Well-being and development embody multidimensional and long-term experience, going much beyond the GDP. The focus in the media is especially in GDP growth rates. Over time, UNDP, OECD, and European Commission have participated in the conferences, indicator developments, and policy discussions of 'Beyond GDP Initiatives'. In the article, the analyses of beyond the GDP indicators are enriched by the application of the dynamic time distance methodology to complement the results of the usual mostly static tools. 

With time distance methodology, a new perspective related to time does not replace but rather adds a new dimension to existing analysis across many variables, fields of concern, and units of comparison. Section 3 deals with the broadened concept of measuring and evaluating the magnitude of inequalities in two dimensions. LEVEL-TIME matrix in section 4 is an additional option of visualisation of time series data which helped to establish that GDP underestimated the scale of damage of the financial crisis in the EU for selected indicators. Section 5 emphasises the function of the time distance tool for monitoring implementation of targets parallel to other methods, with application to about 150 cases of EU2020 targets; as well as to measuring implementation of the UN Millennium Developments Goals that can be used also for the UN initiative of the 2030 Agenda for Sustainable Development. This transparent and innovative method for monitoring implementation of targets at all levels is available but not yet utilised. It can bring a new easily understandable perception of the magnitude of the gap between the actual implementation and proclaimed targets at many levels: it can help governments, the civil society, and businesses in a broader understanding of continuous policy debate and necessary adjustments. The free software tool is available.

The empirical study exposes that GDP underestimated the scale of damage of the financial crisis as selected time matrices showed deterioration in many indicators:

Table 2 shows possible scheme and numerical values for analysing time distance deviations for implementation of five selected headline indicators towards the EU2020 for the entire EU and national targets. It is a clear example of simplicity with an overview of about 150 cases of EU2020 targets, showing the results of 5 selected EU2020 indicators, 28 countries, and the EU aggregate in one single table. Such time distance monitoring supervision could become a standard procedure in numerous other activities of the Commission on the national and local levels, e.g. monitoring and evaluation implementation of budgets, plans, projects, structural funds, etc.

We measure deviations in two dimensions. Firstly, one can measure the difference in variables at a given point in time. And secondly, discrepancies in time (either time lead or time lag) are measured. Monitoring implementation in time is like comparing train or bus arrivals with the timetable provided for each mode of transport. The statistical chart uses the same identifiers as Formula 1 on TV: drivers who score a minus at time distance are shown in green to signify that they are ahead in time. 

The table for EU 28 countries for 2013 (or 2012) shows the results from 2010 on. Yet the summary results confirm the earlier conclusions. For the headline indicator employment rate 20 countries are behind the schedule, 11 of them had in 2013 values below those in 2010 starting year. For 11 countries there was no progress in the 2010-2013 period for employment rate. The earlier graph that contained also the worse years of the financial crisis showed even a more serious situation. The time distance method, either for monitoring or for benchmarking in the time perspective, brings the second dimension of deviations or disparities that the present state-of-the-art is neglecting. 

For early leavers nine countries were in 2013 already better than their 2020 targets, this holds true for tertiary attainment for 10 countries; with only six countries being behind the schedule for both indicators. The headline indicator renewable energy also more countries are ahead of schedule than behind it, but with fewer cases that already reached the 2020 targets. R&D in GDP indicates a different picture, with 9 countries ahead and 16 countries behind the schedule; overall it is closer with the employment rate situation than with the other three indicators. 

The average for EU28 S-time-distance deviations express the situation with being ahead or behind the track to 2020 targets in simple terms: employment rate is more than 3 years behind, R&D 1.2 years behind, renewably energy 0.6 years, early leavers 2.1 years and tertiary attainment 2.4 years, ahead of  the line to the 2020 target.   

It should be reasonably easy to incorporate the S-time-distance methodology for monitoring implementation of the MDGs in the work of the UN, the World Bank and other agencies or countries on these issues, both at macro and at micro levels.

In the interview the time distance innovation and applications in economics and statistics were explained. The main conclusions on the position of Slovenia and Europe are from the article 'Kje je Slovenija?' in the proceedings of the symposium at the Slovenian Academy of Sciences and Arts at the 10th anniverasry of death of Professor Aleksander Bajt.