Category Archives: Technology

Headline from the Land of D’oh: Technology is Closing — and Widening — the Gap

A recent issue of Apparel leads with the headline that Technology is Closing — and Widening — the Gap. Needless to say, this is a headline that I had to read twice to believe I was reading it. It then goes on to say that mobile can be viewed as both a great threat and a great opportunity. Really? Smartphones create interaction much more dynamic than it was back in the days when customers were restricted to flipping through print catalogs. Who’d a thunk it? Mobile also poses a threat allowing customers to hop on Amazon.com or any number of other sites for a quick cost or brand comparison. A browser works on more than one site? Wow!

But seriously, this article is ridiculous. It’s common sense drivel for anyone with half a brain and a memory that remembers more than 10 years of history. (What am I saying? It’s only the last quarter that matters! Thank you Wall Street MBAs for ruining not only innovation but the importance of history. But that’s another rant.) First of all:

Mobile may be new, but it’s just another technology.
It’s going to go through the growing pains of every new technology that came before. There were growing pains with the Web. There were growing pains with television. There were growing pains with radio. And if you study your history (as one of my blogging counterparts will gladly point out as important), you’ll realize that each had the same growing pains, opportunities, and threats. The only difference is that with each generation of new technology, the time frames become more and more compressed. Right now, most minitrends last about five years. In the future, some may only last five months.

The difference between the rich and the poor is $$$.
How much $$$ you have in business depends on market share. It’s a knowledge economy, and how much knowledge you have depends on how fast you can distill it from information. How much information you have depends on how much data you have and how fast you can extract information from it. And both of these steps depend on technology. So, as a corollary, how much technology you have, or have access to, directly affects how rich or how poor you are.

Any change in your situation relative to someone else either narrows or widens the gap.
So if your technology changes, or your competitors’ technology changes, then the gap between you and your competition is going to change as well. D’oh!

Tell me something useful — like how to take advantage of this technology as a retailer. Otherwise, stop wasting my pixels and my time.

What’s the Big Idea?

Seriously, what it is? Inquiring (not enquiring) minds want to know. Because, as far as many of us can tell, there aren’t any big ideas any more. As Neal Gabler said in the New York Times article on the elusive big idea, we live in a society that no longer thinks big. And that’s bad. Why? In many fields of technology, there have been no big ideas for decades. Sure, we see new and better devices every year and sure the iPad just came out, but, let’s face it, the iPad is a netbook with a touchscreen. A netbook is just a miniaturized laptop, and a laptop is just a miniaturized portable computer, and portable computers have been around for over 30 years. (Yes, you read that right, over thirty years, with the first portable computer manufactured in 1979.) And touch-screens have been around almost as long (with the first commercial touchscreen computer released back in 1983). Apple just took the technology to the next generation, while making sure it was easier to use than all of its competitors products. But, contrary to their marketing, there is no new “big idea” in the iPad.

The cloud? Well, I hate to burst your bubble (actually, not true, I love to burst that bubble), but the cloud is just a return to the fundamental concept of mainframe computing with dumb terminals — one big shared computer that services a whole bunch of users who are remote and don’t want, or need, to know how the big computer works. Except this time the big computer is a whole bunch of smaller computers networked together and, since the network is very big (and, in fact, global), the computers can reside anywhere. I could go on, but, even in computing theory, almost everything traces back fifteen to thirty years (or more).

I’m almost ready to agree with the author of a recent Forbes opinion article on the New York Times article that asked why did big ideas die when he said that we live in a post-idea society where people don’t think at all. With exceptions fewer and further between by the day, most people don’t think [deep] anymore.

Why is this? As Gabler says, we are living in an increasingly post-idea world — a world in which big, thought-provoking ideas that can’t instantly be monetized are of so little intrinsic value that fewer people are generating them and fewer outlets are disseminating them.

Who’s to blame? Gabler blames the usual suspects — the web, Twitter, and everything else that, instead of facilitating a lively intellectual life, instead drowns us in information. And while some of these suspects, like Twitter, are indeed a problem, the reality is that they are a symptom and not the root cause.

