When people last week started reading my IBM eBook (available Friday in paperback from Amazon and most distributors — make Mrs. Cringely happy and send one to all your friends) the tales of IBM customer and employee woe were generally accepted as simple fact but some people had a hard time with my assertion that IBM analytics will probably not be successful (I said IBM is already too late to that party). One especially informed reader hit me pretty hard on the topic and I think our conversation is worth repeating here. He’s asked to remain anonymous but I assure you he’s in a position to know.
Reader: The only quibble I have is the point you made about the analytics opportunity, where you mentioned that only about one percent of IBM’s perspective customers will care about it. I respectfully (but wholeheartedly) disagree.
I attended the Gartner annual Supply Chain Executive Summit in Phoenic two weeks ago and there were two overwhelmingly common themes presented by the keynote speakers (Chief Supply Chain Officers at companies including Colgate-Palmolive, 3M, Schneider Electric, Caterpillar and Land-o-Lakes:
Talent Management (including skills, organizational structure and capabilities) in supply chain and operations will heavily shift toward data scientists and modelers; and
“analytics” is being driven by the blurring of the digital and physical supply chains.
Gartner SC analysts remarked that there are three profound impacts of the Internet of Everything:
1) Business processes will be more autonomous (not just “automated”); as such, multi-attribute advanced analytics, scenario modeling and event detection will be the only practical way to profitably manage ever-more complex supply chains;
2) Business models are increasingly relying on the monetization of data, which will further blur the lines between the physical and digital, as well as hardware, software and services; this has enormous SC implications;
3) Business “moments” – i.e., sudden, unplanned opportunities and disruptions such Amazon entering the spare parts delivery space and Apple competing with automotive OEMs for the dashboard user experience – will require the flattening of organizational silos to identify and exploit new ideas.
In short, I think IBM has a HUGE opportunity with analytics. Ironically, IBM’s Global Technology Outlook (GTO) published 5 years ago predicted the rise of the Internet of Everything with startling accuracy. But, like a former colleague of mine from Georgia frequently said, IBM’s response has been “like a pig looking at a wrist watch.”
Bob: My point was that by the time IBM has a real analytic product suite ready most customers will already have other suppliers. They’ll have an opportunity only if they can execute on it and for the past few years what they’ve mainly executed is BS. Yes, they can buy ahead of the wave but even that would require someone being willing to sell (there are better acquirers than IBM) and IBM then not screwing-up the acquisition by starving it or meddling. There are simply too many possible points of failure. And Watson? Watson isn’t a platform or even a technology as far as I can tell. They can’t just point Watson at analytics and create a cost-effective offering.
I’d love to be wrong but I’m probably not.
Reader: You are absolutely correct on all points. Watson’s budget, if the rumors I heard are true (and I knew a couple of people on the Jeopardy team so I didn’t doubt them) IBM spent north of $1 Billion to win that game. Marketing and Research shared the cost. For that kind of money, they’d better have won or even Palmisano might not have survived.
IBM does have Cognos (which is actually a suite of products) lots of data scientists (not just in Research but also in SWG) and most of the other bits they need. At this point, they are still in the game because there are no clear leaders yet and customers have more questions than answers. The Analytics team might also be one of the remaining few with the talent to go to market, but just barely, and the clock is ticking.
Bob: Let’s look at IBM and some typical business analytic use cases:
Talent Management
— Analytics in HR is already a well established business. There are many players and many services on the market already. IBM will be competing with established, mature, and experienced companies.
— Many analytics services have become essentially spam filters. An HR manager recently told me they got 2000 applications in an hour after posting a job opening. Almost all of them were from people who were completely unqualified for the position. People are so desperate for work, they’re applying for anything and everything. Those spam filters are throwing out a lot of good applications. Some people have found the best way to get past the first HR barrier is to copy and paste the job posting into their resume, then edit it to fit in. Colleges are telling their students to do this!
— Baseball is probably the best example of the use of talent management technology. Baseball’s system works because there are good measurements on most aspects of a players performance. The most successful teams are the ones that balance talent and cost. They don’t go after the best of the best, which are also ultra expensive. They look for the best combination of talent and value. The most successful teams still employ human input on the evaluation and selection of players.
