TERRA TECHNOLOGY. Optimisation des stocks. Multi-Enterprise Inventory Optimization. Pour vos appels d offre. 3 e ÉDITION

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1 Pour vos appels d offre Mars 2011 Optimisation des stocks 3 e ÉDITION TERRA TECHNOLOGY Multi-Enterprise Inventory Optimization SupplyChainMagazine.fr 19, rue Saint-Georges Maisons-Alfort

2 1. Publisher s NAME Terra Technology 2. Member of a group? APICS, GMA, IBF, CSCMP, CGF 3. Company s country of origin USA 4. Date on which the company was founded March 9, Global sales 2010 Private company 6. Sales France 2010 Private company 7. Global workforce Workforce France NAME of the Stock Optimization solution Multi-Enterprise Inventory Optimization 10. Number of sites equipped with the stock optimization 2 solution in France 11. Number of sites equipped with stock optimization solution100 abroad 12. Last three references using the stock optimization solution (client name, business sector) Procter & Gamble, global Unilever, global Campbell Soup Company, U.S. 13. Main business sectors served by the installed base Consumer products, high tech 14. Maximum number of SKU (Stock Keeping Units) managed to date by your clients 15. Latest version Languages available for this version English 17. Is it integrated into a larger suite? Y MIO is integrated into Terra s Demand If yes, what type (ERP, APS, SCE, WMS, Replenishment optimization, other)? Sensing and Multi-Enterprise Demand Sensing solutions and APS. If yes, what are the other main modules (name and function)? 18. Main modules/ functions in the global solution (please give the name of each) : - Network Design? No - PLM (Product Life Cycle Management)? No - Demand planning? Demand Sensing, Multi-Enterprise Demand Sensing - Collaborative Demand Planning? No - Finite Capacity Production Planning? No - Scheduling? No - Procurement Planning? No - Distribution resource planning (DRP)? No - Transportation planning? Yes. Transportation Forecasting - Human resource planning? No - Available to Promise (ATP)? No - Capable to Promise? No - SCEM (Supply Chain Event Management, alerts + No actions scenarii)? - VMI (Vendor Managed Inventory)? No - Pooling (between several Suppliers, etc.)? No - Other? Optimized Shelf Life, Inventory Optimization, Inventory optimization multi-enterprise 19. Is the stock optimization solution originally designed to: - Adjust the stock levels of a large number of references according to demand on a site? - Optimize the stock levels of each site in a network MIO optimizes the stock levels of distribution and according to its own specific demand? manufacturing network of multiple levels - Optimize the stock levels of a distribution network of several levels, based on a single demand (the one closest to the final client)? - Other? - MIO minimizes the total inventory investment required across a network given a desired customer service level. Investment includes both finished goods and materials.

3 20. What kind of stock optimization levers does the solution bring : - Better overview on stocks within a company (included Yes those by 3PL)? - Better overview on stocks in a network (suppliers, Yes company, customers)? - Better sales forecast accuracy? Yes (Demand Sensing) - Better response of production plan to demand? Yes (Demand Sensing) - Better response of replenishment plan to demand? Yes (Demand Sensing) - Different SC policies (service levels, safety stocks ) Yes by product? - Just in time? No - Others? What are the main modules/functions in this solution: - History-based sales forecasts? Yes - Collaborative sales forecasts? Yes - Replenishment plan? No - Shared supplies management? No - Mutualized supplies management? No - Collaborative portal? No - Other? Other Demand Sensing based on POS and other downstream data. Safety and maximum inventory 22. Does the demand forecasting module contain the following statistical models as standard: - Trends? Yes - Seasonal? Yes - Mobile average? Yes - Linear regression? Yes - Erratic? Yes 23. Does the forecasting module manage predictive models as standard (e.g. consumption of wear-and-tear parts according to the life-cycle of a product)? setting The demand forecasting model uses a proprietary pattern recognition algorithm with customer and POS data plus all of the methods mentioned. Yes 24. Is the choice of statistical model: - Automatically made by the user? No - Offered by the system and modifiable by the user? - Imposed by the system? No - Other? In the event of a major change in the statistical series, can the system: - Alert the user so that he can change models himself? - Automatically adopt the new, more appropriate model? Yes. The choice of statistical model is optimized by the system but can be overridden by the user on an exception basis. Yes. The system alerts the end user about major changes in demand signal. Yes. The system optimizes itself but can be overridden by the user on an exception basis.