The problem lies with Wall Street and VCs. They’ve convinced the business world that nothing matters beyond the current quarter and any idea that can’t be brought to market overnight isn’t worth it. We did not come further in the last 100 years than in all of human history by only focussing on products that could get to market quickly. (We have to remember that the first cross-Atlantic transmission did not occur until 1902. This transmission, and all major computational and communication advances since, did not happen in a quarter. Most of the advancements took years of research and decades to perfect.) If you’re trying to change a market — to go from a Model-T to a Jaguar — that takes years, but VCs won’t support anything that can’t be done in more than a few months. As a result all we get are small incremental improvements, with significantly diminishing returns as time goes on, as no one is investing to take the big leap forward.

And, despite claims to the contrary, we haven’t really reinvented the organization (as telecommuting and outsourcing have been common for at least a couple of decades), education, health care, or ownership. We’ve simply redefined management and, in some cases, who foots the bill. I’d like to see some fundamentally new big ideas, but these are looking more unlikely by the day.

Risk Detection Can Not Be Automated

No matter how many impressive white papers, including this recent one on Uncovering Surprising Supplier Behaviours Creating Organizational Risk by Atlantic Software Technologies, Inc. (an IBM Software Value Plus Business Partner). This white-paper recommends automation of inbound data classification to expedite throughput because automation of this function enables the organization to redeploy up to 40 percent of staff while increasing processing throughput as much as threefold. This is important because one cannot assess the true business value of a supplier relationship unless one understands his or her own personal relationship with the supplier. And, in order to really get a handle on the quality of the relationship, an organization has to
be able to collect and analyze data points from the multiple impact points throughout [its] supply chain, both internally and externally, not just the ones that are easily visible and retrievable.

This is true. And, as the paper points out, if one does not understand the nature and quality of the relationship, one may never know that:

  • a supplier delay, just communicated to one of your employees, will impact multiple customers,
  • new international suppliers are being tapped to avoid single-sourcing risks, which might be causing quality risks, or
  • foreign nationals are handling sensitive information prohibited by export control laws (and this last risk could put an officer of the company behind bars).

But automating the processing and classification of unstructured data is not going to reduce risk. In reality, it’s going to increase risk. In a nutshell, here’s why.

Let’s say that external testing found lead paint on a children’s toy. If you’ve identified “lead paint” as a risk and set up a rule that alerts someone in Quality Control that a review is required, then you might feel you’ve mitigated the risk, as the document will come in, be sent to quality control, see that lead levels are present and well beyond tolerance, and tell Procurement to refuse the shipment. Problem solved. Right? Wrong!

What happens if the test was performed by an individual who speaks English as a second language, who trusts that all misspellings will be handled by Microsoft Word, and who mistypes “lead paint” as “led pant” in the report. Both are legal English words, and if you turn grammar checking off, Microsoft Word will not complain. Is the automated classifier going to catch this? Not likely. While you may remember to program in one or two misspellings, like “led paint”, or an abbreviation, like “ld pnt”, you are not going to come up with every possible misspelling, and you’re not going to want to because, if you include too many, you’ll get a lot of false positives (and misclassifications). If this is a product where tolerance is 0, and the test results are not acted on in time, not only could you be stuck with a multi-million dollar inventory that can’t be sold, but if a product makes it onto shelves, gets bought, and someone gets sick, that’s a lawsuit that could cost more than what it cost to develop and manufacture the first batch of products.

Now, there’s nothing wrong with deploying such technology to scan documents to look for documents of interest that should be reviewed, but it should not be the foundation of any risk management strategy. Good risk management entails identifying relevant risks and having a mechanism for anyone to report when a risk of interest may be materializing. Then someone knowledgeable about the risk reviews the situation and makes the call.

Public Procurement in 2020 — Are You On Track? Part IV

At the beginning of the week, we began our discussion of Hansen’s predictions for public procurement in 2020, which were offered as a 5-part series last month in response to the 5 predictions of Bob Lohfeld (of Lohfeld Consulting) that were published in Washington Technology in early July. We started with a discussion of the Government Market and then moved onto discussions of Workforce and Process. Today, we tackle the Technology predictions.

In his piece, Lohfeld prognosticated that:

(1) Virtual businesses will avoid brick-and-mortar costs, reducing operations costs and increasing their competitive edge. (2) Mainstream companies will exist in virtual space with no physical offices. (3) Cloud computing will be accepted as the norm, IT security protection will be expected, and IT infrastructure will be designed for virtual workforces. (4) Both contractor and government workforces will telecommute, and geographic boundaries will diminish as virtual meetings replace trips to personal offices.

