I recently read Walt Mossberg’s latest and last column in The Wall Street Journal. I always enjoyed his take on consumer technology and his belief that technology need not be so difficult to use. Since he began his stint over two decades ago, technology has seen incredible changes and in many ways his call for simpler to use products has become a reality. When you consider the ubiquity of computing devices in our everyday lives from mobile devices to wearable tech to apps in the cloud, you cannot help but agree that we have arrived as a technology oriented society.
Walt made a strong case for his list of top consumer products over his time as a columnist at the Journal. Outside of the Apple MessagePad, I and most others I know have used them all. It made me wonder though what would be the most important, innovative, and disruptive technologies over that time? They are not one and the same as products as technology gets to the core upon which most products are built upon. When you consider products like the iPad, it would not have been possible without a myriad of technology innovations that made a device like that possible.
o in the same vein as Walt, I am taking a stab at the 12 most important technologies to come along since 1990. All of these have had immense impact in changing the way we view the world, the way we interact with each other, and the way we work. Some are visible to most, but some are behind the scenes guiding along the advances of other products and services to become an important foundational innovation. Either way, these technologies had an undeniable influence in shaping the course of humanity now and will continue so well into the future.
Therefore, without further ado, here are my views on those 12 technology innovations:
The Web - The Internet had already been going for some time as people were accessing Usenet groups and exposed to the idea through popular culture via movies like War Games. But it was still a very tiny niche and not easy for the general public to grasp. That all changed with the advent of the World Wide Web and the web browser in 1991. It would still take several years for it to become something, but I remember clicking around the early web using Mosaic and thinking how cool this was. Little did most of us know that the Web would become one of the most powerful and disruptive mediums since the advent of the printing press and the underpinning of entirely new industries.
Email - This is where work happens. That is what it might seem like, but when I had my first email account it seemed like it was merely an easy way to leave messages for friends. Now it is pretty much the predominant messaging system with 144 billion messages sent per day used for everything from personal to business to marketing to rich Nigerian princes giving away their wealth. And while you may call it the bane of your existence (studies have said it takes up 28% of our work day), there is no denying that email is an integral part of our lives as we furtively battle towards inbox zero.
Search - Ever use Archie or Gopher? I am probably dating myself here, but that was what I first used to search the Web. Then came commercial offerings by Lycos, Excite, Infoseek, and AltaVista. But it was Google that eventually won the search battle by the early 2000’s with its Page Rank algorithm. It was search that finally brought some level of order to the unruly and ever growing Web that the directories and portals could not. Search also spawned entire new industries as marketers realized the power of organic search and search advertising. It has been the bread and butter of Google’s business ever since, allowing the company to pursue ever more ambitious ideas to become one of the great pillars of the tech innovation ecosystem.
Blogging - In the early days of the Web, there was not all that much content to speak of. You could browse around easily enough, but for what? Eventually people started to post things online, sometimes personal journals, sometimes news, sometimes essays on various subjects. By the late 90’s, the term “blog” became a permanent part of the tech lexicon and platforms like LiveJournal and Blogger emerged to support these intrepid writers. Now it is big business, having created careers and conferences and companies. And it has upended the world of journalism, become as relevant as established media in breaking and spreading news.
The MP3 - I used to have the most killer CD collection when things like that mattered. Now it seems like everyone is renting their music online. None of that would have been possible though without the MP3. Really I should state lossy compression as there are a number of formats used. But it was the MP3 that become the de facto standard and disrupted the world of music as much as the Web disrupted newspapers. The MP3 popularized file sharing, decoupled the entire music economic supply chain, gave Apple it’s first killer product in two decades, and changed the way we listen and consume music forever.
eCommerce - The first iterations of web browsers and Internet technology only accommodated the most rudimentary of websites, which meant lots of text interspersed with images. Then a few things happened. First, Netscape incorporates SSL into its first browser for secure transmissions. Then the National Science Foundation dropped its objections to commerce on the Internet. Then HTML 2.0 added GET and POST form submission in 1995 changing the level of interactivity one could enable in a website. Now a fair criticism would be to say that eCommerce is not one technology, but many technologies such as payments and encryption. But taken together it is a technological trend that has led to over $1 trillion in transactions online and changed the nature of retail commerce forever with new models of local mobile commerce and the sharing (peer-to-peer) economy that is all the current rage.
