CEO & Founder
This session will address how to use large volumes of open-text data, for example the answers of a text question in an employee survey to identify issues, potential solutions and where to focus action. We’ll start with an overview of best-practice approaches developed for ‘small data’ solutions and extend this to how a combination of human & AI can address today’s big-data, multi-lingual situations.
The session will finish by discussing how to use text in a mixed-methods approach, and a discussion of strategies to use to effectively use qualitative and quantitative data to solve today’s organisational challenges.
People Analytics teams in large organisations are increasingly having to deal with large volumes of text data, but the typical barrier that analyses hit is a ‘so what?’ from executives and other stakeholders. Most text analyses only scratch the surface of what is necessary to inspire effective change. Analysts too often approach text from a technical perspective, eager to apply the latest library or technique, without considering how skilled researchers have been tackling this challenge manually for decades.
This session will explore:
- The approaches qualitative researchers have developed to make sense of text data
- The history of ‘AI’ based text analytics
- What makes a good text analysis
- Story telling with text data
- Idea 5: Mixed methods approaches and research strategies.
- Knowledge of pragmatic strategies of how to use text data to drive change
- An understanding of text analysis – how to identify what will be needed
- Knowledge of established techniques, and how to apply AI and machine learning at scale.
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Andrew Marritt is the founder of OrganizationView, a prominent European People Analytics practice. A hands-on analyst, he’s equally at home crafting code as he is advising business leaders on the strategic use of workforce data. OrganizationView work with global firms providing both analysis and technology. They provide additional capability and capacity to some of the most advanced People Analytics teams. Their Workometry product brings text analytics and machine learning to employee feedback. The team of data scientists have advanced degrees in statistics and computer science. OrganizationView is particularly strong at analysing large, unstructured datasets and graph data. As well as leading OrganizationView’s analysis work, Andrew also teaches People Analytics to senior HR leaders. Before starting OrganizationView, Andrew spent 10 years leading global technology and data-centric projects for firms such as Reuters, UBS and Alstom. His early career was in management consulting.