Software + data as business models

Insight on how open source software has changed the game for software businesses, excerpted from Stephen O’Grady:

“The data is clear: while there is substantial money in software, the difficulty of employing it as a primary revenue mechanism is increasing. This supports our observations of generational shifts in attitudes towards the importance of software [coverage]. In short, we recognize four basic generations of software producers.

* First Generation (IBM) “The money is in the hardware, not the software”:

For the early hardware producers, software was less interesting than than hardware because the latter was harder to produce than the former and therefore was more highly valued, commercially.

* Second Generation (MSFT) “Actually, the money is in the software”:

Microsoft’s core innovation was recognizing where IBM and others failed to the commercial value of the operating system. For this single realization, the company realized and continues to realize hundreds of billions of dollars in revenue.

* Third Generation (GOOG) “The money is not in the software, but it is differentiating”:

Google’s origins date back to a competition with the early search engines of the web. By leveraging free, open source software and low cost commodity hardware, Google was able to scale more effectively than its competitors. This has led to Google’s complicated relationship with open source; while core to its success, Google also sees its software as competitively differentiating and thus worth protecting.

* Fourth Generation (Facebook/Twitter) “Software is not even differentiating, the value is the data”:

With Facebook and Twitter, we have come full circle to a world in which software is no longer differentiating. Consider that Facebook transitioned away from Cassandra – a piece of infrastructure it wrote and released as open source software – for its messaging application to HBase, a Hadoop-based open source database originally written by Powerset. For Facebook, Twitter, et al the value of software does not generally justify buying it or maintaining it strictly internally.

The question, as I asked the audience last week at the Open Source Business Conference, is what this means for those in the commercial software business. The answer, from my vantage point, is simple: they need to begin leveraging data alongside their software. As we’ve been saying since 2007 [coverage].

In a very real sense, software is becoming a vehicle for generating data; a means rather than an end. Open source software vendors are universally poor at customer conversion. The best of them converts one out of a thousand users into a paying customer. What they give up in conversion, however, they gain back in distribution. Open source software enjoys intrinsic advantages over commercially licensed alternatives with respect to its ubiquity. Until they begin harnessing this distribution in the form of data aggregation, however, this advantage will remain underleveraged. Which is unfortunate because it is a model that inherently better aligns customer requirements with vendor needs.

Because the majority of open source commercial revenue at present is derived from support and service contracts, customers are effectively paying vendors for services they hope not to need. By collecting, aggregating and analyzing anonymized customer telemetry (i.e. non-transactional data), vendors could supply customers with insight they would be unable to obtain from any other party. A potentially compelling proposition.

Contrary to assertions otherwise, then, the argument is not that software companies are dead. The evidence does not support, and in fact contradicts, such a claim. The evidence does suggest, however, that those startups that wish to get big, in the Apple sense if not the Exxon, should begin leveraging collected data as a complementary revenue stream. Software support and services alone hasn’t produced a Top 20 revenue earner in over two decades, and doesn’t appear poised to anytime soon.

The Age of Software was fun. Welcome to the Age of Data.”

1 Comment Software + data as business models

  1. AvatarLori

    Data stinginess seems to be central to a lot of business models. Even more jealously guarded than data of course, is meta-data, or the machine readability of data. Also note that data counterintelligence measures such as screen scraping do not seem to figure prominently in the public domain software; instead being the stuff of “freelancing” at third-world rates. Hopefully machine readability will at some point enter into our understanding of what it means for information to be in “the public record.”

Leave A Comment

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.