3G Networks - We all remember that scene in Wall Street when Gordon Gekko was talking to Bud Fox on a phone while walking on the beach. How cool was that (even if it looked like a brick)! Cell phones were pretty cool and gained wide acceptance in the 90’s. But when 3G networks came on the scene, it changed the nature of how one could use these devices. They were not just a way to communicate via voice and text from the road, but a way to get information and do other useful stuff. But that would not have been possible without the bandwidth afforded by 3G networks which finally made data transfer possible to support email, web browsing, and more.
The Cloud - This one could be a stretch given how much abuse this term has taken in the hands of overzealous marketers. The Cloud in many ways has always existed from the earliest days of computer networking. And like eCommerce, there are many component technoligies such as virtualization that make the Cloud possible. It was in the 90’s though that the concept started to come into the common tech vernacular to cover various hosted services and the earliest SaaS providers. But it was Amazon that changed the game by turning the cloud into a true utility with the release of AWS in 2002 (and EC2 in 2006), allowing anyone to cheaply host anything, including web and mobile apps. AWS now powers a huge percentage of the Web 2.0 economy and has been instrumental in the recent explosive growth in tech startups.
SaaS - Hand in hand with the Cloud would be Software-as-a-Service. Before this, the cloud was generally considered to be nothing more than a hosting relationship usually in a VPN configuration for companies. The idea that software could be “shared” like one shared a server seemed antithetical to most companies in the late 90’s, but Salesforce.com made it the core of their entire strategy. The real brilliance was not merely creating a multi-tenant environment to share software in the cloud, but “renting” it to customers on a subscription basis. Now they are one of the largest software companies in the world having made SaaS as business as usual as Excel spreadsheets and forever changed the way businesses buy and deploy software.
Social Networking - By far the biggest trend in technology over the past several years other than mobile has been social networking. By 2005, there were quite a few popular social networking sites and the Internet was clearly happening. However the Internet was just not essential for most people. Facebook altered that forever by putting social networking at the forefront, connecting humanity together with digital connections without regard to location or relationship. And with connectivity came frictionless sharing of content and media, changing the nature of how we perceive privacy and trust as well as how we interact with news and information and each other.
Open API’s - Social networking would arguably not have been as disruptive if it had not been for the advent and popularization of open API’s (application programming interfaces). There is nothing new when it comes to the concept of API’s which have existed in various forms since the days of the mainframe. What did change was who could access those API’s and what information could be exchanged and how easy it was to build these integrations. Companies like Facebook and Twitter made their API’s a core growth strategy, creating an ecosystem that encouraged developers to connect their own apps into these major networks and in turn creating other large companies like Zygna. Now Open API’s are even causing governments and private companies to open up their own troves of data to the public, fueling the burgeoning Big Data movement. And how big is Big Data exactly? It is now a $15 billion a year industry and growing rapidly.
Mobile Computing - While the increased bandwidth of 3G was critical for the adoption of data services, it was new devices themselves that unleashed the full potential of computing on the go and all the time. We may laugh at Blackberry now, but they were largely responsible for popularizing smart phones with stellar email and messaging apps. Then Apple and Google got into the mix with full-fledged supercomputers in one’s hand that could do anything one could do on a laptop fueled by vast digital media collections and app stores. Along with Open API’s, mobile devices have accelerated the pace of social networks and SaaS, driving ever more need for Cloud resources. Just as powerful as email has become in changing the nature of how we work, so will mobile computing change how we work, but this time for the better.
Bonus - these are nascent innovations that are still evolving but important to mention:
Bitcoin - Maybe it would be better to state this more generically as cryptocurrency. But Bitcoin has all the the mindshare and attention and capital at this juncture. We are still very early however given Bitcoin came into being in 2009 and is still a niche idea talked about heavily by a niche group of enthusiasts, investors, and entrepreneurs. This is the next big bet in technology, but it is still too early to state that this is a game changing technology. One thing is for sure though, if it does succeed, it could disrupt the very core of the international banking system, global payment systems, and government controlled fiat currencies. What does that portend? The greatest exchange of capital and wealth and power we have seen since the dawn of the industrial age.