— Baseball is one extreme where they have thousands of data points on each player. Business on the other hand has very few. To do a good job HR must augment its data collection on candidates.
— I’ve seen positions where the “system” is solely focused on degree, college, graduation date, and a narrow range of experience. If you’re hiring mindless drones, then this is probably a good system. If you’re hiring people you want to retain more than six months, the system is probably rejecting more good candidates than it is passing. Or someone has an age discrimination suit in their future.
— Do you remember the news reports of IBM hiring in India where people were filling out the applications for others?
Supply Chain
— Most of the major retailers and several other industries have been doing serious supply chain work for over 20 years. IBM is really, really late to this market.
— Let’s suppose IBM finds someone who’s been hiding under a rock for the last 10 years and really needs supply chain help. Let’s walk through the process…
+ you map out the current operation
+ you collect data on the current operation
+ you create computer models of the operation and run analysis against it
+ you find ways to improve it
+ you modify the current system, upgrade it, change processes, etc. That could include making big changes to your distribution centers, building new distribution systems, buying new fleets of trucks, etc.
+ you have to make big improvements in the information systems.
+ you have to train the organization on how to do their job better.
+ you have to assemble a new team to operate and manage the new system
+ for the next 5-10 years you must constantly monitor and continuously improve the system
+ you have to constantly revisit the models and run new business conditions through it, then optimize the system for that point in time
— How much of this can IBM do well?
— Supply chain is a long term, continuous improvement effort. IBM’s business model is sell, do something, get paid, leave. Under the context of “do something” IBM will stick to requirements that may or may not produce the desired results.
— If IBM’s supply chain expertise is so good — why does IBM have so many slow and inefficient internal processes?
Supply Chain and HR
— Let’s start with the assumption IBM is serious about doing supply chain optimizations and has a good HR analytics system.
— I happen to know someone with deep experience in the subject, the right academic credentials, etc. That person’s CV has been posted on IBM’s internal system in plain sight for the last 10 years. Industrial engineering degree, Purdue, graduate work, operations research, simulation. They haven’t called him yet.
— IBM is not looking for people with deep knowledge in an industry to provide the service. This is a great example of how IBM views its people as “resources.” If they can sell a service, someone, somewhere with no education or experience should be able to follow a “process” and perform the work.
Key points
— Companies have been doing this stuff for over a decade. They are many well established outfits doing this stuff with a record of producing results. IBM is coming into this market very late.
— The most successful companies are already doing this stuff.
— If you were one of the potential customers not yet doing this stuff — who would you pick to do the job? High priced IBM with no track record or one of a dozen companies who have been doing this well for a decade?
— It was Gartner that recommended the best way to do big data analytics was to hire a couple people, build your own system, and do it yourself.
Or am I wrong?
Reader: You’re preaching to the choir on the SC topic. That’s where I got my start at IBM. When IBM acquired PwC, they got a fully-dressed SCM practice that could tackle everything from strategy through each function (Plan, Source, Make, Deliver, Return/Customer Service, Product Lifecycle Mgt, Org and Talent, Technology, etc.). So, IBM’s certainly not late to the party, but their entire model, built on billable hours, has devolved into a “butts-in-seats” service rather than the transformative capability it should be. Deciding to completely cut training out of their consulting organization and limit their mobility across clients and projects has further hamstrung their value proposition.
One of the major selling features of IBM’s SC consulting practice was that IBM had one of the highest-performing supply chains in the world (AMR Research once ranked them as high as #3). The year-over-year, incremental improvements in Cost-to-Serve were impressive by any measure. Clients wanted some of that capability for themselves, and IBM took it to the bank. The “We Practice What We Preach” method of sales and marketing was extremely successful at winning SC business — for awhile. After the mid-2000s, it really became a shell game, as you’ve written about many times now.
Believe it or not … Most companies are still in their analytics infancy. Yes, there are pockets of excellence and some companies (Intel comes to mind, as do a few CPG companies like P&G and PepsiCo) are really, really, good at it. One of these days, have a conversation with Mark Wilkinson at Intel. He’ll blow your mind. However, the majority are are not yet grasping the future of analytics: prescriptive solutions to complex events.
