Big Data
6 Ways Big Data Analysis Impacts Enterprise Decision Making
Digital
transformation is restructuring the business process of the organizations
by making it highly integrated. The increased reliance on technology and
its continuous advancement have reshaped the modern workplace. It is changing
the way you operate business activities and deliver value to end customers.
Over the past decade, Big data along with Artificial Intelligence solutions has created a lot of buzz in the corporate industry. With the
ever-increasing use of electronic devices, tremendous growth in computerization,
and massive technological evolution, there is a major improvement in
information availability. It leads to the generation of enormous amounts of digital
data at the organizational level on a daily basis.
It is very clear that today information
is the most important factor that influences the decision-making process. There
is a huge amount of data available for companies but in the raw form. In order
to extract structured and valuable information, these huge data sets need to be
thoroughly analyzed. The correct analysis of data sets aware organizations about
their product quality; whether there is a need to bring efficiency in the operational
process or any improvement required in customer services.
So, if you’re still using the
old-style data processing applications to manage and store data then let me make
it perfectly clear it is not going to deliver valuable insights that can thrive
your business.
Nowadays, a large number of
organizations are integrating Big data analytics into the decision-making
process to gain valuable insights from high volume data. This technology
examines huge chunks of data and reveals hidden patterns that help identify new
growth opportunities. To capture the true value of big data and harness its
potential to the greatest extent, it is essential to align big
data analytics with traditional processes of decision making. Earlier
business decisions were based on experience but with digitalization, these
decisions are made on the basis of data, analytics, and logistics.
Big data is probably the most significant factor in decision making
nowadays, and here are the 6 reasons:
1. Demand Forecasting
Big data processing enhances
forecasting accuracy and improves cross-department collaboration. Especially in
enterprises related to mass markets, like retail & ecommerce or Automobiles, Big data plays a
crucial role to understand preferences, buying patterns, vacuums, and other
opportunities, for making production-related decisions. With the use of this
technology, businesses can predict future requirements of inventory level, plan
the production activities, and allocate resources with minimum distribution
cost. For instance, automobile companies can cut down their production if data
indicates a market slowdown. Data analysis allows companies to make realistic
estimates and targets to prevent morale from crashing.
2. Price Optimization
Price is arguably the single most important factor influencing buying decisions, and hence price analysis is one of the key functions of big data. It plays a key role in establishing any brand in the market. Thousands of companies fail to survive just because of the wrong pricing decision. It is well said that “A price can make or break your product”. By identifying the optimal price of a product that a consumer is willing to pay, Big data also help companies make better pricing decisions. The organizations that deal with multiple products cannot overpower the market by following the traditional pricing approach. Hence, the decision-makers need to practice analytics strategies to gain a competitive edge.
3. Promotes Strategic Decision Making
Business decisions related to
expenses or investments are prone to volatility, which can be devastating at
times. However, with Big data technology, decision-makers and analysts can
identify the areas where investments are required and select the one with
better returns. This helps to make a decision that allows the flow of capital
in formidable and potent areas. For instance, a smartphone company understands
that the requirement of generic cell phones hasn’t declined in certain regions
after big data analysis, and can now safely make investments in launching new
‘dumb phones’.
4. Improved Customer Services
Big data analysis can track all
the activities and actions of your previous buyers and also determines their
personal preferences accordingly. Besides this, CRM integration has
made it easier to collect information from prospective customers in order to
frame the right marketing strategies. In-depth insights into customer needs and
preferences have helped decision-makers to better understand and observe the
customer requirements. Also, it has reduced response time and increased
problem-solving efficiency that promotes business success.
5. Better Allocation of Budget
With the help of market mix
modeling (a big data analytics technique), decision-makers can analyze past
company data and enumerate the impact of several marketing activities on sales,
profit, and ROI. With the correct prediction of successful marketing
strategies, Big data allows companies to determine the right channel that
elevates the brand value and scale up the profit margins.
6. Enhances Operational Efficiency
Big data enables the business
organization to have better insights by analyzing and managing huge sets of
data. It impacts all the operational areas as it predicts the most accurate
future trends, suggests successful marketing strategies and increases customer
satisfaction by providing better services. Thus, enhances the overall operational
efficiency of the organization.
Also Read: How
Big Data Analytics Can Benefit an Enterprise
Summing up
In a nutshell, Big data integration
indeed supports the decision-making process in any organization. This
technological advancement has helped companies to gain a better understanding
of demand and supply units of products and services by predicting the future.
Hence, it is very essential for any organization to recognize the concept of
big data analytics to leverage its full potential.
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