Project description DEENESFRITPL New software simplifies order planning A good order planning policy is important for any business, and it generally entails two approaches: the first is upfront ordering, which allows quantity discounts but causes high inventory costs. The second is just-in-time ordering, which minimises inventory costs but increases order fees. The EU-funded SOPaaS project has a better solution. It will bring to market software that solves the issue of when and how much to order. Using algorithms based on machine learning, the software can access untapped savings of up to 10 % of total purchasing cost on average. What is more, SOPaaS considers real-world factors related to cost (long shelf life, associated storage costs), sustainability (preference for eco-friendly shipments) and responsibility (fair trade considerations). Show the project objective Hide the project objective Objective Knowing how much to order and when is a longstanding industrial problem called order planning. The 2 main approaches are:1. Upfront ordering. Allows capturing quantity discounts and simplifying operations, but causes high inventory costs (e.g. space, amortisation).2. Just-in-time ordering. Minimises inventory costs, but requires a higher quality control, increases order fees and reduces discounts on quantities.However, the right solution lays in the grey area in-between. Sometimes part of the inventory might go bad after a certain time and forces frequent ordering, storage space might be limited, suppliers might impose minimal order amounts, may be some material has long lead times. In summary, a myriad of real-world considerations that current solutions ignore, achieving only partial optimisations.GenLots’ SOPaaS is a Software-as-a-Service (SaaS) solution that untapped savings in the ordering plan (OP) elaboration stage of Supply Chain Management (SCM) process thanks to our machine learning based algorithms. In short, SOPaaS optimally answers the question: “When do I need to order and how much raw material?”Our proprietary machine-learning algorithms unlocks untapped savings of 5-10% of total purchasing cost on average. This translates in millions of euros saved for our clients, a unique value proposition that guarantees their willingness to pay. SOPaaS solves the theoretical problem of obtaining the ordering plan, while also considering real-world factors in various dimensions, e.g. cost (e.g. lots’ shelf life, associated storage cost), sustainability (e.g. prefer eco-friendly shipments) or responsibility (e.g. fair trade considerations) among others. Fields of science natural sciencescomputer and information sciencesartificial intelligencemachine learningsocial scienceseconomics and businessbusiness and managementcommerce Programme(s) H2020-EU.2.3. - INDUSTRIAL LEADERSHIP - Innovation In SMEs Main Programme H2020-EU.3. - PRIORITY 'Societal challenges H2020-EU.2.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies Topic(s) EIC-SMEInst-2018-2020 - SME instrument Call for proposal H2020-EIC-SMEInst-2018-2020 See other projects for this call Sub call H2020-SMEInst-2018-2020-1 Funding Scheme SME-1 - SME instrument phase 1 Coordinator GENLOTS SA Net EU contribution € 50 000,00 Address GRAND RUE 5 1071 CHEXBRES Switzerland See on map SME The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed. Yes Region Schweiz/Suisse/Svizzera Région lémanique Vaud Activity type Private for-profit entities (excluding Higher or Secondary Education Establishments) Links Contact the organisation Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Total cost € 71 429,00
