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Problem of transportation logistics

MM: Not just trucks, but what’s on the pallet and how many pallets get organized by what truck.

MB: That’s right. And how many stops it takes and so forth.

This brings me back to what we mean by a “Diagonal,” BI application.

To build an application that really helps address the problem of transportation logistics, or the truck shipping of goods, you have to embed a lot of industry understanding and knowledge of trucking into the application. So it requires information specific to the business problem of shipping goods by truck, but it’s not specific to any particular industry.

You don’t really care whether you’re shipping machinery or consumer packaged goods or clothing. These applications cut across industries, but not all industries. Obviously, financial services people aren’t shipping goods around by truck, and for the most part, shipping is just not a part of their primary value proposition. Similarly, higher education is not a truck-oriented industry. But any manufacturing company, whether in the food segment, the clothing segment, the toy segment, the industrial products segment, etc., all have a similar trucking problem to solve.

Another example is any company that makes or sells something that typically has sales margin and profitability issues. The companies really want to understand what products are selling at good profit margins. They want to be assured that the inventory they carry, relative to sales rate, is in balance.

Sales margins and profitability issues cut across industries that have goods to buy and sell—but obviously these aren’t applicable to government or higher education. It’s not like a database system because it doesn’t apply across all industries.

These diagonal types of applications are important because they add high value for their customers. They typically save companies thousands and thousands of dollars all the time, or even millions, for large companies. So they are applications that can command high price points, because they really deliver great savings and a very attractive return.

But also, they’re applications that—because they can be sold across many industries—have a pretty large base of prospective customers—larger than vertical-market applications that are targeting a very narrow perspective. They are very attractive from a business standpoint.

Diagonal applications also work very synergistically with SaaS deployments. That was one of the things that I emphasized in the talk I gave at SaaScon. The reason there are companies like Oco and obviously other new market entrants in this space is because of this synergy.

When you build a system for a particular business problem, transportation logistics, let’s say, then the structure of the database of information that’s needed to support it is not specific to that particular customer. It’s a database that’s designed to support transportation logistics.

As a result, you can get great economy of scale in the deployment of that system by creating a SaaS multi-tenant deployment of that database. All the customers sharing that infrastructure are trying to solve the same kind of transportation and logistics problem against a database of similar structure.

This works a lot better than the ASP models of a decade ago. Back then, custom data warehouses would be designed for each business. If you tried to aggregate those together, you’d get a whole bunch of totally different databases. In some sense, they were too customized. You’re not going to get common behavior by putting them together.

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