4 26. What is available as standard: - The forecast calculation meshes (day, week, month, year ) - The forecast calculation horizon (x weeks )? - - The forecast expression units (CU, Package, Euros, tones, bottles )? - The planned axes (product, client, geographical hierarchy, distribution network )? Please give details. 27. How does the forecasting module collect data from an outside population (sales force, subsidiaries, stores, etc.): - Via file integration? Yes - Via direct entry into the forecasting module? Yes - Via a web portal? Yes Forecast granularity can be set for both analysis - and reporting in days, weeks, months, or a telescoping combination of each. All data can be reported against a full product hierarchy, locations, and customers in multiple units of measure. All data can be analyzed and calculated at the item / location / customer level. All data can be reported against a full product hierarchy, locations, and customers in multiple units of measure. 28. Can the software calculate a sales forecast by product, Yes. Default level is daily. store and day? If yes, on which horizon? Does the solution optimize stock levels at each node in the network and for each SKU (Reference stocked by site)? What parameters does it take into account (target service levels, sales forecasts, min/max forecast stock, delivery times, lot size, etc.)? 30. Are safety stocks: - Entered manually by users? - - Imported en masse from another tool? - - Calculated automatically by the software according to various parameters (if yes, please give details of the main ones)? 31. Is it possible to define differentiated stocking policies by Yes category? If yes, according to what criteria (by product family, product/client pairing, product/supplier pairing, by geographical area )? 32. Depending on a target level of service for all products (e.g. 95%), is it possible to calculate an optimum mix of levels of service in the tool, by product category, and work out optimum stock levels from this? The solution optimizes stock levels at each node in the network and for each SKU. The following elements are used by the system: customer and internal replenishment, service levels, forecast error and bias, min/max stock targets, lot size, delivery times, shelf life, quality hold times, transit times, production schedule compliance, delivery reliability. Yes, according to the supply chain parameters. The safety stock recommendation calculated by the software can be overridden by end users. By product family, as well as any other attribute of item and location combination. No in the 4.1. But it this feature is planned for release 4.2. It will be possible to calculate an optimum mix of levels of service by category and work out optimum stock levels from this. 33. Is it possible to optimize, in a global Supply Chain: It is possible to optimize the stock levels of finished goods only or both finished products and components for a complex, multilevel network. - Only the stock levels of finished products for a Yes complex, multi-level network? - The stock levels of both finished products and components (nomenclature management)? Yes

5 34. What are the possible consolidation criteria for replenishment orders : The system optimizes inventory settings; it does not generate replenishment orders. - By supplier? N/A - By product family? N/A - By carrier? N/A - By amount? N/A - By weight? N/A - By volume? N/A 35. Does the user carry out this consolidation manually? N/A Can it be offered automatically on the basis of preestablished rules? 36. Does the software integrate supplier delivery constraints The software integrates supplier delivery constraints: such as: - Timing? Yes (inherent in Transportation Variability) - Full truck imposed? Yes - Minimum order? Yes - Quantity schedule to be optimized? No - Delivery schedule? Yes 37. What supply policies are managed as standard? (financial order quantity, one-for-one replenishment, fixed frequency ) 38. In the event of a shortage (no stock, deferred supply, etc.), can the software automatically manage the theoretical deployment of the quantities available on the sites? One-for-one, fixed frequency, minimum/fixed quantity are managed as standard. The system optimizes inventory settings; it does not generate replenishment orders. If yes, according to what standard criteria? (retail outlet sales, initial forecast by store ) 39. Platforms and Data Base supported? Windows, UNIX, HP-UX, AIX, LINUX, Sun 40. Method of implementation : - On own account? Generally - Via partners? Sometimes with partners Please state the main ones Cost of license from? Depends on the scope. 42. Proposed ASP mode? Not yet Cost of hire from? 43. Proposed SaaS mode? Not yet Rules of pricing? Cost of hire from? 44. Average cost of a project? Depends on the scope. 45. Average R.O.I.? Less than three months 46. Summary of the main strengths of the solution Measures error over replenishment lead time, the relevant error. Significantly reduces forecast error over replenishment lead time (Demand Sensing) Minimal data maintenance, ease of use, very flexible reporting and ROI of less than three months. 47. Development strategy for 2011/ 2012 Further expand our product on engine flexibility, model applicability, ease of use and scalability.