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How Data Analytics Can Help Businesses?


How Data analytics Can Help Businesses?

“In God we trust; all others bring data.”
                                                                             Edwards Deming

Many economists argue that thanks to the pandemic, a recession has matured in 2020 and turned into a financial crisis in many industries (tourism, transportation etc). Additionally, the International Monetary Fund announced that the COVID-19 pandemic has pushed the world economy into a global recession which seriously affected business. To avoid the consequences of the pandemic and economic downturns, which are unfolding around the world on an unprecedented scale, enterprises need to actively prepare to survive the next economic downturn with minimal loss on their business, retain their employees and have a competitive advantage when things return to normal. As with historic recessions such as the 2008 financial crisis, companies that prepared ahead, strategized and positioned themselves to cope with these adversities, emerged from the recession with much less negative consequences, and even provoked phenomenal growth in the post-recession period.

This economic downturn, despite its complexities, is no exception, and data analytics, with their enormous potential, may just be an opportunity that businesses can look to mitigate negative economic impacts or maneuver the business using the market signals through big data. But just collecting big data is not enough. Businesses need to sort it, value it, and analyze it. The correct analysis will help you to focus on:

  • revenue opportunities (to discover cross-selling, up-selling and new sales opportunities),
  • minimizing costs, and
  • maximizing efficiency across the organization.

Nowadays almost all major companies have their own analytics departments or outsource full-time dedicated consulting firms. Analytics is becoming a very important field in a fast-changing world and exponential growth of available useful data sandwiched in globalization.

What is analytics?

Information surrounds us from all sides, and therefore big data is affecting not only the financial decisions of corporations but also social matters like sports, healthcare and government etc. It’s hard to imagine an aspect of our life in which analytics will not be used today. It is such a pervasive industry that even the FBI relies on analytics of behaviour to help identify potential criminals.

Analytics is the ability to collect and use information, making decisions based on facts and trends. Progress in the field of computer technology and the complete informatization of the world will soon make it possible to make such decisions about everything in the world, and people will acquire truly endless possibilities. The big data can then be easily interpreted and applied to a multitude of uses in order to achieve growth.

Due to the fact that the analytics works with various tools, not being limited to ready-made solutions and systems, knows programming languages and formulates hypotheses, helps the company not to lose money during the crisis.

Netflix is a good example of a big brand that uses big data analytics. Netflix data scientists calculated the popularity of House of Cards using analytics: viewers of the original UK House of Cards also loved Fincher’s films and Spacey’s films. Netflix brought together David Fincher (co-director of House of Cards), political intrigue and Spacey in one project. Video Service has signed a contract with Spacey and Fincher without filming the pilot. The rating of the series on IMDb is 8.7 respectively. Moreover, Netflix even used big data and analytics to conduct custom marketing to promote ‘House of Cards’ Netflix cut over ten different versions of a trailer to promote the show. Netflix did not have to spend too much time and resources on marketing the show because they already knew how many people would be interested in it and what would incentivize them to tune in.

Analytics data and recession

An experienced data analyst team can build the correlation of market trends and find a nail in a haystack which helps companies to maneuver in a constantly changing business environment. As a result of their work, the user of the reports should be able to derive specific action points to address challenging market environments. For example, Amazon constantly using big data analysis to processes each customer’s information. If the customer will check some product and it doesn’t matter if he will buy it or not Amazon will use this information and will recommend the same product or similar ones to customers with different offers. So how it helps during the crisis Amazon? By analyzing the personal data of the customer, the company knows the price limit and the way of shopping. Due to this information Amazon tailors the best offer to their customer with the most suitable pricing.

When the threat of a recession arises, companies must analyze each source of income using big data to obtain as much as possible signals from the market proactively. Last decade the world changed from “big eating small” to “quick eating slow”. Based on the best solutions and products on the market, companies can expand data mining and predictive analytics technologies. In that way the data analyst develops the general following actions:

  • Communicates with business representatives and identifies problem areas;
  • Gathers information;
  • Creates hypotheses to improve certain indicators;
  • Prepares data for analysis: sorts, filters and makes a selection;
  • Finds patterns;
  • Visualizes data: translates statistics and Big Data into clear conclusions and visual graphs;
  • Offers solutions that are used to develop a project or business.

Using data analytics during a recession is critical if the business wants to navigate the stormy waters of a recession. Sophisticated data analytics enable companies to objectively assess various business situations, such as how to manage uncertain supply and demand, assess and mitigate supplier risks, adjust to disruptions in operations and supply chains, and adapt to dramatic changes in consumer confidence and priorities. In addition, many data analytics helps you establish KPIs in the maneuvering during the economic downturn.


KPI and data analytics

Every area of business from sales, inventory management to finance is measuring core KPIs that contribute to the overall success of the business. In the next few sections, we’ll look at a few examples of how KPIs measured through data analytics can help during a recession.

1. Eliminate unnecessary expenses and Cost containment

One of the essential goals of data analytics is looking closely at all related expenses before digging into other problems. The goal should be on focusing areas with significant impact on the bottom line–i.e., spending too much to acquire new leads, wasting money on excessive cloud storage meant for smaller data sets or in training and upskilling programs of employees. While many of these components are essential investments, data analysis might uncover opportunities to cut costs by upgrading or eliminating certain solutions.

2. Current data on customers

Data analytics use customer data to find a better solution to preserve customers and reduce customer churn. This allows them to determine which decision works best for each segment, which solutions best align with customer interests, and which factors converge to drive the most conversions. Data processing provides companies with customer insights from every angle, allowing them to develop a nuanced understanding of what motivates customers, how to predict and prevent churn, address pain points, and deliver personalized, and contextual experiences. Data analytics can calculate propensity to buy and make recommendations based on historical data–thus improving buyer engagement and relationships with existing clients.

There are many other KPIs that could be measured through the help of big data. “Done right”, analytic can reveal the exact value big data brings to the table, and how long it will take before your profit will be decreased. KPIs that are derived through Data analytics help companies focus on the right information to survive or take a softer hit during a recession and adjust their business for the opportunities arising during the recession.

Based on the data analysis, the sales team can choose the relevant KPIs including:

  • The sales department might use a KPI to measure monthly gross profit against projected gross profit.
  • The accounting department might measure monthly expenditures against revenue to evaluate costs
  • Sales per location, salesperson etc.

Professionals companies and data analytics frequently use KPIs that are grouped together in one result to obtain a quick and accurate historical summary of business conditions or to identify performance improvement opportunities or stay afloat during the recession.