Run don't walk - Simplicity and Speed

One of the unique features of our taxonomy is that we like to show how near items are in the taxonomy to other items classified using our taxonomy. Since we are classifying companies, it allows for us to define a "sphere of competition". Our first version of software which determined "nearness" used a walking algorithm which would walk up and down the trees to determine distances. Searches for "nearby companies" took a long time, up to a minute. Recently we changed the algorithm to use some algebra to do the walking and now searches take less than a second!. The algebraic algorithm was simpler and faster. Check it out on mandasoft.com. Use the see comparable deals link.

Challenges of Searching a Complex Taxonomy

As I have noted, our team has developed a very complex multi-faceted taxonomy which give a very exact categorization of any given business. The complexity we have created comes with a price. It creates challenges for users searching for businesses. A company is categorized by who their clientele is, what business needs they fulfill and by how they fill those needs, and what channels they use. A typical user does not think of businesses in such a manner. For instance, a typical search would be I would like all businesses that sell education software. In early versions of our application, users would have to savvy enough to enter in the search criteria education for the clientele and to enter software for industry (the "how a business operates"). Needless to say, users had to be trained to use the system, and hence the system was only used by our in house taxonomist who would get search requests and he would then give them results in a handy report. This was not ideal, because our taxonomist has many other things to do. The challenge for us was to make our taxonomy search as easy as Google. Nobody has to be trained to use Google, and we found that if training was involved generally that part of our application was not used unless the payback was great. In addition, since we were already fielding queries, our users found it much easier to send an email to our team, rather than run the search on their own. So how did we simplify our search. Well, in an earlier post, I mentioned we found that were phrases that users wanted in our taxonomy that would not fit in a single tree or dimension of our taxonomy. I called these phrases, "Meta-Terms". The example I gave was Trade Magazines which are B2B magazines. In our taxonomy we then map this term to magazines in our Industry tree and B2B in our Clientele tree. So the key to simplifying our search was to use "Meta-Terms" as a model for Google like search, Users can now type into a text box and it will see if it matches an existing "Meta-Term" or what I call an implicit "Meta-Term". Implicit "Meta-Terms" are created  by synthesizing synonyms from our different trees' vocabularies. There are over a million possible combinations from the trees, but some of the combinations are unlikely to exist like (e-discovery software for teenagers). So we have created a list of synthesized terms from the companies we have already categorized (numbers around 23,000). From these categorized companies and all the synonyms, we get a list of about 200,000 implicit meta-terms. Our "Google" search box then matches the user input to our list of terms and runs a query on how that meta-term maps to our multiple dimensions. This is still in testing, but shows tremendous promise.

A One Way Street to Clarity and Simplicity - More on Mapping a taxonomy to a taxonomy

In my last post, I did not elaborate too much on rules sets that contain the logic to map from one space to another. These rules sets are interesting in that usually when you map from a complex multi-dimensional taxonomy space to a simpler domain specific taxonomy space it is a one way mapping. A good way to think of it is to think about how photography works. A camera has a lens that focuses an image of a three dimensional space onto a two dimensional piece of film. Needless to say, there is a loss of information when the camera takes a picture because the resulting image is just a single view of a three dimensional image. Can we recreate the three dimensional space from our two dimensional photo? Not really, though I have seen some software that guess. Nevertheless, we still love photography. I was just looking at my wedding pictures last night, and in a way photography gives us a clearer vision of our shared reality from an authorial viewpoint.Great portraits or landscapes captures a moment and gives it clarity.

Let's get back to our idea of rules sets (our taxonomy camera), and how they map from from a complex multi-dimensional taxonomy space to a simpler domain specific taxonomy space. We develop the simpler taxonomy to give us a perspective of a domain which gives us vision of clarity and simplicity. We use it to give an authorial view of certain business sectors in a way that our more general purpose taxonomy can not do.

For those with a mathematical bent, I can say that our rules sets are prioritized rules and the fact that we have rules with greater priority than other rules makes these rules sets one way, and collapse the information to a simpler view. If we ran our rules sets on companies classified using the complex taxonomy to get the simpler classification, and then ran the rules sets in reverse on the simple taxonomy to get the categorizations in the complex taxonomy, the original complex classification will not be the same as the derived categorizations.

Mapping a taxonomy to a taxonomy

In my last post, I talked about "meta-terms" which mapped a commonly used expressions to nodes in multiple trees. This concept could be taken much further. When our team built our four dimensional taxonomy, our goal was to be able to classify any business, and to find similarities between companies even though traditionally they  would be considered to be operating in different arenas. My favorite example is to look at Intuit which creates financial software for the consumer, and compare it to H.R. Block which provides a financial services for consumers. In the tax arena, they both provide help to people doing their taxes, and compete directly. Our taxonomy categorizes Intuit as a consumer software company for taxes, while H.R. Block is a consumer service company for taxes. As you see these companies overlap on what they do, and who they do it for, but not on how they do it. Interestingly enough, Intuit started offering a professional help service and H.R. Block started offer a software package.

