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As might have been assumed from the my post on automated testing in SAP systems a couple months ago, I've been delving into testing in the SAP landscape. I'm beginning to put together a series of presentations and workshops on the subject, the first of which I was delighted to deliver last week.

Being the first in the series, this presentation focuses on an overview of the leading edge of the field. It would be nice to be able to emulate the sort of testing techniques we can use in Ruby in SAP BI and EPM application development. Nice, but not necessarily realistic. I can dream!

Stephen O'Grady has a nice post clarifying his position on the telemetry opportunity in the enterprise, for open source vendors especially. "Telemetry" being here the practice of contracting with customers to send data back to the vendor, which the vendor then uses to provide some value add the to the customer. This value might take the form of better software, optimization tips tailored to the customer, or metrics comparing the customer to the full pool of customers.

Oddly enough, this might be one of those places where the enterprise is a bit ahead of the opensource world. Personally, I'm aware of SAP providing several telemetry-like services focuses on performance, maintenance, and bug/problem reporting.

It's also worth pointing out that SAP's traditional business model of partnering with customers to understand processes and develop business applications could be considered telemetry by some definitions. True, it's human-based telemetry rather than a technical system of reporting back to the vendor, but the point is the same: the customer transmits information about how they use or will use the software to the vendor while the vendor uses that information to provide a better experience to all customers.

In the open source space my impression is that we see telemetry (such as it is) focused primarily in the software quality space. Crash reporting is probably the primary place we see this, as in the ubiquitous Firefox beta crash reporter.

As O'Grady point out, software as a service companies have recognized this are as a great opportunity to develop competitive advantage. Google uses telemetry data extensively in its search product (suggestions, especially), as well as in other products like Analytics (benchmarking) to name an example in the enterprisey-er space.

In the consumer space, we're starting to see many tentative steps. Wasabe and Mint are both financial apps that allow the user to compare their activities against the aggregated activity of relevant slices of the apps' user bases. The idea is powerful, though I'm not particularly impressed by the utility of the implementations we're seeing outside of Google. It seems like apps are going to need to give up on trying to get the user to dig through this data goldmine and instead just deliver up specific nuggets, as Google does with its search suggestions.

Knowledge isn't worth anything if you don't use it. Similarly, intellectual property, the crystalized product of knowledge, isn't worth anything if it isn't consumed. Compounding this is the fact that knowledge products age fast. Screencams and whitepapers are old news in a few months. Blog-style analysis is out of date in a matter of weeks or even days. There is some content that stands the test of time, but most of the output of knowledge workers experiences a very fast decay in value.

Over the last few weeks I've found myself making the same point several times, so when I saw this image, it struck a chord.

(Image courtesy of Tom Matrullo and the FASTForward blog.)

When evaluating how to handle knowledge products, businesses tend to focus on how best to defend the value of their investment by keeping it out of the hands of their competitors. This approach is especially prevalent in knowledge- and skill-focused industries like professional services and it is usually misguided.

Since most intellectual property loses value so quickly, it is imperative to extract as much value as possible as quickly as possible. Protecting the investment should be a consideration, but value extraction should be the focus. Value extraction is often enhanced by sharing these types of quickly diminishing IP.

The exception is when a firm has developed a considerable ability to quickly extract value from intellectual property in a closed system. Companies like Gartner and Forrester have this type of ability in place, but even some analyst firms like Redmonk have gone the open source analysis route and found it to be a solid business model.

The bottom line: If it's not your business to sell IP, I'd second guess the impulse to act protectively towards your IP. Instead, think about extracting the maximum value as quickly as possible. Then get back to work generating more of the good stuff.