Logistics and Information Systems intersect and smoothly blend into a homogeneous business support environment. The recipe for this blend is not at all easy to utilize. In many cases, it proves to be a failure. The question is, why? The factors of success or failure are not always evident.
It is important to provide a concrete basis upon which a set of alternative pre-defined steps can be followed in order to formalize a context for operational excellence. The application grounds of logistics are extensive, and it is difficult to see clearly through the vague borders of interrelations between entities of the system’s boundary. The contemporary systems tend to be event-driven, and in this perspective, also data-driven.
Let’s analyze the data input into a system such as a business. When using the term data input, it is understood that we are addressing both master and transactional input data. These data inputs deal with whatever is brought into the business from the outside world like suppliers and vendors. The harnessing of the data input is the major element that allows for aiming at an equilibrium of inventory and, therefore, a sound basis for cost management and decision making. These are critical components to ensuring the correct quantities have been ordered, and the respective capital has been tied down.
In accordance, the same amount of effort is put into analyzing the information output of the business. The effective management of data input/information output allows for optimized inventory, smooth warehouse operations, correct requisitions, and order placement, as well as correct sales order processing. The functional operation and monitoring of purchasing and sales are usually addressed as distribution.
10 Immediate Benefits of Data-Driven Distribution
1. Significant decrease in errors on invoices and dispatch notes - Due to the high complexity of individual shipments and a large number of product codes, the procedure of issuing invoices and despatch notes is highly error-prone. This, in turn, leads to high error correction costs. With data governance and a data-driven system, the errors are virtually eliminated.
2. Improved accuracy in customer order execution - Just as with invoices and despatch notes, there are frequent errors in the execution (preparation, packaging, and shipment) of customer orders. This generates considerable costs (for the replacement of mistakenly shipped items, re-shipment of omissions, and so on). These errors that can cause customer dissatisfaction are eliminated in data-driven systems.
3. Greater accuracy in data acquisition
4. Robust governance mechanisms to control data input
5. Improved overall inventory monitoring
6. Reduction in inventory losses
7. Streamlined operation of the warehouses and Distribution Centres - eliminates the need for a large number of administrative and/or operational staff thus slashing a major overhead. In effect, the total operating costs of the warehouses are reduced.
8. Lead-time reduction for preparing and shipping a customer order.
9. Strict First-Expired-First-Out (FEFO) priorities are kept, so that only fresh products (where applicable) are shipped, and products with expiry dates (e.g., pharmaceuticals) do not remain in the warehouse for long.
10. Traceability & Auditability e.g., lot tracking, that allows the efficient withdrawal of a defective lot. This enables the rapid recall of defective product batches, which previously was almost impossible because of the administrative overheads.
Material logistics can be summarized with a rather simple question. Is it possible to achieve the optimal target, which is a rapid return on investment (ROI) through the minimization of items stock cycle times, detailed traceability, discrete monitoring of stock movements, and maximization of resource performance?
The answer is YES. It is possible by introducing Lean Thinking. This a true flow business approach strategy based on data-driven and event-driven manufacturing and warehouse management. It adjusts smoothly to changes in demand, new product introductions, or any change in the external environment that directly or indirectly affects the entropy of the system. It is standardized and developed based on Demand Flow Technology (DFTÔ). It aligns with the principles of flow manufacturing focused on eliminating waste, streamlining processes, building according to demand, and continuous improvements.
By properly designing production lines and balancing the mix of products to a daily demand rate in the SAP ERP ecosystem, quality goods can be produced as ordered, at a rate that falls within the required order-to-delivery response cycle time. As a result, the entire supply process is pulled and sequenced from actual demand.
Regardless of industry, type of manufacturing environment, or product volumes, Lean Thinking can be implemented successfully. It is easily deployed in a job-shop environment that does highly configured or engineer-to-order products. Yet, it is equally well-deployed for high-volume, more repetitive make-to-demand operations. All it needs is accurate, timely, and coherent data.
Optimization occurs by applying Lean Thinking using the SAP ecosystem with the Master Data Governance environment activated. This seamless integration obtains the following non-exhaustive data-driven list of results:
· Warehouse automation (conveyor belt equipment etc.)
· Minimization of stock volumes
· Optimization of vehicle and staff mobility
· Interoperability with shop floor
· Effective interface with Radio Data Terminals
· Effective space management and control
· Detailed triggering of chores (event-driven)
· Effective use and maintenance of functional locations
· Minimization of human intervention and errors
· Detail monitoring of cost of each item’s transaction in terms of purchases, movements, issues, sales and cycle counts, etc.
For order processing and shipping, the following tasks can be data-driven and event-driven:
· Lean Distribution Centre anticipation allows for multiple wave picking to be easily orchestrated by the Distribution Centre Manager, based on the changing customer priorities and demands
· RF picking. Quantities are consolidated per pallet, location, item, load, etc., to achieve wave picking
· Interchanging of SKUs is possible in picking
· Task management involving all warehouse functions
· Interface automated material handling equipment
· Continuous monitoring of order shortages with the option of real-time adjustment
· Accuracy of picked orders confirmed by scanning bar codes
· Shipping label generation after verification of content
· Repacking
· Automatic bill-of-lading creation
Data-driven Distribution is here. Make use of it!
