So what exactly should IBM do, and have done?

Now that IBM has ended its revenue losing streak, we’re ready to stick a halo on it:

There is no doubt, though, that there are signs of progress at IBM, which would not comment on its financial picture before the release of the earning report. So much attention is focused on the company’s top line because revenue is the broadest measure of the headway IBM is making in a difficult transformation toward cloud computing, data handling and A.I. offerings for corporate customers.

The new businesses — “strategic imperatives,” IBM calls them — now account for 45 percent of the company’s revenue. And though it still has a ways to go, IBM has steadily built up those operations — and gained converts.

Over all those quarters, there hasn’t been that much good analysis of “what went wrong” at IBM in so much as I haven’t really read much about what IBM should have been doing. What did we expect from them? What should they be doing now and in the future? I don’t know the answers, but I’m damn curious.

“State your deal.”

Since the mid-2000’s, all tech companies have been shit on for not getting to and dominating public cloud faster (there are exceptions like Adobe that get lost in the splurty noise of said shitting on). Huge changes have happened at companies HP/HPE and Dell/EMC/VMware (where I work happily at Pivotal, thank you very much), and you can see Oracle quarterly dance-adapting to the new realities of enterprise IT spending.

For the past 8 or 10 years I’ve had a rocky handle on what it is that IBM sell exactly, and in recent years their marketing around it has been fuzzy.  Try to answer the question “so what is it, exactly, that IBM sells?” A good companion is, “why do customers choose IBM over other options?”

You can’t say “solutions” or “digital transformation.” (I’m aware of some black kettle over here, but I and any Pivotal person could tell you exactly the SKUs, tools, and consulting we sell, probably on an index card). I’m pretty sure some people in IBM know, but the press certainly doesn’t know how the fuck to answer that question (with some exception at The Register and from TPM, grand sage of all IBM coverage).

I’ve been a life-long follower of IBM: my dad worked at the Austin campus, it was a major focus at RedMonk, and, you know, just being in the enterprise tech industry gets your face placed facing Armonk frequently. I feel like I know the company pretty well and have enough of an unnatural fascination to put up with spelunking through them when I get the chance; IBMers seem pleasantly bewildered when the first thing I ask them to do is explain the current IBM hierarchy and brand structure.

But I couldn’t really explain what their deal is now. I mean, I get it: enterprise outsourcing, BPaaS (or did they sell all that off?), some enterprise private cloud and the left over public cloud stuff, mainframe, a bunch of branded middleware (MQ, WebSphere, DB2, etc.) that they seem forbidden to mention by name, and “Watson.”

There are clear products & services (right?)

 

When I’ve been involved in competitive situations with IBM over the years, what they’re selling is very, very straight forward: outsourcing, software, and a sense of dependability. But the way they’re talked about in the press is all buzzwordy weirdness. I’m sure blockchain and AI could be a big deal, but their on and off success at doing something everyday, practical with it is weird.

Or, it could just be the difficulty of covering it, explaining it, productizing, and then marketing it. “Enterprise solutions” often amounts to individually customized strategy, programs, and implementations for companies (as it should, most of the time), so you can’t really wrap a clear-cut SKU around that. It’s probably equally hard to explain it to financial analysts.

So, what’s their deal?

Cumulative capex spend by Google, Amazon, and Microsoft since 2001.
How much is that public cloud in the window?

