Many businesses today still operate on creating and making business decisions based on “gut feelings” where the decision maker believes that his intuitive snap judgments are far superior to the rational analytics-backed decisions. However, senior managers who rely heavily on “gut feel” and “soft” factors, including consultation with others, intuition and experience, unfortunately find that these rarely work in the current business environment. Gone are the days when instincts formed the basis for most management decisions.
The dynamic, unpredictable and complex behavior of consumers, whether its B2B or B2C, poses challenging situations to managers and demands smarter decisions to attain multiple business objectives. Decisions based only on intuition without proper rationale have seen serious implications in the long term.
The Math Factor: Data Analytics
When gut feel doesn’t work, the only substantial factor that can support decision making better is DATA. A variety of methods―from common tools used to conduct data analysis (such as simple cross tabulations) to more sophisticated statistical methods (such as logistic regression)―can assist the manager into delving more into the data and getting a clear insight into the problem at hand. In the last few years, optimisation tools and machine learning algorithms like neural networks and genetic algorithms have also been used to perform advanced data analysis to support better decisions.
Recent years have seen increased use of data analytics
in driving business strategies across various industries as a measure to tackle challenging situations. While the data analytics methods have been extensively used in FMCG, pharmaceutical and telecom companies, their mainstay has been the consumer finance industry.
Following are a few scenarios when gut feeling was just not enough:
- TESCO analyses trillions of data points to customise their offerings and invest in direct marketing campaigns. This has seen response rates soar to 20% when the industry average was only 2-3%. This really has maximised the marketing ROI and increased profit per customer.
- Today the FICO Risk score, which is a number that is calculated based on a person’s credit history, is the benchmark for the credit decision process in the U.S.―indeed, so much so that the “Prime” and “Sub-Prime” markets are defined on the basis of this score.
- Harrah's Entertainment (casino), which was taken over by a retired Harvard professor as COO in 1998, has changed the face of casinos and become a billion dollar company by running complex algorithms to understand its most profitable customer segments.
- Best Buy doubled its sales from $20 billion to $40 billion in five years between 2003-2008 by understanding and segmenting its customers better.
- Hockey teams use analytics to determine the factors that affect winning in the National Hockey League.
The Paradigm Shift
The evolution of decision making has come a long way and involves a lot of change within the organisation in terms technology, people, processes and culture. Analytics provides organisations with a framework for decision making to help solve complex business problems, improve performance, encourage innovation, and anticipate and plan for change while mitigating and balancing risk.
In every business, be it in the complex financial industry or the exciting entertainment industry, there are unique scenarios in risk management, marketing and forecasting where intelligent decision making becomes imperative. One of the areas, which is worth mentioning and has dominated the business analytics space, is predictive analytics. Among business intelligence
disciplines, prediction provides the most business value but is also the most complex.
The techniques involved are considered to be critical for any company trying to get deeper insights into their data and who wish to use it to predict future trends and behavior patterns. Additionally, the complexity of decisions is increasing day by day, and the methods by which we can derive meaningful insights are also increasing. Although predictive analytics
can be applied to a variety of fields, below is a list of areas where predictive analytics has shown positive impact in recent years.
Many managers encounter the dilemma of how to apply analytics optimally in their company. Most have only a vague notion about the business areas or applications that can benefit from analytics. Most also don’t know how to get started: who to recruit, how to organise the project, or indeed how to architect the environment. All these initial hiccups can be sorted once the manager embraces the fact that analytics will help him better the decision.
In these situations, the role of analytics has become so crucial that it beats all the traditional approaches and is an inseparable part of the decision-making process. For this purpose, gut feel alone does not suffice as it is likely to have low/no transformational impact on the business.
It is, however, important to keep in mind that analytics and the decision management technology is not and has never been intended to replace people with computers or complex algorithms. Every business organisation should have evidence and rationale behind its decisions in the form of data. Not just gut feel!!!
SOURCE: Analytics: Why Gut Feel is Just Not Enough