The Rise of the Data Vampires: A Tale of Two Georges

The Internet of Things could deliver us the world of George Jetson with helpful robotic assistants attending to, even anticipating, our every need. Our Internet-connected smart homes would learn our patterns, hear what we say, capture images of what we do and even monitor our vital signs through “wearable” to make our lives simpler, safer and maybe less stressful. Or maybe, just maybe, we are being delivered into the 1984 world depicted by the other George—George Orwell.

I mentioned in my last post that I discovered how this new generation of Internet-enabled, cloud-based IoT devices actually work and their undisclosed purpose to feed corporate Big Data engines. That discovery was behind my epiphany that many of these smart home devices were actually “data vampires”.  What else would you call something that silently sucks personal information from consumers’ homes while posing as benign home automation devices? When I shared this discovery with my friend Randy Schultz one Sunday afternoon in May, he had two responses. “Holy shit! Really?” followed by “We need to write a book about this!”.

And so it began two short months ago. Within days, we had pulled together an outline for a book and, in the ensuing weeks, Randy worked on the book proposal while I wrote an introduction and the first two chapters. The Rise of the Data Vampires: How Google, Facebook, Big Data and the Internet of Things Are Stealing Your Privacy ( is ready to be pitched to agents and, ultimately, publishers. This is my first involvement in writing a book. It’s hard work but we feel a commitment to raise the alarm about the promises and perils of the Internet of Things. Data Vampires are not fiction nor do Randy and I wear tin foil hats to protect ourselves from Internet eavesdropping. They are very real and they are heading to our homes in vast hordes. Some Data Vampires have already arrived disguised as Nest (Google) thermostats and Amazon Echo home automation controllers.

The work of writing this book and educating consumers via the Open IoT Foundation about the choices they have is a challenging but important undertaking. Our objective is not to suggest people live off grid in a cave but to be aware of what is entering their homes and to make smart choices. Cohabitation with Data Vampires may be a good choice if the benefits satisfy consumer needs and both parties agree that it is a fair, symmetrical transaction. A bad choice is when consumers have no idea that they opened their doors to Data Vampires.

We Need an Open Internet of Things

Serendipity seems to be the driving force in my ventures and it happened again. After taking off most of 2014 to build a new house in Santa Fe, I was ready to get back to work. Not that building a house where I was the general contractor and worked as a carpenter for much of the time isn’t work. It’s hard work, but I wanted to find another small venture on which to focus my energies and time. I had thought I found a great idea for a specialized home automation system I wanted to build to save water and energy. It would be a sustainable business that combined my interest in home building and technology.

I made an interesting discovery as I was researching Internet of Things (IoT) technology I might be able to use in my project. What I found was a serious threat to consumer privacy and control of their home environments. Now I consider myself a good technologist and a realist about the tradeoffs using modern technology but hardly a privacy maven. The benefits of online technology often come with attached non-monetary costs. I’m usually willing to accept some loss of privacy and being spammed with targeted ads (the usual payment) in exchange for free email, excellent search engine results and great maps. A balanced transaction if not ideal. Quid pro quo.

My discovery alarmed me more than I expected but with good reason. In my assessment, the Internet of Things is rapidly evolving as a vast array of smart home devices that are silently sucking up personal information for use in private Big Data systems owned by Google, Facebook and Amazon. Nothing new you might say. These folks are already “hoovering” up my data, right? True, but this time, they are using slick marketing to sell consumers on the wonders of a George Jetson future their devices bring to consumers homes. They simply neglect to tell consumers that the real purpose of these smart IoT devices is primarily to learn more about them so they can develop even more targeted advertising. A balanced transaction? Hardly.

This use of stealthy “trojan horses” masking an Internet pipeline feeding corporate Big Data systems borders on dishonesty and certainly lacks transparency. This begins the story of how we decided to create the Open IoT Foundation as a nonprofit venue to give voice to these concerns. We tell the back story on the website and also lay out what we think represents a fair consumer Bill of Rights for an open Internet of Things.