Anyhow, I don’t come here to whatnot IBM (genuinely, I’ve always liked the company and still hope they figure it out), but more out of actual curiosity to hear what they should have been doing and what they should do now. Here’s some options:

  1. The first option is always “stay on target, stay on target,” which is to say we just need to be patient and they’ll actually become some sort of “the business of AI/ML, blockchain, and the same old, useful stuff of improving how companies run IT.” I mean, sure. In that case, going private is probably a good idea. The coda to this is always “things are actually fine, so shut the fuck up with your negativity. Don’t kill my vibe!” And if this it true, IBM just needs some new comms/PR strategies and programs.
  2. You could say they should have done public cloud better and (like all the other incumbent tech companies except Microsoft), just ate it. What people leave out of this argument is that they would have had to spend billions (and billions) of dollars to build that up over the past 10 years. Talk about a string of revenue loosing quarters.
  3. As I’m fiddling around with, they could just explain themselves better.
  4. They should have gotten into actual enterprise applications, SaaS. Done something like bought Salesforce, merged with SAP, who knows. IBM people hated it when you suggested this.
  5. The always ambiguous “management sucks.” Another dumb answer that has to be backed up not with missed opportunities and failures (like public cloud), but also proving that IBM could have been successful there in the first place (e.g., with public cloud, would Wall Street have put up with them loosing billions for years to build up a cloud?)

I’m sure there’s other options. Thinking through all this would be illustrative of how the technology industry works (and not the so called tech industry, the real tech industry).

(Obviously, I’m in a weird position working at Pivotal who sells against IBM frequently. So, feel free to dismiss all this if you’re thinking that, now that you’ve read this swill, you need to go put on a new tin-foil hat because your current one is getting a tad ripe.)

Link: WSO2: Our 2017 Results and 2018 Plan

2% profit margin is much better than no- or negative-percent.

“In 2017, we will exit our Annualized Recurring Revenue (ARR) between $24.5 — $25.5M, a growth of 52%, up from 46% growth the previous year. Our gross margin for the recurring business is 88%, and will increase in coming years. In 2017, we will turn our first profit with $603K EBITDA and generate $2.7M cash from operations.”
Original source: WSO2: Our 2017 Results and 2018 Plan

Link: The critics are wrong about AWS’s open source approach

“Is AWS selfish? Sure. Does that selfishness translate into greater developer productivity with machine learning and other enterprise software in the process? Yes. And it’s not merely a convenient byproduct: It’s the whole reason AWS exists.”
Original source: The critics are wrong about AWS’s open source approach

Link: Meltdown and Spectre underscore the ongoing need for infrastructure automation

“In the Cloud Foundry scenario, these are embodied by BOSH to automate the infrastructure resource, namely VMs, container clusters, virtual storage and networks, configuration and deployment and Concourse for the development pipeline. Together, these enable organizations to rapidly and consistently patch all applications using the PaaS environment. Together, these enable organizations to rapidly and consistently patch all applications using the PaaS environment.”
Original source: Meltdown and Spectre underscore the ongoing need for infrastructure automation

Link: Amazon narrows HQ2 search to 20 cities, moving to next phase in contest for $5B economic prize

“Toronto, Columbus, Indianapolis, Chicago, Denver, Nashville, Los Angeles, Dallas, Austin, Boston, New York City, Newark, Pittsburgh, Philadelphia, Montgomery County, Washington, D.C., Raleigh, Northern Virginia, Atlanta, and Miami.”
Original source: Amazon narrows HQ2 search to 20 cities, moving to next phase in contest for $5B economic prize

Link: Google’s AutoML lets you train custom machine learning models without having to code

“The basic idea here, Google says, is to allow virtually anybody to bring their images, upload them (and import their tags or create them in the app) and then have Google’s systems automatically create a customer machine learning model for them. The company says that Disney, for example, has used this system to make the search feature in its online store more robust because it can now find all the products that feature a likeness of Lightning McQueen and not just those where your favorite talking race car was tagged in the text description.”
Original source: Google’s AutoML lets you train custom machine learning models without having to code

Link: GDPR compliance – here are the 14 things you actually need to do

Exciting new audit needs ahead, hoss: “Organisations should review their IT systems and procedures to check they comply with GDPR requirements for privacy by design, ensuring only the minimum amount of personal data necessary is processed. Privacy Impact Assessments (PIAs) should be completed when using new technologies and the data processing is likely to result in a high risk to individuals.”
Original source: GDPR compliance – here are the 14 things you actually need to do