It’s a new day at your store, the place is all set with a welcoming ambience. But alas! Your customer ends up in front of an empty shelf, disappointed and dejected.

These events are setbacks that arise out of the blue which not only disappoint the customers but also affect the revenue of businesses. It is crucial for every inventory driven business to proactively predict these out-of-stock situations across various channels to avoid loss of sales and damage to the brand’s reputation. However, most businesses struggle to forecast the right amount of inventory to be stocked owing to the dynamic nature of demand and ever changing customer preferences. Eventually, businesses end up denying the pleasure of instant gratification to the customers and also help their competitors grow as a result of stockouts. This is where advanced concepts of Demand Sensing with cutting edge technologies like AI and ML come into play.

Demand Sensing has become more accurate and seamless with AI and ML driven tools that help optimize each stage of the supply chain effectively.

Causes of Stockouts

Here are a few common causes of stockouts that will help you take the required preventive measures.

Unexpected surge in demands due to external and seasonal factors

While it is obvious that not all products in the store sell at the same pace throughout the year, businesses struggle to forecast peaks in demand proactively. This happens when they lose sight of certain influencing factors like the weather, holidays, marketing events and promotions etc. Eventually, surge in demands come as unwelcome surprises leading to poor customer experience.

Inaccurate demand forecasting methodology

Even today, most companies rely on non-scientific, gut based predictions made from fixer-upper calculations over many excel sheets to plan their inventory. In addition to being a cumbersome process, this also leads to inaccurate predictions. Demand planners need to move to a more statistically sound framework with the help of advanced inventory planning software to keep up with the dynamic nature of demand and plan inventory accordingly.

Poor shelf replenishment practices

Replenishment is a crucial process that occurs on a regular basis whose potential is often untapped. Businesses that have versatile product lines and several SKUs find manual store replenishment practices grueling. They fail to identify product specific attributes  and  service levels leading to inaccurate forecasts. Rather than looking at replenishment as a mere repetitive process, it is critical to understand its benefits - Improved Inventory Turnover, Lower Operation Costs and Higher Service Levels. These benefits can be reaped with the help of an automated replenishment setup that can eliminate human errors and derive valuable insights from huge amounts of data.

Kronoscope brings the capability of dynamic inventory planning where automated replenishment plans can be setup that dynamically adjust inventory norms, safety buffers and reorder points. Such dynamic replenishment plans completely eliminates human error and help derive valuable insights from large amounts of data.

Inadequate levels of safety stock

Safety stock comes in handy when the on-shelf stock is insufficient to meet the customer demand. However, there is no one-size-fits-all safety stock strategy that can be implemented across all SKUs. For instance, a business that sells perishables or items that have a shorter shelf life should plan their safety stock appropriately so that they don't end up with excess inventory and wastage. Whereas, a business that sells durables or industrial machinery should plan their safety stock ensuring that they don't run out of stock or have their working capital locked in excess inventory. It is also important to factor in aspects like demand variability and service levels to ascertain the appropriate level of safety stock.

Effects of Stockouts

When a customer is ready to buy a product but finds it out of stock, they will either buy it from a different brand or end up not buying it at all. Either way, it is a loss of revenue for the business. Stockouts can also have a serious impact on brand loyalty as customers tend to shop from a different brand. This will inadvertently help the competitors grow and capture your market share. Moreover, it may lead to negative sentiment and tarnish the brand’s reputation.

How does Kronoscope help fix Stockouts?

Fountain9’s AI powered inventory planning solution - Kronoscope, helps identify potential stockouts ahead of time and make informed decisions using the following outlook:

‍

A Bottom Up Approach

Most businesses use a top down approach to forecast future demands. While it is helpful in predicting the demand at higher levels like the mother warehouse, they fail to provide accurate information when we move further down the supply chain.

A bottom up approach works better as it starts with predictions at points that are closer to customers and eventually gets to the top with more accurate demand forecasts. Kronoscope is equipped with ML algorithms that learn the changing trends, cyclic effects, impact of promotions, etc. for each SKU + darkstore. With enhanced accuracy and real time predictions, we can move away from reactive planning to active solving.

Real Time Demand Sensing

A traditional approach where demand is forecasted on a monthly basis becomes futile in today's volatile world. Even a slight deviation from the predicted numbers can begin as a hiccup and soon escalate into a catastrophe. This will deprive us of opportunities to create value. However, these situations can be avoided by continuously sensing demand signals.

Kronoscope with its active demand sensing capability facilitates refreshment of future demand predictions on a daily basis to align with changing demand in real time. This is done by collecting data on buying patterns of customers to deal with volatile demand and unanticipated changes in customer behavior.  

Availability Based Adjustment

As a key decision maker, demand planners need to understand demand on a root level. Kronoscope takes inventory as a signal to infer when there were low sales and finds a correlation to low stock or to actual low demand. If low sales are a result of low stocks, Kronoscope calculates sales if there were no availability issues. This calculation is then used for future demand predictions. This step is crucial because if demand is not adjusted based on availability, the cycle of incorrect demand predictions will continue.

Accurate Stockout Prediction

It is essential for every business to maintain appropriate inventory levels to ensure customer satisfaction. Yet, there are situations when stores end up with empty shelves and miss revenue opportunities. This happens when they underestimate demand and are not equipped with adequate safety stock to meet the unexpected surge.

We’ve got that covered. With the help of its proprietary algorithm, Kronoscope allows businesses to identify their potential out of stock losses and inventory costs ahead of time.This enables them to procure and replenish more proactively and cut down on future out of stock losses.
           

In summary, technologies like AI and ML equip businesses with the superpower to predict the future  enabling them to proactively manage their supply chain activities rather than reacting to misalignments after they have occurred.

‍