Reflecting on the recent financial reports of the giants of computing infrastructure – companies like IBM, HP, Oracle, and Microsoft – I am struck by the continuation of a troubling trend: The technology and its usefulness is moving ahead as fast as, if not faster than, ever before; IT has made some striking adjustments; but the revenues to vendors from this, and therefore IT spend, are flat if not falling. Why?
Let’s see. In databases, Oracle and IBM are almost flat, despite (at least in IBM’s case) two technologies in two years that potentially deliver performance and price-performance gains well ahead of Moore’s Law. I find plenty to criticize in Windows 8, but its implementation with regard to business needs, in Windows and Office usage, should deliver benefits comparable to that of the introduction of the mouse-based user interface – and Microsoft enterprise revenues are flat. Cloud technology is not replacing, but rather complementing, in-house architectures, and therefore should require, initially, more rather than less total spending – and yet, increases in cloud spending are instead paired with overall flat or lower user computing spend. No, I don’t buy the “public cloud saves money” rationale – the benefits come later rather than sooner, and involve mainly flexibility and to a much lesser extent multi-tenancy and grid savings, especially when many users are employing multiple cloud providers that must be coordinated. And the IBM and Oracle/SPARC data suggest the biggest hardware decline is in Unix/Linux hardware, the darling of the cloud set, not in mainframes or PCs.
In the past, a typical explanation for this has been the need for the business to cut back IT spend in response to decreasing profits. Of course, that did not prevent IT and computing from becoming a larger and larger part of overall business spending during the 1980s and 1990s. In the early 2000s, IT spend actually decreased proportionally to the cost-cutting of the rest of the business – and yet, despite an initially tepid overall business recovery, computing spending from about 2003 to 2008 rebounded and grew quite briskly. So this pattern of user computing spending is unprecedented in three ways: its length, its unremitting focus on cost-cutting apparently comparable in size to the rest of the business, and its seeming inability to reflect major technology advances with a good claim to deliver major cost or other benefits to the rest of the business.
The Blame Game
In the past, I have found, when things go wrong in computing spending the first reaction is to blame the vendors. In this case, the obvious critique is that they have failed to communicate the benefits of the technology, cost and otherwise. Except that, as I can attest from my experience as an analyst, both the technology advances and the communications from the vendors are as good as, if not in many cases better than, those of most or all of the past. Big Data, for example, is not pure hyperbole, and vendors have done a reasonable job by traditional standards of highlighting the ability of targeted Big-Data analytics to explain and bind the customer as never before, in a cost-effective way.
OK, then the next line of analysis is to blame IT, typically for failing to align themselves with the business’ strategy, or (when times are tough) identify ways of lifting the dead hand of older systems and other seemingly outdated costs. To this, I have one response: agile IT. As never before, IT is aligning itself with agile development, by supporting a software lifecycle that includes operational feedback integrated with development, and by encouraging automation of functions that provides a basis for rapid response and identification of architectural problems and opportunities at the administrator level. As my studies have shown, these plus the increasingly agile nature of the software that IT makes available to the business translate into major cost-cutting and major benefits beyond what traditional IT approaches can deliver. And as for aligning itself with business strategy, IT is well aware of Big Data as a hot topic, hence the sudden and somewhat odd demand for Hadoop experts. No, whatever IT may have done in the past, it seems clear that it has upped its game.
OK, then, who does that leave? And yet, how can we blame the business types? Aren’t these the same folk who drove those increases in IT percentage of spending over the 1980s and 1990s? Aren’t these the most receptive listeners when we talk about the power of embedded analytics to improve business processes and the importance of analyzing the “customer of one”?
There’s Something Not Going On Here …
To understand why there might be cause for concern and, yes, for blame in business strategy – driven by the CEO, the CFO, and their staff – let’s look in very broad-brush terms at what has been going on, not just for the last five years, but for the last three decades. Here are a few of the highlights, as suggested by various studies:
1. Advances in productivity have been accruing 90% to the CEO – ½ in his income as CEO, and ½ in his increases in wealth as an investor. While this still represents a fairly small percentage of overall expense, it does unnecessarily increase the focus on cutting costs for all except the CEO.