But just as well, you could speak with Paul Giangarra, a Distinguished Engineer at IBM SWG. He has been building analytics engines and applications since the 1970s and is probably the smartest person I’ve ever met (actually, he’s a living, breathing, facsimile of Big Bang Theory’s Sheldon Cooper). At least five years ago he was building proof of concepts for IBM clients using complex event processing and advanced analytics applications that IBM was selling as shrink-wrapped software. He actually built (I saw it myself) — in a single box — a space shuttle launch sequence controller as a demo for United Space Alliance at the Kennedy Space Center. It took him and one person doing software configuration (remember, this was shrink-wrap software and stock hardware they were using; no Watson tomfoolery) 90 days to complete the project. I’m an aerospace engineer and these two guys duplicated in three months what it took an army of my fellow propeller heads decades to create. Needless to say, it was more than a bit humbling.
To your point about Gartner’s recommendations … Yes, they do recommend that companies build the teams to do this work themselves. There are several reasons, but one of the biggest is that this capability is essential to innovation and for some companies, their ability to remain competitive. It really would be the equivalent of the Praetorian Guard to let someone else do it.
So, no, I wouldn’t hire IBM, but neither would I hire any of the other big firms. I have good friends who have moved on to the Accentures, McKinseys and Bains of the world. Those companies aren’t really very different and they aren’t much happier. They’re certainly no richer.
Bob: I’d call this a draw. What do you think?
The end product of a serious analytics project is to make a step change improvement to one’s business, to start doing key things much better than before. From the customer’s perspective is IBM doing anything well these days? If IBM is so good at analytics, why are so many of its business floundering? If I would hire IBM would it get that ultra good “Sheldon Cooper” guy, or the Purdue person, or would I get what ever the next person was on the bench? Chances are I’d get the person from the bench. That person would follow the official IBM “process.” That person really wouldn’t understand the content or what makes a great product or service. (See I read your book.) Would I get the results I expected? Would the money I spent be wasted?
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Saying something over and over again doesn’t make it real or factual. In the end the results are more important than words. All I’ve heard from IBM are words. Show me some solid results.
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Another point to your argument. Credit card companies have very sophisticated fraud detection systems. I have been genuinely impressed how my bank has been protecting my accounts. These systems have been in place for years. Has IBM helped with any of them?
I suspect IBM’s analytics play will be just like its “cloud” play: all hot air and no substance. The “latch on to a buzzword and ride it into every sales meeting” strategy seems to be the only one IBM has any more.
Ordinarily I put my actual name on things but I’m going to take a bit of a swipe at a guy who won’t fight back I don’t imagine — Paul Giangarra used to come to a very big, very public, and very well attended marketing event that typically drew people from all over the world, for more than 10 days, that I helped put on with a large crew of fellow IBMers, for quite a few years. Let’s just say, after 5pm things got a little weird. And before 5pm, well… let’s put it this way, he was someone’s fair haired boy which was why he was there, not because of any great well spring of inspiration or insight he was dispensing. I’d be looking for another guru based on my experience. YMMV of course.
We’ll take your comment as seriously as we take all anonymous internet comments.
“The trouble with posts on the Internet is that you can never know if they are genuine.” –Abraham Lincoln
Is that true, or was it just made up on the spot like the other 78.4% of internet content?
Yes.
“The trouble with posts on the Internet is that you can never know if they are genuine.” –Abraham Lincoln”
–Michel Scott
At an IBM Marketing event, is there ever a well spring of inspirational information?
At any Marketing event, is there ever a well spring of inspirational information?
Good points on both sides of the argument. Analytics in commercial insurance is a growing field. I should know as we just dove in. We already had Cognos, but chose SAS for analytics/modeling work.
SAS is trouble for IBM. Great culture, lower sales pressure and tenured employees. IBM was high pressure and their products didn’t feel as deep or mature.
IBM has been brutal to work with for Cognos. I read Bob’s book and thought he was spot on for the most part.
The saddest moment for me came when you got to the description of the Supply Chain analysis stuff, the idea that it is a long term relationship with the customer (in Marketing Automation, it is much the same: you work to commit to a long term relationship with your customer to help them develop trend data on their campaigns to be able to optimize – customers, prospects, members (for a non-profit like a PBS station) are the Supply in the supply chain in this metaphor).
