## 1 Introduction  
Business performance management (BPM) enables organizations to maximize their performance and achieve their aims through a set of information systems, business processes, and technological tools that focus on strategic indicators [1, 2]. As a fundamental part of this organizational culture, strategic planning (SP) allows the establishment of necessary elements to determine the guidance of an organization [3]. According to [PERSON] et al. [4], SP is one of five management approaches that companies should consider. The actual value for the successful execution of SP depends on several factors. Nevertheless, shared leadership inspires all company collaborators to carry out SP and encourage real change by achieving its objectives [5]. Balanced scorecard (BSC) has proven to be an effective management mechanism for measuring strategic performance [6]. This method is structured based on four perspectives: finance, customers, internal processes, and learning and growth. The determination of key performance indicators (KPIs) focuses on monitoring performance against an organization's objectives. As a reinforcement of its classic elaboration, we consider that external sources, such as social media (SM) can contribute to its automatic development from a large part of its perspective. The fundamental reason is that today, it is impossible to talk about an organization without considering SM as a corporate strategy. The key to business success for many companies is the correct use of data to make faster and better decisions and to reduce failures [7]. Currently, a company's relationships with its customers are generated in real-time. The large amount of SM data generated daily offers enterprises new opportunities. Understanding their influence on customers or users through their comments is essential [8; 9]. Globally, businesses collect data on consumer preferences, purchases, and trends. The correct interpretation of sentiment in SM allows for the prediction of market behavior and can incur profits or losses within companies [10]. In addition, SA analyzes people's opinions and sentiment intention and evaluates and appraises the emotions people post about a product, service, organization, topic, individual, or trend [11]. The basis of SM and opinion mining (OM) models consist of algorithmic techniques [12]. SA faces general stages, such as defining data related to the topics, data collection from a source, sentiment classification, polarity detection, presenting sentiment information in a good summary, and finally, making the decision. The methodology proposed in this study aimed to be straightforward, easy to apply, and efficient. As a first step, the company was selected to guarantee the application. Then, the information from social networks was acquired, to which the pre-processing, processing, evaluation, and validation that determines the KPIs of interest were applied and capitalized in a BSC to support strategic decision-making. This system will make it possible to clarify the initiatives that must be implemented to improve the business. SA allows automation and reduces information processing time during the SP process. The contribution of this study is that the SA of SM can be considered for SP with satisfactory results. Consequently, this study arose from a literature review where an area of opportunity was detected in relation to generating a BSC by integrating SA with SP. Significant classic efforts have been made in business strategy. Still, the gap we are trying to fill is part of generating a BSC fed from external sources (SM), and providing a more complete and robust mechanism to support strategic decision-making focused on its four perspectives. From the above, the following research question (RQ) arose: Do the opinions of SM allow strengthening and adding value to a BSC for better strategic decision-making? This paper is comprised of six sections. Section 2 describes work related to this proposed approach, which is almost zero.