The Importance of “Convergence” In Market and Industry Analysis

If You Get Technology “Convergence” Wrong, Nothing Else Matters

I came across this book during my most recent visit to the UBC Vancouver campus.  As good as I think this book is at focusing attention, in workbook style, on the importance of market and industry analysis in new venture due diligence, there is an issue that I think is not adequately addressed by any model or theory: not Porter, not STEEP or SWAT. Convergence is the issue.

We can imagine and even potentially envision a very cool business idea, but if the technology to achieve it is not ready, not sufficiently mature, the idea is Dead on Arrival (DOA).   I do not mean to pick on young entrepreneurs, but I reviewed a business concept last week that was a superb and compelling idea, but the technology necessary to achieve it simply was not there, either in terms of its capability or its price point. I am confident that it will be there in time, but it is not now.  As if to make my point, Apple announced that it was acquiring a company for $20 Million in the exact same technology area: indoor location tracking (no small feat).  At this point it is not clear that the acquired company has any extraordinary intellectual property or expertise, and the article primarily focused on the point that this “location identification” technology was “heating up.”  It looks like it may be a simple “aquihire.”   Global Positioning and geo tagging as in smart mobile phones, radio frequency identification technology (RFID), and inertial guidance are all currently used in various combinations by a host of competitors (too many) to achieve required levels of accuracy, immediacy and cost.  A local industrial RFID company has just closed its doors because it simply could not compete and make money.  The simple problem was that this company’s idea, as compelling as it was, could not achieve the necessary price point, or possibly would not even work.

So we have the problem of “convergence.”  Great idea but the technology simply is not ready….yet.

I have three personal case study examples of the problem of “convergence,” that every potential entrepreneur should study. I have to admit that I was a senior executive at all three of these Silicon Valley companies, one of which actually made it to the NASDAQ exchange.  All of them had the “convergence” problem.. Too early for the available technology.

1. Silicon Graphics.  Silicon Graphics was founded in the late 1980’s by a pre-eminent Stanford professor, Jim Clark, on the idea that 3D visualization of complex problems would become the next big wave in technology. As a minor side business, it also excelled at computer animation, a growing new market of interest to Steve Jobs and others. It is now obvious that Clark was onto something that has now finally become the Next Big Thing, but at that time, the available technology simply made it too difficult and too expensive. Silicon Graphics no longer exists. Silicon Graphics crown jewel was its enabling software code, the SGI Graphics Library. It does still exist in open form.

Read more:http://mayo615.com/2013/03/31/hans-rosling-makes-visual-sense-of-big-data-analytics/

2. iBEAM Broadcasting.  iBEAM was the precursor of YouTube, but too far ahead of its time.  the founder, Mike Bowles, a former MIT professor, envisioned streaming media across the Internet, but this was in 1999.  Intel, Fox Entertainment, Reuters, Bloomberg, Microsoft were all involved, some investing significant sums in the company. We tried mightily to make it happen for Mike, but there were technology convergence problems.  The Internet at that time simply did not have sufficient reliable broadband capability.  In 1999 the vast majority of Internet users still used a dial-up connection.  The company, with help from Microsoft and its other big pockets investors turned to satellite transmission, which is immensely expensive.  I did learn a lot about the satellite business. Great idea, way too early, and the company failed early.

3. P-Cube.  In 2001, I was approached by prominent friends at two downtown Palo Alto venture capital firms to consider joining an Israeli startup in which they had invested. The idea was wildly popular at the time….traffic policy management and so-called Internet traffic shaping.  I enthusiastically joined the new company and became its first U.S. based employee.  The compelling idea was simple, make money by charging for bandwidth. The background idea was to enable deep IP packet payload snooping to prioritize traffic, but also for its political potential. This is the technology that Dick Cheney employed after 9/11 to snoop all Internet traffic.  The only problem was that the technology was simply not yet ready.  The P-Cube Internet traffic switch was a 24 layer printed circuit board (hideously difficult to fabricate), with 5 IBM PowerPC chips, 1 Gig of onboard memory (at the time bleeding edge, but today laptops have more memory), a host of “application specific integrated circuits” (ASIC), and to top it off a proprietary software language to program the box.  In the end, P-Cube burned up $100 Million in venture capital, and I had great fun traveling the World selling it, but the box never worked, largely because the technology simply was not there..  P-Cube’s assets were bought by Cisco Systems and t0day such capability is built into the boxes of Cisco System, Juniper Networks and others.