My new mission is not my usual product-centric startup by any means but a really important subject. Creating consumer awareness of what is happening with the Internet of Things won’t be easy. The Open IoT Foundation is a starting point and the book I am co-authoring with a friend on this topic (more on the book in the next post) will provide another platform.

Velograf Tools for Data-Driven Community Managers Launches!

I’m excited to report that we launched Velograf Tools this week. David (@DataRiot) has been ‘heads-down’ on this project for a year and I’m convinced it represents a real breakthrough in providing serious community health analytics for data driven-community managers. Too many CMs are forced to use spreadsheets and social media monitoring tools that really don’t give them the kind of insights they need to really understand the health of their communities. A healthy user community can be far more important to an an organization than a ton of mediocre marketing (and I say that as a long-time marketing guy…).

Crowdfunding with Angel List

As David and I prepare to launch Velograf Tools, I scrolled through my postings from 2010 when we were thinking about raising money for a graph analytics service (a recommender engine of some type, I believe). While some of my excessively verbose pontifications might be considered relevant, three years has seen a ton of changes in software development and fundraising. Crowdfunding via Angel List or Kickstarter completely changes the model for raising money from angels and validating the market by raising money at the same time. The most significant impact is the dramatic compression of the fundraising cycle.

As Velograf prepares for fundraising on Angel List, I see the extended process of one-by-one introductions to prospective investors (angel or VC firms), emailing  executive summaries, scheduling meetings to walk through pitch decks and the never-ending follow-up activity rapidly morphing into a short cycle. All the serious prep work still needs to be done since the story must be good—product, team and opportunity—but the time to a decision will be fast. Anybody pitching a deal using Angel List is going to know in a few weeks whether their deal has legs.

As someone who has pitched deals to VCs and been stuck in the middle stack (neither a solid ‘yes’ nor a definitive ‘no’) for weeks and months, the prospect of a quick answer seems ideal. Even better, the validation (or failure to validate) the results from testing your idea against a pool of hundred or even thousands of prospective investors is invaluable. In pre-crowdfunding days, often unwarranted optimism (a necessary virtue/vice of entrepreneurs) kept early-stage startups pitching long after it was clear they were not going to get funded.

So, as we get ready to launch Velograf’s tools for online community managers and kick off a seed fundraising campaign, I find the prospect of using Angel List almost pleasant compared to the dread I usually experienced starting a fundraising effort. I may have a different response in December but right now I’m optimistic.

Another Launch Coming Soon

David and I are rapidly closing in on the launch of another product — Velograf Tools for online community managers. It’s always an exciting time when a new venture steps forward to test the market with an innovative service but it’s also a bit sad for us since we need to move Good Karma Now into hibernation for awhile. Too much to do, too few resources and some challenges with how to fit Good Karma Now into the world of nonprofit giving. I think a post-mortem assessment is in order when I can find the time.

Stay tuned for more details about Velograf Tools.

Privacy-Déjà Vu All Over Again

Another privacy “tempest in a teapot” is about fade away. See  Ever since Internet users discovered the “evil” cookie way back in browser ancient history, the Internet privacy cognoscenti periodically get their knickers in a twist and manage to garner PR far in excess of consumer interest. “The people” (whatever nebulous mass of humankind that phrase represents) have voted with their mouse(s) and decided to ignore the issue. Why? Perhaps…

  1. It’s not important to them.
  2. They never read anything with “privacy” in the headline.
  3. They analyzed the issue in depth and decided the trade-off favored sacrificing some privacy for a better user experience.

I wish it were the last item but that’s highly unlikely. Most folks just don’t care enough to burn any calories thinking about it and maybe, just maybe, intuitively understand that #3 is true. The only thing that will change this is a privacy disaster on par with the Deepwater Horizon oil spill and even that may not have a lasting impact. After all, the real solution to minimizing future oil spills in the Gulf is for everybody to bicycle to work beginning tomorrow. Right.

