Competing on Analytics
Competing on Analytics, by Thomas Davenport, investigates the concept of analytics as a basis for business competition. The article describes the characteristics and practices of an analytical competitor and the changes companies must undergo to compete in industry. Analytics refer to skills, applications and practices used in business to examine past, present and future business performance. It collects significant amounts data, analyzes the data that is collected and uses a statistical model to help a company make optimal business decisions based the data that is collected. This data focuses on developing new insight and understanding business performance – it is a strategic advantage in a business planning.
The use of analytics will allow for companies to be distinguished and gain a competitive advantage over their competitors. Three key attributes were discussed: the use of predictive modeling and optimization, use of enterprise level management approach, and the adoption of this approach by senior management. The use of predictive modeling and optimization looks beyond the basics and gathers necessary information to gain a comprehensive understanding of the customer; optimize techniques used to address issues of supply and demand and any other problems that may arise. An enterprise level management approach allows for multiple skills and resources to combine in an effort to measure the firm’s past and future performance. Support from senior management is imperative, as they must advocate for this approach based on statistical analysis and fact based decision making. Senior management must direct and coordinate the change in culture, processes, behaviors and skills.
Each of these characteristics plays a vital role in facilitating positive change. Businesses must undergo substantial change to successfully build this analytical culture. To compete analytically, a firm must not solely concentrate on statistical and quantitative information,
The use of analytics will allow for companies to be distinguished and gain a competitive advantage over their competitors. Three key attributes were discussed: the use of predictive modeling and optimization, use of enterprise level management approach, and the adoption of this approach by senior management. The use of predictive modeling and optimization looks beyond the basics and gathers necessary information to gain a comprehensive understanding of the customer; optimize techniques used to address issues of supply and demand and any other problems that may arise. An enterprise level management approach allows for multiple skills and resources to combine in an effort to measure the firm’s past and future performance. Support from senior management is imperative, as they must advocate for this approach based on statistical analysis and fact based decision making. Senior management must direct and coordinate the change in culture, processes, behaviors and skills.
Each of these characteristics plays a vital role in facilitating positive change. Businesses must undergo substantial change to successfully build this analytical culture. To compete analytically, a firm must not solely concentrate on statistical and quantitative information,