Catching up on Q2
So much is happening as we approach the end of Q2, our industry’s busiest quarter, at least by some measures. I’m flying around seeing things but not always able to comment from a middle seat on a red-eye. So this piece is an attempt to catch up and set some markers for the traditionally slower summer.
Last time, I was searching for a word to describe a new category I see. You can call it various things like on-demand services or even services as a service which somewhat distinguishes them from things as a service such as SaaS but it’s also confusing.
SaaS has led the way in things as a service and while it’s a perfectly good descriptor the rapid evolution of IoT, Internet of things, has introduced some confusion. Things as a service describe any traditional good delivered as a service, such as software or a car or a cell phone. Services delivered as services often don’t have a physical component or that component is of a different type, perhaps not even human.
For instance you can get software as a service but the training or consulting that needs to go with it is very different. First, it’s delivered by people who show up, do a job, and disappear; you don’t employ them and you certainly don’t own them and their work product is pure service, often leaving behind only thoughts in other’s minds or software code.
Another example, and my favorite right now, is earth moving. Various makers of things like excavators and bulldozers now offer earth moved as a service obviating the need to purchase the big device. The difference is that the service is intentionally and decidedly temporary. These companies calculate amount of earth moved (in a simple example) and charge by a meaningful metric such as tons or cubic yards moved. Moreover, these are short-term services; the equipment and people to run it show up one day, do a specific task and then are gone. Or perhaps they are idle for one week per month—how do you charge for this?
In a SaaS model you might buy a specific number of seats per month and that’s it, if your people don’t use it, too bad. But in the earth-moving example, an idle machine still has overhead for a vendor. How does the vendor capture revenue when the device is idle? It’s not hard to do but it gets into some branching logic that typical billing systems might not cover. So very quickly, we see that service as a service is different from a thing as a service. What do you call that? And what’s the name of the business model and how do you account for these services?
My thoughts include words like precision services or discrete services. Each conveys a sense of the ad hoc, a temporary, specialist thing that won’t become part of the status quo in the sense that it will be gone at some point. Just think of the earth-moving equipment required to build a tall building and understand that it’s not there any more once the building is completed.
So that’s one thing I’ve been noodling on. Send me a note with your thoughts.
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Also on the docket have been Oracle’s results for the last quarter. It’s only important to look at the direction, which is up and to the right of the graphs, to know that the company has hit stride on cloud computing. I am happy for them and have previously written that their model is uniquely suited to their customer base. It includes all phases of cloud computing including infrastructure, applications, and platform to support customers in various stages of the move.
Oracle’s big footprint attracts lots of competition from Amazon’s AWS at the infrastructure end to Microsoft, Salesforce, and SAP on applications and platform. I am not even sure if they all agree on what platform is and that’s important. It tells us that the tip of the spear is platform and that’s the competitive landscape. It’s also the metric that we need to use to analyze and understand the quality of any software vendor’s earnings.
Infrastructure is heading toward pure commodity status and it’s getting close if in fact it has not already arrived there yet. But ironically, you can’t be wildly successful in the other phases of the game if you don’t have a credible infrastructure offering. So you have to look with great interest at Oracle’s infrastructure number which equals just north of $400 million on what I believe is a $1 billion cloud base. Is it a good thing? I think it’s a necessary thing and it might set the company up to do well in other phases but that jury is still out.
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Finally, there was a piece on AI in the New York Times Sunday Review, “The Real Threat of Artificial Intelligence” by Kai-Fu Lee that I am in complete disagreement with. I’ve seen the argument before: AI will swallow up jobs leaving a large and unemployable group of people who will require some form of guaranteed income support. But rather than offer an opinion, let me supply an analysis and some data.
Massive income assistance has never worked well in human history. You might go all the way back to the Roman Empire and recall the idea of bread and circuses as an example of such welfare. But if you do, you also need to factor in that it didn’t work out well for guys named Caesar. In modern times the top earners have always objected to the confiscatory taxes needed to make such a scheme work.
This kind of analysis is too dependent on straight-line thinking. What’s missing is any sense of the dynamism of free markets in a democracy. Free markets enable innovation and entrepreneurship and with them come new industries and new jobs. I know things look kind of bleak for people with high school educations or even people with BA’s in literature or philosophy. But the fact of the matter is that since the Industrial Revolution there have been 5 ages when an industry or a clutch of them took off and did really well for a few decades only to fall back to earth later killing some of the jobs it created in the name of efficiency and commoditization.
What we’re going through with AI is cyclical and not one of a kind. I just wrote a book about it and it’ll be out in September, a time when we come back from the beach and put our game faces back on and rediscover that a machine really can’t do what we do.