**1. Introduction**

With the rise of the modern society and its socio-economic structure based on companies (public or private, profit or non-profit based) and its interdependences, the need for performance excellence has become of the utmost importance. The twenty-first century marked the beginning of a new millennium where uncertainty is at its high and companies are constantly trying to outstand their business performance to thrive and gain competitive advantage.

To excel on their overall business performance, the same must apply to the operational performance. Thus, operational performance management systems must reflect the problems and impediments hindering the company's competitiveness. The trends show they are trying to gain knowledge about themselves and the market by leveraging ICT and Data Analytics (DA) capabilities to transform data into information [1, 2]. At the same time, they are focused on understanding the user's (internal or external) pains and needs and come up with a way of meeting them to improve business performance [3, 4].

This double-sided story shows us both a hard part (described from an objective transformation of the real world into data) and soft part (where humans and their different perspectives of the real world are considered). However, there is little research combining 'soft' and 'hard' methodologies to tackle problems or develop new products or services which gather the emphatic human-centric approach with the rigorous and objective perspective of data science.

Thus, the author's objective is to propose a new hybrid methodology which uses a Design Thinking approach to an unknown problem environment and develops analytic-based solutions to create OPMS tools. This is intended to provide:


The proposed methodology was tested under real-life conditions by performing a case study investigation methodology on a Baggage Handling System (BHS) company, within a European airport. This allowed to test various tools and the overall procedure and is able to critically assess the advantages and limitations of this methodology for the intended purposes.
