Who, if anyone, could actually move everything to the cloud? I’ve never been a fan of the “move-to-the-cloud” model because my data has always shown a different trajectory for cloud growth, but the view that a full migration is inevitable is pretty pervasive. What can we say about that, based on information from enterprises and my modeling? A lot, it turns out, and while it may not support popular views of cloud evolution, it offers a very positive view about cloud growth.
The only motivation to use any IT strategy, including the cloud, is cost/benefit. “Cost” here means total cost of ownership (TCO), and probably the biggest misconception about public cloud service is that it’s less expensive than owning your own gear, because of “economy of scale”. Enterprises achieve nearly the same capital economies of scale as cloud providers do, and the majority of enterprises achieve reasonably good opex economies too. Given the risks associated with moving to the cloud, which include security issues and availability of compute resources you need network access to use, enterprises have generally declined to “move” to the cloud. However, they love the cloud in other missions, and there are some businesses who do show interest in an all-cloud strategy.
If we apply the term “enterprises” traditionally, to mean very large multi-national companies, my work and modeling has never indicated that everything would be moved from data center to the cloud. In fact, it hasn’t showed that much would be “moved” at all. Instead, the trend has been to use the cloud to develop “portals” that provide web and mobile device access to traditional core business applications running in the data center.
At the other end of the scale, it’s pretty obvious that small businesses with just one or two locations, relying on personal computers for their IT, aren’t moving to the cloud either. Still, it’s these one-or-two-site businesses that offer us some insight into just who might be contemplating a shift to the cloud. Most of these smallest businesses have only a few employees, but there are firms with one or two sites and over 50 employees, even over 100, and it’s this group that presents the biggest move-to-the-cloud potential.
What my contacts with users, and modeling, show is that in order to be a candidate for cloud-based IT (other than personal computers), a company has to meet some specific criteria. None of these criteria are decisive, so we have to look at how they all relate. We can gain some insight into how many might fit the bill through a use of government data on businesses.
The first and most obvious criteria for moving everything to the cloud is to have something to move, which means that there has to be at least a rudimentary data center. These days, this usually takes the shape of a rack of servers, which usually run Linux.
The second criteria is a high unit value of labor per employee, meaning that employees on the average are highly compensated. The higher the compensation, the more useful it is to make them productive. This tends to favor “professional” firms over retail firms, for example.
The third criteria is dependence on a single application. Generally speaking, businesses who run a lot of different applications tend to want local skills to support them. Those with a single application, predominately retail but also medical and legal firms, are better candidates for a cloud-only strategy.
The fourth criteria is tolerance to an Internet outage. In some verticals, loss of compute services could be literally life-threatening, and these companies are obviously reluctant to depend on the cloud, accessed via the Internet, to get to their applications.
The final criteria is application software sourced from a VAR/integrator. There are two impacts of this software approach. First, the fact that a firm is getting applications from a third party implies a lower level of in-house technical knowledge, which would make it harder to sustain in-house IT. Second, the VAR/integrator, if they provide a cloud-based strategy, will then influence all their customers to do the same. For self-installed software, there is no common motivator.
If we run all the business data through my model, what we get for the US market is that there are approximately 250,000 firms that fit the firm-size criteria. Of this, about 175,000 have a high unit value of labor, 110,000 are dependent on a single application, and 78,000 get their software from a VAR/integrator. Only 34,000 firms report low tolerance for loss of application access. The model combines these factors to indicate that of the 250,000 qualifying firms, 50,000 represent high-probability cloud-only opportunities, 120,000 represent “possible” cloud-only, and the remaining 80,000 have a low probability of moving everything to the cloud.
The model does suggest that there are a relatively small number of “enterprises” who could be candidates for a cloud-only strategy. These are verticals who represent a large number of employees per firm but a low percentage of high-value-of-labor employees. They also show very slow growth in centralized IT spending. There are roughly 20 verticals (out of 62 I model) that fit this bill. These represent approximately 14% of firms, or about 200 in total. However, up to this point at least, move-everything-to-the-cloud penetration into this group isn’t statistically significant.
One likely reason for this is illuminating for the whole move-to-the-cloud picture. This group of verticals has the lowest percentage of IT personnel, and the lowest average IT wage, of any group of verticals. My contact with this group is limited (for obvious reasons), but what I’ve had suggests that they believe they lack the ability to acquire and retain cloud expertise. They are uncomfortable making a cloud move, feel that they couldn’t support a cloud-resident IT framework, and often don’t even feel qualified to assess the cloud’s value to them, or evaluate the assessments made by others.
Could it be that even the companies who could benefit from moving to the cloud are trapped in their current IT models by a lack of skill? Since that lack of skill in their labor force is a product of their low IT commitment and their minimal career opportunities for IT specialists, and since that makes hosting their own IT difficult, it’s a classic Catch-22. I’m a cloud candidate because I can’t support in-house IT properly, but I also can’t support or even assess a cloud move properly either.
If my data is correct (which I believe it is), there is little to be gained by pushing a move-everything strategy to enterprises. There would be the potential to sell all-cloud service strategies to companies with between 50 and 500 employees, but the best path to pursue for this group would be to encourage their VARs and integrators to use the cloud instead of local compute for hosting those groups’ vertical-market applications.
The real opportunity may lie with the companies with between 500 and about 2,000 employees. This group is not currently committed to the cloud front-end approach that’s commonly used by enterprises for their public cloud services; only about 9% of companies in the 500-1,000 employee range use cloud front-ends for their applications and only 16% of the 1-to-2-thousand employee group does. This compares with 91% of “enterprises”.
The model suggests that the best way to approach a cloud prospect who doesn’t already have a cloud commitment, whether they’re an enterprise or an SMB, is through SaaS, either in the form of software specialized to their vertical or a “horizontal” cloud offering like Salesforce. This approach seems best because (as noted earlier) many of the companies who have not moved to the cloud say they lack the skills to either move or manage their applications there.
The final point the model makes is that even if all the nascent move-to-the-cloud opportunities were realized, the impact on cloud provider revenues would be smaller than that created by full exploitation of the cloud for new applications. We could add perhaps 40% to cloud revenues from realizing all the move-to opportunities, but we could more than triple it if we took advantage of new applications. However, half those gains would come from executing on “edge computing” missions, and the edge is still groping for a path to full deployment and for an architectural model that addresses everything optimally. There’s still a lot of work to do.