10/90 Rule
The 90/10 Principle states 10% of life is made up of what happens to you. 90% of life is decided by how you react. For example, a driver cannot control a red light but the driver can control their reaction. With that line of thinking, famous entrepreneur and author Avinash Kaushik created the 10/90 rule to achieve web analytic successes. Organizations of all kinds are using data to create a competitive advantage in departmental areas such as sales, marketing and operations. Until data is transformed into insight, it is basically worthless. The transformation process and the discovery of information is done by people, not machines. In order to optimize web presence, organizations should maintain a competent staff who have business intelligence
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This a comprehensive evaluation of organizations and the report details issues that affect the web analytics industry. Over 900 digital professionals were surveyed. The report found that more companies in comparison to previous years are looking to grow their in house web analytics team. 50% of businesses surveyed were looking increase spending in that area over the next year. While companies may be looking to increase spending, it may not always be feasible. The book “Web Analytics Demystfified” argued that the 10/90 rule is somewhat unrealistic. Also stating, the 10/90 rule depends on the type of organization, and presents the appearance of a silver bullet. The writer Eric T. Person states while over the long term the majority of expenses will be spent on staffing, specialized skills do not come cheap. Finding analysts that can comprehend an organization’s data, judge its reliability and can harness the data to help achieves business objectives is not easy. Perhaps most importantly web analytics personnel must be able to communicate those insights to other departments. Eric T. Person’s strategy states the tools and people are equally important and should be budgeted as such. The further the budgets for personnel and tools are from one another, the harder time a company has with analytics. I am more inclined to agree the approach of Avinash Kaushik. It has a start small logic and more robust foundation that can be applied to any type of organization. Cost savings are a major competitive advantage. I’m hoping that all companies Person interviewed at least attempted to gain knowledge from the free tools before moving to a more expensive web analytics
This a comprehensive evaluation of organizations and the report details issues that affect the web analytics industry. Over 900 digital professionals were surveyed. The report found that more companies in comparison to previous years are looking to grow their in house web analytics team. 50% of businesses surveyed were looking increase spending in that area over the next year. While companies may be looking to increase spending, it may not always be feasible. The book “Web Analytics Demystfified” argued that the 10/90 rule is somewhat unrealistic. Also stating, the 10/90 rule depends on the type of organization, and presents the appearance of a silver bullet. The writer Eric T. Person states while over the long term the majority of expenses will be spent on staffing, specialized skills do not come cheap. Finding analysts that can comprehend an organization’s data, judge its reliability and can harness the data to help achieves business objectives is not easy. Perhaps most importantly web analytics personnel must be able to communicate those insights to other departments. Eric T. Person’s strategy states the tools and people are equally important and should be budgeted as such. The further the budgets for personnel and tools are from one another, the harder time a company has with analytics. I am more inclined to agree the approach of Avinash Kaushik. It has a start small logic and more robust foundation that can be applied to any type of organization. Cost savings are a major competitive advantage. I’m hoping that all companies Person interviewed at least attempted to gain knowledge from the free tools before moving to a more expensive web analytics