Why was this sad? Because that’s the kind of relationship IBM *used* to have with its customers, both at the sales level and at the support level, to the point of having IBM employees on the customer sites to ensure uptime.
It may not have been *as* profitable as trying to dive into the PC world, or (in the short term), selling the hardware instead of getting into the older long-lease relationships, but it was the better, and would have put them in a far better space in this market than they are today.
In fact, a mere few years after IBM was selling everything, the world was discovering that *recurring revenue* is everything, and cloud hosting contracts are the key to recurring. IBM was finalizing the process of giving up its recurring revenue stream just as the world was discovering that having a baseline revenue that never went away is *the* key to long term survival.
Everybody discovered IBM’s best business model just as IBM was trying to forget it ever existed.
So, Bob: are you a Moneyball proponent? I ask only because the differences between Moneyball and traditional talent evaluation in baseball is the essence of the Moneyball theory itself. For those unfamiliar with the theory, some very smart and dedicated baseball aficionados who were, importantly, not part of the then-current baseball management, realized that traditional ways of measuring a player’s value were not finding the best talent. Resistance to the Moneyball theory is still very high, because most scouts and managers were brought up evaluating baseball talent the “old school” way. But success seems to be convincing owners that adopting the new analytics of Moneyball is the way to win a World Series, or at least to make the most of your money, even if you can’t compete with the Yankees (blech!)
What I’m also implying here is that while a single baseball game has a beginning and an end, the process of managing has no beginning, no middle and no end. It is always developing. You know the old saying, “Make something idiot-proof, and they’ll make a better idiot.” IBM could still come back if it developed a really good process. Based on what I’ve read of your book and articles over the years, that seems highly unlikely since bureaucracy is always the “killer app” that kills innovation. Cf, Nucor Corporation, which is run from a trailer and has only about 4 layers of management between the CEO and the guy pouring the steel. Every company develops bureaucracy, which is the reason they are always eaten by a leaner, hungrier and younger competitor, unless they bureaucracy manages to engage the services of the government to give it a functional or even a real monopoly. That’s the danger for the economy: stagnation by bureaucrats, government or otherwise.
Moneyball theory never won a pennant.
The original Moneyball team, which coincidentally is close to Bob’s home has not won a pennant since adopting the system. That is true. They have however won several division titles and made it into the playoffs. Other teams have adopted the system and have won both the pennant and world series. My fear is IBM who’s nickname is Big Blue has become like that baseball team from Chicago who also wears blue. That Chicago team is in the third largest market in the USA and makes a lot of money. However on closer inspection you will see their ballpark is falling apart and is in need of a long overdue overhaul. They consistently make bad management decisions which hurt the performance of the team. Coincidentally IBM’s CEO is from Chicago and attended Northwestern, just up the road from Wrigleyville.
The Red Sox used the same analytical approach to win two world series. They just had more money than Oakland.
Super Moneyball!!!!
That actually is not what Moneyball is about, though it is what the book and movie are about. The movie makes one of the good guys out to be a bad guy, because they needed a foil for Brad Pitt to work against. In reality the guy is working for Beane again, and he was always well liked. The book reads like a joke now, and even somewhat then. Scott Hatteberg is the perfect batter? Totally downplayed the impact of having three very good pitchers. Those players who were listed as great coups for Oakland’s secret Moneyball approach ended up being mostly busts. There is a lot more to Oakland A’s than valuing OBP, although even now, other teams that have adopted similar things still trail Oakland in OPB.
Now that I think about it, IBM is adopting a Moneyball approach by paying less for offshore developers, who aren’t as good as the real thing but are a better value for the money.
Still involved, so wise to be faceless! Read Bob’s book. Good analysis. Likewise this article. Such top level skill as exists is very limited and near impossible to access, even when you know your way around.
Bottom line – IBM is unmanageable because it is too big and too centralized. Choking on its own matrix. The plan, decades ago, to break it up into autonomous units was the right thing to do, some would have died, some would have soared. Gerstner saved it temporarily by doing the wrong thing (and got very rich, setting that pattern for all who have followed!).
BTW – it was Gerstener, in his book, who pointed out the foolishness of being a slave to Wall Street. How ironic is that!
