The adoption of data science brings vast benefits to Small and Medium-sized Enterprises (SMEs) including business productivity, economic growth, innovation and jobs creation. Data Science can support SMEs to optimise production processes, anticipate customers' needs, predict machinery failures and deliver efficient smart services. Businesses can also harness the power of Artificial Intelligence (AI) and Big Data and the smart use of digital technologies to enhance productivity and performance, paving the way for innovation. However, integrating data science decisions into an SME requires both skills and IT investments. In most cases, such expenses are beyond the means of SMEs due to limited resources and restricted access to financing. This paper presents trends and challenges towards an effective data-driven decision making for organisations based on a case study of 85 SMEs, mostly from the West Midlands region of England. The work is supported as part of a 3 years ERDF (European Regional Development Funded project) in the areas of big data management, analytics and business intelligence. We present two case studies that demonstrates the potential of Digitisation, AI and Machine Learning and use these as examples to unveil challenges and showcase the wealth of current available opportunities for SMEs.

翻译：数据科学的应用为中小企业（SMEs）带来了巨大效益，包括提升业务生产力、促进经济增长、推动创新和创造就业机会。数据科学能够帮助中小企业优化生产流程、预测客户需求、预判设备故障并交付高效的智能服务。企业还可借助人工智能（AI）、大数据技术以及数字技术的智能化应用来增强生产力和绩效，为创新铺平道路。然而，将数据科学决策融入中小企业需要兼具技术技能和信息技术投资。由于资源有限且融资渠道受限，此类投入往往超出中小企业的承受能力。本文基于对85家中小企业（主要来自英格兰西米德兰兹地区）的案例研究，提出了组织实现有效数据驱动决策的趋势与挑战。该研究是欧洲区域发展基金（ERDF）资助的三年期项目的一部分，聚焦大数据管理、分析与商业智能领域。我们通过两个案例研究展示了数字化、人工智能和机器学习的潜力，并以此揭示挑战，同时阐释中小企业当前可把握的丰富机遇。