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.
1 comment:
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