order plans for supply chain factors. - Factor in Supply-side Variations
In the past few years, grocers have realized that disruption in supply is an emerging threat and needs a mitigation strategy. Providing for probabilistic treatment of supply-side variations in your replenishment framework can go a long way in achieving that. - Collaborate With Your Supplier Base
Your replenishment framework is as strong as the weakest link of your supply chain. Even the best replenishment planning framework will fail if the supplier collaboration is poor and cumbersome. Think of supplier integration as part of replenishment planning. - Safeguard Against Risks With More Effective Guardrails
While accounting for expected risks such as delays in lead time during holidays, you must also be prepared for unexpected events such as inclement weather, war, and epidemic/pandemic. Setting up dynamic guard rails such as minimum inventory optimization turnover period as opposed to static ones like minimum safety stock levels can safeguard your operations. - Your Shelves Might Not Be Functioning The Way You Assume
First In, First Out is a fair assumption for ambient products. However, for fresh food categories, it is probably the opposite. Being astute, buyers select produce, meat, fish, poultry, and dairy that show no signs of spoil. They might anticipate that the grocer has placed the oldest inventory at the front and reach further back of the display.
When this behavior becomes a common practice, only dead stock remains on the grocer’s shelves. Hence, incorporating batch-wise stock balances and expiration dates in your retail replenishment software will avoid wastage and keep your shelf looking fresh. - Set Proactive Alerts To Act Preemptively
To ensure you order the right quantities at the right time, simplistic alerts such as the ones based on fixed pre-expiration timeline might not be good enough to react to grocery scenarios. Instead, a proactive notification based on a combination of factors—such as inventory demand prediction, stock balance, and product expiration— will help you course-correct in a timely fashion. - Let People and Technology Augment Each Other
While advanced technologies, such as AI and ML, augment the replenishment planning processes, there are certain limitations that are addressable only by human intervention. Make sure there are humans in the loop who can intervene as needed. People and technology augment each other well!
AI-powered Replenishment Planning Solution Tells You What, When & How Much to Order
Advanced technologies, such as AI and ML, bring revolutionary capabilities to the table across demand forecasting and automatic store replenishment – helping planners make snap yet faultless decisions every time.
One such solution is Algonomy’s Order Right, which helps planners shift their focus from tedious, manual number-crunching to 1-click intelligent order planning.
Order Right generates accurate SKU level order plans with its proprietary optimization algorithms that account for key supply chain and category factors such as shelf-life, lead-time, MOQ, etc. while constantly monitoring stock balance, sales, and demand predictions