3D-Printing - Like Bitcoin, we are still very early days in the market. I would call this current era the first generation of the technology where there are plenty of hobbyists and growing commercial usage, but it is still the tiniest sliver of total manufacturing output. However, the potential for 3D-printing cannot be understated in reinvigorating the manufacturing industry. We are slowly moving from mass production supported by massive transportation and logistics infrastructures (with all its pollution) to just-in-time, mass customization using local resources within local communities. We are not there yet, but that train is leaving the station.
It has been quite a whirlwind of change in just 23 years. Back then, we thought computers were big boxy things on which you did spreadsheets and word documents on. Now we cannot escape the pull of technology and computers anywhere we go as the first digital native generation starts entering into the workforce knowing nothing different. What will come to pass in the next couple of decades I could only guess, but it may very well be as strange and exciting and surprising as the past couple of decades. Here’s to the future!
Harry texted Andie back letting her know he was leaving now before getting dressed in skinny jeans and a flannel. He finished off with his signature brown boots and a beanie before grabbing his phone, wallet and keys and heading to his car. He was excited to spend a day shopping with his sister since he had been out of town lately and he hadn’t gotten to see her in a while. His nephew was set to be born any day now so Harry was excited to sort everything out for him before he gets here. Harry began to drive to his mum’s house, singing along to Christmas music really loud that was playing on the radio. Before he knew it, he was pulling into the driveway. He decided to text her that he was outside since he knew his mum wasn’t home so there was no need to go inside.
The definition of a commodity is a good that is “supplied without qualitative differentiation." You can’t charge more than others for crude oil, you have to turn it at least into gasoline. And if you really want to charge a lot more you have to turn it into a plastic product.
CPU cycles and memory are the crude oil of our times. If you want to charge more for them you have to add value. If you are SaaS company that provides a complete solutions you are adding a lot of value (plastic product). Conversely, if you are a developer platform you are just a smidgen above the commodity (gasoline).
So when thinking about margin, a SaaS business might have 80-plus percent gross margin. But cloud platforms aimed at developers will wind up being in the low double digits or possibly even in the single digits using total revenues as the denominator. Put differently, the financial metrics for the latter over time will look more like a refinery or a retailer.
From a long term investment perspective though it is important to keep in mind that ultimately what matters is total cash flow. If you are Walmart you make very little margin on any one purchase but you process a lot of them. So developer cloud platforms have to be scale businesses. It’s not a surprise then that another retailer, Amazon, is the leading cloud player and recently announced their 42nd price cut.
You can have a great business as a SaaS company or as a cloud platform, just don’t mistake one for the other as how you think about financial metrics will be quite different.
Get just 500 Large Enterprises to spend $250,000 a year to solve a large problem … and that’s a $125,000,000 business and an IPO. $250,000 is nothing in the Enterprise — it’s less than the cost of one person, fully burdened. So that’s where the money has been the past few years in SaaS 2.0.
While the post is about a formula for SaaS solutions that can grow big in the SMB world (still painfully hard to achieve), this part about what it takes for an enterprise SaaS company to get to scale is interesting. 500 is still tough to get to in Enterprise, but definitely realistic when you think of all the large companies out there, even if you just focus on one vertical market.
AT&T is helping with hospitality, with new Remote Patient Monitoring (RPM) technology. The company plans to deliver cloud-based RPM Software-as-a-Service from Ericsson, helping doctors monitor their patients over video on a tablet connected to the Internet.
This new SaaS provides coaching, reminders and health education to help manage chronic diseases better, so that patients won’t have to return to the hospital. It joins the AT&T ForHealth suite of RPM services, which includes such services as an end-to-end RPM service powered by Valued Relationships, Inc., which helps monitor patients around the clock.
We all know that picture of Steve Jobs giving the iconic technology company a piece of his mind back in the early days of Apple. Once the recent mobile partnership between Apple and IBM was announced, it was a picture passed around the Internet with great glee and irony. But the message was clear, the times they are a-changin’ but certainly not in a direction most were expecting.
There was really no surprise with the announcement. In a way that never happened for its desktop computer line, Apple tablets and smartphones have overtaken the enterprise. It was not so long along we were addicted to our Crackberries and banging out emails on our tiny physical keyboards. No business executive was without the device and nothing surpassed it for sheer productivity when on the road (or vacation as often happened). Then Apple stormed the gates with better hardware, significantly better apps, a superior user experience, and a cache that Blackberry could not match. Most of those same executives were sporting iPhones shortly afterwards.
