In today’s world, it is quite common to hear about data as well as data-driven decision-making. It is through data that businesses are able to get an insight into their digital performance as well as make more informed decisions that eventually lead to the drastic growth and evolution of the business. If you understand the process of measuring and analyzing your data well enough, with the help of the right tools you will be able to make accurate data-driven decisions that will help your business thrive in the long run.
Data-driven decision-making has now become a major part of the business industry. We do not disagree that sometimes going with your gut feeling may turn out to be for the best, but, a major portion of your making your business decisions must not just be based upon sheer luck. They must be based upon metrics, facts, and figures that go hand in hand with your ultimate aim and goals. Data-driven decision-making becomes a solid backbone to support all your management aims and operations upon.
1. A Few Instances of Data-driven Decision Making Helping Organizations –
Google –
Google is a name that has almost become synonymous with Data-driven decision-making. With their goal set as to make sure that all your business decisions. No matter how big or small, are always based on data and analytics, a vital part of the company’s culture is to discuss questions rather than pithy answers when it comes to their meetings. Google has an entire department dedicated to helping HR make decisions using data science, known as the People Analytics Department that also surveys whether the managers are able to make a difference in the performance of their team. They, in turn, give a “great managers award” to the managers whose performance has been positive, and spread their practices through the organization to help the managers who are finding it difficult to make a progress.
Amazon –
If you have ever shopped on an e-commerce site such as Amazon, you must already be aware that your recommendations and ads will automatically become based upon what you have purchased, or searched for. This is a great example of a Data-driven decision. Amazon uses the information of what items you have in your cart, products you have bought in the past, items that you have viewed, or reviewed and ranked. They also use key engagement metrics that include open rates, click-through rates, and opt-out rates, to again determine which recommendations to make to the user. Using these recommendations, drive-in sales and an increased bottom line have been observed in the company’s sales rate.
2. What Are The Challenges Faced By Organizations Currently To Create The Data-driven Culture –
Unstructured Data –
Although there has been steep growth in gaining high volume data, a number of companies have unfortunately not been able to achieve their goal of attaining Data-driven decision making in the company. This is due to the fact that most of the data is unorganized, been scattered across many premises of data centers, public as well as private clouds, and even hybrid clouds. It has been a huge challenge for organizations to efficiently orchestrate the data in a way that will have a positive effect on the company’s economy. A recent survey has even revealed that organizations have been losing approximately 2 million USD per year, just because of inefficient data management.
Teams are not Well-Equipped Enough to Analyze Data –
In order to harness the true potential of a company’s data, there is a need for data scientists, professionals, and data analysts. However, a new survey conducted by Accenture and Qlik established that a gap in data literacy often hugely affects the productivity as well as revenue of the company. On average, only about 21 percent of employees feel confident enough with the skills of data literacy, whereas about a major 74 percent tend to feel overwhelmed while handling data. It has become the need of the hour for enterprises to address the growing inefficiency to handle data and equip their employees well enough with the appropriate training and tools to unlock their true potential.
Lesser Skilled Workforce Available In the Market –
When it comes to the IT Industry, there is a concerning shortage of a skilled workforce. It has been estimated that more than about 2 million jobs will be created in the sphere of Artificial Intelligence and Big Data in the near future, creating a worldwide prevalent struggle of finding a skilled techie, with a proficient data science career, who is equipped to handle a company’s data. This big gap of increasing vacant job posts of data analysts and a shortage of trained data analysts are only supposed to increase in the future.
Entry barriers to Data Science education –
Although there is a lot of advantages to integrating data to grow your business you may initially also face a lot of challenges. These entry barriers may include internal barriers within the organization such as poor understanding, lack of in-house expertise, not digitalized data, as well as external barriers such as the necessary up-front investment, complex software, and even a lack of necessary volumes of data.
3. What Is the Solution –
As more and more companies turn to data to base their most important business-related decisions upon, getting proper training and Data Science certification can be a game-changer for every organization, as well as its individual employees. The course has been designed to be integrated and applied, establishing in the team skill for critical thinking as well as problem analysis, relevant to the data and decision-making context.
Final Word
In order to become a company that is data-centric, companies first need to identify their problems and then come up with their solutions. Recent times have pushed companies to keep a track of their digital presence and harness the full potential of their data, but it is all for good reasons. It is in order to give a boost to their business operations, supply chains, and also to improve their customer experience. We hope that this article was of help to you!
