Monitor, assess and develop

Analyse to reach your goals

Data means symbols and figures without meaning (e.g., 30), which are relatively uninformative on their own. Data is refined into information when it can be used to answer the questions “who, what, where, when...?” (e.g., each employee has 30 absences due to illness per year). Information becomes knowledge when it is applied into practice (e.g., how many workdays people at other workplaces spend on sick leave). Wisdom comes from understanding the reason behind an activity and its context-dependence to answer the question “Why?” (e.g., what explains the fact that other workplaces only have an average of 21 days of sick leave?).

Analysis changes data into information and information into wisdom, in accordance with the traditional pyramid model for knowledge management. Based on the attained knowledge and wisdom, you can now reach your goals or at least get closer to them.

Then, you can set new goals and continue to measure, collect, analyse and interpret data. Don’t give up. You will improve each round. Knowledge management at its best is an endless cycle of measurement, data collection, analytics, interpretation and implementation.

Assess knowledge and verify interpretations

A picture is worth a thousand words. To help you interpret work ability data, you can mimic familiar data presentation methods, for example how stock prices or weather data is presented. It is important to see the current state of the thing you are measuring so that you can see how it is developing. If possible, it is worth enriching your measurement results with benchmark data to compare your situation with others. Statistics Finland, The Finnish Centre for Pensions, Kela - The Social Insurance Institution of Finland, the Finnish Workers' Compensation Center, the Finnish Institute of Occupational Health and, increasingly, employment pension insurance companies produce statistical data on various work ability management phenomena and offer good examples of easy-to-use graphs in their information services.

Specialists can use their experience to give information produced from data the correct perspective and do away with misinterpretations. If you have moved on to the predictive or prescriptive level, you will not need as much interpretation help from specialists. There are no quick wins. Predictive and prescriptive models are always created over time when you refine descriptive and diagnostic models together with specialists.

Sources:

• Fitz-Enz & Mattox. 2014. Predictive analytics for human resources. John Wiley & Sons. 
• Saramies & Törnroos. 2021. Henkilöstöanalytiikka. Mittaa, ymmärrä ja menesty. Alma Talent