How great is the domination of Apple in the enterprise? Apple tablets alone now account for over 90% of all tablet devices in the enterprise and over 70% of enterprise activations are iOS devices. In an earnings call earlier in the year, Apple started that the iPhone is used in 97% of the Fortune 500, and 91% of the Global 500, and iPad is used in 98% of the Fortune 500 and 93% of the Global 500. GE and Deloitte have over 50,000 iPhones used for corporate purposes. Medtronic, Nestle, and NASA have thousands of employees using iOS devices for business purposes. Apple is inexplicably king of the enterprise.
So why bring all this up? Because while the alliance between IBM and Apple is newsworthy and intriguing, it may not be the huge win either company might be expecting. If anything, Apple seems to be giving IBM the finger yet again. Tim came bearing gifts of joy and smiles, but Steve Jobs is still lurking underneath this move. How so? For Apple, they get a much needed enterprise publicity boost while IBM might just net a few more opportunities to sell cloud services, if that.
While Apple is the king of the enterprise mobile platform for now, that position is tenuous. So is it Google that is poised to finally make a run at the enterprise and rattle Apple? Nope, the real up and comer is that old, crusty standby Microsoft. With a new breath of life in Nadella and the combination of Azure, Office365, several enterprise business apps like Dynamic, and their mobile platform, Microsoft makes for a compelling solution for most companies. Since Microsoft is already a known entity and firmly entrenched in the enterprise, this is the safe move for IT departments and corporate executives. And as Microsoft has shown in the past, they are not afraid of giving away the product to build market share. Anecdotally people are hearing of real Microsoft tablet deployments in the enterprise.
Sp linking up with IBM gives Apple that much needed stamp of enterprise approval. The biggest question marks about Apple regarding security and ROI get addressed by IBM offering a cloud infrastructure optimized for iOS and a whole slew of business oriented mobile apps. Even though the evidence shows that a mobile enabled workforce is more productive, there is still healthy skepticism from executives about the value of mobile, especially with the paucity of enterprise grade business apps.
As for IBM, they are still a distant contender in the cloud infrastructure space. In fact, they were the lowest ranked vendor on Gartner’s IaaS Magic Quadrant last year. The leaders? AWS, CSC, Rackspace, and Microsoft. In fact, if not for the SoftLayer acquisition, IBM might not have even made it on the chart. What has been interesting to see in the past year however is strong uptake of SoftLayer with existing clients and significant investment by IBM into the business, from data center expansion to deploying cutting edge technology ahead of the industry leaders. But does the Apple alliance really get them anything that they have not already been able to achieve? Maybe it makes IBM look a bit more hip, but not much more than that.
And what of those 100 industry enterprise business apps that got touted? While IBM has a credible software footprint, especially with many of their recent cloud software acquisitions, the business apps are more smoke and mirrors than a real opportunity. If there is something I have learned in the enterprise apps space is that customizable solutions win the day and “industry” apps garner little weight outside of very specific business flows around compliance or regulatory needs. For example, one of my customers GE has widely varying requirements for supporting the sales teams across the different groups. Plugging in a one size fits all approach for their sales team would have been a disaster.
The movement in enterprise business software is towards mass customization by users and groups. That means business owners own and configure the functional layer of the software while IT takes care of the infrastructure layer which in the cloud era means data security and integration. The reason is that businesses need to move faster than the ability for IT to implement changes in the typical enterprise software package. I wager that IBM will however release a bunch of apps that hew towards the older mode of software customization and ultimately create 100 really neat looking demos for their Global Services team to then implement for a good chunk of change.
Ultimately what the alliance sets in place are the teams competing in the mobile space for the next five years. Everyone is looking to build their stacks from apps to infrastructure to the hardware in employees’ hands. So the teams are set; you have Microsoft in one corner, Google looking a bit shabby in the other corner, and a fresh faced Apple/IBM tag team duo. The enterprise app players, mobile deployment managers, and IaaS vendors are all watching the spectacle taking bets. If anything, it should present some good theater as the battle begins.
One of the key metrics we encourage our SaaS portfolio companies at Flybridge to be focused on is the magic number. Sure growth rate and lifetime value and customer acquisition costs and churn are all important but the magic number is magic for a good reason: it gives a great sense for how much sales and marketing spend are driving monthly recurring revenue growth. In other words, it summarizes a number of metrics in a single number. If you’re not familiar with the metric, made famous by Josh James, take a read here to get up to speed.
