Optimizing Supply Chain Decisions: Rule Engines for Enhanced Inventory Management

Łukasz Niedośpiał
June 6, 2024
Blog

$1,6 trillion is at stake.

This is the cost of revenue missed due to supply chain disruptions. 

In this article, we'll talk about:

  • main issues of supply chain management and how fixing them can improve your business profitability and operational efficiency,
  • how business rules engine (BRE) can help you manage inventory,
  • what are the top benefits of implementing business rules engines,
  • how to integrate BREs with Data Analytics and IoT for even better performance.

Read on.

Supply Chain Problems: Demand Volatility, Supply Disruption and Inventory Waste

Companies face various supply chain problems and difficulties in the management of the supply chain. These problems cause operational waste and cost the business dearly. 

Here we discuss the top three common issues faced in supply chain: demand volatility, supply disruption and inventory waste.

Demand Volatility: The Incredibly Volatile Uncertainty

Demand volatility is a key supply chain problem which gives sleepless nights to supply chain managers. The variability in customer demand is difficult to predict due to various reasons like seasonality, competition and economic indicators. During peak demand periods, the company may not be able to fulfill the customer orders leading to stockouts and lost revenue. During low demand periods, the excess inventory accumulates resulting in blocked funds and carrying costs.

Scenario Example:

A retail company’s demand for winter coats may suddenly increase due to early onset of snowfall. In the absence of proper demand forecasting and agile inventory planning, the company may either not have sufficient inventory to meet demand or may overstock winter coats, if the snowfall does not occur.

Supply Disruption: The Hidden Dangers

Supply chain faced supply disruptions are another set of problems which bring the supply chain activity to a halt. The reasons for supply disruptions can vary from natural calamities, political issues, labor strikes to supplier bankruptcies. The effect of these disruptions propagate through the supply chain causing delays, cost overruns and plant shutdowns.

Scenario Example:

A manufacturing company may source a critical component from a single supplier. A factory shutdown due to a natural disaster of the supplier’s plant may bring the entire manufacturing activity to a halt causing delivery delays and customer dissatisfaction.

Inventory Waste: The Stealthy Profit Drain

Excessive inventory, dead stock and low inventory turns are some of the inventory waste which drain the profits of the company. Excess inventory accumulates blocks the funds which otherwise could be invested elsewhere in the business. Lack of inventory may cause loss of business to the company. Maintaining a healthy inventory balance is a tough task.

The Role of Business Rule Engines in inventory management

In today’s competitive business environment, companies are investing in various advanced technologies to automate their supply chain movement. The supply chain optimization technologies are critical to gain competitive edge and to survive the market threats. Among the various supply chain optimization technologies, rule engines are widely used in inventory optimization.

What is a Business Rules Engine?

A rule engine is a software component that carries out business rules of an organization. Business rules are logical statements which define an action or a decision to be made under a given condition. Rule engines automate the decision making process and ensure accuracy, consistency and performance across a range of business applications including inventory optimization.

The key elements and characteristics of business rules engines are:

  1. Rule Repository: A central location for storing and managing business rules.
  2. Inference Engine: The intermediate layer which evaluates rules and fires them based on the input data.
  3. Tools for Authoring and Managing Rules: A simple and easy to use interface for business analysts to write, update and maintain rules without programming expertise.
  4. Execution Environment: The runtime framework in which the rules are deployed and integrated.

Business Rules, Business Logic and Inventory Optimization

Business rules depict the logic and policies an organization should follow for decision-making. In inventory optimization, business rules can dictate anything ranging from simple reorder point calculations to complex stock optimization based on demand forecasts. 

The business logic is the framework and the algorithm which evaluates the rules and produces results.

Business Rules in Decision-Making Processes are Important Because of:

  • Consistency: Inventory decisions are made consistently across business locations eliminating any scope for operator errors.
  • Expandability: Complex multi-location, multi-system decision-making is easily manageable.
  • Flexibility: Business rules can be modified anytime to accommodate changes in business environment or market dynamics.

Few Rule Engine Examples in Inventory Optimization

  1. Reorder Points – Rule engine calculates the reorder point based on the current sales, lead time and safety stocks. When the inventory level reaches the reorder point, the supplier may be notified wirelessly to place the order. This ensures just in time inventory replenishment avoiding excessive or insufficient inventory accumulation.
  2. Demand Forecasting – Rule engine analyzes the past sales movement and external market indicators to predict the future demand for the products. The inventory purchasing or production planning may be triggered based on the forecasted demand and stock levels.
  3. Safety Stock Levels – Rule engine may calculate the safety stock levels dynamically based on the demand volatility, supplier performance and lead time variability. This ensures that the safety stock may always be greater than or equal to the minimum stock required to meet unforeseen demand or supply disruptions.
  4. Dynamic Pricing – Rule engine adjusts product prices based on inventory levels. When stock levels are low, prices may be increased to balance supply and demand. Conversely, when stock levels are high, prices may be lowered to stimulate demand and prevent excess inventory buildup.

