Factsheet ChainScope BV. September Inventory optimization can increase your profitability. Contactperson: Huub Janssen

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Marion Pierce
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1 Factsheet ChainScope BV September 2008 Contactperson: Huub Janssen Phone number +31 (40) Mobile +31 (0)

2 ChainScope ChainScope is a specialised supplier in the fi eld of company-individual supply chain optimisation software. We work from analysis to implementation of logistic planning support systems. The company ChainScope is related to the Eindhoven University of Technology and markets a suite of software tools for supply chain coordination that is centered around an algorithm that performs superior to the commonly used Material Requirements Planning logic currently built into Enterprise Resource Planning software used in companies world-wide. Scientific-Technological Aspects Our business centers around an improved algorithm to coordinate (long) supply chains such that delivery performance is achieved with lowest possible integral inventory costs. The algorithm is based on advanced Stochastic Theory and outperforms signifi cantly the commonly used Material Requirements Planning logic. Software has been developed and used in real-world environments and signifi cant fi nancial benefi ts are indicated. Superior SCM solutions improve service levels and due-date performance, reduce lead times, work-in process and stock levels, higher flexibility, effi cient capacity use, less staff involvement, synchronize material procurement, and more. In recent years it was recognized that a better management of resource constraints, customer preferences, complex material flows and production processes could possibly be accomplished by the use of more advanced mathematical algorithms. This led to the introduction of so-called APS s (Advanced Planning Systems). These are now provided by large global APS vendors such as i2, by standard ERP providers such as SAP and by a great number of local and niche players. The standard MRP logic, however, has signifi cant flaws in its mechanism for co-coordinating long and volatile supply chains. Our algorithm improves on the co-ordination mechanisms. Potential TU/e researcher Prof. Dr. Ton de Kok, together with the Center for Quantitative Methods have developed and tested the software in several environments. The implementations have yielded such promising results, that the estimated pay-back period of the software investment by such businesses is suffi ciently short to justify implementation. Supply Chain co-ordination is a problem of growing importance for all companies worldwide driven by the phenomena: ever shorter product life cycles, and global sourcing. Project Approach Our software interacts and works together with the logic of the Enterprise Resource Planning systems used by companies. ChainScope product needs to get its structure and status data from these ERP systems and needs the ERP system to accept its plans. Therefore, close connection and interfacing with these systems is necessary. Our logic needs to be understood and accepted by the SCM and ICT communities, and eating is the proof of the pudding.

3 Management Team The Management Team consists of three complementary persons: Prof. dr. Ton de Kok, TU/e, concept development Ir. Daan van Boxel, software development Huub Janssen, market development Technological innovative elements Only since a decade standard software has become available for supply chain inventory optimization with a scientifi c basis. This scientifi c basis is essential, as the inventory pa-rameters calculated by this type of applications have an immediate impact on both balance sheet and day-to-day customer satisfaction. Recent research has revealed that tactical optimization should not be separated from the operational ways of working supported by ERP and APS systems. At TU/e, a team headed by Prof. Ton de Kok has worked for years on developing a SCM model that gives due recognition to the stochastic nature of long and volatile chains. Advanced probability theory has been applied in modelling complex (diverging, converging, extended, uncertain) supply chains. In simulation experiments the new SCM model performs signifi cantly better than traditional models. The new SCM models have also been tested and further developed in practice. Concrete projects at the Philips Divisions of Semiconductors, Components, Consumer Electronics and Lighting, Proctor & Gamble, DSM, Organon, Thomson Grass Valley and Unilever have proven the new concepts superior beyond doubt. The major novelty in the approach is improvement of the multi-echelon optimization of production-and-inventory planning, relative to the way of working of the Material Requirements Planning (MRP I) logic that is commonly embedded in Enterprise Resource Planning systems. The MRP I logic is mathematically inconsistent, thereby causing a considerable amount of manual planning to resolve these inconsistencies. In fact these inconsistencies are identifi ed as exception messages that should be solved by human planners. Our logic resolves these inconsistencies by a mathematically rigorous approach, thereby saving a huge amount of manual and complex planning. Furthermore, our planning logic allows for optimization of the control parameters, so-called safety stocks that enable to cope with demand uncertainty. Thereby we integrate tactical control parameter optimization and operational plan generation. Such an integrated mathematically rigorous approach is not known to date. The logic also allows for further functionality such as problem solving support and evaluation capability.