Our praise of the magic number often translates to religion at our SaaS portfolio companies. In one particular company, after implementing magic number reporting and discovering it to be 1.9, a sales manager cold emailed James to share his excitement. James responded “Hire more reps then” and introed the company to his CTO at Domo (who went on to become a customer).
While we get to apply this metric to our portfolio companies - most of our SaaS companies report it on a quarterly basis - it’s sometimes fun to apply the same lens to other companies. With Box filing their S1 earlier this week, we wondered what sort of numbers they have been seeing. The quick: not such magic ones.
As we go through this, remember that James’ rule of thumb:
[I]f you are below 0.75 then step back and look at your business, if you are above 0.75 then start pouring on the gas for growth because your business is primed to leverage spend into growth. If you are anywhere above 1.5 call me immediately.
Revenue and Sales and Marketing
Finding the numbers to calculate the magic number by quarter for Box based on their S1 filing is pretty straight forward: just go to the Quarterly Results of Operations section, find the revenues and sales and marketing costs by quarter and use James’ magic number equation (QRev[X] - Qrev[X-1]) * 4 / ExpSM [X-1]. That leaves the following:
Now this is slightly imprecise in that it looks only at new revenue growth not new annual contract value growth in a given quarter, a more true way of calculating the magic number, but it’s the best we can do with the data reported. Given James’ rule of thumb, ever quarter since the quarter ending 7/31/12 has been one worthy of stepping back from, not one worth pouring gas on.
The issue with the calculations above is that they do not take into account what Box counts as Sales and Marketing expenses. Normally this line would contain just expenses associated with the various functions but, in Box’s case, there is more to the story. Box offers free trials of their product and the Sales and Marketing section of the S1 gives a hint of how Box accounts for the expenses associated with the free trials:
Sales and marketing expense also consists of datacenter and customer support costs related to providing our cloud-based services to our free users
Being true to James’ calculations, it’s not really fair to burden the magic number with the cost of datacenter and customer support expenses so, for the benefit of Box, let’s back these out. It’s impossible to be precise here since the company doesn’t break these items out individually but we can use a note in the filing to guessestimate:
Sales and marketing increased by $72.0 million, or 73%, during the year ended January 31, 2014 compared to the year ended January 31, 2013. The increase was primarily due to an increase of $45.5 million in employee and related costs, including higher commission expenses of $16.0 million, driven by headcount growth from 374 employees as of January 31, 2013 to 513 employees as of January 31, 2014, and higher sales, an increase of $12.6 million in datacenter and customer support costs to support free users, an increase of $6.4 million in allocated overhead costs, and an increase of $2.8 million in travel-related costs.
If you assume that all the expenses grew at the same rate from 2013 to 2014 (and this is a pretty big assumption but really the only one that can be used), you can roughly calculate what percent of sales and marketing expenses go towards each line item:
If you apply this same rule of thumb to the reported Sales and Marketing expenses and back out the 19% costs associated with free customers, you arrive at the following:
Better (because the sales and marketing expenses have been adjusted downwards) but still far from great. So how do these compare with some other enterprise SaaS public companies? The answer: not so well.
The magic number isn’t the end all be all for SaaS metrics but it’s a very useful one. It doesn’t take into account things that may benefit Box’s business such as longer than average lifetime values and increasing customer values over time, but it’s an important metric nonetheless. The magic number analysis in Box’s case suggests that the company is spending money faster yet growing slower than comparable public SaaS companies - essentially throwing cash at growing top line revenue with decelerating results. If one of the Flybridge portfolio companies demonstrated these magic numbers, especially on a downward decline, we’d be wondering if it made sense to keep pouring fuel on the fire. We’ll see if the public market will wonder this as well.
No. I get asked this question often by folks looking to build B2B oriented SaaS businesses leveraging a freemium model, and normally I dither in response. Mostly it is because there is always the possibility that it could happen given the right set of circumstances. Dropbox and Evernote are probably the best examples of SaaS businesses* that reached massive scale and significant revenues yet are still mostly freemium.
However, if I am being honest with folks, I would tell them they have about as good a shot as winning one of those mega payout Powerball lotteries. Why? Because the numbers simply do not add up. When you figure in active user counts, paid conversation rates, pricing tiers, and churn rates, you quickly realize that the number of businesses you would need to sign up is over one million. That is “paid” business users I might add.
