Page 321 - Data Science Algorithms in a Week

302 Mayra Bornacelli, Edgar Gutierrez and John Pastrana

INTRODUCTION

Increasing interest and implementation of data analytics have been demonstrating
how it is possible to extract valuable knowledge from data that companies can collect
through their systems, insights from market experts, data patterns, trends, and
relationships with other markets. Data analytics can help understand the business in a
holistic point of view. Challenges that create techniques and methodologies are beneficial
for this purpose (Chen & Zhang, 2014; Groschupf et al., 2013). Organizations are
investing in data analytics and machine learning techniques. For example, a survey by
Gartner reveals that 73% of the surveyed companies, are investing in data analytics and
big data technology (Rivera, 2014). In general analytics help organizations increase
revenue, speed time to market, optimize its workforce, or realize other operational
improvements Predictive analytics is the arm of data analytics and it is a scientific
paradigm for discoveries (Hey, 2009).
McKinsey stated the potential use of predictive analytics (Manyika et al., 2012) and
its impact in innovation and productivity. Another important factor is that the volume of
data is estimated to increase minimum by double each 1.2 years. This is even more
important in a globalized economy due to continuous changes and uncertainty. Various
decisions are made such as investment decisions, expansion decisions, or simply the
philosophy that the company will adopt in terms of maximizing profits or having a
constant cash flow. Making strategic decisions involves understanding the structure of a
system and the number of variables that influence it (mainly outside the control of the
stakeholders). The complex structure and the numerous variables make these decisions
complex and risky. Risk is determined by four main factors when trying to innovate as
mentioned by Hamel & Ruben (2000):

 Size of the irreversible financial commitment,
 Degree to which the new opportunity moves away from the core of the company,
 Degree of certainty about the project’s critical assumptions (especially the
demand),
 Time Frame

In a rapidly changing world, there are few second chances, and in spite of risks and
uncertainty, companies have to make decisions and take steps forward or try to stay
afloat. This uncertainty is sometimes directly associated with the price of the main
products in the market, and it affects income, return on investment, labor stability, and
financial projections. This is the case of the thermal coal market and many oligopolies,
whose price is regulated internationally under a point of balance between demand and