After sharing what is data, information and knowledge, this post is about Data Explosion, Analytics, and Competitive Advantage. Although this post is written focusing on every business organization, the same concepts apply to construction sector organizations too. Data management and handling of data are becoming important in the construction sector as well due to its rapid digital transformation. How you can gain a competitive advantage in the construction industry?
The way a company handles its data affects its growth. If a company leverages its data well and applies analytics and use new technologies appropriately, the company is creating an advantage over its competitors. Further, companies need to understand that collecting and storing data require money. There are also security concerns if the collected data is sensitive. Therefore, a company needs to develop a data strategy focusing on the things that they need by avoiding drowning in data (Marr, 2016). This discussion post is about data explosion, Thomas Davenport’s assertion and competitive advantage through analytics which is important to know by organizations when creating a data strategy.
Nowadays, Companies around the world collect data without any hassle due to easy access to devices, connectivity and easy sharing. But, most companies do not know how to utilize the data for their business growth. They even do not have any idea about which data is most important for the business success. But, the rate of data producing and collecting is accelerating. This is called as data explosion (Frew, n.d.). Although a company doesn’t use the data they collect every day, they do not trash those unwanted data. Instead, they store data until the day they find the collection of raw data useful. But, most businesses do not know that they store data on a server or in the cloud utilizing the resources. Further, most data doesn’t have a long lifespan (Frew, n.d.).These are some of the notable effects of data explosion for a business.
Thomas Davenport’s assertion and sustainable competitive advantage.
According to the assertion of Thomas Davenport and Jeanne Harris, competitive advantage is a result of predictive analytics and business intelligence exploitation. Companies such as Netflix Inc., Capital One Financial Corp and Amazon.com are already utilizing analytics to create a competitive advantage (Davenport & Harris, 2007). For example, Netflix’s movie recommendation engine is algorithm-driven and that helped the company to gain huge success over its competitor Blockbuster which is a brick and mortar operation (Davenport & Harris, 2007).
Organizations that are based on their analytics have chosen one or a few capabilities are called analytical competitors. These analytical competitors use quantitative analysis and fact-based decision making to enhance their capabilities in managing the business. According to Davenport, analytics help a business to reach a higher level (Davenport & Harris, 2007). For example, Capital One’s approach is an information-based strategy where Harrah’s is customer loyalty and service (Davenport & Harris, 2007).
Regardless of their approach, the companies that compete successfully on analytics own analytical capabilities such as unique and hard to duplicate, adaptable to many situations, renewable and better than the competition. Davenport also suggests that company CIOs have the responsibility for changing the organizational culture and analytical behaviours of employees (Davenport & Harris, 2007).
Data management is important for any business. However, it is also important to understand the data explosion and find ways to utilize the important data for business growth. Companies can leverage data to make more informed decisions, understand customers, and market trends, provide smarter products and services, improve internal operations and create additional revenue opportunities (Hogendoorn, 2020). Discuss Thomas Davenport claims that analytics is the source for any company to gain a sustainable competitive advantage.
Davenport, H., & Harris, J. G. (2007). Competing on Analytics. Computer World. https://www.computerworld.com/article/2553007/competing-on-analytics.html
Frew, S. (n.d.). The Data Explosion, Part 1: How to Manage All That Data?. iasset. https://www.iasset.com/blog/data-explosion-part-1-how-manage-all-data
Hogendoorn, P. (2020). Top 5 Ways Manufacturers Should be Using Their Data. FreePoint. https://getfreepoint.com/top-5-ways-manufacturers-should-be-using-their-data/
Marr, B. (2016). Big Data Overload: Why Most Companies Can’t Deal With The Data Explosion. Forbes. https://www.forbes.com/sites/bernardmarr/2016/04/28/big-data-overload-most-companies-cant-deal-with-the-data-explosion/?sh=3cce2bf06b0d
Disclaimer: This article was created using a paper written as part of the MBA program.
Also read: implications of Moore’s law