I’m skeptical of analytics models in supply chain areas. In my experience, models end up costing their users more than they ever make in profits, simply because you can’t model all the externalities. Just like Wall Street (LTCM and so forth), the models make money until they break in a spectacular and catastrophic manner.
That’s not to say you shouldn’t do your best to plan, make, and do all the other SCOR activities. But tax regimes change in Southeast Asia, shipping rates change, labor condition scandals, derailments shut down trunk lines, and you’re still on the phone to truckers paying spot rates to get your containers off the dock. Look at the fortunes of the SCM software companies: i2, JDAS, Manhattan, … all of them looking for partners. Supply chains require constant human oversight. It’s great to have your analytic software predict that it will eliminate bullwhips, optimize sourcing decisions, and all that other great stuff, but few companies go back and check how much reality matched to their original predictions.
Case in point… in the late 90’s my ocean liner company had a pretty good yield management tool. We ran the numbers on buying new vessels in one of our Pacific strings. One of the assumptions we made was that Yokohama would dredge its port so that the new and bigger ships could get in and out – we even had a signed contract with the port. $300 million of ships eventually got delivered, but surprise… Yokohama wasn’t dredged and our ships couldn’t call at the port to pick up all the lucrative auto parts we’d expected to help pay for those ships.
And looking to the future (5+ years) 3D printing will have an enormous impact. How many of the items in your typical Wal-Mart or Target could be made at home? Even if the ability to print replacement Mr. Coffee carafes or flatware is 10 years away, that’s well within the strategic timeline of today’s capital investment decisions. Would you invest in new warehouse facilities or transport fleets, or buy options on someone else’s under those circumstances? Yes, 3D printing seems like a bogus fad today, but I know of at least one air freight company that is heavily investing in analysis of 3D printing to see how it’s going to shape their business.
There will always be a market for analytics because people should try to base their investment decisions on quantitative factors… but companies shouldn’t (and won’t) bet the farm on those tools. Because of its scale IBM needs companies to bet the farm, and they’ll be disappointed.
Dave’s comment proves the truth of Bob’s assertion that IBM will fail in analytics, where we define ‘analytics’ here as being the fancy predictive stuff, not just cross-tabulations and spreadsheets or dashboards provided by the likes of Cognos. Dave described how his organisation already had Cognos and still chose SAS over the IBM equivalent. The IBM equivalent should have come from a company IBM absorbed a few years ago called SPSS (thus the origins of my handle …). SPSS provided directly comparable predictive analytics to SAS and competed head-to-head in the same markets. SPSS was the arch-rival of SAS for decades (SPSS was founded in the 60’s and SAS in the mid-70’s – they were age-old rivals in tech terms). SPSS’s predictive analytics were so good they continued to sell well to their core market years after they were absorbed by IBM. Further evidence of SPSS’s strength came from IBM retiring it’s ‘Intelligent Miner’ data mining suite soon after acquiring SPSS in favour of SPSS’s Clementine data mining suite. [BTW: Intelligent Miner was a rip-off of SAS’s Enterprise Miner which in turn was a rip-off of Clementine.] SPSS had (and still has from my last peek a few months ago) a better interface than SAS and equivalent functionality for a fraction of the price – a fact I exploited to an early retirement :-). At the time, SPSS’s weakness versus SAS was that it did not vertically integrate into datawarehousing and consequently could be outflanked by the well-prepared SAS sales rep. This datawarehousing vertical integration is what IBM should have been able to provide, as well as vertical integration in the other direction with the Cognos business reporting tool. And yet IBM’s sales people obviously could not communicate this to Dave’s company. If IBM’s people cannot communicate a simple message like this in the situation described by Dave, IBM’s chances of winning the predictive analytics race are (in the words of the SPSS-folks) … statistically insignificant.
This is a perfect example of how things work in IBM. IBM has a check box mentality. Do we have a predictive analysis tool like SAS? Check. Do we have a data warehouse like SAS? Check. Do we have reporting tools like SAS? Check. Should they all be integrated and work seamlessly together like SAS? To IBM that doesn’t matter. It wasn’t on their checklist.
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Quoting Steve Jobs from Bob’s book:
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“So the people who can make the company more successful are in sales and marketing and they end up running the companies. And the product people get driven out of decision-making forums. And the companies forget what it means to make great products. Sort of the product sensibility and the product genius that brought them to that monopolistic position gets rotted out by people running these companies who have no conception of a good product versus a bad product… They really have no feeling in their hearts usually about wanting to help customers.”