Own the Exit Strategy

At one point earlier in my startup career when I was VP of Marketing at a 3D graphics startup, I was advised by a well-known Silicon Valley VC that I wasn’t to worry about the exit strategy. Our job was to build value and the exit would come. Basically, go away and let the smart folks (VCs) determine the exit strategy. For many years, I generally accepted this philosophy but 20 years later when the world of startups and venture capital is in the midst of major upheaval, I believe entrepreneurs need to own the exit strategy as a fundamental part of the business model from day one. The product decisions you make and the organization you build must reflect your exit strategy. More critically, it determines your capital requirements over the life of the company and quite possibly the investors you target.

The accepted world view is that there are two basic exit options for enterprise software startups that have taken capital from institutional VCs or angel investors—IPO and acquisition. Given the IPO option is off the table for the vast majority of startups, the choice comes down to the strategy for an M&A exit. One approach which I label the Oracle “Mini-Me” model under which you develop a feature-rich product and all the sales, marketing, tech support and F&A infrastructure that you would find in a big company. My general assessment is that this takes 5-7 years to reach exit, $20-40 million dollars of capital and, if all goes extremely well, an exit at 8-10X capital in. It fits nicely with the timeline and capital available to large VC firms. Many large acquirers have the capacity to process an acquisition of this type and many actually prefer to have risk-free market validation through several years of growing customer revenues.

The other approach is what I refer to as “portfolio completion” (I’m certain there are sexier labels but nothing comes to me at the moment). Under this model, a target acquirer is looking for new products or technology that can fill the gaps in their product line to give them a more complete solution for their customers. They have established distribution channels (direct sales or otherwise) and a customer base that can be readily leveraged. The need for extensive market validation via proven revenue streams over several years is less critical since the acquirer has already determined the need for the product and/or technology and actually prefers a much leaner organization without the other functions that duplicate what they already have. The startup objective under this model is capital-efficient delivery of a basic product with solid market validation. These types of exits can occur in 2-3 years with capital investments well under $10 million and possibly under $5 million. The multiples are probably a bit lower in the 5-7X range but the IRR can actually be higher because of the shorter term. Not all VCs can operate under this model but smaller VC firms and angel groups can generally handle this approach.

Large VC firms will push startups towards the Oracle “Mini-Me” model because of the partnership structure (portfolio company to partner ratio), fund size and management fees which enable these firms to deal with much longer horizons. Smaller VC firms and angels (groups or individuals) may be more appropriate for the entrepreneur who believes the “portfolio completion” model is a better fit for his or her business model. A spin on the “rich versus king” issue also comes in to play here since the “Mini-Me” model generally has at least one CEO shift over the life of the startup before exit and it’s quite unlikely the founding team will be in charge or even have a role in the company after 5-7 years.

It’s not an obvious nor simple choice. I’m biased towards the “portfolio completion” model since I’m not convinced that business model in an early-stage startup should be driven too excessively by external factors like the minimum size checks a VC fund can write. In reality, it’s probably a hybrid model that demands agility when the context changes. At the outset, I believe startups should employ the “portfolio completion” model since it reflects a customer-driven product focus as the startup strives to find a market fit. Once the market demand has been validated, the decision to seek an exit or swing for fences with the Oracle “Mini-Me” model can be made.

In the final analysis, the exit strategy will be driven by the product, market sector, investor demands, capital requirements and external conditions but my point is that it must be acknowledged in the startup business model from day one. Own the exit strategy.

Angels vs. VCs

An angel investor in Knowledge Reef Systems sent me a copy of Basil Peters presentation (no link at this time) to the Angel Capital Association Summit in San Francisco this month. Absolutely spot on with one minor complaint (see a couple paragraphs below). Basil’s key points:

  • Target an early M&A exit (get out in 2-3 years)
  • Build a product that a larger company can grow as part of their portfolio (leverage their expensive sales organization)
  • Aim for the sweet spot of the M&A market ($15-30 million)
  • Run lean (a cliché but true)
  • Seriously consider angel investors even if your capital requirements are in the $2-5 million range

This is stunningly contrary to conventional institutional VC wisdom that demands entrepreneurs build Oracle “Mini-Me” clones. Why do they do so? My assessment is they simply have too much capital that must be put to work, they need to limit the number of bets they make and management fees tend extend the exit horizon beyond what is reasonable for angel investors. VCs have no choice but to swing for the fences on every investment even if a more rational strategy of base hits wins more games. Is there a relationship between this “home run” approach and the dismal VC returns of the last decade? The answer is far too complicated for my pay grade…;-).

