Here's how you can optimize inventory levels by leveraging data analytics tools.

Businesses can attain ideal inventory levels with the use of data analytics. ?? To avoid stockouts and overstocking, firms can estimate demand and determine reorder points by analysing sales data, past trends, and lead times. Analytics can also be used to optimise warehouse layouts and identify slow-moving inventory, which lowers carrying costs and boosts productivity. ??By using a data-driven strategy, companies may maximise profitability and customer pleasure by having the appropriate amount of stock on hand at the correct moment.

- Demand Forecasting: Predict demand accurately, avoiding overstocking/ stockouts. - ABC Analysis: Prioritize inventory efforts based on item value. - Safety Stock Optimization: Adjust levels to prevent stockouts while minimizing excess inventory. - Supplier Collaboration: Enhance lead times and order accuracy. - Optimized Order Quantities: Determine cost-effective quantities. - Inventory Turnover Ratio: Efficiently convert inventory to improve cash flow. - Dynamic Pricing Strategies: Stimulate demand with promotions. - Warehouse Layout and Organization: Optimize layout for efficiency. - Technology Integration: Streamline tracking and forecasting. - Continuous Improvement: Monitor metrics, refine strategies for efficiency and profitability.

Let's define "Optimize Inventory". Optimizing inventory is balancing two numbers. 1. Having the smallest number of items on hand at all times 2. Lowest lost sales due to inventory unavailability. This is the sweet spot. But how each of these are done at different for different types of companies and their business model. This can differ from MTO (Made to Order) to MTS (Made to Stock). For rentals vs sales. And for raw materials vs finished goods. Breaking it down to key elements that suit your specific business is important before we jump into data. It's important to set the objective.

Inventory level data analytics is very important to leverage on stock of inventory. Say if I get alert before issue of PO to know how much I have theoretical stock I can take the purchase decision wisely. Also I can prevent stock out , get stock at lower price , keep Stock Turnover in control.

Look at your sales trends and what category is moving based on seasonality , the inventory that’s not performing well create an action plan to reduce the dead inventory that will help you manage your inventory yearly,

1. Historical Sales Data: Leverage historical sales data to forecast future demand. Analytics tools can identify seasonal trends, account for promotional periods, and factor in external influences like economic conditions. 2. Machine Learning Integration: Some advanced data analytics platforms incorporate machine-learning algorithms. These algorithms can analyze vast amounts of data (including external market data) to generate even more accurate demand forecasts, minimizing the risk of stockouts or overstocking. 3. Safety Stock Optimization: Based on your forecasts, optimize safety stock levels to ensure you have enough inventory to meet anticipated demand without tying up excessive capital in stock holding costs.

Utilize statistical methods or machine learning algorithms to forecast future demand for your products. Time series analysis, regression models, and predictive analytics can help predict demand patterns accurately. It is extremely important to identify the correct error measure which takes into account bias.

Data analytics will give you a view of trend movements with the outlook of the future. Forecasting will then utilize these insights coupled with human sentiment(sales, marketing and Executive view) to determine what an ideal requirement and level is to hold. At the end of the day we get paid when the customer receives and pays for the product. Hence product availability in a billed invoice has to be the ultimate goal of any inventory modelling. So take into consideration the below 1.Data trends and insights 2.Human input 3.Warehouse and logistics limitations 4.Speed to market or turnaround to meet the customer needs. 5.Any other constraints that may limit or lower customer service .Then determine what the optimum inventory is.

As a maintenance planner I have to be very well informed and familiar with: 1-Technical aspects such: The maintenace schedule for all the equipments and engines under my supervision, their maintenace types, parts life time as per original equipment manufacturer, change intervals, mean time between failures, utilization, recommended service hours. 2- Commercial aspects: Lead time, spare category shelf item or made to order, suppliers history, local or overseas, nature of the parts, whether you can stock or they have a short shelf life. long term supply price agreements can also greatly affect positively smooth uninterruptible supply and regulate inventory level. Both technical and commercial aspects data analysis lead to effective stock

Demand forecasting is integral to achieving a fine balance between inventory levels and customer demand, thereby minimizing the risks of overstocking or stockouts, while enhancing operational efficiency and customer satisfaction.

