Intellectual capital: from intangible assets to fitness landscapes
Introduction
Managing corporations is a difficult and risky business. Doing it well requires the ability to understand factors including market, customers, employees, technology, culture, history, and opportunities. Management is made all the more difficult because variables interact. For instance, increasing expenditure on information technology may decrease next year's profitability, but increase the number of projects completed on-time. Such variable interactions may be separated in time, non-causal, non-linear, and involve multiple variables.
This is where a knowledge management tool and can help. This paper introduces a knowledge management technique we call “IC mapping”. IC mapping extracts knowledge from historical company data and converts them into an interactive three-dimensional landscape. Using this map, managers can interactively query the landscape, perform what-if analysis, identify problems in their business, and understand their company's performance in relation to others.
Section snippets
Multivariate measures of company performance
With the growth of the services sector in major industrialized countries (USBLS, 1999), many authors have suggested that non-traditional or “intangible” assets of business operations — such as customer relationships, and skills of employees may be increasingly important, and worthy of reporting on profit–loss sheets in their own right. In effect, a wider measurement net needs to be cast in order to capture the fitness of a company (Edvinsson and Malone, 1997, Karlgaard, 1993, Kaplan and Norton,
The promise of mapping
IC Mapping is designed to provide a visual tool that unifies the operating state of the company, and is easy to use. The method is based on a body of well-known statistical methods including multi-dimensional scaling, which was pioneered by Kruskal, 1978, Shepard, 1974, Torgerson, 1958, Young and Hamer, 1987, and others; and non-parametric estimation investigated by Girosi, Jones and Poggio (1993) among others.
Fig. 2 shows an example of an IC map, with a company traveling across a fitness
Building a map
The mapping process consists of two stages. The first task is to project the high dimensional company data into two dimensions. The second is to add a fitness variable as a third dimension, and then interpolate between those points to predict the shape of the fitness surface connecting these regions.
Step 2: Fitness as the third dimension
The most important feature of the landscape we want to plot is fitness. Fitness refers to the health of the company, and examples can include “total operating income”, or “net profit after tax”. Because knowing the fitness of the company at a given position is so important, we carry fitness into the 2D projection unaltered, and have it plotted as the third dimension.
After adding a fitness variable we now have a set of 3D points. We can think of these 3D points as a scaffold for the landscape
Adding details to the map
Once the final landscape is built, a variety of details can be added to the basic map. Some observations may coincide with an important event, for instance “competitor came onto the market”, “company went public”, and so on. We can carry these labels from our high dimensional data into our 2D map, and display them on the map. This can help the user navigate the map.
Finally if the trajectory across the landscape is itself observed once every 12 months, the points in-between are not known. Since
Time to reach destination
In the early days of navigation, ship captains used calipers to measure the distance between locations on their map. They would measure speed by dropping buoys and using a stopwatch to calculate speed across water, a process known as “heaving the log” (Bowditch, 1826). Using these tools, ships could estimate the time to reach their destination.
On IC Maps the same calculation can be performed. A simple method is to compare the parameter difference needed to reach the new location, with the
Experiment 1: Skandia fitness landscape
In order to test whether IC Mapping could be used for real companies, we selected four companies from the large multinational Skandia investment group to be projected together onto a fitness map. The companies were Intercaser, Dial, American, and UK Life. Intercaser, American, and UK Life are the Spanish, American, and UK branches of Skandia Investment firm. Dial is a telemarketing insurance company which operates throughout Nordic countries.
The state of each company was fixed with a vector of
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