As Basil points out, angel investors may be more aligned with founders than VCs are. It certainly gives me pause for thought as I get ready to launch my fund raising effort for veloGraf Systems. The VC path is the default but my strategy for building the company is probably more aligned with angel investors. I enjoyed working with angel investors in my last company and if I can meet my capital targets with angel investors this time around, it certainly beats being forced into the wrong business strategy simply because of excess capital in VC funds.

My exception to Basil’s presentation was his discussion of the “weekender” startup. I know I’m an old war horse when it comes to creating value in startups but I remain convinced that it takes more than a couple guys in a garage over a weekend to build a meaningful venture. If it can be done by these, why won’t another team (or ten teams?) be able to do the same thing the following weekend? What is the barrier to entry to a startup product/service that can be developed and deployed in a few days, weeks or a couple of months? I can’t help but believe that this type of investing is like buying lottery tickets. Maybe you can win the jackpot but the odds are much higher that you will spend a small fortune on $10,000 investments and never hit the jackpot. A couple small wins perhaps but your overall IRR will be negative.

I am in 100% agreement with Basil that the cost of building software solutions is far less than what it was 10-20 years ago but it simply isn’t $10,000. This “weekender” myth (also called startup “boot camps”) drives me crazy because it makes angel investment look more like a weekend in Las Vegas than an effort at reasonable due diligence on the capabilities of the founding team, the market opportunity and differentiated technology with a sustainable advantage. Yes, angel investing is risky but investing in this type of venture seems to heighten the risk.

Oracle “Mini-Me” vs. “Cool-Tech” Startups

Why is it that so many enterprise software startups continue to be structured as “mini-me” clones of Oracle (or pick your favorite large, established software vendor)? In a world of agile development processes, alternative distribution channels and customers accustomed to employing open source software that demands “self-help” evaluations, you would think that new business models would emerge. Instead, we see these very small companies, most of who have yet to reach cash flow break-even, adopt an extremely costly customer-facing organization (direct sales and support) paralleled by a rigid, long product development and release cycle. This seems particularly true in the data warehouse/business intelligence sector that our company, veloGraf Systems, is targeting.

My observation is that these companies are caught up in a vicious cycle based on the unproven premise that success in this space demands $20-50 million in capital. Assuming that is true, then only VCs who can (and must just because of the mechanics of large funds) write large checks invest in this sector. Having committed big sums and believing they are competing with large, established enterprise software vendors, these VCs insist on bringing in executives whose first reaction to the apparent chaos in many early-stage companies is to build a structure that reflects the large organization from which they have been recruited. A self-fulfilling prophesy. The burn rate takes off, the organization becomes less nimble and even more funding is required to build competitive sales and engineering organizations. Maybe I’m just showing my age and having a flashback to a database startup I ran using this model during the Internet bubble era but I found several contemporary exemplars of this approach while undertaking a quick competitive analysis exercise recently.

Of course, at the other extreme, there are the open source enterprise software startups who practice the “build-it-and-they-shall-come” model on the presumption that if you simply make enough noise tweeting about your cool technology and preaching to the converted cognoscenti, the sales will materialize. While usually practitioners of agile product development, startups operating under this scenario frequently lack a disciplined customer development process so critical to converting technology interest to product revenues.

Somewhere between the Oracle “mini-me” model and the freewheeling “cool-tech” approach is a business model that acknowledges the need for structure and experience but avoids a heavy-handed approach of jamming an inflexible large-company organization into a small startup. As I noted in earlier posts, I believe Steve Blank‘s agile customer development process and Eric Ries‘ lean startup principles can be applied to an enterprise software startup. With the right discipline exercised by the leadership team and investors, capital requirements can easily be half of Oracle “mini-me” model and quite likely even less. Even more interesting is that a lean startup with a differentiated product that is cash flow positive without the burden of an expensive, field-based direct sales organization potentially has a higher value to an acquirer looking to extend its product portfolio.