Competing on Analytics

The article “Competing on Analytics” (Davenport, 2005) discusses how organizations are relying more on quantitative models than in previous years. Companies within the financial services have used analytics for years. However, companies in other industries have recently begun making extensive use of quantitative models in less conventional ways.
While all companies use quantitative models to some extent, some rely on it much more heavily than others. Davenport claims that there are several important attributes that can be used to identify which companies use analytics as a central part of their strategy. One of the most important elements of a company with a strong analytics program is that one or more of the highest-level managers must try to promote analytics within the organization. This is because creating an analytics based organization requires a strong shift in organizational culture and practice. Some lower-level employees have helped successfully make such a change in their companies, but such a change usually needs to come from a manager with more power and influence.
Companies with strong analytics programs also use sophisticated techniques for analyzing and predicting different variables. These companies maximize effectiveness in areas such as customer retention, pricing and management of inventory through the use of analytics. In addition to conducting thorough analyses, these companies also conduct experiments to better understand the models that they will use in the future. Analytics are used within many different functions within the organization, and become a standard.
Davenport and his colleagues interviewed many organizations that had reputations for being highly analytical, and identified several stages that these organizations went through. Initially, organizations begin as being interested in being more analytical, but do not have the resources or skills to do so. They usually begin by applying analytics in a specific, narrowly defined area. Over time, they expand their use of analytics before they are finally able to develop a program that gives them an advantage over their competitors.
In addition to identifying the factors that are common to organizations with strong analytics programs and the stages they must go through to develop them, Davenport identified the different areas where analytics could be helpful to the organization. Davenport found that analytics were useful in identifying and retaining key customers, managing supply chains, developing new products and minimizing costs. They also were commonly used for overseeing the overall strategy of the organizations.
Finally, Davenport discussed what firms needed for successful analytics programs. His group claimed that the most important factor was access to large amounts of high-quality data. Firms also needed to be capable of processing and interpreting this data, which requires a strong technological environment and employees with strong quantitative competencies. If there are no employees within the firm that are capable of interpreting the data, the company has the option of outsourcing these functions to other organizations.
In addition to needing plenty of data and the capability to interpret it, organizations need to make the need for this data clear so that members of the organization can understand its importance. If top executives are not willing to accept the use of analytics, the organization is unlikely to develop a strong analytics program regardless of the amount or quality of the data available. If current leaders do not advocate the use of analytics, a change in management can encourage their use. The executives that successfully implemented the use of analytics was not always the CEO, although the CEO tended to be most successful.
Organizations have done different things to create a demand for analytics among their members. Many organizations have appointed specific individuals or even assigned entire teams to be responsible for handling the analytics of different functional divisions within the organization. Another way for lower level to promote the use of analytics is to provide busy and impatient executives with readily available data so they don’t have to use an analytical approach at the expense of saving time. Changing an organization to make it more analytically based always involves persuading higher-level managers and other relevant stakeholders that using analytics is realistic and would improve the organization.
Many companies are beginning to use analytics to become more competitive. Davenport seems to be making it clear that analytics can be a strong tool for improving companies’ performance in a number of different areas. However, there are a number of different factors that can limit companies’ ability to use analytics and managers’ ability to convince executives and other individuals to make analytics a central role of the organizations.