The key takeaway lesson from this: do not underestimate the importance of technology convergence with a great idea.

The Importance of “Convergence” In Market and Industry Analysis

If You Get Technology “Convergence” Wrong, Nothing Else Matters

I came across this book during my most recent visit to the UBC Vancouver campus.  As good as I think this book is at focusing attention, in workbook style, on the importance of market and industry analysis in new venture due diligence, there is an issue that I think is not adequately addressed by any model or theory: not Porter, not STEEP or SWAT. Convergence is the issue.

We can imagine and even potentially envision a very cool business idea, but if the technology to achieve it is not ready, not sufficiently mature, the idea is Dead on Arrival (DOA).   I do not mean to pick on young entrepreneurs, but I reviewed a business concept last week that was a superb and compelling idea, but the technology necessary to achieve it simply was not there, either in terms of its capability or its price point. I am confident that it will be there in time, but it is not now.  As if to make my point, Apple announced that it was acquiring a company for $20 Million in the exact same technology area: indoor location tracking (no small feat).  At this point it is not clear that the acquired company has any extraordinary intellectual property or expertise, and the article primarily focused on the point that this “location identification” technology was “heating up.”  It looks like it may be a simple “aquihire.”   Global Positioning and geo tagging as in smart mobile phones, radio frequency identification technology (RFID), and inertial guidance are all currently used in various combinations by a host of competitors (too many) to achieve required levels of accuracy, immediacy and cost.  A local industrial RFID company has just closed its doors because it simply could not compete and make money.  The simple problem was that this company’s idea, as compelling as it was, could not achieve the necessary price point, or possibly would not even work.

So we have the problem of “convergence.”  Great idea but the technology simply is not ready….yet.

I have three personal case study examples of the problem of “convergence,” that every potential entrepreneur should study. I have to admit that I was a senior executive at all three of these Silicon Valley companies, one of which actually made it to the NASDAQ exchange.  All of them had the “convergence” problem.. Too early for the available technology.

1. Silicon Graphics.  Silicon Graphics was founded in the late 1980’s by a pre-eminent Stanford professor, Jim Clark, on the idea that 3D visualization of complex problems would become the next big wave in technology. As a minor side business, it also excelled at computer animation, a growing new market of interest to Steve Jobs and others. It is now obvious that Clark was onto something that has now finally become the Next Big Thing, but at that time, the available technology simply made it too difficult and too expensive. Silicon Graphics no longer exists. Silicon Graphics crown jewel was its enabling software code, the SGI Graphics Library. It does still exist in open form.

Read more:http://mayo615.com/2013/03/31/hans-rosling-makes-visual-sense-of-big-data-analytics/

2. iBEAM Broadcasting.  iBEAM was the precursor of YouTube, but too far ahead of its time.  the founder, Mike Bowles, a former MIT professor, envisioned streaming media across the Internet, but this was in 1999.  Intel, Fox Entertainment, Reuters, Bloomberg, Microsoft were all involved, some investing significant sums in the company. We tried mightily to make it happen for Mike, but there were technology convergence problems.  The Internet at that time simply did not have sufficient reliable broadband capability.  In 1999 the vast majority of Internet users still used a dial-up connection.  The company, with help from Microsoft and its other big pockets investors turned to satellite transmission, which is immensely expensive.  I did learn a lot about the satellite business. Great idea, way too early, and the company failed early.

3. P-Cube.  In 2001, I was approached by prominent friends at two downtown Palo Alto venture capital firms to consider joining an Israeli startup in which they had invested. The idea was wildly popular at the time….traffic policy management and so-called Internet traffic shaping.  I enthusiastically joined the new company and became its first U.S. based employee.  The compelling idea was simple, make money by charging for bandwidth. The background idea was to enable deep IP packet payload snooping to prioritize traffic, but also for its political potential. This is the technology that Dick Cheney employed after 9/11 to snoop all Internet traffic.  The only problem was that the technology was simply not yet ready.  The P-Cube Internet traffic switch was a 24 layer printed circuit board (hideously difficult to fabricate), with 5 IBM PowerPC chips, 1 Gig of onboard memory (at the time bleeding edge, but today laptops have more memory), a host of “application specific integrated circuits” (ASIC), and to top it off a proprietary software language to program the box.  In the end, P-Cube burned up $100 Million in venture capital, and I had great fun traveling the World selling it, but the box never worked, largely because the technology simply was not there..  P-Cube’s assets were bought by Cisco Systems and t0day such capability is built into the boxes of Cisco System, Juniper Networks and others.

