8/1/2016The ultimate goal of knowledge intermediaries such as SciDev.Net is to improve development outcomes by enhancing the application of robust research evidence to policy and practice. This goal is premised on the assumption that policies and practices that are informed by evidence are more effective at reducing poverty, enhancing wellbeing and stimulating sustainable economic growth. While it is clear that research uptake is not a homogenous process, there is a large body of literature around ‘sense making’, which seeks to shed light on the processes by which users select research, extract information and transform that information into action (see for example Russell et al. n.d.; Abraham et al. n.d.; DFID forthcoming). Within this literature, various stages or steps towards the application of evidence to policy and practice can be identified. These stages include selection, engagement and uptake (cf. Wang 1998; DFID forthcoming). While other stages – such as external checking and validation – can be identified, the following section focuses on these three stages as they are fundamental to the application of research to policy and practice and can be influenced by those who produce or publish research.
Few weeks ago, I came across Rocketgraph. This is a new platform that offers custom reports based on cloud data sources. While the concept is not new, what sets this company apart is the reports & dashboards are sold to users in a marketplace. The platform brings the analytics buyers and sellers together and provides the infrastructure. For years, many vendors have promised custom out-of-the-box solutions. In a majority of cases, most businesses require significant customizations. Will a marketplace approach to analytics offer an intermediate solution with significant time & cost savings? I interviewed Rocketgraph co-founder Constantine Nikitiadis to found out. Take a listen.
Data visualization blogosphere is filled with great ideas and inspiration. What is missing is the candid conversations about the limitations of data. Unfortunately, finding quality content on this topic is like finding a needle in a haystack. So, when one of the greatest thought leaders in SaaS data world wrote on this topic, I feel obligated to share it with you. Here is Tomasz Tunguz on the limitations of data.
Self-service has been a buzzword in the analytics industry for the last few years. While the self-service movement has been instrumental in bringing about rapid decision making and empowering business users get answers to their data questions, one has to be aware of the key skills still required. Stephen Few highlights this important foundation of building a data-driven culture.
Subscribing to email newsletters written by experts on growth and analytics is a great way to learn. Here are five newsletters that stand out from the rest. Written by entrepreneurs, data scientists, growth marketers and venture capitalists, each one offers unique insight into the process of using data to make better decisions and build a better company.