Supply chain is dynamic. Inventory management has to be on Minimum Maximum pattern. Also there has to be a periodic review of the Sales pattern. Fefo has to be arranged and team to be dedicated for same with ownership of working zone Stock pull out as per movement pattern 1. Non Moving items . 2. Near Expiry items. Programming needed to maintain all this in cycle. Exception reports / checks to be managed for reviewing the process.

Gather data from all corners of your operations, from sales records, supplier lead times, inquiry records Piece it all together, using data analytics tools. Using this data to predict the future You anticipate peaks and valleys in demand, helping you stock up just enough2 meet customer needs without overstocking Fine-tune your inventory levels using sophisticated algorithms that balance factors like lead times, costs, and service levels. It's not a one-time thing. Refine&improve your inventory mgt based on real-time data & insights. By harnessing the power of data analytics, you're not just managing inventory – you're orchestrating a symphony of efficiency&customer satisfaction. #the physical operations = automated operations.

We can improve it by following things 1.supplier Onboarding and performance monitoring 2.Supply Chain Transparency and Traceability 3.Dynamic Supplier Collaboration Platforms etc

Strong supplier relationships can have a number of benefits for inventory management. 1. Improved forecasting:?When you have a strong relationship with your suppliers, you can get better insights into their production capacity and lead times. This can help you to improve your?forecasting accuracy?and avoid?stockouts. 2. Reduced costs:?Strong supplier relationships can help you to?negotiate lower prices and better payment terms. This can save you money on?inventory costs. 3. Improved quality:?When you have a strong relationship with your suppliers, you can work together to improve the quality of the products you sell. This can lead to increased customer satisfaction and loyalty.

With available data we can understand actual lead time. How many times delay/fail/rejected to supply with valid reason. Periodic analysis we understand supplier performance & accordingly decide to alternative supply locations

Inventory turnover ratio=cost of goods sold/ average inventory Cost of goods sold=opening inventory+purchase -closing inventory

Inv. Turnover is a crucial point for the business. Since the CCC depends on 3 Parts. One of these parts is DIH which is the opposite of Inventory Turnover. So when increasing the Inv. Turnover we support the Cash flow in the business. To make the Inv. Turnover better we should do the following: 1) Streamline the supply chain: streamlining the supply chain to eradicate inefficiencies will benefit your sales, profits, and overall margins 2) Adjust your pricing strategy: Adjust pricing to realize larger margins. 3. Classify your stock in your industry:?Understanding your stock classification helps you to measure your turnover correctly 4. Improve forecasting: Sales and inventory reports supply 5. Automate purchase orders.

Unlock the power of inventory optimization with advanced tools that analyze sales patterns and market shifts. By accurately forecasting demand, businesses can fine-tune their stock levels to avoid overstock or shortages. Identify sluggish-selling items and take decisive action to clear excess inventory, driving up profitability. With these insights, businesses can streamline inventory management, cut expenses, and meet customer needs with precision.

* Inventory turnover shows how quickly a company sells and replaces its inventory. * High turnover can mean good sales or managing inventory well. * Low turnover means having too much stock or not enough demand. * Using data analysis helps track and understand inventory turnover.

I'll put my 30 year retail hat on. Too many times inventory is over bought for the sale and hung on to for too long for not wanting to mark down. Respectfully, this is how TJ Maxx companies have created their whole business model. As well as Nordstrom rack. The pride has to go! Every promotional buy is not a winner, get over it. Your cost margin is still quite large, retailers! Bite the bullet, clearance it out, get it off the ledger in the same quarter. Customers shop bargain places for bargains, top retailers for best, newest, highest quality.