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Consider also how analytic is changing.
SAP with HANA and Oracle with Exadata are proposing in-memory databases, where the distinction between transactional and analytic are no longer valid (OLTP vs OLAP using the classic data warehouse’s theory).
In a nutshell, they same server holding the ERP (or SCM, or HR or other tools) has built in analytic capabilities, and it works pretty well.
You don’t need anymore a separate Cognos server, it will come integrated with your ERP.
IBMs problems come down to one thing . . . how do you standardize and replicate, even commoditize, the value that a good team of engineers bring to a problem space? Steve Jobs would have said you can’t. Keep hiring the best people, weed out the ones who can’t keep up, and throw interesting problems at them, and see what they produce. IBM anwer is process, and it’s true of the Accentures, McKinseys and Bains of the world as well. The lifecycle of developing and tuning a process may be too long for this approach to work in a rapidly changing environment. For some problems, requiring creativity, it may not work at all. But a lot of business problems are very similar, even across industries. Cookie cutter analytics may actually work. Not in every case, but in enough of them, and with great ROIs to sustain IBM.
Sure do it yourself because no one is doing it right, but someone will get it right and since your business problems are not really that different from other people’s business problems, analytics can be commoditized. I’m sure of it.
I’m not sure I agree. IBM has big problems, but the very significant differences between between problem spaces at Apple and IBM to me says that Steve Jobs’ observations and experiences may not be as relevant as you suggest.
Apple only sells a small number of products and is very careful to restrict their interoperability specifically to control how well they perform. As a company they’ve always been unafraid to completely drop a feature rather than provide a bad experience or get involved in messy support situations. IBM makes and sells some hardware too, but much more of their future is tied up in their services practice, which is less “controllable” (for lack of a better word.) Jobs could choose to set up a small team of elite engineers to build a super product in something of a vacuum. But the services market is far larger (more IBM engagements to staff than Apple product teams), more labor-intensive in general (broader skill sets, round the clock responsibilities, etc), and you don’t have nearly the same degree of freedom to say things like “Flash is hard to do well, hard to control, and so we just won’t do it.”
I think the many companies in the services market do what you suggest: lots of project and deliverable templates for various engagement types, canned analytics to use as jumping off points, etc. But if you’re a large consulting firm trying to get more efficient, one of the biggest risks is being seen by your customers as too standardized, not taking my contract seriously, merely dispensing templates and cashing checks, etc. “Commoditize” can be a bad word in the consulting business.
Process IS the product at these big consultancies, and the process is roughly:
-define the scope of the work: “I don’t know anything about your business yet, but you are 25% overstaffed.”
-get paid.
-enlarge the scope of work
-get paid
-enlarge the scope of work
-get paid
-rinse and repeat until the client realizes there is no product in sight and cancels the project
-get paid cancellation charges
I walked into one of these dances after about $15 Million spent on “scoping”, looked around and went to the senior executive who had asked me to evaluate progress. I told him it was $1.5 Million a month, how many months did he want? He said it couldn’t be that bad, and assigned me to see it through. Somebody finally convinced him to cancel after 30 months and $60 Million, which I learned was peanuts to these asshats.
Once senior executives have taken the bait it is very hard to admit it was a mistake.
Tough to judge. The first part of reader’s comments just looks like a supply of buzzwords trying to make a sale.
On the other hand, having read Cringely for a few years, I know he tends to go overboard into ranting towards his pet causes. His describing Microsoft’s Nokia acquisition as money laundering is one example. When asked to explain it, it was clear he was way out of his league.
Reading further, the reader certainly looks more credible as he is conceding Cringely points, a good sign of someone who is not merely advocating. Also Bob gets credit for running the post. In the end it looks like they are mostly in agreement.
I’d agree that it’s a draw. It’s good to see such a well informed opinion as counter point. (I trust Bob ergo I trust Bob’s vetting rather than just someone’s ability to sign up for the blog)
You said,
“– IBM is not looking for people with deep knowledge in an industry to provide the service. This is a great example of how IBM views its people as “resources.” If they can sell a service, someone, somewhere with no education or experience should be able to follow a “process” and perform the work. ”
The financial institution (International, US Based) that I worked at for nearly a decade hired their CO’s (CEO, CIO, CFO) like this while I was there. We had more than 5 of each during that time….
