I work for Iloom Ltd as a partner and Chief Analytics Officer. In addition, I am involved in the Humap ecosystem as a partner in data and analytics application.
I have been able to apply the data in a number of different ways over the last twenty years, including cultural and value analysis, market, marketing and sales analysis, and various process analytics. The most important thing for me has always been that the results can be used to take the right measures to achieve the right goals. In recent years, I have focused in particular on how openly expressed opinions can be analyzed using artificial intelligence.
My free time includes singing a cappella (bass baritone), reading (philosophy, sci-fi and fantasy), and playing with my children. Outdoors is close to my heart, and I especially enjoy long walks, walking in the woods, and climbing.
The views of staff are far too seldom heard in management teams. As a result, many opportunities are lost for the right kind of leadership, the development of skills and the exploitation of hidden opportunities, not to mention the pitfalls of communication. The actual practices and culture of an organization are not found in documents or statements, but in the thoughts and opinions of staff, and good leadership begins with understanding what people think. Having people openly express their opinions is the best way to find out the real thoughts and reasons behind them. For example, the answers to the question ‘What are you proud of at work?’ Provide much more detailed information about what is good in the workplace than the best quantitative question.
The same can and should be applied to customers and other stakeholders. Hopes, thoughts and attitudes can and should be compared between different groups – and in this way you will find not only how the views differ but also what unites people. It is good to build the right measures on this foundation.
The best data and even the sharpest analysis is only an expense unless the results are known or can be applied in practice. The information on which the analysis is based must be reliable and tell the things you want to find out and study: the data must be representative and its context and generalizability must be understood before the analysis is carried out. The Wordloom® algorithm serves as a tool in the interpretation of open answers – the tool is used to find out the main issues and the reasons behind them in an impartial, efficient manner and with all respondents in the same way. The end result is an informative and detailed understanding of what the organization thinks about, how this supports the company’s strategy, and what should be done in the light of the information.