High Resolution Management

High-Resolution Management is a concept created by Professor Elgar Fleisch and Christian Flockmeier. It relates to the fact that most business management practices are based on living in an information-poor environment, wherein information was expensive to collect. But in the modern business world, increasingly important information has become easier to collect, through mechanisms such as RFID. The ability to track complex business activities, both through direct inspection and automatic mechanisms, has grown dramatically. However, our approach to management of important business processes is largely unchanged.

Professors Fleisch and Flockmeier suggest a new paradigm, High-Resolution Management, that would take advantage of the wealth of information, and allow companies to manage various parts of their business with better results.

Context and background

High-Resolution Management is a discipline that is emerging and is being applied by companies with complex and chaotic processes, which they are aware could be optimized if they could know about more of the vast array of activity that goes on and, through that knowledge, direct the activity.

In the past, optimization of these chaotic processes was rarely attempted. High-Resolution Management is the practice of examining these processes and attempting to understand them more deeply. One of the most often used examples of High-Resolution Management is the retail distribution of store displays, which need to be synchronized with promotions. Using High-Resolution Management techniques, a Consumer Product company was able to track when its in-store displays were put out at a series of drug stores. The company found that the business results were highly sensitive to the timing and placement of the in-store displays, relative to the radio and other media campaigns. In many stores, the highest-yielding results came when the displays were set up one or two days before the promotion began. The manufacturer also discovered that, in many stores, the promotion did not get installed until well after the promotion began. By being able to track exactly what was happening with the promotion and the displays, a much more optimized process was begun.

Research Goal

This research will cover the general theory of High-Resolution Management, describe its application in a variety of business contexts, in an attempt to capture the learning of early adopters and explore how High-Resolution Management can be applied in a variety of contexts. A high-level description of the processes that are most susceptible to High-Resolution Management will also be explored.

Scope

What is High-Resolution Management?

Who invented it?

How is it related to RFID and the internet of things?

What sort of processes are best for High-Resolution Management?

What has been the learning from early users of High-Resolution Management?

How can High-Resolution Management be used as a diagnostic tool?

What technologies are related to the application of data gathering for High-Resolution Management?

What technologies are related to the analysis of that data?

How does High-Resolution Management fit into the existing complex of enterprise operations?

What are the biggest payoffs from the use of High-Resolution Management?

What are the major questions now being asked about High-Resolution Management?