4 Technological advances: Speed The extreme effi ciency of both inventory optimization and operational planning typically provides solutions for large-scale supply chains within a minute on a normal server. This speed of response allow for true interaction between our software and its user. This interaction both creates trust in our solution proposals and allows for incorporating the user s tacit knowledge. The latter enables a performance leap. Consistency Our software offers a consistent tactical optimization and operations planning and control approach. The logic proposed to operationally control the supply chain is at the heart of the optimization. The tool has been extensively tested, showing potential savings of 30-60% in inventory capital and 5-20% customer service level improvement. Problem solving support Solutions generated by our software involve millions of consistent and coordinated decisions with respect to item order releases. Even though the decisions have been derived from the optimal control parameters, the actual situation may reveal that particular customers cannot be satisfi ed due to resource and material constraints. The software automatically detects supplydemand imbalances at the fi nal product level and identifi es the bottleneck item orders anywhere in the supply chain. The planner can decide to speed up these bottleneck item orders based on local and real-time information not accessible to the planning system. This approach refl ects the fundamental insights form hierarchical and distributed planning on which our software is based. Evaluation capability Inventory optimization involves mathematical modelling, thereby abstracting from reality to a certain extent. Like any new aircraft is tested extensively before it is allowed to become operational, any supply chain model should be validated before it can be relied on. Validation is nothing more than predicting the past. Based on facts and fi gures gathered in the process of model development, the predictions of our software about operational customer service and average inventories are checked against actual measurements. Once approved, the optimization capabilities can be invoked with trust. 20%-30%. In large chains, a major portion of the investment in our software can be recovered from the cash disbursement resulting from the initial inventory reduction. The applicability of our software and its planning method are broad. It is very suitable for use in sectors where supply chains are long, plagued by uncertainties and products have short life cycles. It can be stated that in any situation where the MRP approach was chosen for control, our software will yield considerable performance improvements. Exception messages and fi re fi ghting will be greatly reduced. Attention can be shifted to proactive problem solving and tactical-strategic considerations of planning and risk management.

5 The introduction of our software will realize: Applicability and Added value Our algorithm and software are applicable in virtually all multi-item, multi-echelon supply chains. It will interface with common ERP systems and provide the planners with superior optimization, planning, problem solving and evaluation capabilities. Thus better in-sight and fi ne-tuning possibilities are provided. Simulations and pilot applications have yielded impressive results, consistently increasing service levels throughout the chain with inventory holding cost reductions of 30%-60%. In large chains, a major portion of the investment in our software can be recovered from the cash disbursement resulting from the initial inventory reduction. The applicability of our software and its planning method are broad. It is very suitable for use in sectors where supply chains are long, plagued by uncertainties and products have short life cycles. It can be stated that in any situation where the MRP approach was chosen for control, our software will yield considerable performance improvements. Exception messages and fi re fi ghting will be greatly reduced. Attention can be shifted to proactive problem solving and tactical-strategic considerations of planning and risk management. The introduction of our software will realize: A fast and effective planning process Reliable and attainable planning Integral reduction of stocks Improvement of delivery performance Chain transparency The basis of the added value leis in the following factors: Extreme speed of the planning ( times as fast as MRP, reducing cycles from hours to seconds) Verifi able improvement of planning quality Substantially improved support for planners. Contact ChainScope today: Huub Janssen +31 (0) info@chainscope.eu Chainscope 2008

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