The key takeaway lesson from this: do not underestimate the importance of technology convergence with a great idea.

Hans Rosling Makes Visual Sense of Big Data Analytics

I started this post to make a relative mundane point for UBC Management students about the importance of making their presentations easily understandable, particularly when they involve lots of numbers or spreadsheet data. But after mulling over the post for a few days, I realized that this is a much bigger story.

Further back in my career than I prefer to admit, I had the exceptional opportunity to work with the founders of Silicon Graphics, Jim Clark, (who later went on to start Netscape with Mark Andreeson), Mike Ramsay and Jim Barton (who later started TiVo, the original PVR company). The premise of SGI was making 3D visualization ubiquitous in engineering, complex simulation, and computer animation. As often happens with the convergence of technology and great ideas, SGI was well ahead of its time. Disney loved it but the big engineering customers were not over the moon.  The concept  of 3D visualization of complex data was compelling.  Extraordinary examples of SGI visualization of tornados, molecular modelling and animation can still be found on YouTube.  But the chip technology required to achieve it, MIPS RISC (reduced instruction set computing) microprocessors) at that time, was not ready for prime time. Both MIPS and SGI are now long gone, and only SGI’s graphics computing instruction set, known as OpenGL survives.  But the era of Big Data and Visual Analytics is just beginning to emerge into the mainstream, as the technology has fully caught up.  If you have not seen this TED Talk video by Hans Rosling, it is only 4 minutes long, but it explains where we are going with Big Data, and how interpreting Big Data visually is already making a major impact on our thinking.  I have also included a reblogged post from the HBR Network which I think you will find is related to this much bigger concept.

Hans Rosling: 200 Countries, 200 Years, 4 Minutes

Reblogged from the HBR Blog Network

When Presenting Your Data, Get to the Point Fast

by Nancy Duarte  |   9:00 AM March 28, 2013

Projecting your data on slides puts you at an immediate disadvantage: When you’re giving a presentation, people can’t pull the numbers in for a closer look or take as much time to examine them as they can with a report or a white paper. That’s why you need to direct their attention. What do you want people to get from your data? What’s the message you want them to take away.

Data slides aren’t really about the data. They’re about the meaning of the data. And it’s up to you to make that meaning clear before you click away. Otherwise, the audience won’t process — let alone buy — your argument.

Take this table, for instance:

It’s confusing — especially if you project it for five seconds and then move on. And even if you leave it up for five minutes while you talk, anyone who’s struggling to derive meaning from it won’t be paying much attention to what you have to say. They’ll be too busy squinting from their seats, trying to navigate all those heavy grid lines that give every single cell equal weight. It’s not at all clear where the eye should go. Your audience won’t know what direction to read — horizontally or vertically — or what conclusions to draw. Though the Grand Total line is emphasized, is that really the main point you want to convey?

Now let’s look at the data presented more simply. Say you’ve identified three business units with potential for sustained growth in Europe. By eliminating the dense matrix and connecting only key numbers to a pie with leader lines, you remove clutter that distracts from your message. And notice the clear hierarchy of information: You can highlight important pieces of the pie by rendering them in color and their corresponding annotations in large, blue type. Other sections recede to the background, where they belong, with their neutral shades and small, gray labels.

But pie charts can be tricky for an audience to process when segments are similar in size — it’s hard to distinguish between them at a glance. If you’re running into that problem, consider displaying the same data in a linear way. In this bar chart, for example, you draw attention to the poorest-performing unit, a point that got lost in the pie:

These few tricks will help audiences see what you want them to see in your data. By focusing their attention on the message behind the numbers, not on the numbers themselves, you can create presentations that resonate with them and compel them to act.

 

Gaming Market Case Study: NVIDIA To Go Vertical

This is getting messy..  NVIDIA announced yesterday at CES in Las Vegas, that it will market its own game console, which will compete directly with Sony, Microsoft, Nintendo, and for all intents and purposes, Google and Apple TV.  Does this sound to you, as it does to me, like a disaster in the making. Analysts at the launch event in Las Vegas, were reportedly “stunned.”   Students of corporate and product strategy should watch this space, as may well be a classic shakeout, and because it is gaming, it may happen at an accelerated pace.