To build a $100,000,000 business on Freemium alone, think about the math. Assume you can get $10/mo per paid user (many times, you can’t). You’d need almost 1,000,000 paid seats to hit that. Assume a 2% conversion rate, for simplicity’s sake. You’d need 50,000,000 active users. Not pretend users. Not users who registered and never came back. Not even users than use you once a year. 50,000,000 active, passionate, engaged users.
That is extremely tough in consumer internet, but it can happen. Facebook is almost at 1,000,000,000. Twitter is past that, Pinterest may be, etc. In SOHO or SMB business apps, one million paying customers – it almost never happens. Intuit, Microsoft, Adobe, PayPal. But not too many with 1,000,000 paid business customers.
Not an easy climb at all, which is why so many SaaS businesses quickly move up the value chain towards enterprise customers. That is what Box did. Salesforce was never “freemium”, but they were focused on the SMB market initially before going on to close nine figure enterprise deals as they hurtle towards $4 billion in revenues by year end. Freemium at best is a stepping stone to build a sizable user base, but not something that a SaaS business can afford to ride for the long term.
* Note: Even still, much of their revenue is coming from consumers rather than businesses and is more akin to a consumer paid apps model than a true B2B SaaS business.
People often ask me where the smart money is in big data. I often tell them
that’s a foolish question, because I’m not an investor — but if I were, I’d
look to software as a service.
There are two primary reasons why, the first of which is obvious: Companies
are tired of managing applications and infrastructure, so something that
optimizes a common task using techniques they don’t know on servers they
don’t have to manage is probably compelling. It’s called cloud computing.
The other reason is that the big part of big data really is important if you
want to get a really clear picture of what’s happening in any given space.
While no single end-user company can (or likely would) address search-engine
optimization, for example, by building a massive store comprised of data
from hundreds or thousands of companies as well as the entire web, a cloud
service dedicated to that specific task can.
These are obvious advantages of moving the responsibility to a third party service. But I don’t believe SaaS is the future of big data and here’s why big data is not the sweet spot of SaaS:
a SaaS solution is good at a particular job, but it’s rarely the case that particular job is answering all your company questions and reveal the insights in your data. SaaS solutions will tell you want they, not you, think is important about your data.
the promise of a SaaS solution to give you access to more aggregate data sounds wrong. Big data is mostly about your data and each customer will have access to their own slices. Indeed a SaaS solution could augment your data with open data or extra data you’d need to pay for.
transporting your data to each SaaS to answer every question your company has is extremely expensive. If possible.
the nature and form of the questions big data tries to answer is changing. SaaS services will not adapt as fast as you want to the range and depth you need.
having your data in different SaaS solutions is just equivalent to having it in different internal silos. Except you’d pay someone else to protect the silo. The costs of breaking these silos will be much, much higher, so long term you might actually find a real reason why you cannot analyze your data.
Big Data is about agility. It’s about experiments. It’s trial and error. SaaS is about none of these when speaking years and years of data.
There are dozens more services like these operating in and around San Francisco…they’ve formed the backbone of a strange urban economy: one in which massive venture-capital injections allow money-losing start-ups to flourish, while providing services that no traditional, unsubsidized business can match. It’s an economy built on patience, and the hope that someday, after the land grab is over and the dust has settled, a better business model will emerge.
h/t to John Fazzolari for the heads up on this article, which speaks volumes to my post from earlier today on the challenge of B2B SaaS business models that rely heavily upon unsustainable freemium practices. It’s like throwing a Hail Mary pass when it is completely unnecessary to throw a Hail Mary. Businesses are used to and want to pay for software, so there is no reason to offer free.
A thoughtful analysis of the economics of price, cost, and churn across SaaS vendors. The decision on which distribution strategy to employ weighs heavily on choices made on price, cost of acquisition, sales & marketing expenses, and churn rates.
Looking at this chart would lead one to believe that there are only three strategies one could employ, which is borne out by the historical data. However, this is also where the best opportunity lies to upend the entire SaaS distribution model.
Can you have a predominantly low touch distribution strategy and successfully sell high-end technologies? I believe this indeed possible. In fact, no one believed complex and expensive database technology could be sold over the phone by inside sales reps, then an Oracle executive proved that it could, accelerating the adoption of RDBMS across the enterprise.