Data Governance Reference Model to streamline the supply chain process in SMEs

In this paper, we propose a Data Governance reference model to streamline supply chain processes in SMEs through Data Integration and Business Analytics techniques, using the DAMA-DMBOK reference framework which involves a set of processes and areas of knowledge that are accepted as good practices. We defined a data governance model, measuring the quality of data, the Purchasing, Sales and Inventory processes can make decisions based on more reliable and accurate data, that management time and costs are reduced customer service is improved and staff performance is measurable. In this way, the expected results can be achieved through a Data Warehouse of Key Performance Indicators (KPIs) and Dashboards implemented in the Pentaho Open Source platform. The proposed model is defined in 5 stages: 1. Data Management, 2. Data Architecture, 3. Data Integration, 4. Data Warehousing & Business Intelligence, 5. Data Quality. A real scenario was defined in a textile company located in Lima, Perú to validate the proposal; the supply chain processes were chosen as they are critical for the business. The monthly results showed that, for the Sales process, the issuance time for sales quotations was reduced by 50% equivalent to a total of 60 man hours which means that it takes less time to produce the sales quotations. The delivery cycle for sold products was reduced by 25% equivalent to a total of 30 man hours, for the inventory process the compliance cycle of satisfactory purchase orders was reduced by 37.5% equivalent to a total of 90 man hours, which means that it takes less time to manage purchase orders; finally, for the Purchasing process the withdrawal of complaints about purchased products was reduced by 25% equivalent to a total of 30 man-hours, and the delivery time of the supplier per order of purchase was reduced in a 41.67% equivalent to a total of 150 man hours.