To this, Hansen quickly responded that once again, the above prognostication says a great deal without actually providing any meaningful insight or substance as it reflects broad generalizations without getting into the mechanics in terms of practical application.

SI has to agree. Why? Let’s review the prognostication sentence by sentence. Virtual businesses are already avoiding brick-and-mortar costs, just as they have been since the mid-nineties and the beginning of the e-Commerce and dot-com boom. Not only can we consider a number of virtual businesses as mainstream in the niches they serve, but many companies, especially in consulting and IT, have been aggressively moving towards virtualization since broadband penetration reached the point that real-time video conference was an affordable reality for a majority of their workforce. Even in our space, many of the office locations of your global solution providers are shared business centers or home offices of key personnel. Since one can define “cloud” any way one wants to, as no one knows what “cloud” really is, we can already say that “cloud” is the norm. Furthermore, IT security has been expected by anyone with any technical savvy for a decade and IT infrastructure has been designed for virtual workforces for the better part of the last decade. Finally, many government departments are already allowing their contractors who don’t interact with the public to telecommute, as this reduces their fixed overhead. With budget shortfalls expected to be the norm for the foreseeable future, and office space so expensive in ideal metropolitan locations, it’s obvious that the amount of telecommuting is going to increase and that most consulting organizations are going to strive to have all of their contractors work remote.

However, Hansen, who simply reprinted a post he wrote in 2007 on the emergence of the metaprise (that runs on a distributed synchronized supply chain platform that simultaneously links the unique operating attributes of all transactional stakeholders on a real-time basis), also failed to provide any useful insight. While the post did note that process and not technology is the driving force behind a successful e-procurement initiative, it was essentially a post on cost avoidance through advanced spend analysis (that included commodity-characteristic analyses) and the need for process and technology alignment to realize such cost avoidance.

the doctor has to say that he was disappointed with Hansen’s effort on this piece. While the doctor, who has been immersed in cutting edge technology on an almost daily basis since starting his Master’s research back in 1994, knows better than anyone the difficulty in predicting the technology landscape even three to five years out, he did expect a much better response to Lohfeld’s post and some solid predictions (or at least some more direct rebuttals). Unlike many bloggers and analysts in the space, who come from non-technical backgrounds and couldn’t cut a line of code if their life depended on it, Hansen actually has technology in his background and a pretty good understanding of what it can, and can’t do, as well as where it’s likely to go based on where it is now and where it’s been. And, more importantly, there’s no way he could have done any worse than Lohfeld!

So what will the Supply Chain technology landscape look like in 2020? Pretty much what it looks like today, actually. Until we see a quantum leap in computing (theory), it’s just going to be more of the same old, same old in a new package. The only difference is that it’s going to be faster and more powerful. Not only will optimization on even the largest global supply chain models be real-time (and power every real-time e-Negotiation with your supply base if the organization uses a leading platform from a leading provider), but analytics will be real-time across all organizational transactions. A couple of providers already have real-time optimization capability for models of moderate size (where changes are limited to price, volume, and “route” availability, for e.g.) and at least one provider has a spend analysis solution that allows an analyst to real-time drill on a spend cube of up to 10 Million transactions on a laptop. Expected improvements in bus speed, parallel processing, inline computation, and federation technology will soon allow real-time drilling on a spend cube of 1 Billion transactions. It’s only a matter of time before 1 Trillion transactions can be handled and data can be explored in real time. This will not only improve forecasting, but allow for a host of predictive analytics applications that can be used to update forecasts for global demand and market prices in real time.

Furthermore, as broadband penetration becomes almost universal and more modern standards are adopted for data interchange by supply management solution vendors, the metaprise will become a reality and end-to-end supply chain visibility will finally become a reality for the average Fortune 3000 company. However, what we won’t see are any entirely new applications or software capabilities that aren’t already being investigated. Since the tens are shaping up to be another decade without any quantum leaps in the computing world, and since the specialist enterprise space always lags the consumer space, which always lags fundamental research, even if a quantum leap is made in computing technology this decade, Supply Management still won’t see anything new for a while.