We had a need for a VB programmer (VB had been out less than 1 year) and HR required us to post it as ‘needing 3+ years of VB programming experience’. Fought against that for months but all the senior execs in our area could not see an issue with that. Those were all the ones without ANY tech background (some had Fine Arts degrees, one had Zoology if I recall correctly).
That was back in the 90’s – if HR has the right ear, and if most of HR is clueless, they can bring an IT group to its knees faster than any revival tent meeting to date…
In the time I was there, we had more than 3 complete staff turnovers (in less than 9 years) – every time we got a new top level CO position filled, we got new hardware and software vendors.
One CIo was brazen enough to copy (what he thought) was the only version of a business proposal, replace the submitting company’s name, logo and contact info with his favorite vendor. He would have gotten it approved if not for the manager I was under at the time – she confronted him with her copy and let him know there were other copies in the organization that she could call upon if he did not withdraw his vendor. He did withdraw and left to join THAT organization within a month…..
FYI – It was not IBM, though it could have been….
I think Bob and the reader are largely in agreement. One says there’s an opportunity for IBM, and the other is very skeptical that they’ll succeed. I agree with both in general, with the caveat that it’s going to be a long, long time before *anyone* does good work handling the analytics for this new Internet Of Things That’ll Be Tracked Beyond Popular Expectations, Frequently Hacked And Eventually Commoditized.
IBM is as qualified to grab some of this new business as anyone. But as far as being the ones to figure out the model that works, get some high-visibility customers working, set the industry standards, and deliver the somewhat shink-wrapped software to the world, I don’t see them anywhere near the front of the parade.
Take this IBM whitepaper with a pinch of salt then …
http://tdwi.org/whitepapers/2014/02/analytics-the-key-to-unlocking-the-intelligence-in-data
Bob, what do you think of the elevation of Lisa Su to the office of COO, and the heir apparent to the CEO, at AMD?
Also, what do you think about the possibility of Global Foundries taking on the IBM chip portfolio?
Thanks!
I suspect that GloFo will buy parts of the IBM chip business.
https://www.poughkeepsiejournal.com/story/news/2014/06/30/word-expected-ibm-deal/11812553/
Bob, I wonder if IBM could use their analytics to improve their strategic planning?
🙂
“Eating their own dog food”, so to speak?
I found 320 meanings for “SC” here: https://www.acronymfinder.com/SC.html . Does anyone know which one Bob and Reader are talking about?
Supply Chain: https://www.thefreedictionary.com/Supply+Chain
I think the critical point from the exchange is the analytics market is nowhere near as mature as I think “Bob” thinks, rather the “Reader” has it right here as far as that goes. A lot of it is the practice of analytics, not the tools; I suspect the tools really are better than we tend to believe and we fail to properly capitalize. But the biggest issue, and it is certainly true in HR Analytics, especially recruiting, is that these tools aren’t (yet) really helping us ask the right questions. And most businesses don’t want to put the money and effort into the hard work of determining the “right question,” hoping instead for a silver bullet from some combination of third party services and software.
I don’t at all have an opinion on whether IBM can make it here, though I think the opportunity in general is there.
Bob, I agree with your assessment. As an example, HANA is a very appealing choice for companies running SAP ERP. To use any other solution requires the user to believe there is a huge benefit for choosing a separate Analytics solution which is unlikely. SAP is the world’s most widely used ERP solution for major corporates. Equally Oracle are working hard to provide the easiest low risk option for their ERP users. Once you remove Oracle and SAP there is not a lot of large corporate customers left.
On the Watson situation it is my understanding that delivering Watson to regular customers requires substantial numbers of highly skilled people. This is difficult to replicate and expensive. Unless IBM can find a way to automate the process of building the data store required that Watson analyses (possible) and the decision algorithms (doubtful) it is unlikely that they will grow this business quickly enough to capitalize on their first mover advantage.
I’d like to buy Paul Giangarra a sandwich and just talk for a while. IBM seems a lot less interesting than he.