Highlighting the significance of analyzing aged stock by last purchase date, especially when reviewing historical sales data. While examining slow-moving items based solely on sales data is crucial, incorporating the last purchase date offers a more comprehensive understanding of stock dynamics.This helps us identify "dead batches" or stagnant inventory that may require attention. Also,helps prevent exposure of wrong merchandise. It ensures that products are not inadvertently stocked beyond their shelf life. By actively monitoring last purchase dates, we can take proactive measures to rotate stock, implement markdowns, or explore alternative strategies to prevent losses due to product deterioration.

Strong collaboration and timely decisions can help the data that is available. Delays in approvals and alignments make the ERP data ineffective.

Eliminating Waste is otherwise know as WOW (wealth out of waste). Fix periodicity for identifying & disbursement of waste. Resulting good productive time saving, huge cost saving etc.

One of the wastes that we have is Extra Stock. So, it is essential to have all the needed calculations to avoid such results while considering the customer's needs. This Calculation Like: 1) EOQ (Economic Order Quantity. 2) ROP (Re-order Point) 3) Safety Stock 4) Warehouse Capacity 5) Inv. Process throughput 6) WH productivity ratio.

No matter how lean your operation is, your company will likely end up with excess inventory at some point. The culprit may be previously purchased product arriving from areas with supply chain constraints, purchasing too much, or overly optimistic forecasting.? In most cases, you won’t be able to recover all your costs. But, at least you can stem the bleeding from carrying costs and halt the inevitable decline in value faced by aging inventory. At least annually, your company should evaluate potential obsolete inventory or inventory whose value is less than cost. Amounts that would be considered obsolete, or value has reduced, should be adjusted in the financial statements accordingly.

The biggest inventory you will ever keep is your customers happiness! It is important that they know that you care about them enough to learn what they need and to keep their most valuable assets on hand at all times. I have conversations around par levels with my customers often. I find that in limited areas it is best to truly understand what to keep on a minimum to maximum space for higher moving items. These small conversations make a big impact in improving interrelationships.

Customer feedback is the important role. Indentify mater reached customer destination. Customer got itas per required time & place

Effective inventory management is crucial to maintaining accurate stock levels, avoiding product shortages and shortages, and consequently customer dissatisfaction. Paying attention to customer feedback is essential to have the products they are looking for, generating satisfaction and loyalty.

data analysis ,helps in making sure that you keep the correct stock and right quantity ,that will assist in customer satisfaction and loyalty

Ensure there are clearly defined success and failure criteria for inventory optimization then report compared to the predefined endpoints. Often there is misalignment in companies about what success looks like. Defining the expectations allows everyone to be on the same page and allows for the data to be meaningful.

Utilize real-time data analytics tools to monitor inventory levels, track sales trends, and identify inventory anomalies or deviations from expected patterns. Implement automated alerts and notifications to flag stockouts, overstock situations, or inventory discrepancies in real-time, enabling proactive intervention and corrective actions. Leverage predictive analytics algorithms to anticipate future demand fluctuations and adjust replenishment plans dynamically to align with changing customer needs and market conditions.

Data Collection: Gather historical sales data, supplier lead times, and demand forecasts. Demand Forecasting: Use statistical methods or machine learning algorithms to predict future demand accurately. Supplier Analysis: Analyze supplier performance, lead times, and reliability to ensure timely replenishment. Inventory Optimization Models: Employ techniques like Economic Order Quantity (EOQ), Just-In-Time (JIT), or reorder point optimization to determine optimal inventory levels. ABC Analysis: Categorize products based on their value and prioritize inventory management efforts accordingly.

To optimize inventory levels, you can leverage data analytics tools to predict future demand based on historical patterns, seasonal trends, and other influencing factors. This can help prevent overstocking or understocking, ensuring you have the right products available at the right time. Additionally, data analysis can identify opportunities to reduce costs, improve operational efficiency and increase customer satisfaction.

Ensure there are clearly defined success and failure criteria for inventory optimization then report compared to the predefined endpoints. Often there is misalignment in companies about what success looks like. Defining the expectations allows everyone to be on the same page and allows for the data to be meaningful.