In an era where data is a crucial resource, small and medium-sized enterprises (SMEs) must harness analytics to remain competitive. This research paper synthesizes existing studies on analytics value for SMEs, resulting in a comprehensive model that outlines key aspects of value creation. The model covers enabling capabilities, main risks, core profiting business functions, and impact on firm performance. Transactional, transformational, strategic, and informational value creation types are identified. Given resource constraints, SMEs are encouraged to initiate pilot projects in distinct business functions, aided by cost-effective, user-friendly cloud solutions. A proposed scoring framework further aids in assessing and prioritizing business analytics projects, enabling informed decisions and resource allocation for sustainable competitiveness in the data-driven future.

Recent changes in the workplace have led to a significant increase in the use of enterprise collaboration software. The adoption of collaboration software is not always straightforward and its interpretive flexibility can easily lead to its uncontrolled and heterogeneous use. If we are to improve this situation, we need to understand the actual practices of users. However, there are no readily available analysis tools for the (longitudinal) analysis of collaborative work processes. Users leave behind traces when they interact with the software. These traces are a by-product, and their examination has great potential for uncovering how collaboration processes are carried out. In its current form, however, this data is not suited for analysis. For this reason, we developed a novel approach for the collection, transformation and harmonisation of trace data. Using Design Science Research, we developed and successfully evaluated a software prototype.