What this brings up is that our taxonomy is complicated. Our team produces reports on Merger and Acquisition activity in a variety of segments (http://mandasoft.com), and each of these business segments like to break down using their own taxonomies specific to their domain. How do we reconcile the need for a taxonomy with nodes that can be used cross multiple domains, while needing to have easy to understand domain specific terms in a given domain?  The way I like to see this problem is that we have a vocabulary that works great when looking at the business world at the 50,000 foot level, but when we get down into trenches, the terms start to look vague and confusing at the lower altitudes. The way we solved this was by building a system to create 50 ft level simple taxonomies for specific domains (e.g. healthcare media and software). We then categorize each business using the 50,000 foot level taxonomy, and we then have rules sets that map from 50,000 ft level taxonomy to the 50 ft level taxonomy. The utility is especially noted when we create multiple domains with their own rules sets  (e.g. healthcare media and software, and  Cloud Computing) and a business which may reside in both domains, only needs to be categorized once at the 50,000 ft level taxonomy. We can create as many domains as we need and not have to reclassify companies as our domain views evolve!

Spheres of Competition

Last week I spoke of looking at a business taxonomy in new way. Generally, people think of taxonomies as a vocabulary with perhaps a hierarchical structure of categories and sub-categories. However when you build a multi-dimensional taxonomy as our team has, you can now start to think of it as a spatial topology. There are four trees and each one defines a dimension in our business taxonomy space. This thought is analogous to the special theory of relativity from physics where you have the x, y, z dimensions plus the time dimension. An "event" is a point in the space time continuum is defined by those four dimensions. In our business taxonomy space, a "company" is a point in the spatial topology defined by our four dimensions. If you draw a small sphere around a given company's point in our taxonomy, you will get all the competitors of that company. We have seen as you widen the sphere the outlying companies are less likely to be competitors. The key to making this work is to define the distances between points in a given dimension's tree. We generally realize that the distance between parent and child is shorter the deeper you get into the tree, and the distance between siblings is slightly more than that between parent and child. We also realize that you may define siblings where some siblings are closer in meaning than others. Our distance algorithm has to take all these things into consideration. Our work has been experimental, but has returned interesting results. We have use this in our drill-down feature on mandasoft.com.  The space defined has to be tweaked, and I may leverage algorithms similar to Einstein's general relativity where actual data defining company revenue at a point in our topology could warp the spatial distances, just like physical mass warps physical space. Any thoughts?

Requirements for a better Business Taxonomy Part 4

My last post talked about how we can categorize a company in three different ways:  1) Who their customers or audience are. 2). How they serve their clientele. 3). What business need do they fulfill for their clientele. This is what I have heard called a faceted taxonomy. But I prefer it to be called a multidimensional taxonomy. Now we must ask ourselves are there anymore dimensions which could be useful. Our team has found one which is a little goofy. This is what I call the channel dimension. A company will provide a service, but with all these new means of reaching clients via mobile or internet. Maybe we can have a small domain which defines these different ways of reaching people. So for our example of healthcare EMR software, this company could channel their services through licensed software installed at the client, or via a subscription of hosted software also known as Software as a Service (SaaS). Could anyone think of another useful dimension for a Business Taxonomy?

Requirements for a better Business Taxonomy Part 3

Having discussed that we can have multiple dimensions for a detailed Business Taxonomy, lets see what dimensions we might want to have. The first two dimensions we discussed about described 1) Who is the company's clientele (for media we should look at the audience) 2)How the company services their clientele. I suggest we also give a dimension for 3)What business need the company accomplishes for their clientele. For instance, our hypothetical healthcare software could accomplish a particular process. A big new push in healthcare is Electronic Medical Records (EMR). If we have this third dimension, we can now classify a Healthcare Consulting company specializing in EMR. Now, if we search for businesses providing EMR solutions, we will get results for any company who are working in that space weather they are software or a consultant. Most taxonomies that "solve" this problem by searching on a mix of keywords and their tree structure. This third dimension gives a way to tie in companies that are working on related subjects but using different methodologies. Look at HR Block and Intuit. One is a service company and one is a software company, but both provide tax solutions. We will look at more dimensions in the next post.

Requirements for a better Business Taxonomy Part 2

Following my previous post, we see that a business can be classified in a parent child hierarchical taxonomy, but sometimes one could create a sub-category which is really expressing a not a sub-type of the parent category, but rather a different aspect of the business. As in healthcare software is not really a sub-category of software. Healthcare defines the customer base or subject matter of the software. A true sub-type of software would be infrastructure software or business application software. An improved business taxonomy would then categorize a company in multiple ways or dimensions. For instance you could have, a dimension to describe the clientele or market that. So our healthcare software company would have its clientele be set to healthcare. Another dimension would describe how the company solves the business problems in the case of our  healthcare software the company would be categorized as software. In my next post we will discuss other possible dimensions for a business taxonomy.