Exploring Futuring and Predictive Analytics for Developing Organizational Strategy

Introduction

In a vibrant, unstable, and complicated business environment, organizations are forced to use the most accurate information and knowledge available, not only in the present but into the future, to assess and predict the external and internal environments for making strategic, operational, and tactical decisions (Shujahat, Hussain, Javed, Malik, Thurasamy, & Ali, 2017). The future will not arrive entirely shaped but emerges in a step by step method (Webb, 2016). Academics and business leaders are seeking the next big strategic move to enhance their competitive edge (Siegel, 2016). Millett (2006) remarked that providing direction into the future is the responsibility of Leadership. Decisions made based on information and knowledge resources can result in a competitive advantage (Shujahat et al., 2017). A critical role of Leadership is to provide direction into the future. In the world of companies, organizations, and governments, the executive leader is one who plays the principal part in defining the mission, setting the goals, developing a vision, and making plans that move beyond the familiar of today to the uncertainties of tomorrow (Ag Budin & Wafa, 2015).

This study looks at two different processes that organizations can use to develop strategic planning into the future. The first process is called futuring. In the management environment, futuring merges useful history with methods from science, mathematics, and system analytics to structure well-thought-out opportunities for the future (Millet, 2011). Webb (2016) exclaimed that the future might first materialize as arbitrary ideas at the fringe of society, but never in the mainstream. Crews (2017) remarked that the future is not factual and hard to predict.

Millet (2011) describes futuring as a process that helps us make decisions today that will have positive long-term effects. In the aspect of a business, futuring is a characteristic of due diligence and risk management. Normative scenarios generate lively descriptions of desired futures (Crews, 2017). Smith (2015) explained the role of the futurists as evolving inside companies to help predict the desired future of the organization created on methodical procedures involving group action and collaboration. Crews (2017) stated that trends might offer and an indication of the direction the future is moving. Let us move on to the second process of Predictive Analytics.

Iovan (2017) asserted that Predictive Analytics gives organizations a way to generate decisions based on precise information at the correct time by developing systems that are capable of converting collected data information to produce actions that directly benefit the organization. Companies that have embraced predictive analytics have been able to leverage the data into useful knowledge that enables them to save money and improve operations across many areas of their companies (Siegel, 2016). The use of information to enhance decision-making and motivate innovation, converting information to knowledge. Predictive analytics is an excellent way to convert information into knowledge (Hair, 2007). The goal of predictive analytics is to support the decision-making process by identifying patterns and emphasizing valuable information (Fadairo, Williams, & Maggio, 2015).