Benefits of Implementing Rules Engine – how it improve supply chain management

The rule engines, when implemented in inventory optimization, offer various advantages to the business by partially automating decision-making processes. It gives a competitive edge to the business in the market and brings unparalleled efficiency to business operations. 

Here are some of the advantages of rule engines in optimizing supply chain business processes.

Faster and Accurate Decision-Making

Rule engines partially automate the decision-making processes ensuring uniform application of business rules across the enterprise. The complex decision-making is completed faster with less effort reducing the human bias and errors and improving risk management.

Few Examples of Faster and Accurate Decision Making:

  • Inventory Replenishment: The rule engine automatically calculates the reorder points and may trigger the purchase orders when the inventory levels reach the threshold value. This is what Amazon does.
  • Demand Forecasting: The rule engine analyzes the external and internal data indicators and adjusts the demand forecasts when the inventory levels reach the maximum or minimum stock points.

Thus, business rule engine software works best when integrated with data analytics, machine learning, and IoT.

Improved Efficiency: Simple and Flexible Operations

The inventory optimization processes when automated reduces the intensive manual effort. The rule engines process the repetitive and complex decision-making scenarios automatically, freeing the human effort which could be directed towards other strategic activities.

Improved Efficiencies:

  • Minimized Manual Efforts: The automated processes require less manual effort for data checking and updates reducing the cycle time and human errors.
  • Expandability: The rule engines can process large volumes of data and complex business logic with minimal effort. As the business grows, the rule engines can be scaled up without any extra effort or cost.

Mitigated Risks: Preemptive and Uniform Risk Control

Uniform application mitigates the supply chain and inventory related risks.

Mitigated Risks:

  • Supplier Performance: The rule engine may evaluate the supplier performance and assign ratings automatically taking into account the lead time, cost and quality indicators.
  • Inventory Stock Levels: The safety stock levels may be calculated and adjusted automatically considering the inventory stock points and demand volatility reducing the stockout and dead stock risks.

Real Time Visibility with Data Analytics and IoT

The rule engines when combined with data analytics and IoT offers real time visibility to the inventory optimization. Such integration and automation of decision-making processes bring accuracy, speed and responsiveness to the business.

Real Time Visibility:

  • Demand Predictions: The rule engine when integrated with data analytics tools may predict the future demand leading to just in time inventory optimization reducing the inventory waste.
  • Wireless Sensors: The IoT sensors may monitor the inventory stock levels, warehouse environmental conditions and equipment performance and transmit to the rule engines for automatic decision-making.

How to integrate rule engines with data analytics and IoT solutions

Finally, to unleash the true potential of rule engines for optimized inventory management, it’s essential to integrate them with data analytics and Internet of Things (IoT) solutions. 

This combination allows you to achieve real-time insights for intelligent, automated decision-making that reacts to changing supply chain conditions.

Data analytics boosts decision-making with valuable insights

Data analytics influences inputs for the business rules and logic that activate business rule engine. For example, applying advanced analytics to your supply chain data helps you detect valuable patterns, trends, and correlations that can be turned into business rules.

For instance, historical sales data can be used to build demand forecasting models that predict future demand patterns. These predictions can then be integrated into rule engines that automatically calculate reorder points, safety stock, and replenishment quantities for expected demand changes.

Data analytics can also detect inefficiencies, bottlenecks, and opportunities for improvement in supply chain operations. 

For example, analyzing data from supplier performance, transportation logistics, and inventory turnover rate can help you establish rules and workflows that minimize waste and optimize inventory levels.

IoT solutions provide real-time data for proactive inventory management

Rule engines can also be integrated with Internet of Things (IoT) solutions to monitor assets and automate decisions based on real-time streaming data. IoT devices such as sensors, RFID tags, and smart shelves provide a continuous flow of inventory levels, product movements, and environmental conditions, so that rule engines can react instantly to supply chain changes.

For example, IoT-enabled smart shelves can trigger automatic reorder notifications when inventory levels drop below a certain threshold, thus enabling on-time replenishment and reducing stockouts. 

Temperature and humidity sensors can monitor the status of perishable goods, so that rule engines can trigger actions such as rerouting the shipment or changing the storage temperature to avoid spoilage or quality degradation. This is especially popular in pharma companies and some of them like Pfizer, Merck, Novartis, or GlaxoSmithKline are known to be using these systems.

In transportation and logistics, IoT solutions such as GPS tracking and telematics can transmit real-time location and status information for shipments. Based on this data, rule engines can trigger actions such as rerouting the delivery or changing the production schedule to react to delays or other disruptions. This way rules engines can revolutionize logistics and save your company a lot of money.

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