2. Hedge funds that sometimes act as turnaround artists or “shadow banks” have taken a good 90% or so of the funds’ investment profits for themselves, and thus receive compensation not just in the tens of millions of dollars but, at the top, in billions of dollars, despite the fact that they deliver less to the investor than an index fund in most if not all cases. While it is difficult to see direct effects of this “fleecing of the rich” on corporate strategies, one significant effect is to increase the fleeced CEO’s focus on growing profits uber alles, to at least get some return from their investments – with the Googles of the world the few happy exceptions.
3. The present long-lasting recession/stagnation has effectively removed perhaps 10% of the workforce from work over a long period of time. This has the effect, since businesses often discriminate against the long-term underemployed, of creating a permanent gap between “potential” GNP and real GNP. To put it another way, even if the economy grows at a reasonable pace, it will still be much smaller it should be. That means smaller markets and, again, more relative emphasis on cost-cutting to achieve profit growth rather than growing revenues to grow profits.There are three concerns about this excessive focus on cost-cutting. The first, which probably is not serious right now but is far more troubling than five years ago, is that cost-cutting eventually runs out as a strategy if revenues continue to be flat (and, don’t forget, revenues are pretty flat for the bulk of businesses, hence the 1% growth in GNP over the first part of this year). The second concern is that this cost-cutting, applied economy-wide (as it seems to be doing), reinforces and cements smaller markets by eliminating the part of the market funded by the now underemployed. Ordinarily, recessions are too short for this to happen; but it seems to be happening now, as new jobs continue to make no dent in the workforce/working-age-population ratio.
The third concern, which I for one find the most troubling, is the possibility that reflexive cost-cutting becomes the answer to every situation, the reflex of the business. If that is true, it would suggest that businesses are blowing opportunities for savvy increases in computing technology spend because it’s all about cost-cutting, not strategic investment.
Blame or Not, What Might Business Strategists Do Better?
First, I would suggest that businesses set up a long-term plan and process for using analytics to better understand and improve the relationship with the customer. This means acquiring data virtualization software and the like, to allow aggressive searching out and combination of all the new customer information constantly being created. It also means buying the new infrastructure tools (database and information architecture) that can scale to handle aggregation of social-media data on the Web and in-house customer-experience data.
Second, I would argue (not that I expect many businesses to listen) that in order to grow revenues as well as profits (and probably grow profits faster), business types need to acquire and foster use of agile tools and processes – such as agile marketing, with its emphasis on data-driven understanding of the customer and prospect rather than the anecdotal, top-down opinion that has been all too common in the past. As I noted in a recent blog post, an agile business is a possibility, if the CEO and his lieutenants really commit to it – and it typically means not only the CEO using a Scrum-type planning process, but also constant modification and constant feedback up and down the organization about plans. I should also note that an agile process specifically builds in slack for learning and review, and yet (according to my studies) it produces much better cost-saving and profit results than a “cram as much work as possible in, be as cost-efficient as possible” approach, for the CEO as well as the developer.
And then there is the really controversial stuff. Sustainability efforts are, by and large, really underperforming, as a recent article in www.thinkprogress.com confirms my impression that gains in the US in carbon emissions are effectively coming from offshoring the problem. Businesses need to acquire effective global carbon-tracking software, and use it. Businesses need to join to push shared quality regulations that will move all towards new computer and software technology that is more productive, rather than clinging to the infrastructure of the past that in the long run costs more, as in the electrical/energy grid vs. software-coordinated regional combined solar/wind – and rather than enabling the block-all-regulation political excesses of the U.S. Chamber of Commerce and its ilk.
I’m not saying that all this is doable, or that the case for questioning the approach of the overall business to computing technology is clear. I am saying that it’s time we recognize the seriousness of the overall problem of which computing spend is a part, and we stop blaming the usual suspects. Five years is enough. Thirty years is enough. In the long run, a cost-cutting strategy is not enough – and the long run is beginning to arrive.